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Mohamed-Slim Alouini

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preprint2026arXiv

AUV Trajectory Learning for Underwater Acoustic Energy Transfer and Age Minimization

Internet of underwater things (IoUT) is increasingly gathering attention with the aim of monitoring sea life and deep ocean environment, underwater surveillance as well as maintenance of underwater installments. However, conventional IoUT devices, reliant on battery power, face limitations in lifespan and pose environmental hazards upon disposal. This paper introduces a sustainable approach for simultaneous information uplink from the IoUT devices and acoustic energy transfer (AET) to the devices via an autonomous underwater vehicle (AUV), potentially enabling them to operate indefinitely. To tackle the time-sensitivity, we adopt age of information (AoI), and Jain's fairness index. We develop two deep-reinforcement learning (DRL) algorithms, offering a high-complexity, high-performance frequency division duplex (FDD) solution and a low-complexity, medium-performance time division duplex (TDD) approach. The results elucidate that the proposed FDD and TDD solutions significantly reduce the average AoI and boost the harvested energy as well as data collection fairness compared to baseline approaches.

preprint2026arXiv

From Ground to Sky: Architectures, Applications, and Challenges Shaping Low-Altitude Wireless Networks

In this article, we introduce a novel low-altitude wireless network (LAWN), which is a reconfigurable, three-dimensional (3D) layered architecture. In particular, the LAWN integrates connectivity, sensing, control, and computing across aerial and terrestrial nodes that enable seamless operation in complex, dynamic, and mission-critical environments. Different from the conventional aerial communication systems, LAWN's distinctive feature is its tight integration of functional planes in which multiple functionalities continually reshape themselves to operate safely and efficiently in the low-altitude sky. With the LAWN, we discuss several enabling technologies, such as integrated sensing and communication (ISAC), semantic communication, and fully-actuated control systems. Finally, we identify potential applications and key cross-layer challenges. This article offers a comprehensive roadmap for future research and development in the low-altitude airspace.

preprint2026arXiv

Frontiers of Generative AI for Network Optimization: Theories, Limits, and Visions

While interest in the application of generative AI (GenAI) in network optimization has surged in recent years, its rapid progress has often overshadowed critical limitations intrinsic to generative models that remain insufficiently examined in existing literature. This survey provides a comprehensive review and critical analysis of GenAI in network optimization. We focus on the two dominant paradigms of GenAI including generative diffusion models (GDMs) and large pre-trained models (LPTMs), and organize our discussion around a categorization we introduce, dividing network optimization problems into two primary formulations: one-shot optimization and Markov decision process (MDP). We first trace key works, including foundational contributions from the AI community, and categorize current efforts in network optimization. We also review frontier applications of GDMs and LPTMs in other networking tasks, providing additional context. Furthermore, we present theoretical generalization bounds for GDMs in both one-shot and MDP settings, offering insights into the fundamental factors affecting model performance. Most importantly, we reflect on the overestimated perception of GenAI's general capabilities and caution against the all-in-one illusion it may convey. We highlight critical limitations, including difficulties in constraint satisfying, limited concept understanding, and the inherent probabilistic nature of outputs. We also propose key future directions, such as bridging the gap between generation and optimization. Although they are increasingly integrated in implementations, they differ fundamentally in both objectives and underlying mechanisms, necessitating a deeper understanding of their theoretical connections. Ultimately, this survey aims to provide a structured overview and a deeper insight into the strengths, limitations, and potential of GenAI in network optimization.

preprint2026arXiv

Label-Efficient School Detection from Aerial Imagery via Weakly Supervised Pretraining and Fine-Tuning

Accurate school detection is essential for supporting education initiatives, including infrastructure planning and expanding internet connectivity to underserved areas. However, many regions around the world face challenges due to outdated, incomplete, or unavailable official records. Manual mapping efforts, while valuable, are labor-intensive and lack scalability across large geographic areas. To address this, we propose a weakly supervised framework for school detection from aerial imagery that minimizes the need for human annotations while supporting global mapping efforts. Our method is specifically designed for low-data regimes, where manual annotations are extremely scarce. We introduce an automatic labeling pipeline that leverages sparse location points and semantic segmentation to generate infrastructure masks from which we generate bounding boxes. Using these automatically labeled images, we train our detectors on a first training stage to learn a representation of what schools look like, then using a small set of manually labeled images, we fine-tune the previously trained models on this clean dataset. This two stage training pipeline enables large-scale and strong detection in low-data setting of school infrastructure with minimal supervision. Our results demonstrate strong object detection performance, particularly in the low-data regime, where the models achieve promising results using only 50 manually labeled images, significantly reducing the need for costly annotations. This framework supports education and connectivity initiatives worldwide by providing an efficient and extensible approach to mapping schools from space. All models, training code and auto-labeled data will be publicly released to foster future research and real-world impact.

preprint2026arXiv

Low-Complexity RSS-based Underwater Localization with Unknown Transmit Power

Underwater wireless sensor networks (UWSNs) have received significant attention due to their various applications, with underwater target localization playing a vital role in enhancing network performance. Given the challenges and high costs associated with UWSN deployments, Received Signal Strength (RSS)-based localization offers a viable solution due to its minimal hardware requirements and cost-effectiveness. In this paper, we assign distance-based weights to RSS measurements, providing higher reliability to closer anchor nodes. Using the weighted RSS measurements and generalized trust region subproblem (GTRS), we propose the GTRS-based localization technique with Unknown Transmit Power (GUTP), which can be solved by a simple bisection method. Unlike conventional localization methods that require prior knowledge of the target node's transmit power, GUTP jointly estimates both the location and transmit power of the target node, broadening its practical use. Additionally, we derive the Cramer-Rao lower bounds (CRLBs) for RSS-based underwater localization with known and unknown transmit power, respectively. Extensive simulations demonstrate that GUTP achieves enhanced accuracy and significantly lower computational complexity in estimating the target node's location and transmit power compared to existing semidefinite programming (SDP)-based techniques.

preprint2023arXiv

On Performance of Integrated Satellite HAPS Ground Communication: Aerial IRS Node vs Terrestrial IRS Node

With a motive of ubiquitous connectivity over the globe with enhanced spectral efficiency, intelligent reflecting surfaces (IRS) integrated satellite-terrestrial communications is a topic of research interest in an infrastructure-deficient remote terrains. In line with this vision, this paper entails the performance analysis of satellite-terrestrial networks leveraging both aerial and terrestrial IRS nodes, with the support of high altitude platforms over diverse fading channels including shadowed Rician, Rician, and Nakagami-$m$ fading channels. The merits of IRS in enhancing spectral efficiency is analyzed through closed-form expressions of outage probability and ergodic rate. Further, the average symbol error rate analysis for the higher-order quadrature amplitude modulation (QAM) schemes such as hexagonal QAM, rectangular QAM, cross QAM, and square QAM is performed. Practical constraints like antenna gains, path loss, and link fading are considered to characterize the satellite terrestrial links. Finally, a comparison between the high-altitude platforms based IRS node and terrestrial IRS nodes is performed and various insights are drawn under various fading scenarios and path loss conditions. This paper contribute towards understanding and potential implementation of IRS-integrated satellite-terrestrial networks for efficient and reliable communication.

preprint2023arXiv

On the Uplink SINR Meta Distribution of UAV-assisted Wireless Networks

This letter studies the signal-to-interference-plus-noise (SINR) meta distribution of uplink transmission of UAV-enabled wireless networks with inversion power control. Within a framework of stochastic geometry, the Matern cluster process (MCP) is used to model the locations of users and UAVs. Conditional success probability and moments are derived to compute the exact expression and moment matching approximation of SINR meta distribution (beta approximation). Specifically, the effect of the power control compensation factor and UAV altitude are studied. Our numerical results show that UAV altitude has a higher impact on the system reliability than transmit power at low values of SINR threshold since users benefit more from establishing line-of-sight (LoS) links with UAVs.

preprint2023arXiv

Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network

Using unmanned aerial vehicles (UAVs) to enhance network coverage has proven a variety of benefits compared to terrestrial counterparts. One of the commonly used mathematical tools to model the locations of the UAVs is stochastic geometry (SG). However, in the existing studies, both users and UAVs are often modeled as homogeneous point processes. In this paper, we consider an inhomogeneous Poisson point process (PPP)-based model for the locations of the users that captures the degradation in the density of active users as we move away from the town center. In addition, we propose the deployment of aerial vehicles following the same inhomogeneity of the users to maximize the performance. In addition, a multi-tier network model is also considered to make better use of the rich space resources. Then, the analytical expressions of the coverage probability for a typical user and the total coverage probability are derived. Finally, we optimize the coverage probability with limitations of the total number of UAVs and the minimum local coverage probability. Finally we give the optimal UAV distribution parameters when the maximum overall coverage probability is reached.

preprint2022arXiv

A New Analytical Approximation of the Fluid Antenna System Channel

Fluid antenna systems (FAS) are an emerging technology that promises a significant diversity gain even in the smallest spaces. Motivated by the groundbreaking potentials of liquid antennas, researchers in the wireless communication community are investigating a novel antenna system where a single antenna can freely switch positions along a small linear space to pick the strongest received signal. However, the FAS positions do not necessarily follow the ever-existing rule separating them by at least half the radiation wavelength. Previous work in the literature parameterized the channels of the FAS ports simply enough to provide a single-integral expression of the probability of outage and various insights on the achievable performance. Nevertheless, this channel model may not accurately capture the correlation between the ports, given by Jake's model. This work builds on the state-of-the-art and accurately approximates the FAS channel while maintaining analytical tractability. The approximation is performed in two stages. The first stage approximation considerably reduces the number of multi-fold integrals in the probability of outage expression, while the second stage approximation provides a single integral representation of the FAS probability of outage. Further, the performance of such innovative technology is investigated under a less-idealized correlation model. Numerical results validate our approximations of the FAS channel model and demonstrate a limited performance gain under realistic assumptions. Further, our work opens the door for future research to investigate scenarios in which the FAS provides a performance gain compared to the current multiple antennas solutions.

preprint2022arXiv

Bridging the Urban-Rural Connectivity Gap through Intelligent Space, Air, and Ground Networks

Connectivity in rural areas is one of the main challenges of communication networks. To overcome this challenge, a variety of solutions for different situations are required. Optimizing the current networking paradigms is therefore mandatory. The high costs of infrastructure and the low revenue of cell sites in rural areas compared with urban areas are especially unattractive for telecommunication operators. Therefore, space, air, and ground networks should all be optimized for achieving connectivity in rural areas. We highlight the latest works on rural connectivity, discuss the solutions for terrestrial networks, and study the potential benefits of nonterrestrial networks. Furthermore, we present an overview of artificial intelligence (AI) techniques for improving space, air, and ground networks, hence improving connectivity in rural areas. AI enables intelligent communications and can integrate space, air, and ground networks for rural connectivity. We discuss the rural connectivity challenges and highlight the latest projects and research and the empowerment of networks using AI. Finally, we discuss the potential positive impacts of providing connectivity to rural communities.

preprint2022arXiv

Conditional Contact Angle Distribution in LEO Satellite-Relayed Transmission

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the \ac{CDF} of the conditional contact angle is derived. Furthermore, the conditional contact angle is applied to analyze the inaccessibility of common satellites between the ground transmitter and receiver. Finally, with the help of the conditional contact angle, coverage probability and achievable data rate in LEO satellite-relayed transmission are studied.

preprint2022arXiv

Energy Efficiency Analysis of Charging Pads-powered UAV-enabled Wireless Networks

This paper analyzes the energy efficiency of a novel system model where unmanned aerial vehicles (UAVs) are used to provide coverage for user hotspots (user clusters) and are deployed on charging pads to enhance the flight time. We introduce a new notion of "cluster pairs" to capture the dynamic nature of the users' spatial distribution in order to exploit one of the top advantages of UAVs, which is the mobility and relocation flexibility. Using tools from stochastic geometry, we first derive a new distance distribution that is vital for energy efficiency analysis. Next, we compute the coverage probability under two deployment strategies: (i) one UAV per cluster pair, and (ii) one UAV per cluster. Finally, we compute the energy efficiency for both strategies. Our numerical results reveal which of the two strategies is better for different system parameters. Our work investigates some new aspects of the UAV-enabled communication system such as the dynamic density of users and the advantages or disadvantages of one- or two-UAV deployment strategies per cluster pair. By considering the relationships between the densities of user cluster pairs and the charging pads, it is shown that an optimal cluster pair density exists to maximize energy efficiency.

preprint2022arXiv

Evaluating the Accuracy of Stochastic Geometry Based Models for LEO Satellite Networks Analysis

This paper investigates the accuracy of recently proposed stochastic geometry-based modeling of low earth orbit (LEO) satellite networks. In particular, we use the Wasserstein Distance-inspired method to analyze the distances between different models, including Fibonacci lattice and orbit models. We propose an algorithm to calculate the distance between the generated point sets. Next, we test the algorithm's performance and analyze the distance between the stochastic geometry model and other more widely acceptable models using numerical results.

preprint2022arXiv

High-Rate Uninterrupted Internet-of-Vehicle Communications in Highways: Dynamic Blockage Avoidance and CSIT Acquisition

In future wireless networks, one of the use-cases of interest is Internet-of-vehicles (IoV). Here, IoV refers to two different functionalities, namely, serving the in-vehicle users and supporting the connected-vehicle functionalities, where both can be well provided by the transceivers installed on top of vehicles. Such dual functionality of on-vehicle transceivers implies strict rate and reliability requirements, for which one may need to communicate at millimeter wave (mmW) frequencies. However, IoV communication at mmW requires up-to-date channel state information (CSI) and blockage avoidance. In this article, we incorporate the recently proposed concept of predictor antennas (PAs) into a large-scale cooperative PA (LSCPA) setup where both temporal blockages and CSI out-dating are avoided via base stations (BSs)/vehicles cooperation. Summarizing the ongoing standardization progress enabling IoV communications, we present the potentials and challenges of the LSCPA setup, and compare the effect of cooperative and non-cooperative schemes on the performance of IoV links. As we show, BSs cooperation and blockage/CSI prediction can boost the performance of IoV links remarkably.

preprint2022arXiv

Joint Trajectory Design and User Scheduling of Aerial Cognitive Radio Networks

Unmanned aerial vehicles (UAVs) have been widely employed to enhance the end-to-end performance of wireless communications since the links between UAVs and terrestrial nodes are line-of-sight (LoS) with high probability. However, the broadcast characteristics of signal propagation in LoS links make it vulnerable to being wiretapped by malicious eavesdroppers, which poses a considerable challenge to the security of wireless communications. This paper investigates the security of aerial cognitive radio networks (CRNs). An airborne base station transmits confidential messages to secondary users utilizing the same spectrum as the primary network. An aerial base station transmits jamming signals to suppress the eavesdropper to enhance secrecy performance. The uncertainty of eavesdropping node locations is considered, and the average secrecy rate of the cognitive user is maximized by optimizing multiple users' scheduling, the UAVs' trajectory, and transmit power. To solve the non-convex optimization problem with mixed multiple integers variable problem, we propose an iterative algorithm based on block coordinate descent and successive convex approximation. Numerical results verify the effectiveness of our proposed algorithm and demonstrate that our scheme is beneficial to improving the secrecy performance of aerial CRNs.

preprint2022arXiv

Laser-Powered UAVs for Wireless Communication Coverage: A Large-Scale Deployment Strategy

The use of unmanned aerial vehicles (UAVs) is strongly advocated for sixth-generation (6G) networks, as the 6G standard will not be limited to improving broadband services, but will also target the extension of the geographical cellular coverage. In this context, the deployment of UAVs is considered a key solution for seamless connectivity and reliable coverage. That being said, it is important to underline that although UAVs are characterized by their high mobility and their ability to establish line-of-sight (LOS) links, their use is still impeded by several factors such as weather conditions, their limited computing power, and, most importantly, their limited energy. In this work, we are aiming for the novel technology that enables indefinite wireless power transfer for UAVs using laser beams. We propose a novel UAV deployment strategy, based on which we analyze the overall performance of the system in terms of wireless coverage. To this end, we use tractable tools from stochastic geometry to model the complex communication system. We analyze the user's connectivity profile under different laser charging capabilities and in different type of environments. We show a decrease in the coverage probability by more than 12% in moderate-to-strong turbulence conditions compared to low turbulence conditions. We also show how the connection rate to the aerial network significantly decreases in favor of the terrestrial network for short laser charging ranges. We conclude that laser-powered drones are considered interesting alternatives when placed in LOS with users, in low-to-moderate optical turbulence, and at reasonable ranges from the charging stations.

preprint2022arXiv

Maritime Communications: A Survey on Enabling Technologies, Opportunities, and Challenges

Water covers 71% of the Earth's surface, where the steady increase in oceanic activities has promoted the need for reliable maritime communication technologies. The existing maritime communication systems involve terrestrial, aerial, and satellite networks. This paper presents a holistic overview of the different forms of maritime communications and provides the latest advances in various marine technologies. The paper first introduces the different techniques used for maritime communications over the RF and optical bands. Then, we present the channel models for RF and optical bands, modulation and coding schemes, coverage and capacity, and radio resource management in maritime communications. After that, the paper presents some emerging use cases of maritime networks, such as the Internet of Ships (IoS) and the ship-to-underwater Internet of things (IoT). Finally, we highlight a few exciting open challenges and identify a set of future research directions for maritime communication, including bringing broadband connectivity to the deep sea, using THz and visible light signals for on-board applications, and data-driven modeling for radio and optical marine propagation.

preprint2022arXiv

Max-Min Data Rate Optimization for RIS-aided Uplink Communications with Green Constraints

Smart radio environments aided by reconfigurable intelligent reflecting surfaces (RIS) have attracted much research attention recently. We propose a joint optimization strategy for beamforming, RIS phases, and power allocation to maximize the minimum SINR of an uplink RIS-aided communication system. The users are subject to constraints on their transmit power. We derive a closed-form expression for the beam forming vectors and a geometric programming-based solution for power allocation. We also propose two solutions for optimizing the phase shifts at the RIS, one based on the matrix lifting method and one using an approximation for the minimum function. We also propose a heuristic algorithm for optimizing quantized phase shift values. The proposed algorithms are of practical interest for systems with constraints on the maximum allowable electromagnetic field exposure. For instance, considering $24$-element RIS, $12$-antenna BS, and $6$ users, numerical results show that the proposed algorithm achieves close to $300 \%$ gain in terms of minimum SINR compared to a scheme with random RIS phases.

preprint2022arXiv

On Secure NOMA-CDRT Systems with Physical Layer Network Coding

This paper proposes a new scheme to enhance the secrecy performance of a NOMA-based coordinated direct relay transmission system (NOMA-CDRT) with an untrusted relay. The physical-layer network coding and the non-orthogonal multiple access scheme are combined to improve the spectrum efficiency. Furthermore, inter-user interference and friendly jamming signals are utilized to suppress the eavesdropping ability of the untrusted relay without affecting the acceptance quality of legitimate users. Specifically, the far user in the first slot and the near user in the second slot act as jammers to generate jamming signals to ensure secure transmissions of the confidential signals. We investigate the secrecy performance of the proposed scheme in NOMA-CDRT systems and derive the closed-form expression for the ergodic secrecy sum rate. The asymptotic analysis at high signal-to-noise ratio is performed to obtain more insights. Finally, simulation results are presented to demonstrate the effectiveness of the proposed scheme and the correctness of the theoretical analysis.

preprint2022arXiv

On the Asymptotic Performance Analysis of the k-th Best Link Selection over Non-identical Non-central Chi-square Fading Channels

This paper derives the asymptotic distribution of the normalized $k$-th maximum order statistics of a sequence of non-central chi-square random variables with non-identical non-centrality parameter. We demonstrate the utility of these results in characterizing the signal to noise ratio in three different applications in wireless communication systems where the statistics of the $k$-th maximum channel power over Rician fading links are of interest. Furthermore, we derive simple expressions for the asymptotic outage probability, average throughput, achievable throughput, and the average bit error probability. The proposed results are validated via extensive Monte Carlo simulations.

preprint2022arXiv

On the Performance Optimization of Two-way Hybrid VLC/RF based IoT System over Cellular Spectrum

This paper investigates the system outage performance of a useful architecture of two-way hybrid visible light communication/radio frequency (VLC/RF) communication using overlay mode of cooperative cognitive radio network (CCRN). The demand of high data rate application can be fulfilled using VLC link and communication over a wide area of coverage with high reliability can be achieved through RF link. In the proposed architecture, cooperative communication between two licensed user (LU) nodes is accomplished via an aggregation agent (AA). AA can perform like a relay node and in return, it can access the LU spectrum for two-way communications with Internet-of-Things (IoT) device. First, closed form expressions of outage probability of both LU and IoT communication are established. On the basis of these expressions, optimization problems are formulated to achieve minimum outage probability of both LU and IoT network. The impacts of both VLC and RF system parameters on these systems outage probability and throughput are finally shown in simulation results.

preprint2022arXiv

Performance Analysis of Charging Infrastructure Sharing in UAV and EV-involved Networks

Electric vehicles (EVs) and unmanned aerial vehicles (UAVs) show great potential in modern transportation and communication networks, respectively. However, with growing demands for such technologies, the limited energy infrastructure becomes the bottleneck for their future growth. It might be of high cost and low energy efficiency for all the operators to each have their own dedicated energy infrastructure, such as charging stations. In this paper, we analyze a wireless charging infrastructure sharing strategy in UAV and EV-involved networks. We consider a scenario where UAVs can charge in EV charging stations and pay for the sharing fee. On the EVs' side, sharing infrastructure can earn extra profit but their service quality, such as waiting time, might slightly reduce. On the UAVs' side, if renting EV charging stations can achieve an acceptable system performance, say high coverage probability, while considering the cost, they may not need to build their dedicated charging stations. In this case, we use tools from stochastic geometry to model the locations and propose an optimization problem that captures the aforementioned trade-offs between cost or profit and quality of service. Our numerical results show that sharing infrastructure slightly increases the waiting time of EVs, say within $5$ min, but dramatically decreases the waiting time of drones, say more than $50$ min, and deploying more charging stations do achieve better performances, but all these better performances are expected to cost more.

preprint2022arXiv

Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, this paper surveys the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for counteracting any large-scale disasters. Then, we present the possible technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterward, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer. This paper also presents interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, placement optimization of aerial base stations, and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers.

preprint2022arXiv

Proactive Traffic Offloading in Dynamic Integrated Multi-Satellite Terrestrial Networks

The integration between the satellite network and the terrestrial network will play a key role in the upcoming sixth-generation (6G) of mobile cellular networks thanks to the wide coverage and bandwidth offered by satellite networks. To leverage this integration, we propose a proactive traffic offloading scheme in an integrated multi-satellite terrestrial network (IMSTN) that considers the future networks' heterogeneity and predicts their variability. Our proposed offloading scheme hinges on traffic prediction to answer the stringent requirements of data-rate, latency and reliability imposed by heterogeneous and coexisting services and traffic namely enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) and ultra-reliable low latency communication (URLLC). However, the fulfilment of these requirements during offloading in dynamic IMSTN comes at the expense of significant energy consumption and introduces inherently supplementary latency. Therefore, our offloading scheme aims to balance the fundamental trade-offs first between energy consumption and the achievable data-rate and second between energy consumption and latency while meeting the respective needs of the present traffic. Our findings prove the importance of the cooperation between the multi-satellite network and the terrestrial network conditioned by traffic prediction to enhance the performance of IMTSN in terms of latency and energy consumption.

preprint2022arXiv

Stochastic Geometry-based Analysis of Multi-Purpose UAVs for Package and Data Delivery

Using drones for communications and transportation is drawing great attention in many practical scenarios, such as package delivery and providing additional wireless coverage. However, the increasing demand for UAVs from industry and academia will cause aerial traffic conflicts in the future. This, in turn, motivates the idea of this paper: multi-purpose UAVs, acting as aerial wireless data relays and means of aerial transportation simultaneously, to deliver packages and data at the same time. This paper aims to analyze the feasibility of using drones to collect and deliver data from the Internet of Things (IoT) devices to terrestrial base stations (TBSs) while delivering packages from warehouses to residential areas. We propose an algorithm to optimize the trajectory of UAVs to maximize the size of collected/delivered data while minimizing the total round trip time subject to the limited onboard battery of UAVs. Specifically, we use tools from stochastic geometry to model the locations of the IoT clusters and the TBSs and study the system performance with respect to energy efficiency, average size of collected/delivered data, and package delivery time. Our numerical results reveal that multi-functional UAVs have great potential to enhance the efficiency of both communication and transportation networks.

preprint2022arXiv

Stochastic Geometry-Based Low Latency Routing in Massive LEO Satellite Networks

In this paper, the routing in massive low earth orbit (LEO) satellite networks is studied. When the satellite-to-satellite communication distance is limited, we choose different relay satellites to minimize the latency in a constellation at a constant altitude. Firstly, the global optimum solution is obtained in the ideal scenario when there are available satellites at all the ideal locations. Next, we propose a nearest neighbor search algorithm for realistic (non-ideal) scenarios with a limited number of satellites. The proposed algorithm can approach the global optimum solution under an ideal scenario through a finite number of iterations and a tiny range of searches. Compared with other routing strategies, the proposed algorithm shows significant advantages in terms of latency. Furthermore, we provide two approximation techniques that can give tight lower and upper bounds for the latency of the proposed algorithm, respectively. Finally, the relationships between latency and constellation height, satellites' number, and communication distance are investigated.

preprint2022arXiv

Technical Report: Development of an Ultrahigh Bandwidth Software-defined Radio Platform

For the development of new digital signal processing systems and services, the rapid, easy, and convenient prototyping of ideas and the rapid time-to-market of products are becoming important with advances in technology. Conventionally, for the development stage, particularly when confirming the feasibility or performance of a new system or service, an idea is first confirmed through a computerbased software simulation after developing an accurate model of the operating environment. Next, this idea is validated and tested in the real operating environment. The new systems or services and their operating environments are becoming increasingly complicated. Hence, their development processes too are more complex cost- and time-intensive tasks that require engineers with skill and professional knowledge/experience. Furthermore, for ensuring fast time-to-market, all the development processes encompassing the (i) algorithm development, (ii) product prototyping, and (iii) final product development, must be closely linked such that they can be quickly completed. In this context, the aim of this paper is to propose an ultrahigh bandwidth software-defined radio platform that can prototype a quasi-real-time operating system without a developer having sophisticated hardware/software expertise. This platform allows the realization of a software-implemented digital signal processing system in minimal time with minimal efforts and without the need of a host computer.

preprint2022arXiv

Toward Sustainable Transportation: Accelerating Vehicle Electrification with Dynamic Charging Deployment

Electric vehicles (EVs) are being actively adopted as a solution to sustainable transportation. However, a bottleneck remains with charging, where two of the main problems are the long charging time and the range anxiety of EV drivers. In this research, we investigate the deployment of dynamic charging systems, i.e., electrified roads that wirelessly charge EVs on the go, with a view to accelerating EVs adoption rate. We propose a traffic-based deployment strategy, statistically quantify its impact, and apply the strategy to two case studies of real traffic in New York City (USA) and Xi'an (China). We find that our analytical estimates not only closely match the real data, but they also suggest that dynamic charging considerably extends the driving range of popular EV models in urban mobility. For example, when only 5% of the existing roads in New York City are equipped with this technology, an EV model such as the Nissan Leaf will approximately maintain its battery level without stopping to recharge. If the percentage of charging roads is increased to 10%, then the Leaf will gain nearly 10% of its battery after every 40 kilometers of driving. Our framework provides a solution to public and private organizations that support and facilitate vehicle electrification through charging infrastructure.

preprint2022arXiv

Towards 6G Holographic Localization: Enabling Technologies and Perspectives

In the last years, we have experienced the evolution of wireless localization from being a simple add-on feature for enabling specific applications to become an essential characteristic of wireless cellular networks, as for sixth-generation (6G) cellular networks. This paper illustrates the importance of radio localization and its role in all the cellular generations, from first-generation (1G) to 6G. Also, it speculates about the idea of holographic localization where the characteristics of electromagnetic (EM) waves, including the spherical wavefront in the near-field, are fully controlled and exploited to achieve better wireless localization. Along this line, we briefly overview possible technologies, such as large intelligent surfaces, and challenges to realize holographic localization. To corroborate our vision, we also include a numerical example that confirms the potentialities of holographic localization.

preprint2021arXiv

Charging Techniques for UAV-assisted Data Collection: Is Laser Power Beaming the Answer?

As Covid-19 has increased the need for connectivity around the world, researchers are targeting new technologies that could improve coverage and connect the unconnected in order to make progress toward the United Nations Sustainable Development Goals. In this context, drones are seen as one of the key features of 6G wireless networks that could extend the coverage of previous wireless network generations. That said, limited on-board energy seems to be the main drawback that hinders the use of drones for wireless coverage. Therefore, different wireless and wired charging techniques, such as laser beaming, charging stations, and tether stations are proposed. In this paper, we analyze and compare these different charging techniques by performing extensive simulations for the scenario of drone-assisted data collection from ground-based Internet of Things (IoT) devices. We analyze the strengths and weaknesses of each charging technique, and finally show that laser-powered drones strongly compete with, and outperform in some scenarios other charging techniques.

preprint2021arXiv

Data-Driven State Estimation for Light-Emitting Diode Underwater Optical Communication

Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots. However, maintaining a controlled line of sight link between transmitter and receiver is challenging due to the constant movement of the underlying optical platform caused by the dynamic uncertainties of the LED model and vibration effects. Additionally, the alignment angle required for tracking is not directly measured and has to be estimated. Besides, the light scattering propagates beam pulse in water temporally, resulting in time-varying underwater optical links with interference. We address the state estimation problem by designing an LED communication system that provides the angular position and velocity information to overcome the challenges. In this way, we leverage the power of deep learning-based observer design to explore the LED communication's state space properly. Simulation results are presented to illustrate the performance of the data-driven LED state estimation.

preprint2021arXiv

Establishing and Maintaining a Reliable Optical Wireless Communication in Underwater Environment

This paper proposes the trajectory tracking problem between an autonomous underwater vehicle (AUV) and a mobile surface ship, both equipped with optical communication transceivers. The challenging issue is to maintain stable connectivity between the two autonomous vehicles within an optical communication range. We define a directed optical line-of-sight (LoS) link between the two-vehicle systems. The transmitter is mounted on the AUV while the surface ship is equipped with an optical receiver. However, this optical communication channel needs to preserve a stable transmitter-receiver position to reinforce service quality, which typically includes a bit rate and bit error rates. A cone-shaped beam region of the optical receiver is approximated based on the channel model; then, a minimum bit rate is ensured if the AUV transmitter remains inside of this region. Additionally, we design two control algorithms for the transmitter to drive the AUV and maintain it in the cone-shaped beam region under an uncertain oceanic environment. Lyapunov function-based analysis that ensures asymptotic stability of the resulting closed-loop tracking error is used to design the proposed NLPD controller. Numerical simulations are performed using MATLAB/Simulink to show the controllers' ability to achieve favorable tracking in the presence of the solar background noise within competitive times. Finally, results demonstrate the proposed NLPD controller improves the tracking error performance more than $70\%$ under nominal conditions and $35\%$ with model uncertainties and disturbances compared to the original PD strategy.

preprint2021arXiv

On the Performance of Spectrum Sharing Backscatter Communication Systems

Spectrum sharing backscatter communication systems are among the most prominent technologies for ultralow power and spectrum efficient communications. In this paper, we propose an underlay spectrum sharing backscatter communication system, in which the secondary network is a backscatter communication system. We analyze the performance of the secondary network under a transmit power adaption strategy at the secondary transmitter, which guarantees that the interference caused by the secondary network to the primary receiver is below a predetermined threshold. We first derive a novel analytical expression for the cumulative distribution function (CDF) of the instantaneous signal-to-noise ratio of the secondary network. Capitalizing on the obtained CDF, we derive novel accurate approximate expressions for the ergodic capacity, effective capacity, and average bit error rate. We further validate our theoretical analysis using extensive Monte Carlo simulations.

preprint2021arXiv

Smart Buildings Enabled by 6G Communications

Smart building (SB), a promising solution to fast-paced and continuous urbanization around the world, includes the integration of a wide range of systems and services and involves the construction of multiple layers. SB is capable of sensing, acquiring, and processing a very large amount of data as well as performing appropriate actions and adaptation. Rapid increases in the number of connected nodes and thereby the data transmission demand of SB have led to conventional transmission and processing techniques becoming insufficient to provide satisfactory services. In order to enhance the intelligence of SBs and achieve efficient monitoring and control, sixth generation (6G) communication technologies, particularly indoor visible light communications (VLC) and machine learning (ML), are required to be incorporated in SBs. Herein, we envision a novel SB framework featuring a reliable data transmission network, powerful data processing, and reasoning abilities, all of which are enabled by 6G communications. Primary simulation results support the promising visions of the proposed SB framework.

preprint2021arXiv

Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks

The emerging space-air-ground integrated network has attracted intensive research and necessitates reliable and efficient aeronautical communications. This paper investigates terahertz Ultra-Massive (UM)-MIMO-based aeronautical communications and proposes an effective channel estimation and tracking scheme, which can solve the performance degradation problem caused by the unique {\emph{triple delay-beam-Doppler squint effects}} of aeronautical terahertz UM-MIMO channels. Specifically, based on the rough angle estimates acquired from navigation information, an initial aeronautical link is established, where the delay-beam squint at transceiver can be significantly mitigated by employing a Grouping True-Time Delay Unit (GTTDU) module (e.g., the designed {\emph{Rotman lens}}-based GTTDU module). According to the proposed prior-aided iterative angle estimation algorithm, azimuth/elevation angles can be estimated, and these angles are adopted to achieve precise beam-alignment and refine GTTDU module for further eliminating delay-beam squint. Doppler shifts can be subsequently estimated using the proposed prior-aided iterative Doppler shift estimation algorithm. On this basis, path delays and channel gains can be estimated accurately, where the Doppler squint can be effectively attenuated via compensation process. For data transmission, a data-aided decision-directed based channel tracking algorithm is developed to track the beam-aligned effective channels. When the data-aided channel tracking is invalid, angles will be re-estimated at the pilot-aided channel tracking stage with an equivalent sparse digital array, where angle ambiguity can be resolved based on the previously estimated angles. The simulation results and the derived Cramér-Rao lower bounds verify the effectiveness of our solution.

preprint2021arXiv

Terahertz-Band MIMO-NOMA: Adaptive Superposition Coding and Subspace Detection

We consider the problem of efficient ultra-massive multiple-input multiple-output (UM-MIMO) data detection in terahertz (THz)-band non-orthogonal multiple access (NOMA) systems. We argue that the most common THz NOMA configuration is power-domain superposition coding over quasi-optical doubly-massive MIMO channels. We propose spatial tuning techniques that modify antenna subarray arrangements to enhance channel conditions. Towards recovering the superposed data at the receiver side, we propose a family of data detectors based on low-complexity channel matrix puncturing, in which higher-order detectors are dynamically formed from lower-order component detectors. We first detail the proposed solutions for the case of superposition coding of multiple streams in point-to-point THz MIMO links. We then extend the study to multi-user NOMA, in which randomly distributed users get grouped into narrow cell sectors and are allocated different power levels depending on their proximity to the base station. We show that successive interference cancellation is carried with minimal performance and complexity costs under spatial tuning. We derive approximate bit error rate (BER) equations, and we propose an architectural design to illustrate complexity reductions. Under typical THz conditions, channel puncturing introduces more than an order of magnitude reduction in BER at high signal-to-noise ratios while reducing complexity by approximately 90%.

preprint2021arXiv

Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing

Wireless power transfer (WPT) is an emerging paradigm that will enable using wireless to its full potential in future networks, not only to convey information but also to deliver energy. Such networks will enable trillions of future low-power devices to sense, compute, connect, and energize anywhere, anytime, and on the move. The design of such future networks brings new challenges and opportunities for signal processing, machine learning, sensing, and computing so as to make the best use of the RF radiations, spectrum, and network infrastructure in providing cost-effective and real-time power supplies to wireless devices and enable wireless-powered applications. In this paper, we first review recent signal processing techniques to make WPT and wireless information and power transfer as efficient as possible. Topics include power amplifier and energy harvester nonlinearities, active and passive beamforming, intelligent reflecting surfaces, receive combining with multi-antenna harvester, modulation, coding, waveform, massive MIMO, channel acquisition, transmit diversity, multi-user power region characterization, coordinated multipoint, and distributed antenna systems. Then, we overview two different design methodologies: the model and optimize approach relying on analytical system models, modern convex optimization, and communication theory, and the learning approach based on data-driven end-to-end learning and physics-based learning. We discuss the pros and cons of each approach, especially when accounting for various nonlinearities in wireless-powered networks, and identify interesting emerging opportunities for the approaches to complement each other. Finally, we identify new emerging wireless technologies where WPT may play a key role -- wireless-powered mobile edge computing and wireless-powered sensing -- arguing WPT, communication, computation, and sensing must be jointly designed.

preprint2020arXiv

A 6G White Paper on Connectivity for Remote Areas

In many places all over the world rural and remote areas lack proper connectivity that has led to increasing digital divide. These areas might have low population density, low incomes, etc., making them less attractive places to invest and operate connectivity networks. 6G could be the first mobile radio generation truly aiming to close the digital divide. However, in order to do so, special requirements and challenges have to be considered since the beginning of the design process. The aim of this white paper is to discuss requirements and challenges and point out related, identified research topics that have to be solved in 6G. This white paper first provides a generic discussion, shows some facts and discusses targets set in international bodies related to rural and remote connectivity and digital divide. Then the paper digs into technical details, i.e., into a solutions space. Each technical section ends with a discussion and then highlights identified 6G challenges and research ideas as a list.

preprint2020arXiv

A Journey from Improper Gaussian Signaling to Asymmetric Signaling

The deviation of continuous and discrete complex random variables from the traditional proper and symmetric assumption to a generalized improper and asymmetric characterization (accounting correlation between a random entity and its complex conjugate), respectively, introduces new design freedom and various potential merits. As such, the theory of impropriety has vast applications in medicine, geology, acoustics, optics, image and pattern recognition, computer vision, and other numerous research fields with our main focus on the communication systems. The journey begins from the design of improper Gaussian signaling in the interference-limited communications and leads to a more elaborate and practically feasible asymmetric discrete modulation design. Such asymmetric shaping bridges the gap between theoretically and practically achievable limits with sophisticated transceiver and detection schemes in both coded/uncoded wireless/optical communication systems. Interestingly, introducing asymmetry and adjusting the transmission parameters according to some design criterion render optimal performance without affecting the bandwidth or power requirements of the systems. This dual-flavored article initially presents the tutorial base content covering the interplay of reality/complexity, propriety/impropriety and circularity/noncircularity and then surveys majority of the contributions in this enormous journey.

preprint2020arXiv

A PHY Layer Security Analysis of a Hybrid High Throughput Satellite with an Optical Feeder Link

Hybrid terrestrial-satellite (HTS) communication systems have gained a tremendous amount of interest recently due to the high demand for global high data rates. Conventional satellite communications operate in the conventional Ku (12 GHz) and Ka (26.5-40 GHz) radio-frequency bands for assessing the feeder link, between the ground gateway and the satellite. Nevertheless, with the aim to provide hundreds of Mbps of throughput per each user, free-space optical (FSO) feeder links have been proposed to fulfill these high data rates requirements. In this paper, we investigate the physical layer security performance for a hybrid very high throughput satellite communication system with an FSO feeder link. In particular, the satellite receives the incoming optical wave from an appropriate optical ground station, carrying the data symbols of $N$ users through various optical apertures and combines them using the selection combining technique. Henceforth, the decoded and regenerated information signals of the $N$ users are zero-forcing (ZF) precoded in order to cancel the interbeam interference at the end-users. The communication is performed under the presence of malicious eavesdroppers nodes at both hops. Statistical properties of the signal-to-noise ratio of the legitimate and wiretap links at each hop are derived, based on which the intercept probability metric is evaluated. The derived results show that above a certain number of optical apertures, the secrecy level is not improved further. Also, the system's secrecy is improved using ZF precoding compared to the no-precoding scenario for some specific nodes' positions. All the derived analytical expressions are validated through Monte Carlo simulations.

preprint2020arXiv

A Survey on Design and Performance of Higher-Order QAM Constellations

As the research on beyond 5G heats up, we survey and explore power and bandwidth efficient modulation schemes in details. In the existing publications and in various communication standards, initially square quadrature amplitude modulation (SQAM) constellations (even power of 2) were considered. However, only the square constellations are not efficient for varying channel conditions and rate requirements, and hence, odd power of 2 constellations were introduced. For odd power of 2 constellations, rectangular QAM (RQAM) is commonly used. However, RQAM is not a good choice due to its lower power efficiency, and a modified cross QAM (XQAM) constellation is preferred as it provides improved power efficiency over RQAM due to its energy efficient two dimensional (2D) structure. The increasing demand for high data-rates has further encouraged the research towards more compact 2D constellations which lead to hexagonal lattice structure based constellations, referred to as hexagonal QAM (HQAM). In this work, various QAM constellations are discussed and detailed study of star QAM, XQAM, and HQAM constellations is presented. Generation, peak and average energies, peak-to-average-power ratio, symbol-error-rate, decision boundaries, bit mapping, Gray code penalty, and bit-error-rate of star QAM, XQAM, and HQAM constellations with different constellation orders are presented. Finally, a comparative study of various QAM constellations is presented which justifies the supremacy of HQAM over other QAM constellations. With this, it can be claimed that the use of the HQAM in various wireless communication systems and standards can further improve the performance targeted for beyond 5G wireless communication systems.

preprint2020arXiv

A Tutorial on Clique Problems in Communications and Signal Processing

Since its first use by Euler on the problem of the seven bridges of Königsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and $k$-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems.

preprint2020arXiv

Accurate Closed-Form Approximations to Channel Distributions of RIS-Aided Wireless Systems

This paper proposes highly accurate closed-form approximations to channel distributions of two different reconfigurable intelligent surface (RIS)-based wireless system setups, namely, dual-hop RIS-aided (RIS-DH) scheme and RIS-aided transmit (RIS-T) scheme. Differently from previous works, the proposed approximations reveal to be very tight for arbitrary number $N$ of reflecting metasurface's elements. Our findings are then applied to the performance analysis of the considered systems, in which the outage probability, bit error rate, and average channel capacity are derived. Results show that the achievable diversity orders $G_d$ for RIS-DH and RIS-T schemes are $N-1<G_d<N$ and $N$, respectively. Furthermore, it is revealed that both schemes can not provide the multiplexing gain and only diversity gains are achieved. For the RIS-DH scheme, the channels are similar to the keyhole multiple-input multiple-output (MIMO) channels with only one degree of freedom, while the RIS-T scheme is like the transmit diversity structure.

preprint2020arXiv

Adaptive Acquisition Schemes for Photon-Limited Free-Space Optical Communications

Acquisition and tracking systems form an important component of free-space optical communications due to directional nature of the optical signal. Acquisition subsystems are needed in order to search and locate the receiver terminal in an uncertainty/search region with very narrow laser beams. In this paper, we have proposed and analyzed two adaptive search schemes for acquisition systems that perform better---for the low probability of detection---than the spiral scanning approach. The first of these schemes, the adaptive spiral search, provides a better acquisition time performance by dividing the search region into a number of smaller subregions, and prioritizing search in regions of higher probability mass. The second technique---the shotgun approach---searches the region in a random manner by sampling the search region according to a Gaussian distribution. The adaptive spiral scheme outperforms the shotgun approach in terms of acquisition time, especially if the number of search subregions is large enough. However, a higher pointing accuracy is required by the adaptive spiral search in order to search the region precisely. On the other hand, the shotgun scanning approach does not require such stringent pointing accuracy.

preprint2020arXiv

Aerial Base Stations Deployment in 6G Cellular Networks using Tethered Drones: The Mobility and Endurance Trade-off

Airborne base stations (carried by drones) have a great potential to enhance coverage and capacity of cellular networks. Multiple scenarios and use cases will highly benefit from such technology such as (i) offloading terrestrial base stations (BSs) in dense and urban areas, and (ii) providing coverage for rural areas. However, one of the main challenges facing the deployment of airborne BSs is the limited available energy at the drone, which limits the flight time. In fact, most of the currently used unmanned aerial vehicles (UAVs) can only operate for one hour maximum. This limits the performance of the UAV-enabled cellular network due to the need to frequently visit the ground station to recharge, leaving the UAV's coverage area temporarily out of service. In this article, we propose a new UAV-enabled cellular network setup based on tethered UAVs (TUAVs). In the proposed setup, the TUAV is connected to a ground station (GS) through a tether, which provides the TUAV with both energy and data. This enables a flight that can stay for days. We describe in detail the components of the proposed system. Furthermore, we enlist the main advantages of a TUAV-enabled cellular network compared to typical untethered UAVs. Next, we discuss the potential applications and use cases for TUAVs. Finally, we discuss the challenges, design considerations, and future research directions to realize the proposed setup.

preprint2020arXiv

Analog Versus Hybrid Precoding for Multiuser Massive MIMO with Quantized CSI Feedback

In this letter, we study the performance of a downlink multiuser massive multiple-input multiple-output (MIMO) system with sub-connected structure over limited feedback channels. Tight rate approximations are theoretically analyzed for the system with pure analog precoding and hybrid precoding. The effect of quantized analog and digital precoding is characterized in the derived expressions. Furthermore, it is revealed that the pure analog precoding outperforms the hybrid precoding using maximal-ratio transmission (MRT) or zero forcing (ZF) under certain conditions, and we theoretically characterize the conditions in closed form with respect to signal-to-noise ratio (SNR), the number of users and the number of feedback bits. Numerical results verify the derived conclusions on both Rayleigh channels and mmWave channels.

preprint2020arXiv

Asymptotic Analysis of an Ensemble of Randomly Projected Linear Discriminants

Datasets from the fields of bioinformatics, chemometrics, and face recognition are typically characterized by small samples of high-dimensional data. Among the many variants of linear discriminant analysis that have been proposed in order to rectify the issues associated with classification in such a setting, the classifier in [1], composed of an ensemble of randomly projected linear discriminants, seems especially promising; it is computationally efficient and, with the optimal projection dimension parameter setting, is competitive with the state-of-the-art. In this work, we seek to further understand the behavior of this classifier through asymptotic analysis. Under the assumption of a growth regime in which the dataset and projection dimensions grow at constant rates to each other, we use random matrix theory to derive asymptotic misclassification probabilities showing the effect of the ensemble as a regularization of the data sample covariance matrix. The asymptotic errors further help to identify situations in which the ensemble offers a performance advantage. We also develop a consistent estimator of the misclassification probability as an alternative to the computationally-costly cross-validation estimator, which is conventionally used for parameter tuning. Finally, we demonstrate the use of our estimator for tuning the projection dimension on both real and synthetic data.

preprint2020arXiv

Backflash Light as a Security Vulnerability in Quantum Key Distribution Systems

Based on the fundamental rules of quantum mechanics, two communicating parties can generate and share a secret random key that can be used to encrypt and decrypt messages sent over an insecure channel. This process is known as quantum key distribution (QKD). Contrary to classical encryption schemes, the security of a QKD system does not depend on the computational complexity of specific mathematical problems. However, QKD systems can be subject to different kinds of attacks, exploiting engineering and technical imperfections of the components forming the systems. Here, we review the security vulnerabilities of QKD. We mainly focus on a particular effect known as backflash light, which can be a source of eavesdropping attacks. We equally highlight the methods for quantifying backflash emission and the different ways to mitigate this effect.

preprint2020arXiv

Beam Tracking with Photon-Counting Detector Arrays in Free-Space Optical Communications

Optical beam center position on an array of detectors is an important (hidden) parameter that is essential not only from a tracking perspective, but is also important for optimal detection of Pulse Position Modulation symbols in free-space optical communications. In this paper, we have examined the beam position estimation problem for photon-counting detector arrays, and to this end, we have proposed and analyzed a number of non-Bayesian beam position estimators. These estimators are compared in terms of their mean-square error, bias and the probability of error performance. Additionally, the Cramer-Rao Lower Bounds (CRLB) of the tracking error is also derived, and the CRLB curves give us additional insights concerning the effect of number of detectors and the beam radius on mean-square error performance. Finally, the effect of beam position estimation on the probability of error performance is investigated, and our study concludes that the probability of error of the system is minimized when the beam position on the array is estimated as accurately as possible.

preprint2020arXiv

Beamforming Through Reconfigurable Intelligent Surfaces in Single-User MIMO Systems: SNR Distribution and Scaling Laws in the Presence of Channel Fading and Phase Noise

We consider a fading channel in which a multi-antenna transmitter communicates with a multi-antenna receiver through a reconfigurable intelligent surface (RIS) that is made of $N$ reconfigurable passive scatterers impaired by phase noise. The beamforming vector at the transmitter, the combining vector at the receiver, and the phase shifts of the $N$ scatterers are optimized in order to maximize the signal-to-noise-ratio (SNR) at the receiver. By assuming Rayleigh fading (or line-of-sight propagation) on the transmitter-RIS link and Rayleigh fading on the RIS-receiver link, we prove that the SNR is a random variable that is equivalent in distribution to the product of three (or two) independent random variables whose distributions are approximated by two (or one) gamma random variables and the sum of two scaled non-central chi-square random variables. The proposed analytical framework allows us to quantify the robustness of RIS-aided transmission to fading channels. For example, we prove that the amount of fading experienced on the transmitter-RIS-receiver channel linearly decreases with $N$. This proves that RISs of large size can be effectively employed to make fading less severe and wireless channels more reliable.

preprint2020arXiv

Classes of Full-Duplex Channels with Capacity Achieved Without Adaptation

Full-duplex communication allows a terminal to transmit and receive signals simultaneously, and hence, it is helpful in general to adapt transmissions to received signals. However, this often requires unaffordable complexity. This work focuses on simple non-adaptive transmission, and provides two classes of channels for which Shannon's information capacity regions are achieved without adaptation. The first is the injective semi-deterministic two-way channel that includes additive channels with various types of noises modeling wireless, coaxial cable, and other settings. The other is the Poisson two-way channel, for which we show that non-adaptive transmission is asymptotically optimal in the high dark current regime.

preprint2020arXiv

Climate Monitoring using Internet of X-Things

Global climate change is significantly affecting the life on planet Earth. Predicting timely changes in the climate is a big challenge and requires great attention from the scientific community. Research now suggests that using the internet of X-things (X-IoT) helps in monitoring global climate change.

preprint2020arXiv

CubeSat Communications: Recent Advances and Future Challenges

Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity. CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system. This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives. We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking. Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.

preprint2020arXiv

Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput. Most existing work assumes the ideal channel estimation, which can be challenging due to the high-dimensional cascaded MIMO channels and passive reflecting elements. Therefore, this paper proposes a deep denoising neural network assisted compressive channel estimation for mmWave IRS systems to reduce the training overhead. Specifically, we first introduce a hybrid passive/active IRS architecture, where very few receive chains are employed to estimate the uplink user-to-IRS channels. At the channel training stage, only a small proportion of elements will be successively activated to sound the partial channels. Moreover, the complete channel matrix can be reconstructed from the limited measurements based on compressive sensing, whereby the common sparsity of angular domain mmWave MIMO channels among different subcarriers is leveraged for improved accuracy. Besides, a complex-valued denoising convolution neural network (CV-DnCNN) is further proposed for enhanced performance. Simulation results demonstrate the superiority of the proposed solution over state-of-the-art solutions.

preprint2020arXiv

Deep Learning in Industrial Internet of Things: Potentials, Challenges, and Emerging Applications

The recent advancements in the Internet of Things (IoT) are giving rise to the proliferation of interconnected devices, enabling various smart applications. These enormous number of IoT devices generates a large capacity of data that further require intelligent data analysis and processing methods, such as Deep Learning (DL). Notably, the DL algorithms, when applied in the Industrial Internet of Things (IIoT), can enable various applications such as smart assembling, smart manufacturing, efficient networking, and accident detection-and-prevention. Therefore, motivated by these numerous applications; in this paper, we present the key potentials of DL in IIoT. First, we review various DL techniques, including convolutional neural networks, auto-encoders, and recurrent neural networks and there use in different industries. Then, we outline numerous use cases of DL for IIoT systems, including smart manufacturing, smart metering, smart agriculture, etc. Moreover, we categorize several research challenges regarding the effective design and appropriate implementation of DL-IIoT. Finally, we present several future research directions to inspire and motivate further research in this area.

preprint2020arXiv

Efficient Importance Sampling for the Left Tail of Positive Gaussian Quadratic Forms

Estimating the left tail of quadratic forms in Gaussian random vectors is of major practical importance in many applications. In this letter, we propose an efficient importance sampling estimator that is endowed with the bounded relative error property. This property significantly reduces the number of simulation runs required by the proposed estimator compared to naive Monte Carlo (MC), especially when the probability of interest is very small. Selected simulation results are presented to illustrate the efficiency of our estimator compared to naive MC as well as some of the well-known approximations.

preprint2020arXiv

Energy-Efficient Fixed-Gain AF Relay Assisted OFDM with Index Modulation

To broaden the application scenario and reduce energy consumption, we propose an energy-efficient fixed-gain (FG) amplify-and-forward (AF) relay assisted orthogonal frequency-division multiplexing with index modulation (OFDM-IM) scheme in this letter. The proposed system needs neither instantaneous channel state information (CSI) nor complicated processing at the relay node. It operates based on the power allocation scheme that minimizes the sum of transmit power at both source and relay node, given an outage probability constraint. Through a series of problem transformation and simplification, we convert the original power allocation problem to its relaxed version and solve it using convex programming techniques. To reveal the computing efficiency of the proposed power allocation scheme, we analyze its computational complexity. Numerical simulations substantiate that the proposed optimization scheme has a neglectable loss compared with the brute force search, but the computational complexity can be considerably reduced.

preprint2020arXiv

Enhanced Huffman Coded OFDM with Index Modulation

In this paper, we propose an enhanced Huffman coded orthogonal frequency-division multiplexing with index modulation (EHC-OFDM-IM) scheme. The proposed scheme is capable of utilizing all legitimate subcarrier activation patterns (SAPs) and adapting the bijective mapping relation between SAPs and leaves on a given Huffman tree according to channel state information (CSI). As a result, a dynamic codebook update mechanism is obtained, which can provide more reliable transmissions. We take the average block error rate (BLER) as the performance evaluation metric and approximate it in closed form when the transmit power allocated to each subcarrier is independent of channel states. Also, we propose two CSI-based power allocation schemes with different requirements for computational complexity to further improve the error performance. Subsequently, we carry out numerical simulations to corroborate the error performance analysis and the proposed dynamic power allocation schemes. By studying the numerical results, we find that the depth of the Huffman tree has a significant impact on the error performance when the SAP-to-leaf mapping relation is optimized based on CSI. Meanwhile, through numerical results, we also discuss the trade-off between error performance and data transmission rate and investigate the impacts of imperfect CSI on the error performance of EHC-OFDM-IM.

preprint2020arXiv

Exploiting Randomly-located Blockages for Large-Scale Deployment of Intelligent Surfaces

One of the promising technologies for the next generation wireless networks is the reconfigurable intelligent surfaces (RISs). This technology provides planar surfaces the capability to manipulate the reflected waves of impinging signals, which leads to a more controllable wireless environment. One potential use case of such technology is providing indirect line-of-sight (LoS) links between mobile users and base stations (BSs) which do not have direct LoS channels. Objects that act as blockages for the communication links, such as buildings or trees, can be equipped with RISs to enhance the coverage probability of the cellular network through providing extra indirect LoS-links. In this paper, we use tools from stochastic geometry to study the effect of large-scale deployment of RISs on the performance of cellular networks. In particular, we model the blockages using the line Boolean model. For this setup, we study how equipping a subset of the blockages with RISs will enhance the performance of the cellular network. We first derive the ratio of the blind-spots to the total area. Next, we derive the probability that a typical mobile user associates with a BS using an RIS. Finally, we derive the probability distribution of the path-loss between the typical user and its associated BS. We draw multiple useful system-level insights from the proposed analysis. For instance, we show that deployment of RISs highly improves the coverage regions of the BSs. Furthermore, we show that to ensure that the ratio of blind-spots to the total area is below 10^5, the required density of RISs increases from just 6 RISs/km2 when the density of the blockages is 300 blockage/km^2 to 490 RISs/km^2 when the density of the blockages is 700 blockage/km^2.

preprint2020arXiv

Flying Car Transportation System: Advances, Techniques, and Challenges

Since the development of transport systems, humans have exploited ground-level, below-ground, and high-altitude spaces for transportation purposes. However, with the increasing burden of expanding populations and rapid urbanization in recent decades, public transportation systems and freight traffic are suffering huge pressure, plaguing local governments and straining economies. Engineers and researchers have started to re-examine, propose, and develop the underused near-ground spaces (NGS) for transportation purposes. For instance, flying cars, which are not a totally novel idea, aim at solving the traffic congestion problem and releasing the strains on existing city transport networks by utilizing unoccupied NGS. Flying cars differ from traditional grounded transportation systems that are entirely limited by their physical space, such as trains on tracks or automobiles on roads. Flying cars do not occupy or compete for high-altitude spaces used by air traffic for long-distance transfer. However, there is a clear lack of specific literature on flying cars and flying car transportation systems (FCTS), which this paper aims to address by describing modern advances, techniques, and challenges of FCTS. We explore the inherent nature of NGS transportation and devise useful proposals to facilitate the construction and commercialization of FCTS. We begin with an introduction to the increasing need for NGS transportation and we address the advantages of using flying cars. Next, we present a brief overview of the history of the development of flying cars in terms of the historic timeline and technique development. Then, we discuss and compare the state of the art in the design of flying cars, including the take-off \& landing (TOL) modes, pilot modes, operation modes, and power types, ...

preprint2020arXiv

Free-Space Optical MISO Communications With an Array of Detectors

Multiple-input multiple-output (MIMO) and multiple-input single-output (MISO) schemes have yielded promising results in free space optical (FSO) communications by providing diversity against fading of the received signal intensity. In this paper, we have analyzed the probability of error performance of a \emph{muliple-input single-output} (MISO) free-space optical channel that employs array(s) of detectors at the receiver. In this regard, we have considered the \emph{maximal ratio combiner} (MRC) and \emph{equal gain combiner} (EGC) fusion algorithms for the array of detectors, and we have examined the performance of these algorithms subject to phase and pointing errors for strong atmospheric turbulence conditions. It is concluded that when the variance of the phase and pointing errors are below certain thresholds, signal combining with a single array of detectors yields significantly better performance than a multiple arrays receiver. In the final part of the paper, we examine the probability of error of the single detector array receiver as a function of the beam radius, and the probability of error is minimized by (numerically) optimizing the beam radius of the received signal beams.

preprint2020arXiv

GMD-Based Hybrid Beamforming for Large Reconfigurable Intelligent Surface Assisted Millimeter-Wave Massive MIMO

Reconfigurable intelligent surface (RIS) is considered to be an energy-efficient approach to reshape the wireless environment for improved throughput. Its passive feature greatly reduces the energy consumption, which makes RIS a promising technique for enabling the future smart city. Existing beamforming designs for RIS mainly focus on optimizing the spectral efficiency for single carrier systems. To avoid the complicated bit allocation on different spatial domain subchannels in MIMO systems, in this paper, we propose a geometric mean decomposition-based beamforming for RIS-assisted millimeter wave (mmWave) hybrid MIMO systems so that multiple parallel data streams in the spatial domain can be considered to have the same channel gain. Specifically, by exploiting the common angular-domain sparsity of mmWave massive MIMO channels over different subcarriers, a simultaneous orthogonal match pursuit algorithm is utilized to obtain the optimal multiple beams from an oversampling 2D-DFT codebook. Moreover, by only leveraging the angle of arrival and angle of departure associated with the line of sight (LoS) channels, we further design the phase shifters for RIS by maximizing the array gain for LoS channel. Simulation results show that the proposed scheme can achieve better BER performance than conventional approaches. Our work is an initial attempt to discuss the broadband hybrid beamforming for RIS-assisted mmWave hybrid MIMO systems.

preprint2020arXiv

High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model

Quadratic discriminant analysis (QDA) is a widely used classification technique that generalizes the linear discriminant analysis (LDA) classifier to the case of distinct covariance matrices among classes. For the QDA classifier to yield high classification performance, an accurate estimation of the covariance matrices is required. Such a task becomes all the more challenging in high dimensional settings, wherein the number of observations is comparable with the feature dimension. A popular way to enhance the performance of QDA classifier under these circumstances is to regularize the covariance matrix, giving the name regularized QDA (R-QDA) to the corresponding classifier. In this work, we consider the case in which the population covariance matrix has a spiked covariance structure, a model that is often assumed in several applications. Building on the classical QDA, we propose a novel quadratic classification technique, the parameters of which are chosen such that the fisher-discriminant ratio is maximized. Numerical simulations show that the proposed classifier not only outperforms the classical R-QDA for both synthetic and real data but also requires lower computational complexity, making it suitable to high dimensional settings.

preprint2020arXiv

Intelligent Reflecting Surface Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design

The concept of reconfiguring wireless propagation environments using intelligent reflecting surfaces (IRS)s has recently emerged, where an IRS comprises of a large number of passive reflecting elements that can smartly reflect the impinging electromagnetic waves for performance enhancement. Previous works have shown promising gains assuming the availability of perfect channel state information (CSI) at the base station (BS) and the IRS, which is impractical due to the passive nature of the reflecting elements. This paper makes one of the preliminary contributions of studying an IRS-assisted multi-user multiple-input single-output (MISO) communication system under imperfect CSI. Different from the few recent works that develop least-squares (LS) estimates of the IRS-assisted channel vectors, we exploit the prior knowledge of the large-scale fading statistics at the BS to derive the Bayesian minimum mean squared error (MMSE) channel estimates under a protocol in which the IRS applies a set of optimal phase shifts vectors over multiple channel estimation sub-phases. The resulting mean squared error (MSE) is both analytically and numerically shown to be lower than that achieved by the LS estimates. Joint designs for the precoding and power allocation at the BS and reflect beamforming at the IRS are proposed to maximize the minimum user signal-to-interference-plus-noise ratio (SINR) subject to a transmit power constraint. Performance evaluation results illustrate the efficiency of the proposed system and study its susceptibility to channel estimation errors.

preprint2020arXiv

Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques

This paper surveys the optimization frameworks and performance analysis methods for large intelligent surfaces (LIS), which have been emerging as strong candidates to support the sixth-generation wireless physical platforms (6G). Due to their ability to adjust the behavior of interacting electromagnetic (EM) waves through intelligent manipulations of the reflections phase shifts, LIS have shown promising merits at improving the spectral efficiency of wireless networks. In this context, researchers have been recently exploring LIS technology in depth as a means to achieve programmable, virtualized, and distributed wireless network infrastructures. From a system level perspective, LIS have also been proven to be a low-cost, green, sustainable, and energy-efficient solution for 6G systems. This paper provides a unique blend that surveys the principles of operation of LIS, together with their optimization and performance analysis frameworks. The paper first introduces the LIS technology and its physical working principle. Then, it presents various optimization frameworks that aim to optimize specific objectives, namely, maximizing energy efficiency, sum-rate, secrecy-rate, and coverage. The paper afterwards discusses various relevant performance analysis works including capacity analysis, the impact of hardware impairments on capacity, uplink/downlink data rate analysis, and outage probability. The paper further presents the impact of adopting the LIS technology for positioning applications. Finally, we identify numerous exciting open challenges for LIS-aided 6G wireless networks, including resource allocation problems, hybrid radio frequency/visible light communication (RF-VLC) systems, health considerations, and localization.

preprint2020arXiv

Joint Reflecting and Precoding Designs for SER Minimization in Reconfigurable Intelligent Surfaces Assisted MIMO Systems

This paper investigates the use of a reconfigurable intelligent surface (RIS) to aid point-to-point multi-data-stream multiple-input multiple-output (MIMO) wireless communications. With practical finite alphabet input, the reflecting elements at the RIS and the precoder at the transmitter are alternatively optimized to minimize the symbol error rate (MSER). In the reflecting optimization with a fixed precoder, two reflecting design methods are developed, referred as eMSER-Reflecting and vMSER-Reflecting. In the optimization of the precoding matrix with a fixed reflecting pattern, the matrix optimization is transformed to be a vector optimization problem and two methods are proposed to solve it, which are referred as MSER-Precoding and MMED-Precoding. The superiority of the proposed designs is investigated by simulations. Simulation results demonstrate that the proposed reflecting and precoding designs can offer a lower SER than existing designs with the assumption of complex Gaussian input. Moreover, we compare RIS with a full-duplex Amplify-and-Forward (AF) relay system in terms of SER to show the advantage of RIS.

preprint2020arXiv

Latency-Aware Offloading in Integrated Satellite Terrestrial Networks

Next-generation communication networks are expected to integrate newly-used technologies in a smart way to ensure continuous connectivity in rural areas and to alleviate the traffic load in dense regions. The prospective access network in 6G should hinge on satellite systems to take advantage of their wide coverage and high capacity. However, adopting satellites in 6G could be hindered because of the additional latency introduced, which is not tolerable by all traffic types. Therefore, we propose a traffic offloading scheme that integrates both the satellite and terrestrial networks to smartly allocate the traffic between them while satisfying different traffic requirements. Specifically, the proposed scheme offloads the Ultra-Reliable Low Latency Communication (URLLC) traffic to the terrestrial backhaul to satisfy its stringent latency requirement. However, it offloads the enhanced Mobile Broadband (eMBB) traffic to the satellite since eMBB needs high data rates but is not always sensitive to delay. Our scheme is shown to reduce the transmission delay of URLLC packets, decrease the number of dropped eMBB packets, and hence improve the network's availability. Our findings highlight that the inter-working between satellite and terrestrial networks is crucial to mitigate the expected high load on the limited terrestrial capacity.

preprint2020arXiv

Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

With the increasing demand for greener and more energy efficient transportation solutions, electric vehicles (EVs) have emerged to be the future of transportation across the globe. However, currently, one of the biggest bottlenecks of EVs is the battery. Small batteries limit the EVs driving range, while big batteries are expensive and not environmentally friendly. One potential solution to this challenge is the deployment of charging roads, i.e., dynamic wireless charging systems installed under the roads that enable EVs to be charged while driving. In this paper, we use tools from stochastic geometry to establish a framework that enables evaluating the performance of charging roads deployment in metropolitan cities. We first present the course of actions that a driver should take when driving from a random source to a random destination in order to maximize dynamic charging during the trip. Next, we analyze the distribution of the distance to the nearest charging road. This distribution is vital for studying multiple performance metrics such as the trip efficiency, which we define as the fraction of the total trip spent on charging roads. Next, we derive the probability that a given trip passes through at least one charging road. The derived probability distributions can be used to assist urban planners and policy makers in designing the deployment plans of dynamic wireless charging systems. In addition, they can also be used by drivers and automobile manufacturers in choosing the best driving routes given the road conditions and level of energy of EV battery.

preprint2020arXiv

Modeling of Viral Aerosol Transmission and Detection

In this paper, we propose studying the disease spread mechanism in the atmosphere as an engineering problem. Aerosol transmission is the most significant mode among the viral transmission mechanisms that do not include physical contact, where airflows carry virus-laden droplets over long distances. Throughout this work, we study the transport of these droplets as a molecular communication problem, where one has no control over the transmission source, but a robust receiver can be designed using bio-sensors. To this end, we present a complete system model and derive an end-to-end mathematical model for the transmission channel under certain constraints and boundary conditions. We derive the system response for both continuous sources such as breathing and jet or impulsive sources such as coughing and sneezing. In addition to transmitter and channel, we assumed a receiver architecture composed of air sampler and Silicon Nanowire field-effect transistor. Then, we formulate a detection problem to maximize the likelihood decision rule and minimize the corresponding missed detection probability. Finally, we present several numerical results to observe the impact of parameters that affect the performance and justify the feasibility of the proposed setup in related applications.

preprint2020arXiv

Nearest Neighbor and Contact Distance Distribution for Binomial Point Process on Spherical Surfaces

This letter characterizes the statistics of the contact distance and the nearest neighbor (NN) distance for binomial point processes (BPP) spatially-distributed on spherical surfaces. We consider a setup of $n$ concentric spheres, with each sphere $S_k$ has a radius $r_k$ and $N_k$ points that are uniformly distributed on its surface. For that setup, we obtain the cumulative distribution function (CDF) of the distance to the nearest point from two types o observation points: (i) the observation point is not a part of the point process and located on a concentric sphere with a radius $r_e<r_k\forall k$, which corresponds to the contact distance distribution, and (ii) the observation point belongs to the point process, which corresponds to the nearest-neighbor (NN) distance distribution.

preprint2020arXiv

Next Generation Terahertz Communications: A Rendezvous of Sensing, Imaging, and Localization

Terahertz (THz)-band communications are celebrated as a key enabling technology for next-generation wireless systems that promises to integrate a wide range of data-demanding and delay-sensitive applications. Following recent advancements in optical, electronic, and plasmonic transceiver design, integrated, adaptive, and efficient THz systems are no longer far-fetched. In this paper, we present a progressive vision of how the traditional "THz gap" will transform into a "THz rush" over the next few years. We posit that the breakthrough that the THz band will introduce will not be solely driven by achievable high data rates, but more profoundly by the interaction between THz sensing, imaging, and localization applications. We first detail the peculiarities of each of these applications at the THz band. Then, we illustrate how their coalescence results in enhanced environment-aware system performance in beyond-5G use cases. We further discuss the implementation aspects of this merging of applications in the context of shared and dedicated resource allocation, highlighting the role of machine learning.

preprint2020arXiv

On Integrated Access and Backhaul Networks: Current Status and Potentials

In this paper, we introduce and study the potentials and challenges of integrated access and backhaul (IAB) as one of the promising techniques for evolving 5G networks. We study IAB networks from different perspectives. We summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on IAB, and highlight the main IAB-specific agreements on different protocol layers. Also, concentrating on millimeter wave-based communications, we evaluate the performance of IAB networks in both dense and suburban areas. Using a finite stochastic geometry model, with random distributions of IAB nodes as well as user equipments (UEs) in a finite region, we study the service coverage rate defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between IAB and hybrid IAB/fiber-backhauled networks where a part or all of the small base stations are fiber-connected. Finally, we study the robustness of IAB networks to weather and various deployment conditions and verify their effects, such as blockage, tree foliage, rain as well as antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive approach to enable the network densification required by 5G and beyond.

preprint2020arXiv

On Secure Mixed RF-FSO Systems With TAS and Imperfect CSI

In this work, we analyze the secrecy outage performance of a dual-hop relay system composed of multiple-input-multiple-output radio-frequency (RF) links and a free-space optical (FSO) link while a multiple-antenna eavesdropper wiretaps the confidential information by decoding the received signals from the resource node. The channel state information (CSI) of the RF and FSO links is considered to be outdated. We propose three transmit antenna selection (TAS) schemes to enhance the secrecy performance of the considered systems. The secrecy outage performance with different TAS schemes is analyzed and the effects of misalignment and detection technology on the secrecy outage performance of mixed systems are studied. We derive the closed-form expressions for probability density function (PDF) and cumulative distribution function (CDF) over Málaga channel with imperfect CSI. Then the closed-form expressions for the CDF and PDF of the equivalent signal-to-noise ratio (SNR) at the legitimate receiver over Nakagami-$m$ and Málaga channels are derived. Furthermore, the lower bound of the secrecy outage probability (SOP) with different TAS schemes are derived. Besides, the asymptotic results for SOP are investigated by exploiting the unfolding of Meijer's $G$-function when the electrical SNR of FSO link approaches infinity. Finally, Monte-Carlo simulation results are presented to testify the correctness of the proposed analysis. The results illustrate that the outdated CSI shows a strong effect on the secrecy outage performance. In addition, increasing the number of antennas at the source cannot significantly enhance the secrecy performance of the considered systems.

preprint2020arXiv

On the Performance of Dual-Hop Systems over Mixed FSO/mmWave Fading Channels

Free-space optical (FSO) links are considered as a cost-efficient way to fill the backhaul/fronthaul connectivity gap between millimeter wave (mmWave) access networks and optical fiber based central networks. In this paper, we investigate the end-to-end performance of dual-hop mixed FSO/mmWave systems to address this combined use. The FSO link is modeled as a Gamma-Gamma fading channel using both heterodyne detection and indirect modulation/direct detection with pointing error impairments, while the mmWave link experiences the fluctuating two-ray fading. Under the assumption of both amplify-and-forward and decode-and-forward relaying, we derive novel closed-form expressions for the outage probability, average bit error probability (BER), ergodic capacity, effective capacity in terms of bivariate Fox's $H$-functions. Additionally, we discuss the diversity gain and provide other important engineering insights based on the high signal-to-noise-ratio analysis of the outage probability and the average BER. Finally, all our analytical results are verified using Monte Carlo simulations.

preprint2020arXiv

On the Precise Error Analysis of Support Vector Machines

This paper investigates the asymptotic behavior of the soft-margin and hard-margin support vector machine (SVM) classifiers for simultaneously high-dimensional and numerous data (large $n$ and large $p$ with $n/p\toδ$) drawn from a Gaussian mixture distribution. Sharp predictions of the classification error rate of the hard-margin and soft-margin SVM are provided, as well as asymptotic limits of as such important parameters as the margin and the bias. As a further outcome, the analysis allow for the identification of the maximum number of training samples that the hard-margin SVM is able to separate. The precise nature of our results allow for an accurate performance comparison of the hard-margin and soft-margin SVM as well as a better understanding of the involved parameters (such as the number of measurements and the margin parameter) on the classification performance. Our analysis, confirmed by a set of numerical experiments, builds upon the convex Gaussian min-max Theorem, and extends its scope to new problems never studied before by this framework.

preprint2020arXiv

On the Secrecy of UAV Systems With Linear Trajectory

By observing the fact that moving in a straight line is a common flying behavior of unmanned aerial vehicles (UAVs) in normal applications, e.g., power line inspections, and air patrols along with highway/streets/borders, in this paper we investigate the secrecy outage performance of a UAV system with linear trajectory, where a UAV ($S$) flies in a straight line and transmits its information over the downlink to a legitimate receiver ($D$) on the ground while an eavesdropping UAV ($E$) trying to overhear the information delivery between $S$ and $D$. Meanwhile, some information is delivered to $S$ over the uplink from $D$, such as commanding messages to control $S$'s detecting operations, which can also be eavesdropped by $E$. The locations of $S$, $D$, and $E$ are randomly distributed. We first characterize the statistical characteristics (including cumulative distribution functions and probability density function) of the received signal-to-noise ratio over both downlink and uplink, and then the closed-form analytical expressions for the lower boundary of the secrecy outage probability of both downlink and uplink have also been derived accordingly. Finally, Monte-Carlo simulations are given to testify our proposed analytical models.

preprint2020arXiv

Opportunistic Routing for Opto-Acoustic Internet of Underwater Things

Internet of underwater things (IoUT) is a technological revolution that could mark a new era for scientific, industrial, and military underwater applications. To mitigate the hostile underwater channel characteristics, this paper hybridizes underwater acoustic and optical wireless communications to achieve a ubiquitous control and high-speed low-latency networking performance, respectively. Since underwater optical wireless communications (UOWC) suffers from limited range, it requires effective multi-hop routing solutions. In this regard, we propose a Sector-based Opportunistic Routing (SectOR) protocol. Unlike the traditional routing (TR) techniques which unicast packets to a unique relay, opportunistic routing (OR) targets a set of candidate relays by leveraging the broadcast nature of the UOWC channel. OR improves the packet delivery ratio as the likelihood of having at least one successful packet reception is much higher than that in conventional unicast routing. Contingent upon the performance characterization of a single-hop link, we obtain a variety of local and global metrics to evaluate the fitness of a candidate set (CS) and prioritize the members of a CS. Since rate-error and range-beamwidth tradeoffs yield different candidate set diversities, we develop a candidate filtering and searching algorithm to find the optimal sector-shaped coverage region by scanning the feasible search space. Moreover, a hybrid acoustic/optic coordination mechanism is considered to avoid duplicate transmission of the relays. Numerical results show that SectOR protocol can perform even better than an optimal unicast routing protocol in well-connected UOWNs.

preprint2020arXiv

Performance Analysis and Optimization of Cooperative Satellite-Aerial-Terrestrial Systems

Aerial relays have been regarded as an alternative and promising solution to extend and improve satellite-terrestrial communications, as the probability of line-of-sight transmissions increases compared with adopting terrestrial relays. In this paper, a cooperative satellite-aerial-terrestrial system including a satellite transmitter (S), a group of terrestrial receivers (D), and an aerial relay (R) is considered. Specifically, considering the randomness of S and D and employing stochastic geometry, the coverage probability of R-D links in non-interference and interference scenarios is studied, and the outage performance of S-R link is investigated by deriving an approximated expression for the outage probability. Moreover, an optimization problem in terms of the transmit power and the transmission time over S-R and R-D links is formulated and solved to obtain the optimal end-to-end energy efficiency for the considered system. Finally, some numerical results are provided to validate our proposed analysis models, as well as to study the optimal energy efficiency performance of the considered system.

preprint2020arXiv

Performance Analysis of Dual-Hop Underwater Wireless Optical Communication Systems over Mixture Exponential-Generalized Gamma Turbulence Channels

In this work, we present a unified framework for the performance analysis of dual-hop underwater wireless optical communication (UWOC) systems with amplify-and-forward fixed gain relays in the presence of air bubbles and temperature gradients. Operating under either heterodyne detection or intensity modulation with direct detection, the UWOC is modeled by the unified mixture Exponential-Generalized Gamma distribution that we have proposed based on an experiment conducted in an indoor laboratory setup and has been shown to provide an excellent fit with the measured data under the considered lab channel scenarios. More specifically, we derive the cumulative distribution function (CDF) and the probability density function of the end-to-end signal-to-noise ratio (SNR) in exact closed-form in terms of the bivariate Fox's H function. Based on this CDF expression, we present novel results for the fundamental performance metrics such as the outage probability, the average bit-error rate (BER) for various modulation schemes, and the ergodic capacity. Additionally, very tight asymptotic results for the outage probability and the average BER at high SNR are obtained in terms of simple functions. Furthermore, we demonstrate that the dual-hop UWOC system can effectively mitigate the short range and both temperature gradients and air bubbles induced turbulences, as compared to the single UWOC link. All the results are verified via computer-based Monte-Carlo simulations.

preprint2020arXiv

Performance Evaluation of UAV-enabled Cellular Networks with Battery-limited Drones

Unmanned aerial vehicles (UAVs) can be used as flying base stations (BSs) to offload Macro-BSs in hotspots. However, due to the limited battery on-board, UAVs can typically stay in operation for less than 1.5 hours. Afterward, the UAV has to fly back to a dedicated charging station that recharges/replaces the UAV's battery. In this paper, we study the performance of a UAV-enabled cellular network while capturing the influence of the spatial distribution of the charging stations. In particular, we use tools from stochastic geometry to derive the coverage probability of a UAV-enabled cellular network as a function of the battery size, the density of the charging stations, and the time required for recharging/replacing the battery.

preprint2020arXiv

Performance of Multibeam Very High Throughput Satellite Systems Based on FSO Feeder Links with HPA Nonlinearity

Due to recent advances in laser satellite communications technology, free-space optical (FSO) links are presented as an ideal alternative to the conventional radio frequency (RF) feeder links of the geostationary satellite for next generation very high throughput satellite (VHTS) systems. In this paper, we investigate the performance of multibeam VHTS systems that account for nonlinear high power amplifiers at the transparent fixed gain satellite transponder. Specifically, we consider the forward link of such systems, where the RF user link is assumed to follow the shadowed Rician model and the FSO feeder link is modeled by the Gamma-Gamma distribution in the presence of beam wander and pointing errors where it operates under either the intensity modulation with direct detection or the heterodyne detection. Moreover, zero-forcing precoder is employed to mitigate the effect of inter-beam interference caused by the aggressive frequency reuse in the user link. The performance of the system under study is evaluated in terms of the outage probability, the average bit-error rate (BER), and the ergodic capacity that are derived in exact closed-forms in terms of the bivariate Meijer's G function. Simple asymptotic results for the outage probability and the average BER are also obtained at high signal-to-noise ratio.

preprint2020arXiv

Physical Layer Security in Cooperative NOMA Hybrid VLC/RF Systems

Integrating visible light communication (VLC) and radio-frequency (RF) networks can improve the performance of communication systems in terms of coverage and data rates. However, adding RF links to VLC networks weakens the secrecy performance due to the broadcast and ubiquitous nature of RF links. This paper studies the physical layer security (PLS) in cooperative non-orthogonal multiple access (CoNOMA) hybrid VLC/RF systems. Consider a VLC system, where two entrusted users close to a VLC access point (AP) help an out-of-coverage legitimate user using RF signals in the presence of an eavesdropper. The AP transmits data to both entrusted users and the legitimate user using the principle of NOMA, where the entrusted users harvest energy from the received light intensity, decode the legitimate user's message, forward it using a RF link, and then decode their messages. It is required to maximize the secrecy rate at the legitimate user under quality-of-service (QoS) constraints using beamforming and DC-bias and power allocation. Different solutions are proposed for both active and passive eavesdropper cases, using semidefinite relaxation, zero-forcing, beamforming, and jamming. Numerical results compare between the different proposed approaches and show how the proposed approaches contribute in improving the secrecy performance of the proposed model.

preprint2020arXiv

Power Allocation in HARQ-based Predictor Antenna Systems

In this work, we study the performance of predictor antenna (PA) systems using hybrid automatic repeat request (HARQ). Here, the PA system is referred to as a system with two sets of antennas on the roof of a vehicle. In this setup, the PA positioned in the front of the vehicle can be used to predict the channel state information at the transmitter (CSIT) for data transmission to the receive antenna (RA) that is aligned behind the PA. Considering spatial mismatch, due to the vehicle mobility, we derive closed-form expressions for the optimal power allocation and the minimum average power of the PA systems under different outage probability constraints. The results are presented for different types of HARQ protocols and we study the effect of different parameters on the performance of PA systems. As we show, our proposed approximation scheme enables us to analyze PA systems with high accuracy. Moreover, for different vehicle speeds, we show that HARQ-based feedback can reduce the outage-limited power consumption of PA systems by orders of magnitude.

preprint2020arXiv

Precise Error Analysis of the LASSO under Correlated Designs

In this paper, we consider the problem of recovering a sparse signal from noisy linear measurements using the so called LASSO formulation. We assume a correlated Gaussian design matrix with additive Gaussian noise. We precisely analyze the high dimensional asymptotic performance of the LASSO under correlated design matrices using the Convex Gaussian Min-max Theorem (CGMT). We define appropriate performance measures such as the mean-square error (MSE), probability of support recovery, element error rate (EER) and cosine similarity. Numerical simulations are presented to validate the derived theoretical results.

preprint2020arXiv

Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds

Next-generation cellular networks will witness the creation of smart radio environments (SREs), where walls and objects can be coated with reconfigurable intelligent surfaces (RISs) to strengthen the communication and localization coverage by controlling the reflected multipath. In fact, RISs have been recently introduced not only to overcome communication blockages due to obstacles but also for high-precision localization of mobile users in GPS denied environments, e.g., indoors. Towards this vision, this paper presents the localization performance limits for communication scenarios where a single next-generation NodeB base station (gNB), equipped with multiple-antennas, infers the position and the orientation of the user equipment(UE) in a RIS-assisted SRE. We consider a signal model that is valid also for near-field propagation conditions, as the usually adopted far-field assumption does not always hold, especially for large RISs. For the considered scenario, we derive the Cramer-Rao lower bound (CRLB) for assessing the ultimate localization and orientation performance of synchronous and asynchronous signaling schemes. In addition, we propose a closed-form RIS phase profile that well suits joint communication and localization. We perform extensive numerical results to assess the performance of our scheme for various localization scenarios and RIS phase design. Numerical results show that the proposed scheme can achieve remarkable performance, even in asynchronous signaling and that the proposed phase design approaches the numerical optimal phase design that minimizes the CRLB.

preprint2020arXiv

Relay Assisted OFDM with Subcarrier Number Modulation in Multi-Hop Cooperative Networks

Orthogonal frequency-division multiplexing (OFDM) with subcarrier number modulation (OFDM-SNM) manifests its superior nature of high spectral efficiency (SE) and low complexity for signal estimation. To exploit the spatial gain of OFDM-SNM, we propose a relay assisted OFDM-SNM scheme for multi-hop cooperative systems in this letter. It is stipulated that a relay operated by decode-and-forward (DF) and half-duplex (HD) protocols exists in each hop. We analyze the outage performance of the relay assisted OFDM-SNM system. The average outage probability is approximated in closed form. Moreover, to reveal the diversity and coding gains of relay assisted OFDM-SNM, we explore the asymptotic outage performance at high signal-to-noise ratio (SNR) by power series expansion. To verify the improvement on outage performance and energy efficiency, we carry out the comparison among different multi-hops systems with traditional OFDM-SNM fixing a certain distance from source to destination. Simulation results corroborate the derived outage probabilities and provide insight into the proposed system in this letter.

preprint2020arXiv

Residual Clipping Noise in Multi-layer Optical OFDM: Modeling, Analysis, and Application

Optical orthogonal frequency division multiplexing (O-OFDM) schemes are variations of OFDM schemes which produce non-negative signals. Asymmetrically-clipped O-OFDM (ACO-OFDM) is a single-layer O-OFDM scheme, whose spectral efficiency can be enhanced by adopting multiple ACO-OFDM layers or a combination of ACO-OFDM and other O-OFDM schemes. However, since symbol detection in such enhanced ACO-OFDM (eACO-OFDM) is done iteratively, erroneous detection leads to residual clipping noise (RCN) which can degrade performance in practice. Thus, it is important to develop an accurate model for RCN which can be used to design RCN-aware eACO-OFDM schemes. To this end, this paper provides a mathematical analysis of RCN leading to an accurate model of RCN power. The obtained model is used to analyze the performance of various eACO-OFDM schemes. It is shown that the model provides an accurate evaluation of symbol error rate (SER), which would be underestimated if RCN is ignored. Moreover, the model is shown to be useful for designing an RCN-aware resource allocation that increases the robustness of the system in terms of meeting a target SER, compared to an RCN-unaware design.

preprint2020arXiv

Robust Design for IRS-Aided Communication Systems with User Location Uncertainty

In this paper, we propose a robust design framework for IRS-aided communication systems in the presence of user location uncertainty. By jointly designing the transmit beamforming vector at the BS and phase shifts at the IRS, we aim to minimize the transmit power subject to the worse-case quality of service (QoS) constraint, i.e., ensuring the user rate is above a threshold for all possible user location error realizations. With unit-modulus, this problem is not convex. The location uncertainty in the QoS constraint further increases the difficulty of solving this problem. By utilizing techniques of Taylor expansion, S-Procedure and semidefinite relaxation (SDP), we transform this problem into a sequence of semidefinite programming (SDP) sub-problems. Simulation results show that the proposed robust algorithm substantially outperforms the non-robust algorithm proposed in the literature, in terms of probability of reaching the required QoS target.

preprint2020arXiv

Secure Transmission for Intelligent Reflecting Surface-Assisted mmWave and Terahertz Systems

This letter focuses on the secure transmission for an intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) and terahertz (THz) systems, in which a base station (BS) communicates with its destination via an IRS, in the presence of a passive eavesdropper. To maximize the system secrecy rate, the transmit beamforming at the BS and the reflecting matrix at the IRS are jointly optimized with transmit power and discrete phase-shift constraints. It is first proved that the beamforming design is independent of the phase shift design under the rank-one channel assumption. The formulated non-convex problem is then converted into two subproblems, which are solved alternatively. Specifically, the closed-form solution of transmit beamforming at the BS is derived, and the semidefinite programming (SDP)-based method and element-wise block coordinate descent (BCD)-based method are proposed to design the reflecting matrix. The complexity of our proposed methods is analyzed theoretically. Simulation results reveal that the proposed IRS-assisted secure strategy can significantly boost the secrecy rate performance, regardless of eavesdropper's locations (near or blocking the confidential beam).

preprint2020arXiv

Securing Multi-User Broadcast Wiretap Channels with Finite CSI Feedback

In this work, we investigate the problem of secure broadcasting over block-fading wiretap channels with limited channel knowledge at the transmitter. More particularly, we analyze the effect of having a finite rate feedback on the throughput of multi-user broadcast wiretap channels. We consider that the transmitter is only provided by a $b$-bits feedback of the main channel state information (CSI) sent by each legitimate receiver, at the beginning of each fading block, over error-free public links with limited capacity. Also, we assume that the transmitter is aware of the statistics of the eavesdropper's CSI but not of its channel's realizations. Under these assumptions of CSI uncertainty, we characterize the ergodic secrecy capacity of the system when a common message is broadcasted to all legitimate receivers, the ergodic secrecy sum-capacity when multiple independent messages are transmitted, and the ergodic secrecy capacity region for the broadcast channel with confidential messages (BCCM). In all three scenarios, we show that as long as the transmitter has some knowledge of the main CSI, obtained even through a 1-bit CSI feedback, a non-zero secrecy rate can still be achieved. The impact of having the feedback sent over a binary erasure channel (BEC) is also investigated for the BCCM case. Here again, and even with the possibility of having the feedback bits erased, a positive secrecy rate can still be achieved as long as the erasure event is not a probability-one event. An asymptotic analysis of the obtained results is provided for the high SNR regime, and the scaling law of the system, when the number of legitimate receivers is large, is also presented.

preprint2020arXiv

Signal Shaping for Non-Uniform Beamspace Modulated mmWave Hybrid MIMO Communications

This paper investigates adaptive signal shaping methods for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications based on the maximizing the minimum Euclidean distance (MMED) criterion. In this work, we utilize the indices of analog precoders to carry information and optimize the symbol vector sets used for each analog precoder activation state. Specifically, we firstly propose a joint optimization based signal shaping (JOSS) approach, in which the symbol vector sets used for all analog precoder activation states are jointly optimized by solving a series of quadratically constrained quadratic programming (QCQP) problems. JOSS exhibits good performance, however, with a high computational complexity. To reduce the computational complexity, we then propose a full precoding based signal shaping (FPSS) method and a diagonal precoding based signal shaping (DPSS) method, where the full or diagonal digital precoders for all analog precoder activation states are optimized by solving two small-scale QCQP problems. Simulation results show that the proposed signal shaping methods can provide considerable performance gain in reliability in comparison with existing mmWave transmission solutions.

preprint2020arXiv

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead

What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

preprint2020arXiv

Spatial Firewalls: Quarantining Malware Epidemics in Large Scale Massive Wireless Networks

Billions of wireless devices are foreseen to participate in big data aggregation and smart automation in order to interface the cyber and physical worlds. Such large-scale ultra-dense wireless connectivity is vulnerable to malicious software (malware) epidemics. Malware worms can exploit multi-hop wireless connectivity to stealthily diffuse throughout the wireless network without being noticed to security servers at the core network. Compromised devices can then be used by adversaries to remotely launch cyber attacks that cause large-scale critical physical damage and threaten public safety. This article overviews the types, threats, and propagation models for malware epidemics in large-scale wireless networks (LSWN). Then, the article proposes a novel and cost efficient countermeasure against malware epidemics in LSWN, denoted as spatial firewalls. It is shown that equipping a strategically selected small portion (i.e., less than 10\%) of the devices with state-of-the-art security mechanisms is sufficient to create spatially secured zones that quarantine malware epidemics. Quarantined infected devices are then cured by on-demand localized software patching. To this end, several firewall deployment strategies are discussed and compared.

preprint2020arXiv

Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments

In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered for the imperfect IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than the phase noise of IRS. We further obtain the optimal transmit power in closed form for energy efficiency maximization. Simulation results are provided to verify these results.

preprint2020arXiv

Statistical Modeling of the Impact of Underwater Bubbles on an Optical Wireless Channel

In underwater wireless optical communications (UWOC), the random obstruction of light propagation by air bubbles can cause fluctuations in the incoming light intensity of a receiver. In this paper, we propose a statistical model for determining the received power by a receiver in the presence of air bubbles. First, based on real experiments of the behavior of air bubbles underwater, we propose statistical models for the generation, size, and horizontal distribution of each air bubble. Second, we mathematically derive the obstruction caused by the shadow of each bubble as it passes over the beam area. We then compute the combined obstruction of all generated air bubbles to determine the total obstructed power, which is a random variable due to the randomness of bubble behavior. Next, we find the first and second moments of the total obstructed power to model the statistical distribution of the obstructed received power by using the method of moments, which shows that the Weibull distribution suitably matches the simulation data. We also estimate the shape and scale parameters by using two derived moments. Furthermore, we also construct a statistical model of the received power with complete blockage in the presence of air bubbles and we derive the distribution of the composite channel model combining the proposed bubble-obstruction model with a Gamma-Gamma turbulence model. Finally, we obtain and verify the analytic forms of the average bit error rate and the capacity of UWOC systems under this newly proposed composite channel model.

preprint2020arXiv

Stochastic Geometry-based Analysis of LEO Satellite Communication Systems

This letter studies the performance of a low-earth orbit (LEO) satellite communication system where the locations of the LEO satellites are modeled as a binomial point process (BPP) on a spherical surface. In particular, we study the user coverage probability for a scenario where satellite gateways (GWs) are deployed on the ground to act as a relay between the users and the LEO satellites. We use tools from stochastic geometry to derive the coverage probability for the described setup assuming that LEO satellites are placed at n different altitudes, given that the number of satellites at each altitude ak is Nk for all k. To resemble practical scenarios where satellite communication can play an important role in coverage enhancement, we compare the performance of the considered setup with a scenario where the users are solely covered by a fiber-connected base station (referred to as anchored base station or ABS in the rest of the paper) at a relatively far distance, which is a common challenge in rural and remote areas. Using numerical results, we show the performance gain, in terms of coverage probability, at rural and remote areas when LEO satellite communication systems are adopted. Finally, we draw multiple system-level insights regarding the density of GWs required to outperform the ABS, as well as the number of LEO satellites and their altitudes.

preprint2020arXiv

The Optimal and the Greedy: Drone Association and Positioning Schemes for Internet of UAVs

This work considers the deployment of unmanned aerial vehicles (UAVs) over a predefined area to serve a number of ground users. Due to the heterogeneous nature of the network,the UAVs may cause severe interference to the transmissions of each other. Hence, a judicious design of the user-UAV association and UAV locations is desired. A potential game is defined where the players are the UAVs. The potential function is the total sum-rate of the users. The agents utility in the potential games is their marginal contribution to the global welfare or their so-called wonderful life utility. A game-theoretic learning algorithm, binary log-linear learning (BLLL), is then applied to the problem. Given the potential game structure, a consequence of our utility design, the stochastically stable states using BLLL are guaranteed to be the potential maximizers. Hence, we optimally solve the user-UAV association and 3D-location problem. Next, we exploit the sub-modular features of the sum rate function for a given configuration of UAVs to design an efficient greedy algorithm. Despite the simplicity of the greedy algorithm, it comes with a guaranteed performance of $1-1/e$ of the optimal solution. To further reduce the number of iterations, we propose another heuristic greedy algorithm that provides very good results. Our simulations show that, in practice, the proposed greedy approaches achieve significant performance in a few number of iterations.

preprint2020arXiv

Throughput Maximization of Mixed FSO/RF UAV-aided Mobile Relaying with a Buffer

In this paper, we consider an unmanned aerial vehicle (UAV) aided mobile relaying system under a buffer constraint. We propose a new relaying protocol employing mixed free-space optical/radio frequency (FSO/RF) communication, i.e., the source-relay and relay-destination links utilize FSO and RF links, respectively, under the buffer constraint at the UAV relay node. Taking the conditions of an imbalance in transmission rate between RF and FSO links into consideration, we study the trajectory optimization problem of buffer-constrained UAV relay node in order to maximize the end-to-end data throughput. Especially, we classify two relaying transmission schemes according to the delay requirements, i.e., i) delay-limited transmission and ii) delay-tolerant transmission. We solve the locally optimal trajectory problem of the UAV to maximize the throughput of ground user terminal. As a result, we propose an iterative algorithm that efficiently finds a local optimum solution for the throughput maximization problems. Through this algorithm, we present the resulting trajectories over the the atmospheric condition, the buffer size, and the delay requirement. Also, we show the optimum buffer size and the throughput-delay tradeoff for a given system. Our numerical results validate that the proposed buffer-aided mobile relaying scheme achieves 65.55% throughput gains compared to conventional static relaying scheme.

preprint2020arXiv

Topology Optimization for 6G Networks: A Network Information-Theoretic Approach

The classical approach of avoiding or ignoring interference in wireless networks cannot accommodate the ambitious quality-of-service demands of ultra-dense cellular networks (CNs). However, recent ground-breaking information-theoretic advances changed our perception of interference from a foe to a friend. This paper aims to shed light on harnessing the benefits of integrating modern interference management (IM) schemes into future CNs. To this end, we envision a hybrid multiple access (HMA) scheme that decomposes the network into sub-topologies of potential IM schemes for more efficient utilization of network resources. Preliminary results show that HMA can multiply non-orthogonal multiple access performance, especially under dense user deployment.

preprint2020arXiv

Ultra-Massive MIMO Systems at Terahertz Bands: Prospects and Challenges

Terahertz (THz)-band communications are currently being celebrated as a key technology that could fulfill the increasing demands for wireless data traffic in the upcoming sixth-generation (6G) of wireless communications. Many challenges, such as high propagation losses and power limitations, which result in short communication distances, have yet to be addressed for this technology to be realized. Ultra-massive multiple-input, multiple-output (UM-MIMO) antenna systems have emerged as practical means for combatting this distance problem, thereby increasing system capacity. Towards that end, graphene-based nano-antennas have recently been proposed, as they can be individually tuned and collectively controlled in compact UM-MIMO array-of-sub-arrays architectures. In this paper, we present a holistic overview of THz UM-MIMO systems. We assess recent advancements in transceiver design and channel modeling, and discuss the major challenges and shortcomings of such designs by deriving the relationship between communication range, array dimensions, and system performance. We further highlight several research advances that could enhance resource allocation at the THz band, including waveform designs, multi-carrier configurations, and spatial modulations. Based on this discussion, we highlight prospective use cases that can bring THz UM-MIMO into reality in the context of sensing, data centers, cell-free systems, and mid-range wireless communications.

preprint2020arXiv

Viral Aerosol Concentration Characterization and Detection in Bounded Environments

Viral spread has been intermittently threatening human life over time. Characterizing the viral concentration and modelling the viral transmission are, therefore, considered major milestones for enhancing viral detection capabilities. This paper addresses the problem of viral aerosol detection based on the exhaled breath in a bounded environment, e.g., a bounded room. The paper models the exhaled breath as a cloud which is emitted through the room continuously, and analyzes the temporal-spatial virus concentration by accounting for partial absorption and reflection at each side of the room. The paper first derives a closed form expression of the temporal-spatial virus concentration. It then considers the deployment of a receiver composed of an air sampler and a bio-sensor to detect the viral existence of a specific virus. We, therefore, assess the detection capabilities of the proposed system via evaluating the viral miss-detection probability as a function of the sampling volume and the detection time-instance at the receiver side. Our numerical simulations verify the validity of the analytical results, and illustrate the ability of the proposed system to detect viruses in indoor environments. The results further characterize the impacts of several system parameters on the miss-detection probability.

preprint2020arXiv

What should 6G be?

The standardization of fifth generation (5G) communications has been completed, and the 5G network should be commercially launched in 2020. As a result, the visioning and planning of sixth generation (6G) communications has begun, with an aim to provide communication services for the future demands of the 2030s. Here we provide a vision for 6G that could serve a research guide in the post-5G era. We suggest that human-centric mobile communications will still be the most important application of 6G and the 6G network should be human centric. Thus, high security, secrecy, and privacy should be key features of 6G and should be given particular attention by the wireless research community. To support this vision, we provide a systematic framework in which potential application scenarios of 6G are anticipated and subdivided. We subsequently define key potential features of 6G and discuss the required communication technologies. We also explore the issues beyond communication technologies that could hamper research and deployment of 6G.

preprint2020arXiv

When Full-Duplex Transmission Meets Intelligent Reflecting Surface: Opportunities and Challenges

Full-duplex (FD) transmission has already been regarded and developed as a promising method to improve the utilization efficiency of the limited spectrum resource, as transmitting and receiving are allowed to simultaneously occur on the same frequency band. Nowadays, benefiting from the recent development of intelligent reflecting surface (IRS), some unique electromagnetic (EM) functionalities, like wavefront shaping, focusing, anomalous reflection, absorption, frequency shifting, and nonreciprocity can be realized by soft-controlled elements at the IRS, showing the capability of reconfiguring the wireless propagation environment with no hardware cost and nearly zero energy consumption. To jointly exploit the virtues of both FD transmission and IRS, in this article we first introduce several EM functionalities of IRS that are profitable for FD transmission; then, some designs of FD-enabled IRS systems are proposed and discussed, followed by numerical results to demonstrate the obtained benefits. Finally, the challenges and open problems of realizing FD-enabled IRS systems are outlined and elaborated upon.

preprint2020arXiv

When Probabilistic Shaping Realizes Improper Signaling for Hardware Distortion Mitigation

Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals' geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWD and derive the optimal maximum a posterior detector. Then, we design the symbols' probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte-Carlo simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput.

preprint2020arXiv

When Wireless Communication Faces COVID-19: Combating the Pandemic and Saving the Economy

The year 2020 is experiencing a global health and economic crisis due to the COVID-19 pandemic. Countries across the world are using digital technologies to fight this global crisis. These digital technologies, in one way or another, strongly rely on the availability of wireless communication technologies. In this paper, we present the role of wireless communications in the COVID-19 pandemic from different perspectives. First, we show how these technologies are helping to combat this pandemic, including monitoring of the virus spread, enabling healthcare automation, and allowing virtual education and conferencing. Also, we show the importance of digital inclusiveness in the pandemic and possible solutions to connect the unconnected. Next, we discuss the challenges faced by wireless technologies, including privacy, security, and misinformation. Then, we present the importance of wireless communication technologies in the survival of the global economy, such as automation of industries and supply chain, e-commerce, and supporting occupations that are at risk. Finally, we reveal that how the technologies developed during the pandemic can be helpful in the post-pandemic era.

preprint2019arXiv

Frequency Diverse Array Radar: New Results and Discrete Fourier Transform Based Beampattern

In the phased-array radar (PAR) signals from each antenna are transmitted at the same carrier frequency, which yields narrowly focused only angle dependent beampattern. In contrast, in the frequency-diverse-array (FDA) radar signals from antenna array are generally transmitted at linearly increasing frequencies that yields range, time, and angle dependent beampattern. Reported literature on FDA radar missed the contribution of path-differences in the signal model due to the antenna array elements, which may lead to misleading results. In this work, incorporating missed path-differences, the signal model of FDA radar is corrected. Using the corrected signal model, it is shown that the instantaneous beampattern depends on the number of transmit antenna and average beampattern depends on the product of frequency-offset and pulse-duration. Moreover, to illuminate the desired region-of-interest for longer dwell time, discrete-Fourier-transform based low-complexity algorithm is proposed. In contrast to the conventional FDA radar's 'S' shaped beampattern, the beampattern of the proposed algorithm changes linearly with range. Simulation results compare the performance of our proposed algorithm with the existing ones and show the superiority of our proposed algorithm.

preprint2019arXiv

Risk Convergence of Centered Kernel Ridge Regression with Large Dimensional Data

This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call \emph{centered kernel ridge regression} (CKRR), also known in the literature as kernel ridge regression with offset. This modified technique is obtained by accounting for the bias in the regression problem resulting in the old kernel ridge regression but with \emph{centered} kernels. The analysis is carried out under the assumption that the data is drawn from a Gaussian distribution and heavily relies on tools from random matrix theory (RMT). Under the regime in which the data dimension and the training size grow infinitely large with fixed ratio and under some mild assumptions controlling the data statistics, we show that both the empirical and the prediction risks converge to a deterministic quantities that describe in closed form fashion the performance of CKRR in terms of the data statistics and dimensions. Inspired by this theoretical result, we subsequently build a consistent estimator of the prediction risk based on the training data which allows to optimally tune the design parameters. A key insight of the proposed analysis is the fact that asymptotically a large class of kernels achieve the same minimum prediction risk. This insight is validated with both synthetic and real data.

preprint2016arXiv

3D Massive MIMO Systems: Modeling and Performance Analysis

Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. Recently, the trend is to enhance system performance by exploiting the channel's degrees of freedom in the elevation, which necessitates the characterization of 3D channels. We present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles. Based on this model, we provide analytical expression for the cumulative density function (CDF) of the mutual information (MI) for systems with a single receive and finite number of transmit antennas in the general signal-to-interference-plus-noise-ratio (SINR) regime. The result is extended to systems with finite receive antennas in the low SINR regime. A Gaussian approximation to the asymptotic behavior of MI distribution is derived for the large number of transmit antennas and paths regime. We corroborate our analysis with simulations that study the performance gains realizable through meticulous selection of the transmit antenna downtilt angles, confirming the potential of elevation beamforming to enhance system performance. The results are directly applicable to the analysis of 5G 3D-Massive MIMO-systems.

preprint2016arXiv

Blind Measurement Selection: A Random Matrix Theory Approach

This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.

preprint2016arXiv

Can Uplink Transmissions Survive in Full-duplex Cellular Environments?

In-band full-duplex (FD) communication is considered a potential candidate to be adopted by the fifth generation (5G) cellular networks. FD communication renders the entire spectrum simultaneously accessible by uplink and downlink, and hence, is optimistically promoted to double the transmission rate. While this is true for a single communication link, cross-mode interference (i.e., interference between uplink and downlink) may diminish the full-duplexing gain. This paper studies FD operation in large-scale cellular networks with real base stations (BSs) locations and 3GPP propagation environment. The results show that the uplink is the bottleneck for FD operation due to the overwhelming cross-mode interference from BSs. Operating uplink and downlink on a common set of channels in an FD fashion improves the downlink rate but significantly degrades (over 1000-fold) the uplink rate. Therefore, we propose the $α$-duplex scheme to balance the tradeoff between the uplink and downlink rates via adjustable partial overlap between uplink and downlink channels. The $α$-duplex scheme can provide a simultaneous $30\%$ improvement in each of the uplink and downlink rates. To this end, we discuss the backward compatibility of the $α$-duplex scheme with half-duplex user-terminals. Finally, we point out future research directions for FD enabled cellular networks.

preprint2016arXiv

Cooperative Handover Management in Dense Cellular Networks

Network densification has always been an important factor to cope with the ever increasing capacity demand. Deploying more base stations (BSs) improves the spatial frequency utilization, which increases the network capacity. However, such improvement comes at the expense of shrinking the BSs' footprints, which increases the handover (HO) rate and may diminish the foreseen capacity gains. In this paper, we propose a cooperative HO management scheme to mitigate the HO effect on throughput gains achieved via cellular network densification. The proposed HO scheme relies on skipping HO to the nearest BS at some instances along the user's trajectory while enabling cooperative BS service during HO execution at other instances. To this end, we develop a mathematical model, via stochastic geometry, to quantify the performance of the proposed HO scheme in terms of coverage probability and user throughput. The results show that the proposed cooperative HO scheme outperforms the always best connected based association at high mobility. Also, the value of BS cooperation along with handover skipping is quantified with respect to the HO skipping only that has recently appeared in the literature. Particularly, the proposed cooperative HO scheme shows throughput gains of 12% to 27% and 17% on average, when compared to the always best connected and HO skipping only schemes at user velocity ranging from 80 km/h to 160 Km/h, respectively.

preprint2016arXiv

Distributed Hybrid Scheduling in Multi-Cloud Networks using Conflict Graphs

Recent studies on cloud-radio access networks assume either signal-level or scheduling-level coordination. This paper considers a hybrid coordinated scheme as a means to benefit from both policies. Consider the downlink of a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and, therefore, allows for joint signal processing within the cloud transmission. Across the multiple clouds, however, only scheduling-level coordination is permitted, as low levels of backhaul communication are feasible. The frame structure of every BS is composed of various time/frequency blocks, called power-zones (PZs), which are maintained at a fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled to a single cloud at most, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The considered scheduling problem is, then, shown to be equivalent to a maximum-weight independent set problem in the constructed graph, which can be solved using efficient techniques. The paper then proposes solving the problem using both optimal and heuristic algorithms that can be implemented in a distributed fashion across the network. The proposed distributed algorithms rely on the well-chosen structure of the constructed conflict graph utilized to solve the maximum-weight independent set problem. Simulation results suggest that the proposed optimal and heuristic hybrid scheduling strategies provide appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

preprint2016arXiv

Flexible Design for $α$-Duplex Communications in Multi-Tier Cellular Networks

Backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band full-duplex (FD) communication, FD base stations (BSs) should support half-duplex (HD) users' equipment (UEs) without sacrificing the foreseen FD gains. This paper presents flexible and tractable modeling framework for multi-tier cellular networks with FD BSs and FD/HD UEs. The presented model is based on stochastic geometry and accounts for the intrinsic vulnerability of uplink transmissions. The results show that FD UEs are not necessarily required to harvest rate gains from FD BSs. In particular, the results show that adding FD UEs to FD BSs offers a maximum of $5\%$ rate gain over FD BSs and HD UEs case if multi-user diversity is exploited, which is a marginal gain compared to the burden required to implement FD transceivers at the UEs' side. To this end, we shed light on practical scenarios where HD UEs operation with FD BSs outperforms the operation when both the BSs and UEs are FD and we find a closed form expression for the critical value of the self-interference attenuation power required for the FD UEs to outperform HD UEs.

preprint2016arXiv

Fluctuations of the SNR at the output of the MVDR with Regularized Tyler Estimators

This paper analyzes the statistical properties of the signal-to-noise ratio (SNR) at the output of the Capon's minimum variance distortionless response (MVDR) beamformers when operating over impulsive noises. Particularly, we consider the supervised case in which the receiver employs the regularized Tyler estimator in order to estimate the covariance matrix of the interference-plus-noise process using $n$ observations of size $N\times 1$. The choice for the regularized Tylor estimator (RTE) is motivated by its resilience to the presence of outliers and its regularization parameter that guarantees a good conditioning of the covariance estimate. Of particular interest in this paper is the derivation of the second order statistics of the SINR. To achieve this goal, we consider two different approaches. The first one is based on considering the classical regime, referred to as the $n$-large regime, in which $N$ is assumed to be fixed while $n$ grows to infinity. The second approach is built upon recent results developed within the framework of random matrix theory and assumes that $N$ and $n$ grow large together. Numerical results are provided in order to compare between the accuracies of each regime under different settings.

preprint2016arXiv

Handover Management in Dense Cellular Networks: A Stochastic Geometry Approach

Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios.

preprint2016arXiv

Harvesting Full-Duplex Rate Gains in Cellular Networks with Half-Duplex User Terminals

Full-Duplex (FD) transceivers may be expensive in terms of complexity, power consumption, and price to be implemented in all user terminals. Therefore, techniques to exploit in-band full-duplex communication with FD base stations (BSs) and half-duplex (HD) users' equipment (UEs) are required. In this context, 3-node topology (3NT) has been recently proposed for FD BSs to reuse the uplink (UL) and downlink (DL) channels with HD terminals within the same cell. In this paper, we present a tractable mathematical framework, based on stochastic geometry, for 3NT in cellular networks. To this end, we propose a design paradigm via pulse-shaping and partial overlap between UL and DL channels to maximize the harvested rate gains in 3NT. The results show that 3NT achieves a close performance to networks with FD BSs and FD UEs, denoted by 2-node topology (2NT) networks. A maximum of 5$\%$ rate loss is reported when 3NT is compared to 2NT with efficient self-interference cancellation (SIC). If the SIC in 2NT is not efficient, 3NT highly outperforms 2NT. Consequently, we conclude that, irrespective to the UE duplexing scheme, it is sufficient to have FD BSs to harvest FD rate gains.

preprint2016arXiv

Improper Gaussian Signaling in Full-Duplex Relay Channels with Residual Self-Interference

We study the potential employment of improper Gaussian signaling (IGS) in full-duplex cooperative settings with residual self-interference (RSI). IGS is recently shown to outperform traditional proper Gaussian signaling (PGS) in several interference-limited channel settings. In this work, IGS is employed in an attempt to alleviate the RSI adverse effect in full-duplex relaying (FDR). To this end, we derive a tight upper bound expression for the end-to-end outage probability in terms of the relay signal parameters represented in its power and circularity coefficient. We further show that the derived upper bound is either monotonic or unimodal in the relay's circularity coefficient. This result allows for easily locating the global optimal point using known numerical methods. Based on the analysis, IGS allows FDR systems to operate even with high RSI. It is shown that, while the communication totally fails with PGS as the RSI increases, the IGS outage probability approaches a fixed value that depends on the channel statistics and target rate. The obtained results show that IGS can leverage higher relay power budgets than PGS to improve the performance, meanwhile it relieves its RSI impact via tuning the signal impropriety.

preprint2016arXiv

In-Band $α$-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach

In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This paper presents a tractable framework, based on stochastic geometry, to study FD communications in cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that the improved FD rate gains harvested in the downlink (up to $97\%$) comes at the expense of a significant degradation in the uplink rate (up to $94\%$). Therefore, we propose a novel fine-grained duplexing scheme, denoted as $α$-duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the $α$-duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the $α$-duplex scheme provides a simultaneous improvement of $28\%$ for the downlink rate and $56\%$ for the uplink rate. Finally, we show that the amount of the overlap can be optimized based on the network design objective.

preprint2016arXiv

Joint Hybrid Backhaul and Access Links Design in Cloud-Radio Access Networks

The cloud-radio access network (CRAN) is expected to be the core network architecture for next generation mobile radio systems. In this paper, we consider the downlink of a CRAN formed of one central processor (the cloud) and several base-station (BS), where each BS is connected to the cloud via either a wireless or capacity-limited wireline backhaul link. The paper addresses the joint design of the hybrid backhaul links (i.e., designing the wireline and wireless backhaul connections from the cloud to the BSs) and the access links (i.e., determining the sparse beamforming solution from the BSs to the users). The paper formulates the hybrid backhaul and access link design problem by minimizing the total network power consumption. The paper solves the problem using a two-stage heuristic algorithm. At one stage, the sparse beamforming solution is found using a weighted mixed `1=`2 norm minimization approach; the correlation matrix of the quantization noise of the wireline backhaul links is computed using the classical rate-distortion theory. At the second stage, the transmit powers of the wireless backhaul links are found by solving a power minimization problem subject to quality-of-service constraints, based on the principle of conservation of rate by utilizing the rates found in the first stage. Simulation results suggest that the performance of the proposed algorithm approaches the global optimum solution, especially at high signal-to-interference-plus-noise ratio (SINR).

preprint2016arXiv

Mobility-Aware Modeling and Analysis of Dense Cellular Networks with C-plane/U-plane Split Architecture

The unrelenting increase in the population of mobile users and their traffic demands drive cellular network operators to densify their network infrastructure. Network densification shrinks the footprint of base stations (BSs) and reduces the number of users associated with each BS, leading to an improved spatial frequency reuse and spectral efficiency, and thus, higher network capacity. However, the densification gain come at the expense of higher handover rates and network control overhead. Hence, users mobility can diminish or even nullifies the foreseen densification gain. In this context, splitting the control plane (C-plane) and user plane (U-plane) is proposed as a potential solution to harvest densification gain with reduced cost in terms of handover rate and network control overhead. In this article, we use stochastic geometry to develop a tractable mobility-aware model for a two-tier downlink cellular network with ultra-dense small cells and C-plane/U-plane split architecture. The developed model is then used to quantify the effect of mobility on the foreseen densification gain with and without C-plane/U-plane split. To this end, we shed light on the handover problem in dense cellular environments, show scenarios where the network fails to support certain mobility profiles, and obtain network design insights.

preprint2016arXiv

Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a basic cellular network model. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the baseline unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. Finally, we point out future research directions.

preprint2016arXiv

Modeling Cellular Networks in Fading Environments with Dominant Specular Components

Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency.

preprint2016arXiv

On The Construction of Capacity-Achieving Lattice Gaussian Codes

In this paper, we propose a new approach to proving results regarding channel coding schemes based on construction-A lattices for the Additive White Gaussian Noise (AWGN) channel that yields new characterizations of the code construction parameters, i.e., the primes and dimensions of the codes, as functions of the block-length. The approach we take introduces an averaging argument that explicitly involves the considered parameters. This averaging argument is applied to a generalized Loeliger ensemble to provide a more practical proof of the existence of AWGN-good lattices, and to characterize suitable parameters for the lattice Gaussian coding scheme proposed by Ling and Belfiore.

preprint2016arXiv

On the Performance of Millimeter Wave-based RF-FSO Links with HARQ Feedback

This paper studies the performance of hybrid radio-frequency (RF) and free-space optical (FSO) links in the cases with and without hybrid automatic repeat request (HARQ). Considering millimeter wave (mmwave) characteristics in the RF link and pointing errors in the FSO link, we derive closed-form expressions for the message decoding probabilities as well as the throughput and the outage probability of the RF-FSO setups. We also evaluate the effect of various parameters such as power amplifiers efficiency, different transmission techniques in the FSO link, pointing errors in the FSO link as well as different coherence times/symbol rates of the RF and the FSO links on the throughput and outage probability. The results show the efficiency of the RF-FSO links in different conditions. Moreover, the HARQ can effectively improve the outage probability/energy efficiency, and compensate the effect of hardware impairments in RF-FSO links.

preprint2016arXiv

On the Performance of RF-FSO Links with and without Hybrid ARQ

This paper studies the performance of hybrid radio-frequency (RF) and free-space optical (FSO) links assuming perfect channel state information (CSI) at the receiver. Considering the cases with and without hybrid automatic repeat request (HARQ), we derive closed-form expressions for the message decoding probabilities as well as the throughput and the outage probability of the RF-FSO setups. We also evaluate the effect of adaptive power allocation and different channel conditions on the throughput and the outage probability. The results show the efficiency of the RF-FSO links in different conditions.

preprint2016arXiv

On the Secrecy Capacity of the Broadcast Wiretap Channel with Limited CSI Feedback

In this paper, we investigate the problem of secure broadcasting over block-fading channels with limited channel knowledge at the transmitter. More particularly, we analyze the effect of having imperfect channel state information (CSI) via a finite rate feedback on the throughput of a broadcast channel where the transmission is intended for multiple legitimate receivers in the presence of an eavesdropper. First, we partially characterize the ergodic secrecy capacity of the system when the source broadcasts the same information to all the receivers, i.e., common message transmission. Then, we look at the independent messages case, where the transmitter broadcasts multiple independent messages to the legitimate receivers. For this case, we present lower and upper bounds on the ergodic secrecy sum-capacity. In both scenarios, we show that the proposed lower and upper bounds coincide asymptotically as the capacity of the feedback links becomes large, hence, fully characterizing the secrecy capacity in this case.

preprint2016arXiv

Performance Analysis of ARQ-based RF-FSO Links

In this letter, we study the performance of hybrid radio-frequency (RF) and free-space optical (FSO) links using automatic repeat request (ARQ). We derive closed-form expressions for the message decoding probabilities, throughput, and outage probability with different relative coherence times of the RF and FSO links. We also evaluate the effect of adaptive power allocation between the ARQ retransmissions on the system performance. The results show that joint implementation of the RF and FSO links leads to substantial performance improvement, compared to the cases with only the RF or the FSO link.

preprint2016arXiv

Precoding design for single-RF massive MIMO systems: A large system analysis

This work revisits a recently proposed precoding design for massive multiple-input multiple output (MIMO) systems that is based on the use of an instantaneous total power constraint. The main advantages of this technique lie in its suitability to single RF MIMO systems coupled with a very-high power efficiency. Such features have been proven using simulations for uncorrelated channels. Based on tools from random matrix theory, we propose in this work to analyze the performance of this precoder for more involved channels accounting for spatial correlation. The obtained expressions are then optimized in order to maximize the signal-to-interference-plus-noise ratio (SINR). Simulation results are provided in order to illustrate the performance of the optimized precoder in terms of peak-to-average power ratio (PAPR) and signal-to-interference-plus-noise ratio (SINR).

preprint2016arXiv

Robust Beamforming in Cache-Enabled Cloud Radio Access Networks

Popular content caching is expected to play a major role in efficiently reducing backhaul congestion and achieving user satisfaction in next generation mobile radio systems. Consider the downlink of a cache-enabled cloud radio access network (CRAN), where each cache-enabled base station (BS) is equipped with limited-size local cache storage. The central computing unit (cloud) is connected to the BSs via a limited capacity backhaul link and serves a set of single-antenna mobile users (MUs). This paper assumes that only imperfect channel state information (CSI) is available at the cloud. It focuses on the problem of minimizing the total network power and backhaul cost so as to determine the beamforming vector of each user across the network, the quantization noise covariance matrix, and the BS clustering subject to imperfect channel state information and fixed cache placement assumptions. The paper suggests solving such a difficult, non-convex optimization problem using the semidefinite relaxation (SDR). The paper then uses the $\ell_0$-norm approximation to provide a feasible, sub-optimal solution using the majorization-minimization (MM) approach. Simulation results particularly show how the cache-enabled network significantly improves the backhaul cost especially at high signal-to-interference-plus-noise ratio (SINR) values as compared to conventional cache-less CRANs.

preprint2016arXiv

Tractable Stochastic Geometry Model for IoT Access in LTE Networks

The Internet of Things (IoT) is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the high volumes of traffic that must be accommodated. Cellular networks are indeed a natural candidate for the data tsunami the IoT is expected to generate in conjunction with legacy human-type traffic. However, the random access process for scheduling request represents a major bottleneck to support IoT via LTE cellular networks. Accordingly, this paper develops a mathematical framework to model and study the random access channel (RACH) scalability to accommodate IoT traffic. The developed model is based on stochastic geometry and discrete time Markov chains (DTMC) to account for different access strategies and possible sources of inter-cell and intra-cell interferences. To this end, the developed model is utilized to assess and compare three different access strategies, which incorporate a combination of transmission persistency, back-off, and power ramping. The analysis and the results showcased herewith clearly illustrate the vulnerability of the random access procedure as the IoT intensity grows. Finally, the paper offers insights into effective scenarios for each transmission strategy in terms of IoT intensity and RACH detection thresholds.

preprint2016arXiv

Underlay Spectrum Sharing Techniques with In-band Full-Duplex Systems using Improper Gaussian Signaling

Sharing the spectrum with in-band full-duplex (FD) primary users (PU) is a challenging and interesting problem in the underlay cognitive radio (CR) systems. The self-interference introduced at the primary network may dramatically impede the secondary user (SU) opportunity to access the spectrum. To tackle this problem, we use the so-called improper Gaussian signaling. Particularly, we assume a system with a SU pair working in a half-duplex mode that uses improper Gaussian signaling while the FD PU pair implements the regular proper Gaussian signaling. First, we derive a closed form expression and an upper bound for the SU and PU outage probabilities, respectively. Second, we optimize the SU signal parameters to minimize its outage probability while maintaining the required PU quality-of-service based on the average channel state information (CSI). Moreover, we provide the conditions to reap merits from employing improper Gaussian signaling at the SU. Third, we design the SU signal parameters based on perfect knowledge of its direct link instantaneous CSI and investigate all benefits that can be achieved at both the SU and PU. Finally, we provide some numerical results that demonstrate the advantages of using improper Gaussian signaling to access the spectrum of the FD PU.

preprint2016arXiv

Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

preprint2016arXiv

Velocity-Aware Handover Management in Two-Tier Cellular Networks

While network densification is considered an important solution to cater the ever-increasing capacity demand, its effect on the handover (HO) rate is overlooked. In dense 5G networks, HO delays may neutralize or even negate the gains offered by network densification. Hence, user mobility imposes a nontrivial challenge to harvest capacity gains via network densification. In this paper, we propose a velocity-aware HO management scheme for two-tier downlink cellular network to mitigate the HO effect on the foreseen densification throughput gains. The proposed HO scheme sacrifices the best BS connectivity, by skipping HO to some BSs along the user's trajectory, to maintain longer connection durations and reduce HO rates. Furthermore, the proposed scheme enables cooperative BS service and strongest interference cancellation to compensate for skipping the best connectivity. To this end, we consider different HO skipping scenarios and develop a velocity-aware mathematical model, via stochastic geometry, to quantify the performance of the proposed HO scheme in terms of the coverage probability and user throughput. The results highlight the HO rate problem in dense cellular environments and show the importance of the proposed HO schemes. Finally, the value of BS cooperation along with handover skipping is quantified for different user mobility profiles.

preprint2015arXiv

A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums

Previous studies have confirmed the adverse impact of fading correlation on the mutual information (MI) of two-dimensional (2D) multiple-input multiple-output (MIMO) systems. More recently, the trend is to enhance the system performance by exploiting the channel's degrees of freedom in the elevation, which necessitates the derivation and characterization of three-dimensional (3D) channels in the presence of spatial correlation. In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for 3D MIMO channels. This novel SCF is developed for a uniform linear array of antennas with nonisotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. The resulting expression depends on the underlying arbitrary angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. The developed SCF determines the covariance matrices at the transmitter and the receiver that form the Kronecker channel model. In order to quantify the effects of correlation on the system performance, the information-theoretic deterministic equivalents of the MI for the Kronecker model are utilized in both mono-user and multi-user cases. Numerical results validate the proposed analytical expressions and elucidate the dependence of the system performance on azimuth and elevation angular spreads and antenna patterns. Some useful insights into the behaviour of MI as a function of downtilt angles are provided. The derived model will help evaluate the performance of correlated 3D MIMO channels in the future.

preprint2015arXiv

A Graph Model for Opportunistic Network Coding

Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.

preprint2015arXiv

An Improved Hazard Rate Twisting Approach for the Statistic of the Sum of Subexponential Variates (Extended Version)

In this letter, we present an improved hazard rate twisting technique for the estimation of the probability that a sum of independent but not necessarily identically distributed subexponential Random Variables (RVs) exceeds a given threshold. Instead of twisting all the components in the summation, we propose to twist only the RVs which have the biggest impact on the right-tail of the sum distribution and keep the other RVs unchanged. A minmax approach is performed to determine the optimal twisting parameter which leads to an asymptotic optimality criterion. Moreover, we show through some selected simulation results that our proposed approach results in a variance reduction compared to the technique where all the components are twisted.

preprint2015arXiv

Analytical Derivation of the Inverse Moments of One-sided Correlated Gram Matrices with Applications

This paper addresses the development of analytical tools for the computation of the moments of random Gram matrices with one side correlation. Such a question is mainly driven by applications in signal processing and wireless communications wherein such matrices naturally arise. In particular, we derive closed-form expressions for the inverse moments and show that the obtained results can help approximate several performance metrics such as the average estimation error corresponding to the Best Linear Unbiased Estimator (BLUE) and the Linear Minimum Mean Square Error LMMSE or also other loss functions used to measure the accuracy of covariance matrix estimates.

preprint2015arXiv

Convergence and Fluctuations of Regularized Tyler Estimators

This article studies the behavior of regularized Tyler estimators (RTEs) of scatter matrices. The key advantages of these estimators are twofold. First, they guarantee by construction a good conditioning of the estimate and second, being a derivative of robust Tyler estimators, they inherit their robustness properties, notably their resilience to the presence of outliers. Nevertheless, one major problem that poses the use of RTEs in practice is represented by the question of setting the regularization parameter $ρ$. While a high value of $ρ$ is likely to push all the eigenvalues away from zero, it comes at the cost of a larger bias with respect to the population covariance matrix. A deep understanding of the statistics of RTEs is essential to come up with appropriate choices for the regularization parameter. This is not an easy task and might be out of reach, unless one considers asymptotic regimes wherein the number of observations $n$ and/or their size $N$ increase together. First asymptotic results have recently been obtained under the assumption that $N$ and $n$ are large and commensurable. Interestingly, no results concerning the regime of $n$ going to infinity with $N$ fixed exist, even though the investigation of this assumption has usually predated the analysis of the most difficult $N$ and $n$ large case. This motivates our work. In particular, we prove in the present paper that the RTEs converge to a deterministic matrix when $n\to\infty$ with $N$ fixed, which is expressed as a function of the theoretical covariance matrix. We also derive the fluctuations of the RTEs around this deterministic matrix and establish that these fluctuations converge in distribution to a multivariate Gaussian distribution with zero mean and a covariance depending on the population covariance and the parameter $ρ$.

preprint2015arXiv

Delay Reduction in Multi-Hop Device-to-Device Communication using Network Coding

This paper considers the problem of reducing the broadcast decoding delay of wireless networks using instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In a D2D configuration, devices in the network can help hasten the recovery of the lost packets of other devices in their transmission range by sending network coded packets. Unlike previous works that assumed fully connected network, this paper proposes a partially connected configuration in which the decision should be made not only on the packet combinations but also on the set of transmitting devices. First, the different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. The joint optimization problem over the set of transmitting devices and the packet combinations of each is, then, formulated. The optimal solution of the joint optimization problem is derived using a graph theory approach by introducing the cooperation graph and reformulating the problem as a maximum weight clique problem in which the weight of each vertex is the contribution of the device identified by the vertex. Through extensive simulations, the decoding delay experienced by all devices in the Point to Multi-Point (PMP) configuration, the fully connected D2D (FC-D2D) configuration and the more practical partially connected D2D (PC-D2D) configuration are compared. Numerical results suggest that the PC-D2D outperforms the FC-D2D and provides appreciable gain especially for poorly connected networks.

preprint2015arXiv

Distributed Cloud Association in Downlink Multicloud Radio Access Networks

This paper considers a multicloud radio access network (M-CRAN), wherein each cloud serves a cluster of base-stations (BS's) which are connected to the clouds through high capacity digital links. The network comprises several remote users, where each user can be connected to one (and only one) cloud. This paper studies the user-to-cloud-assignment problem by maximizing a network-wide utility subject to practical cloud connectivity constraints. The paper solves the problem by using an auction-based iterative algorithm, which can be implemented in a distributed fashion through a reasonable exchange of information between the clouds. The paper further proposes a centralized heuristic algorithm, with low computational complexity. Simulations results show that the proposed algorithms provide appreciable performance improvements as compared to the conventional cloud-less assignment solutions.

preprint2015arXiv

Extended Delivery Time Analysis for Cognitive Packet Transmission with Application to Secondary Queuing Analysis

Cognitive radio transceiver can opportunistically access the underutilized spectrum resource of primary systems for new wireless services. With interleave implementation, the secondary transmission may be interrupted by the primary user's transmission. To facilitate the delay analysis of such secondary transmission for a fixed-size secondary packet, we study the resulting extended delivery time that includes both transmission time and waiting time. In particular, we derive the exact distribution function of extended delivery time of secondary transmission for both continuous sensing and periodic sensing cases. Selected numerical and simulation results are presented for illustrating the mathematical formulation. Finally, we consider a generalized M/G/1 queue set-up at the secondary user and formulate the closed-form expressions for the expected delay with Poisson traffic. The analytical results will greatly facilitate the design of the secondary system for particular target application.

preprint2015arXiv

Hybrid Radio/Free-Space Optical Design for Next Generation Backhaul Systems

The deluge of date rate in today's networks imposes a cost burden on the backhaul network design. Developing cost efficient backhaul solutions becomes an exciting, yet challenging, problem. Traditional technologies for backhaul networks include either radio-frequency backhauls (RF) or optical fibers (OF). While RF is a cost-effective solution as compared to OF, it supports lower data rate requirements. Another promising backhaul solution is the free-space optics (FSO) as it offers both a high data rate and a relatively low cost. FSO, however, is sensitive to nature conditions, e.g., rain, fog, line-of-sight. This paper combines both RF and FSO advantages and proposes a hybrid RF/FSO backhaul solution. It considers the problem of minimizing the cost of the backhaul network by choosing either OF or hybrid RF/FSO backhaul links between the base-stations (BS) so as to satisfy data rate, connectivity, and reliability constraints. It shows that under a specified realistic assumption about the cost of OF and hybrid RF/FSO links, the problem is equivalent to a maximum weight clique problem, which can be solved with moderate complexity. Simulation results show that the proposed solution shows a close-to-optimal performance, especially for practical prices of the hybrid RF/FSO links.

preprint2015arXiv

Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

In the context of resource allocation in cloud-radio access networks, recent studies assume either signal-level or scheduling-level coordination. This paper, instead, considers a hybrid level of coordination for the scheduling problem in the downlink of a multi-cloud radio-access network, as a means to benefit from both scheduling policies. Consider a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and therefore allows joint signal processing between them. Across the multiple clouds, however, only scheduling-level coordination is permitted, as it requires a lower level of backhaul communication. The frame structure of every BS is composed of various time/frequency blocks, called power-zones (PZs), and kept at fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled, at most, to a single cloud, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The scheduling problem is, then, shown to be equivalent to a maximum-weight independent set problem in the constructed graph, in which each vertex symbolizes an association of cloud, user, BS and PZ, with a weight representing the utility of that association. Simulation results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

preprint2015arXiv

In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as $α$-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting $α$ to achieve a certain design objective.

preprint2015arXiv

Interference Management with Partial Uplink/Downlink Spectrum Overlap

Simultaneous reuse of spectral resources by uplink and downlink, denoted as in-band full duplex (FD) communication, is promoted to double the spectral efficiency when compared to its half-duplex (HD) counterpart. Interference management, however, remains challenging in FD cellular networks, especially when high disparity between uplink and downlink transmission powers exists. The uplink performance can be particularly deteriorated when operating on channels that are simultaneously occupied with downlink transmission. This paper considers a cellular wireless system with partial spectrum overlap between the downlink and uplink. The performance of the system becomes, therefore, a function of the overlap fraction, as well as the power level of both the uplink and downlink transmissions. The paper considers the problem of maximizing an overall network utility to find the uplink/downlink transmission powers and the spectrum overlap fraction between the uplink and downlink spectrum in each cell, and proposes solving the problem using interior point method. Simulations results confirm the vulnerability of the uplink performance to the FD operation, and show the superiority of the proposed scheme over the FD and HD schemes. The results further show that explicit uplink and downlink performance should be considered for efficient design of cellular networks with overlapping uplink/downlink resources.

preprint2015arXiv

Limits on the Capacity of In-Band Full Duplex Communication in Uplink Cellular Networks

Simultaneous co-channel transmission and reception, denoted as in-band full duplex (FD) communication, has been promoted as an attractive solution to improve the spectral efficiency of cellular networks. However, in addition to the self-interference problem, cross-mode interference (i.e., between uplink and downlink) imposes a major obstacle for the deployment of FD communication in cellular networks. More specifically, the downlink to uplink interference represents the performance bottleneck for FD operation due to the uplink limited transmission power and venerable operation when compared to the downlink counterpart. While the positive impact of FD communication to the downlink performance has been proved in the literature, its effect on the uplink transmission has been neglected. This paper focuses on the effect of downlink interference on the uplink transmission in FD cellular networks in order to see whether FD communication is beneficial for the uplink transmission or not, and if yes for which type of network. To quantify the expected performance gains, we derive a closed form expression of the maximum achievable uplink capacity in FD cellular networks. In contrast to the downlink capacity which always improves with FD communication, our results show that the uplink performance may improve or degrade depending on the associated network parameters. Particularly, we show that the intensity of base stations (BSs) has a more prominent effect on the uplink performance than their transmission power.

preprint2015arXiv

MGF Approach to the Analysis of Generalized Two-Ray Fading Models

We analyze a class of Generalized Two-Ray (GTR) fading channels that consist of two line of sight (LOS) components with random phase plus a diffuse component. We derive a closed form expression for the moment generating function (MGF) of the signal-to-noise ratio (SNR) for this model, which greatly simplifies its analysis. This expression arises from the observation that the GTR fading model can be expressed in terms of a conditional underlying Rician distribution. We illustrate the approach to derive simple expressions for statistics and performance metrics of interest such as the amount of fading, the level crossing rate, the symbol error rate, and the ergodic capacity in GTR fading channels. We also show that the effect of considering a more general distribution for the phase difference between the LOS components has an impact on the average SNR.

preprint2015arXiv

New Results On the Sum of Two Generalized Gaussian Random Variables

We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented.

preprint2015arXiv

On the Required Number of Antennas in a Point-to-Point Large-but-Finite MIMO System: Outage-Limited Scenario

This paper investigates the performance of the point-to-point multiple-input-multiple-output (MIMO) systems in the presence of a large but finite numbers of antennas at the transmitters and/or receivers. Considering the cases with and without hybrid automatic repeat request (HARQ) feedback, we determine the minimum numbers of the transmit/receive antennas which are required to satisfy different outage probability constraints. Our results are obtained for different fading conditions and the effect of the power amplifiers efficiency on the performance of the MIMO-HARQ systems is analyzed. Moreover, we derive closed-form expressions for the asymptotic performance of the MIMO-HARQ systems when the number of antennas increases. Our analytical and numerical results show that different outage requirements can be satisfied with relatively few transmit/receive antennas.

preprint2015arXiv

Optimal Design of the Adaptive Normalized Matched Filter Detector

This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the scatter estimates to be greater than a positive regularization parameter rho. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. While an increase of rho seems to improve the conditioning of the estimate, it might however cause it to significantly deviate from the true covariance matrix. The setting of the optimal regularization parameter is a difficult question for which no convincing answers have thus far been provided. This constitutes the major motivation behind our work. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), appropriate when the clutter follows a Gaussian distribution and the regularized Tyler estimator (RTE) for non-Gaussian spherically invariant distributed clutters. Based on recent random matrix theory results studying the asymptotic fluctuations of the statistics of the ANMF detector when the number of samples and their dimension grow together to infinity, we propose a design for the regularization parameter that maximizes the detection probability under constant false alarm rates. Simulation results which support the efficiency of the proposed method are provided in order to illustrate the gain of the proposed optimal design over conventional settings of the regularization parameter.

preprint2015arXiv

Rate Aware Instantly Decodable Network Codes

This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications and abstract the model as equally slotted time for all users, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The consideration of asymmetric rates for receivers reflects more practical application scenarios and introduces a new trade-off between the choice of coding combinations for various receivers and the broadcasting rate for achieving shorter completion time. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. The highest weight clique in the created graph being potentially not unique, the paper further suggests a multi-layer version of the proposed solution to improve the obtained results from the employed completion time approximation. Simulation results indicate that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme.

preprint2015arXiv

Resilient Backhaul Network Design Using Hybrid Radio/Free-Space Optical Technology

The radio-frequency (RF) technology is a scalable solution for the backhaul planning. However, its performance is limited in terms of data rate and latency. Free Space Optical (FSO) backhaul, on the other hand, offers a higher data rate but is sensitive to weather conditions. To combine the advantages of RF and FSO backhauls, this paper proposes a cost-efficient backhaul network using the hybrid RF/FSO technology. To ensure a resilient backhaul, the paper imposes a given degree of redundancy by connecting each node through $K$ link-disjoint paths so as to cope with potential link failures. Hence, the network planning problem considered in this paper is the one of minimizing the total deployment cost by choosing the appropriate link type, i.e., either hybrid RF/FSO or optical fiber (OF), between each couple of base-stations while guaranteeing $K$ link-disjoint connections, a data rate target, and a reliability threshold. The paper solves the problem using graph theory techniques. It reformulates the problem as a maximum weight clique problem in the planning graph, under a specified realistic assumption about the cost of OF and hybrid RF/FSO links. Simulation results show the cost of the different planning and suggest that the proposed heuristic solution has a close-to-optimal performance for a significant gain in computation complexity.

preprint2015arXiv

Robust Node Estimation and Topology Discovery Algorithm in Large-Scale Wireless Sensor Networks

This paper introduces a novel algorithm for cardinality, i.e., the number of nodes, estimation in large scale anonymous graphs using statistical inference methods. Applications of this work include estimating the number of sensor devices, online social users, active protein cells, etc. In anonymous graphs, each node possesses little or non-existing information on the network topology. In particular, this paper assumes that each node only knows its unique identifier. The aim is to estimate the cardinality of the graph and the neighbours of each node by querying a small portion of them. While the former allows the design of more efficient coding schemes for the network, the second provides a reliable way for routing packets. As a reference for comparison, this work considers the Best Linear Unbiased Estimators (BLUE). For dense graphs and specific running times, the proposed algorithm produces a cardinality estimate proportional to the BLUE. Furthermore, for an arbitrary number of iterations, the estimate converges to the BLUE as the number of queried nodes tends to the total number of nodes in the network. Simulation results confirm the theoretical results by revealing that, for a moderate running time, asking a small group of nodes is sufficient to perform an estimation of 95% of the whole network.

preprint2015arXiv

Sharing the Licensed Spectrum of Full-Duplex Systems using Improper Gaussian Signaling

Sharing the spectrum with in-band full-duplex (FD) primary users (PU) is a challenging and interesting problem in the underlay cognitive radio (CR) systems. The self-interference introduced at the primary network may dramatically impede the secondary user (SU) opportunity to access the spectrum. In this work, we attempt to tackle this problem through the use of the so-called improper Gaussian signaling. Such a signaling technique has demonstrated its superiority in improving the overall performance in interference limited networks. Particularly, we assume a system with a SU pair working in half-duplex mode that uses improper Gaussian signaling while the FD PU pair implements the regular proper Gaussian signaling techniques. First, we derive a closed form expression for the SU outage probability and an upper bound for the PU outage probability. Then, we optimize the SU signal parameters to minimize its outage probability while maintaining the required PU quality-of-service based on the average channel state information. Finally, we provide some numerical results that validate the tightness of the PU outage probability bound and demonstrate the advantage of employing the improper Gaussian signaling to the SU in order to access the spectrum of the FD PU.

preprint2015arXiv

Spectrum Sharing Opportunities of Full-Duplex Systems using Improper Gaussian Signaling

Sharing the licensed spectrum of full-duplex (FD) primary users (PU) brings strict limitations on the underlay cognitive radio operation. Particularly, the self interference may overwhelm the PU receiver and limit the opportunity of secondary users (SU) to access the spectrum. Improper Gaussian signaling (IGS) has demonstrated its superiority in improving the performance of interference channel systems. Throughout this paper, we assume a FD PU pair that uses proper Gaussian signaling (PGS), and a half-duplex SU pair that uses IGS. The objective is to maximize the SU instantaneous achievable rate while meeting the PU quality-of-service. To this end, we propose a simplified algorithm that optimizes the SU signal parameters, i.e, the transmit power and the circularity coefficient, which is a measure of the degree of impropriety of the SU signal, to achieve the design objective. Numerical results show the merits of adopting IGS compared with PGS for the SU especially with the existence of week PU direct channels and/or strong SU interference channels.

preprint2014arXiv

A Fast Simulation Method for the Sum of Subexponential Distributions

Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. Closed-form expression of the sum distribution is usually intractable and presents an open problem. A crude Monte Carlo (MC) simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive especially when dealing with rare events (i.e events with very small probabilities). Importance Sampling (IS) is an alternative approach which effectively improves the computational efficiency of the MC simulation. In this paper, we develop a general framework based on IS approach for the efficient estimation of the probability that the sum of independent and not necessarily identically distributed heavy-tailed RVs exceeds a given threshold. The proposed IS approach is based on constructing a new sampling distribution by twisting the hazard rate of the original underlying distribution of each component in the summation. A minmax approach is carried out for the determination of the twisting parameter, for any given threshold. Moreover, using this minmax optimal choice, the estimation of the probability of interest is shown to be asymptotically optimal as the threshold goes to infinity. We also offer some selected simulation results illustrating first the efficiency of the proposed IS approach compared to the naive MC simulation. The near-optimality of the minmax approach is then numerically analyzed.

preprint2014arXiv

A Game Theoretic Approach to Minimize the Completion Time of Network Coded Cooperative Data Exchange

In this paper, we introduce a game theoretic framework for studying the problem of minimizing the completion time of instantly decodable network coding (IDNC) for cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is employed herein as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. We model the session by self-interested players in a non-cooperative potential game. The utility function is designed such that increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Pareto optimal solution. Through extensive simulations, our approach is compared to the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process. Numerical results show that our formulation largely outperforms the conventional PMP scheme in most practical situations and achieves a lower delay.

preprint2014arXiv

A Game-Theoretic Framework for Decentralized Cooperative Data Exchange using Network Coding

In this paper, we introduce a game theoretic framework for studying the problem of minimizing the delay of instantly decodable network coding (IDNC) for cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is employed herein as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. We model the session by self-interested players in a non-cooperative potential game. The utility functions are designed such that increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash bargaining solution. Three games are developed: the first aims to reduce the completion time, the second to reduce the maximum decoding delay and the third the sum decoding delay. We improve these formulations to include punishment policy upon collision occurrence and achieve the Nash bargaining solution. Through extensive simulations, our framework is tested against the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process in numerous cases: first we simulate the problem with complete information. We, then, simulate with incomplete information and finally we test it in lossy feedback scenario. Numerical results show that our formulation with complete information largely outperforms the conventional PMP scheme in most situations and achieves a lower delay. They also show that the completion time formulation with incomplete information also outperforms the conventional PMP.

preprint2014arXiv

Completion Time Reduction in Instantly Decodable Network Coding Through Decoding Delay Control

For several years, the completion time and decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users' and overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we design a novel heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.

preprint2014arXiv

Consumption Factor Optimization for Multihop Relaying over Nakagami-m Fading channels

In this paper, the energy efficiency of multihop relaying over Nakagami-$m$ fading channels is investigated. The "consumption factor" is used as a metric to evaluate the energy efficiency, and it is derived in closed-form for both amplify-and-forward and decode-and-forward relaying. Then, based on the obtained expressions, we propose a power allocation strategy maximizing the consumption factor. In addition, two sub-optimal, low complexity, power allocation algorithms are proposed and analyzed, and the obtained power allocation schemes are compared, in terms of energy efficiency as well as other common performance metrics, to other power allocation schemes from the literature. Analytical and simulation results confirm the accuracy of our derivations, and assess the performance gains of the proposed approach.

preprint2014arXiv

Coordinated Hybrid Automatic Repeat Request; Extended Version

We develop a coordinated hybrid automatic repeat request (HARQ) approach. With the proposed scheme, if a user message is correctly decoded in the first HARQ rounds, its spectrum is allocated to other users, to improve the network outage probability and the users' fairness. The results, which are obtained for single- and multiple-antenna setups, demonstrate the efficiency of the proposed approach in different conditions. For instance, with a maximum of M retransmissions and single transmit/receive antennas, the diversity gain of a user increases from M to (J+1)(M-1)+1 where J is the number of users helping that user.

preprint2014arXiv

Coordinated Scheduling for the Downlink of Cloud Radio-Access Networks

This paper addresses the coordinated scheduling problem in cloud-enabled networks. Consider the downlink of a cloud-radio access network (C-RAN), where the cloud is only responsible for the scheduling policy and the synchronization of the transmit frames across the connected base-stations (BS). The transmitted frame of every BS consists of several time/frequency blocks, called power-zones (PZ), maintained at fixed transmit power. The paper considers the problem of scheduling users to PZs and BSs in a coordinated fashion across the network, by maximizing a network-wide utility under the practical constraint that each user cannot be served by more than one base-station, but can be served by one or more power-zone within each base-station frame. The paper solves the problem using a graph theoretical approach by introducing the scheduling graph in which each vertex represents an association of users, PZs and BSs. The problem is formulated as a maximum weight clique, in which the weight of each vertex is the benefit of the association represented by that vertex. The paper further presents heuristic algorithms with low computational complexity. Simulation results show the performance of the proposed algorithms and suggest that the heuristics perform near optimal in low shadowing environments

preprint2014arXiv

Decoding Delay Controlled Reduction of Completion Time in Instantly Decodable Network Coding

For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution in persistent erasure channels. We first derive the decoding-delay-dependent expressions of the users' and overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we design two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. We, then, extend our study to the limited feedback scenario. Simulation results show that our new algorithms achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.

preprint2014arXiv

Delay Minimization for Instantly Decodable Network Coding in Persistent Channels with Feedback Intermittence

In this paper, we consider the problem of minimizing the multicast decoding delay of generalized instantly decodable network coding (G-IDNC) over persistent forward and feedback erasure channels with feedback intermittence. In such an environment, the sender does not always receive acknowledgement from the receivers after each transmission. Moreover, both the forward and feedback channels are subject to persistent erasures, which can be modelled by a two state (good and bad states) Markov chain known as Gilbert-Elliott channel (GEC). Due to such feedback imperfections, the sender is unable to determine subsequent instantly decodable packets combination for all receivers. Given this harsh channel and feedback model, we first derive expressions for the probability distributions of decoding delay increments and then employ these expressions in formulating the minimum decoding problem in such environment as a maximum weight clique problem in the G-IDNC graph. We also show that the problem formulations in simpler channel and feedback models are special cases of our generalized formulation. Since this problem is NP-hard, we design a greedy algorithm to solve it and compare it to blind approaches proposed in literature. Through extensive simulations, our adaptive algorithm is shown to outperform the blind approaches in all situations and to achieve significant improvement in the decoding delay, especially when the channel is highly persistent

preprint2014arXiv

Extended Delivery Time Analysis for Non-work-preserving Packet Transmission in Cognitive Environment

Cognitive radio transceiver can opportunistically access the underutilized spectrum resource of primary systems for new wireless services. With interweave cognitive implementation, the secondary transmission may be interrupted by the primary user's transmission. To facilitate the packet delay analysis of such secondary transmission, we study the resulting extended delivery time that includes both transmission time and waiting time. In particular, we derive the exact distribution function of extended delivery time of a fixed-size secondary packet with non-work-preserving strategy i.e. interrupted packets will be retransmitted. Both continuous sensing and periodic sensing with and without missed detection cases are considered. Selected numerical and simulation results are presented for verifying the mathematical formulation. Finally, we apply the results to secondary queuing analysis with a generalized M/G/1 queue set-up. The analytical results will greatly facilitate the design of the secondary system for particular target application.

preprint2014arXiv

High SNR BER Comparison of Coherent and Differentially Coherent Modulation Schemes in Lognormal Fading Channels

Using an auxiliary random variable technique, we prove that binary differential phase-shift keying and binary phase-shift keying have the same asymptotic bit-error rate performance in lognormal fading channels. We also show that differential quaternary phase-shift keying is exactly 2.32 dB worse than quaternary phase-shift keying over the lognormal fading channels in high signal-to-noise ratio regimes.

preprint2014arXiv

Interference Statistics and Capacity Analysis for Uplink Transmission in Two-Tier Small Cell Networks: A Geometric Probability Approach

Small cell networks are evolving as an economically viable solution to ameliorate the capacity and coverage of state-of-the-art wireless cellular systems. Nonetheless, the dense and unplanned deployment of the small cells (e.g., femtocells, picocells) with restricted user access significantly increases the impact of interference on the overall network performance. To this end, this paper presents a novel framework to derive the statistics of the interference considering dedicated and shared spectrum access for uplink transmissions in two-tier small cell networks such as the macrocell-femtocell networks. The derived expressions are validated by the Monte-Carlo simulations. Numerical results are generated to assess the feasibility of shared and dedicated spectrum access in femtocells under varying traffic load and spectral reuse scenarios.

preprint2014arXiv

On Low-Complexity Full-diversity Detection In Multi-User MIMO Multiple-Access Channels

Multiple-input multiple-output (MIMO) techniques are becoming commonplace in recent wireless communication standards. This added dimension (i.e., space) can be efficiently used to mitigate the interference in the multi-user MIMO context. In this paper, we focus on the uplink of a MIMO multiple access channel (MAC) where perfect channel state information (CSI) is only available at the destination. We provide a new set of sufficient conditions for a wide range of space-time block codes (STBC)s to achieve full-diversity under \emph{partial interference cancellation group decoding} (PICGD) with or without successive interference cancellation (SIC) for completely blind users. Explicit interference cancellation (IC) schemes for two and three users are then provided and shown to satisfy the derived full-diversity criteria. Besides the complexity reduction due to the fact that the proposed IC schemes enable separate decoding of distinct users without sacrificing the diversity gain, further reduction of the decoding complexity may be obtained. In fact, thanks to the structure of the proposed schemes, the real and imaginary parts of each user's symbols may be decoupled without any loss of performance. Finally, our theoretical claims are corroborated by simulation results and the new IC scheme for two-user MIMO MAC is shown to outperform the recently proposed two-user IC scheme especially for high spectral efficiency while requiring significantly less decoding complexity.

preprint2014arXiv

On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay [1] and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints.

preprint2014arXiv

Performance Analysis of Hybrid ARQ with Incremental Redundancy over Amplify-and-Forward Dual-Hop Relay Channels

In this paper, we consider a three node relay network comprising a source, a relay, and a destination. The source transmits the message to the destination using hybrid automatic repeat request (HARQ) with incremental redundancy (IR). The relay overhears the transmitted message, amplifies it using a variable gain amplifier, and then forwards the message to the destination. This latter combines both the source and the relay message and tries to decode the information. In case of decoding failure, the destination sends a negative acknowledgement. A new replica of the message containing new parity bits is then transmitted in the subsequent HARQ round. This process continues until successful decoding occurs at the destination or a maximum number $M$ of rounds is reached. We study the performance of HARQ-IR over the considered relay channel from an information theoretic perspective. We derive exact expressions and bounds for the information outage probability, the average number of transmissions, and the average transmission rate. Moreover, we evaluate the delay experienced by Poisson arriving packets over the considered relay network. We also provide analytical expressions for the expected waiting time, the sojourn time, and the energy efficiency. The derived exact expressions are validated by Monte Carlo simulations.

preprint2014arXiv

Technical Report: Finger Replacement Schemes for RAKE Receivers in the Soft Handover Region with Multiple BSs over I.N.D. Fading Channels

A new finger replacement technique which is applicable for RAKE receivers in the soft handover (SHO) region has been proposed and studied in [1], [2] under the ideal assumption that the fading is both independent and identically distributed from path to path. To supplement our previous work, we present a general comprehensive framework for the performance assessment of the proposed finger replacement schemes operating over independent and non-identically distributed (i.n.d.) faded paths. To accomplish this object, we derive new closed-form expressions for the target key statistics which are composed of i.n.d. exponential random variables. With these new expressions, the performance analysis of various wireless communication systems over more practical environments can be possible.

preprint2014arXiv

The random matrix regime of Maronna's M-estimator for observations corrupted by elliptical noises

This article studies the behavior of the Maronna robust scatter estimator $\hat{C}_N\in \mathbb{C}^{N\times N}$ of a sequence of observations $y_1,...,y_n$ which is composed of a $K$ dimensional signal drown in a heavy tailed noise, i.e $y_i=A_N s_i+x_i$ where $A_N \in \mathbb{C}^{N\times K}$ and $x_i$ is drawn from elliptical distribution. In particular, we prove that as the population dimension $N$, the number of observations $n$ and the rank of $A_N$ grow to infinity at the same pace and under some mild assumptions, the robust scatter matrix can be characterized by a random matrix $\hat{S}_N$ that follows a standard random model. Our analysis can be very useful for many applications of the fields of statistical inference and signal processing.

preprint2014arXiv

Transmit Antenna Selection in Underlay Cognitive Radio Environment

Cognitive radio (CR) technology addresses the problem of spectrum under-utilization. In underlay CR mode, the secondary users are allowed to communicate provided that their transmission is not detrimental to primary user communication. Transmit antenna selection is one of the low-complexity methods to increase the capacity of wireless communication systems. In this article, we propose and analyze the performance benefit of a transmit antenna selection scheme for underlay secondary system that ensures the instantaneous interference caused by the secondary transmitter to the primary receiver is below a predetermined level. Closed-form expressions of the outage probability, amount of fading, and ergodic capacity for the secondary network are derived. Monte-carlo simulations are also carried out to confirm various mathematical results presented in this article.

preprint2014arXiv

Unified Performance Analysis of Mixed Line of Sight RF-FSO Fixed Gain Dual-Hop Transmission Systems

In this work, we carry out a unified performance analysis of a dual-hop fixed gain relay system over asymmetric links composed of both radio-frequency (RF) and unified free-space optics (FSO) under the effect of pointing errors. The RF link is modeled by the Nakagami-$m$ fading channel and the FSO link by the Gamma-Gamma fading channel subject to both types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection (IM/DD)). In particular, we derive new unified closed-form expressions for the cumulative distribution function, the probability density function, the moment generation function, and the moments of the end-to-end signal-to-noise ratio of these systems in terms of the Meijer's G function. Based on these formulas, we offer exact closed-form expressions for the outage probability, the higher-order amount of fading, and the average bit-error rate of a variety of binary modulations in terms of the Meijer's G function. Further, an exact closed-form expression for the end-to-end ergodic capacity for the Nakagami-$m$-unified FSO relay links is derived in terms of the bivariate G function. All the given results are verified via Computer-based Monte-Carlo simulations.

preprint2013arXiv

A Lossy Graph Model for Decoding Delay Reduction in Instantly Decodable Network Coding

In this paper, we study the broadcast decoding delay performance of generalized instantly decodable network coding (G-IDNC) in the lossy feedback scenario. The problem is formulated as a maximum weight clique problem over the G-IDNC graph in [1]. In order to further minimize the decoding delay, we introduce in this paper the lossy G-IDNC graph (LG-IDNC). Whereas the G-IDNC graph represents only doubtless combinable packets, the LG-IDNC graph represents also uncertain packet combinations when the expected decoding delay of the encoded packet is lower than the individual expected decoding delay of each packet encoded in it. Since the maximum weight clique problem is known to be NP-hard, we use the heuristic introduced in [2] to discover the maximum weight clique in the LG-IDNC graph and finally we compare the decoding delay performance of LG-IDNC and G-IDNC graphs through extensive simulations. Numerical results show that our new LG-IDNC graph formulation outperforms the G-IDNC graph formulation in all situations and achieves significant improvement in the decoding delay especially when the feedback erasure probability is higher than the packet erasure probability.

preprint2013arXiv

Compression and Combining Based on Channel Shortening and Rank Reduction Techniques for Cooperative Wireless Sensor Networks

This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of $L$ sensors. As the destination has the capacity of processing only $U$ out of these $L$ signals, the strongest $U$ signals are selected while the remaining $(L-U)$ signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio.

preprint2013arXiv

Efficient Incremental Relaying

We propose a novel relaying scheme which improves the spectral efficiency of cooperative diversity systems by utilizing limited feedback from destination. Our scheme capitalizes on the fact that relaying is only required when direct transmission suffers deep fading. We calculate the packet error rate for the proposed efficient incremental relaying scheme with both amplify and forward and decode and forward relaying. Numerical results are also presented to verify their analytical counterparts.

preprint2013arXiv

Energy-Efficient Cooperative Protocols for Full-Duplex Relay Channels

In this work, energy-efficient cooperative protocols are studied for full-duplex relaying (FDR) with loopback interference. In these protocols, relay assistance is only sought under certain conditions on the different link outages to ensure effective cooperation. Recently, an energy-efficient selective decode-and-forward protocol was proposed for FDR, and was shown to outperform existing schemes in terms of outage. Here, we propose an incremental selective decode-and-forward protocol that offers additional power savings, while keeping the same outage performance. We compare the performance of the two protocols in terms of the end-to-end signal-to-noise ratio cumulative distribution function via closed-form expressions. Finally, we corroborate our theoretical results with simulation, and show the relative relay power savings in comparison to non-selective cooperation in which the relay cooperates regardless of channel conditions.

preprint2013arXiv

Impact of Pointing Errors on the Performance of Mixed RF/FSO Dual-Hop Transmission Systems

In this work, the performance analysis of a dual-hop relay transmission system composed of asymmetric radio-frequency (RF)/free-space optical (FSO) links with pointing errors is presented. More specifically, we build on the system model presented in [1] to derive new exact closed-form expressions for the cumulative distribution function, probability density function, moment generating function, and moments of the end-to-end signal-to-noise ratio in terms of the Meijer's G function. We then capitalize on these results to offer new exact closed-form expressions for the higher-order amount of fading, average error rate for binary and M-ary modulation schemes, and the ergodic capacity, all in terms of Meijer's G functions. Our new analytical results were also verified via computer-based Monte-Carlo simulation results.

preprint2013arXiv

On Lattice Sequential Decoding for The Unconstrained AWGN Channel

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we will characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.

preprint2013arXiv

On the Capacity of Multiple Access and Broadcast Fading Channels with Full Channel State Information at Low SNR

We study the throughput capacity region of the Gaussian multi-access (MAC) fading channel with perfect channel state information (CSI) at the receiver and at the transmitters, at low power regime. We show that it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points. More specifically, we show that at low power regime, the boundary surface of the capacity region shrinks to a single point corresponding to the sum rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Inspired by this result, we propose an on-off scheme, compute its achievable rate, and show that this scheme achieves single user capacity bounds of the MAC channel for a wide class of fading channels at asymptotically low power regime. We argue that this class of fading encompasses all known wireless channels for which the capacity region of the MAC channel has even a simpler expression in terms of users' average power constraints only. Using the duality of Gaussian MAC and broadcast channels (BC), we deduce a simple characterization of the BC capacity region at low power regime and show that for a class of fading channels (including Rayleigh fading), time-sharing is asymptotically optimal.

preprint2013arXiv

On the Effect of Correlated Measurements on the Performance of Distributed Estimation

We address the distributed estimation of an unknown scalar parameter in Wireless Sensor Networks (WSNs). Sensor nodes transmit their noisy observations over multiple access channel to a Fusion Center (FC) that reconstructs the source parameter. The received signal is corrupted by noise and channel fading, so that the FC objective is to minimize the Mean-Square Error (MSE) of the estimate. In this paper, we assume sensor node observations to be correlated with the source signal and correlated with each other as well. The correlation coefficient between two observations is exponentially decaying with the distance separation. The effect of the distance-based correlation on the estimation quality is demonstrated and compared with the case of unity correlated observations. Moreover, a closed-form expression for the outage probability is derived and its dependency on the correlation coefficients is investigated. Numerical simulations are provided to verify our analytic results.

preprint2013arXiv

On the Low SNR Capacity of Maximum Ratio Combining over Rician Fading Channels with Full Channel State Information

In this letter, we study the ergodic capacity of a maximum ratio combining (MRC) Rician fading channel with full channel state information (CSI) at the transmitter and at the receiver. We focus on the low Signal-to-Noise Ratio (SNR) regime and we show that the capacity scales as (L Omega/(K+L)) SNR log(1/SNR), where Omega is the expected channel gain per branch, K is the Rician fading factor, and L is the number of diversity branches. We show that one-bit CSI feedback at the transmitter is enough to achieve this capacity using an on-off power control scheme. Our framework can be seen as a generalization of recently established results regarding the fading-channels capacity characterization in the low-SNR regime.

preprint2013arXiv

Optimal Transmit Power Allocation for MIMO Two-Way Cognitive Relay Networks with Multiple Relays

In this letter, we consider a multiple-input multiple-output two-way cognitive radio system under a spectrum sharing scenario, where primary and secondary users operate on the same frequency band. The secondary terminals aims to exchange different messages with each other using multiple relays where each relay employs an amplify-and-forward strategy. The main objective of our work is to maximize the secondary sum rate allowed to share the spectrum with the primary users by respecting a primary user tolerated interference threshold. In this context, we derive a closed-form expression of the optimal power allocated to each antenna of the terminals. We then discuss the impact of some system parameters on the performance in the numerical result section.

preprint2013arXiv

Partially Blind Instantly Decodable Network Codes for Lossy Feedback Environment

In this paper, we study the multicast completion and decoding delay minimization problems of instantly decodable network coding (IDNC) in the case of lossy feedback. In such environments, the sender falls into uncertainties about packet reception at the different receivers, which forces it to perform partially blind selections of packet combinations in subsequent transmissions. To determine efficient partially blind policies that handle the completion and decoding delays of IDNC in such environment, we first extend the perfect feedback formulation in [2], [3] to the lossy feedback environment, by incorporating the uncertainties resulting from unheard feedback events in these formulations. For the completion delay problem, we use this formulation to identify the maximum likelihood state of the network in events of unheard feedback, and employ it to design a partially blind graph update extension to the multicast IDNC algorithm in [3]. For the decoding delay problem, we derive an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to derive the optimal policy to reduce the decoding delay in such lossy feedback environment. Results show that our proposed solution both outperforms other approaches and achieves a tolerable degradation even at relatively high feedback loss rates.

preprint2013arXiv

Performance of Opportunistic Fixed Gain Bidirectional Relaying With Outdated CSI

This paper studies the impact of using outdated channel state information for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplifyand- forward relays. For a Rayleigh faded channel, closed-form expressions for the outage probability, moment generating function and symbol error rate are derived. Simulations results are also presented to corroborate the derived analytical results. It is shown that adding relays does not improve the performance if the channel is substantially outdated. Furthermore, relay location is also taken into consideration and it is shown that the performance can be improved by placing the relay closer to the source whose channel is more outdated.

preprint2013arXiv

Relay Selection and Resource Allocation for Two Way DF-AF Cognitive Radio Networks

In this letter, the problem of optimal resource power allocation and relay selection for two way relaying cognitive radio networks using half duplex Decode and Forward (DF) and Amplify and Forward (AF) systems are investigated. The primary and secondary networks are assumed to access the spectrum at the same time, so that the interference introduced to the primary network caused by the secondary network should be below a certain interference threshold. In addition, a selection strategy between the AF and DF schemes is applied depending on the achieved secondary sum rate without affecting the quality of service of the primary network. A suboptimal approach based on a genetic algorithm is also presented to solve our problem. Selected simulation results show that the proposed suboptimal algorithm offers a performance close to the performance of the optimal solution with a considerable complexity saving.

preprint2013arXiv

Technical Report: An MGF-based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables

The joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. We also discussed a couple of other sample applications of the generic results presented in this work.

preprint2013arXiv

Technical Report: Beaconless Geo-Routing Under The Spotlight: Practical Link Models and Application Scenarios

Analysis and simulation of beaconless geo-routing protocols have been traditionally conducted assuming equal communication ranges for the data and control packets. In reality, this is not true since the communication range is actually function of the packet length. Control packets are typically much shorter than data packets. As a consequence, a substantial discrepancy exists in practice between their respective communication ranges. In this paper, we devise a practical link model for computing the effective communication range. We further introduce two simple strategies for bridging the gap between the control and data packet communication ranges. Our primary objective in this paper is to construct a realistic analytical framework describing the end-to-end performance of beaconless geo-routing protocols. Two flagship protocols are selected in this paper for further investigation under the developed framework. For a better perspective, the two protocols are actually compared to a hypothetical limit case; one which offers optimal energy and latency performance. Finally, we present four different application scenarios. For each scenario, we highlight the geo-routing protocol which performs the best and discuss the reasons behind it.

preprint2012arXiv

A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

This paper presents a novel framework for modeling the uplink intercell interference (ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

preprint2012arXiv

A Novel Ergodic Capacity Analysis of Diversity Combining and Multihop Transmission Systems over Generalized Composite Fading Channels

Ergodic capacity is an important performance measure associated with reliable communication at the highest rate at which information can be sent over the channel with a negligible probability of error. In the shadow of this definition, diversity receivers (such as selection combining, equal-gain combining and maximal-ratio combining) and transmission techniques (such as cascaded fading channels, amplify-and-forward multihop transmission) are deployed in mitigating various performance impairing effects such as fading and shadowing in digital radio communication links. However, the exact analysis of ergodic capacity is in general not always possible for all of these forms of diversity receivers and transmission techniques over generalized composite fading environments due to it's mathematical intractability. In the literature, published papers concerning the exact analysis of ergodic capacity have been therefore scarce (i.e., only [1] and [2]) when compared to those concerning the exact analysis of average symbol error probability. In addition, they are essentially targeting to the ergodic capacity of the maximal ratio combining diversity receivers and are not readily applicable to the capacity analysis of the other diversity combiners / transmission techniques. In this paper, we propose a novel moment generating function-based approach for the exact ergodic capacity analysis of both diversity receivers and transmission techniques over generalized composite fading environments. As such, we demonstrate how to simultaneously treat the ergodic capacity analysis of all forms of both diversity receivers and multihop transmission techniques.

preprint2012arXiv

A Unified Framework for the Ergodic Capacity of Spectrum Sharing Cognitive Radio Systems

We consider a spectrum sharing communication scenario in which a primary and a secondary users are communicating, simultaneously, with their respective destinations using the same frequency carrier. Both optimal power profile and ergodic capacity are derived for fading channels, under an average transmit power and an instantaneous interference outage constraints. Unlike previous studies, we assume that the secondary user has a noisy version of the cross link and the secondary link Channel State Information (CSI). After deriving the capacity in this case, we provide an ergodic capacity generalization, through a unified expression, that encompasses several previously studied spectrum sharing settings. In addition, we provide an asymptotic capacity analysis at high and low signal-to-noise ratio (SNR). Numerical results, applied for independent Rayleigh fading channels, show that at low SNR regime, only the secondary channel estimation matters with no effect of the cross link on the capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI. Furthermore, a practical on-off power allocation scheme is proposed and is shown, through numerical results, to achieve the full capacity at high and low SNR

preprint2012arXiv

Ergodic Capacity of Cognitive Radio under Imperfect Channel State Information

A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel state information (CSI) of the secondary link, but knows only the statistics and an estimated version of the secondary transmitter-primary receiver (ST-PR) link, is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels (with continuous probability density function) under average and peak transmit-power constraints and with respect to two different interference constraints: an interference outage constraint and a signal-to-interference outage constraint. When applied to Rayleigh fading channels, our results show, for instance, that the interference constraint is harmful at high-power regime in the sense that the capacity does not increase with the power, whereas at low-power regime, it has a marginal impact and no-interference performance corresponding to the ergodic capacity under average or peak transmit power constraint in absence of the primary user, may be achieved.

preprint2012arXiv

Exact Performance Analysis of Partial Relay Selection Based on Shadowing Side Information over Generalized Composite Fading Channels

Relay technology has recently gained great interest in millimeter wave (60 GHz or above) radio frequencies as a promising transmission technique improving the quality of service, providing high data rate, and extending the coverage area without additional transmit power in deeply shadowed fading environments. The performance of relay-based systems considerably depends on which relay selection protocols (RSPs) are used. These RSPs are typically using the channel side information (CSI). Specifically, the relay terminal (RT) is chosen among all available RTs by a central entity (CE) which receives all RTs' CSI via feedback channels. However, in the millimeter wave radio frequencies, the rate of the CSI variation is much higher than that of the CSI variation in 6 GHz frequencies under the same mobility conditions, which evidently results in a serious problem causing that the CSI at the CE is inaccurate for the RSP since the feedback channels have a backhaul / transmission delay. However and fortunately, the shadowing side information (SSI) varies very slowly in comparison to the rate of the CSI variation. In this context, we propose in this paper a partial-RSP in dual-hop amplify-and-forward relaying system, which utilize only the SSI of the RTs instead of their CSI. Then for the performance analysis, we obtain an exact average unified performance (AUP) of the proposed SSI-based partial-RSP for a variety shadowed fading environments. In particular, we offer a generic AUP expression whose special cases include the average bit error probability (ABEP) analysis for binary modulation schemes, the ergodic capacity analysis and the moments-generating function (MGF)-based characterization. The correctness of our newly theoretical results is validated with some selected numerical examples in an extended generalized-K fading environment.

preprint2012arXiv

Joint Filter Design of Alternate MIMO AF Relaying Networks with Interference Alignment

We study in this paper a two-hop relaying network consisting of one source, one destination, and three amplify-and-forward (AF) relays operating in a half-duplex mode. In order to compensate for the inherent loss of capacity pre-log factor 1/2 in a half-duplex mode, we consider alternate transmission protocol among three relays where two relays and the other relay alternately forward messages from source to destination. We consider a multiple-antenna environment where all nodes have $M$ antennas. Aligning the inter-relay interference due to the alternate transmission is utilized to make additional degrees of freedom (DOFs) and recover the pre-log factor loss. It is shown that the proposed relaying scheme can achieve $\frac{3M}{4}$ DOFs compared with the $\frac{M}{2}$ DOFs of conventional AF relaying. In addition, suboptimal linear filter designs for a source and three relays are proposed to maximize the system achievable sum-rate for different fading scenarios when the destination utilizes a linear minimum mean-square error filter for decoding. We verify from our selected numerical results that the proposed filter designs give significant improvement over a naive filter or conventional relaying schemes.

preprint2012arXiv

Multiuser Switched Diversity Scheduling Schemes

Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions.

preprint2012arXiv

New Results on the Sum of Gamma Random Variates With Application to the Performance of Wireless Communication Systems over Nakagami-m Fading Channels

The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed Gamma variates, applicable to the output statistics of maximal ratio combining (MRC) receiver operating over Nakagami-m fading channels or in other words to the statistical analysis of the scenario where the sum of squared Nakagami-m distributions are user-of-interest, is presented in closed-form in terms of well-known Meijer's G function and easily computable Fox's H-bar function for integer valued and non-integer valued m fading parameters. Further analysis, particularly on bit error rate via a PDF-based approach is also offered in closed form in terms of Meijer's G function and Fox's H-bar function for integer valued fading parameters, and extended Fox's H-bar function (H-hat) for non-integer valued fading parameters. Our proposed results complement previous known results that are either expressed in terms of infinite sums, nested sums, or higher order derivatives of the fading parameter m.

preprint2012arXiv

Novel Relations between the Ergodic Capacity and the Average Bit Error Rate

Ergodic capacity and average bit error rate have been widely used to compare the performance of different wireless communication systems. As such recent scientific research and studies revealed strong impact of designing and implementing wireless technologies based on these two performance indicators. However and to the best of our knowledge, the direct links between these two performance indicators have not been explicitly proposed in the literature so far. In this paper, we propose novel relations between the ergodic capacity and the average bit error rate of an overall communication system using binary modulation schemes for signaling with a limited bandwidth and operating over generalized fading channels. More specifically, we show that these two performance measures can be represented in terms of each other, without the need to know the exact end-to-end statistical characterization of the communication channel. We validate the correctness and accuracy of our newly proposed relations and illustrated their usefulness by considering some classical examples.

preprint2012arXiv

On the Computation of the Higher Order Statistics of the Channel Capacity over Generalized Fading Channels

The higher-order statistics (HOS) of the channel capacity $μ_n=\mathbb{E}[\log^n(1+γ_{end})]$, where $n\in\mathbb{N}$ denotes the order of the statistics, has received relatively little attention in the literature, due in part to the intractability of its analysis. In this letter, we propose a novel and unified analysis, which is based on the moment generating function (MGF) technique, to exactly compute the HOS of the channel capacity. More precisely, our mathematical formalism can be readily applied to maximal-ratio-combining (MRC) receivers operating in generalized fading environments (i.e., the sum of the correlated noncentral chi-squared distributions / the correlated generalized Rician distributions). The mathematical formalism is illustrated by some numerical examples focussing on the correlated generalized fading environments.

preprint2012arXiv

On the Computation of the Higher-Order Statistics of the Channel Capacity for Amplify-and-Forward Multihop Transmission

Higher-order statistics (HOS) of the channel capacity provide useful information regarding the level of reliability of the signal transmission at a particular rate. We propose in this letter a novel and unified analysis, which is based on the moment-generating function (MGF) approach, to efficiently and accurately compute the HOS of the channel capacity for amplify-and-forward multihop transmission over generalized fading channels. More precisely, our mathematical formulism is easy-to-use and tractable specifically requiring only the reciprocal MGFs of the instantaneous signal-to-noise ratio distributions of the transmission hops. Numerical and simulation results, performed to exemplify the usefulness of the proposed MGF-based analysis, are shown to be in perfect agreement.

preprint2012arXiv

On the Performance of Transmit Antenna Selection Based on Shadowing Side Information

In this paper, a transmit antenna selection scheme, which is based on shadowing side information, is investigated. In this scheme, the selected single transmit antenna provides the highest shadowing coefficient between transmitter and receiver. By the proposed technique, the frequency of the usage of the feedback channel from the receiver to the transmitter and also channel estimation complexity at the receiver can be reduced. We study the performance of our proposed technique and in the analysis, we consider an independent but not identically distributed Generalized-K composite fading model. More specifically exact and closed-form expressions for the outage probability, the moment generating function, the moments of signal-to-noise ratio, and the average symbol error probability are derived. In addition, asymptotic outage probability and symbol error probability expressions are also presented in order to investigate the diversity order and the array gain. Finally, our theoretical performance results are validated by Monte Carlo simulations.

preprint2012arXiv

On the Sum of Squared η-μRandom Variates With Application to the Performance of Wireless Communication Systems

The probability density function (PDF) and cumulative distribution function of the sum of L independent but not necessarily identically distributed squared η-μvariates, applicable to the output statistics of maximal ratio combining (MRC) receiver operating over η-μfading channels that includes the Hoyt and the Nakagami-m models as special cases, is presented in closed-form in terms of the Fox's H-bar function. Further analysis, particularly on the bit error rate via PDF-based approach, is also represented in closed form in terms of the extended Fox's H-bar function (H-hat). The proposed new analytical results complement previous results and are illustrated by extensive numerical and Monte Carlo simulation results.

preprint2012arXiv

Performance Analysis of Spectrum Sensing With Multiple Status Changes in Primary User Traffic

In this letter, the impact of primary user traffic with multiple status changes on the spectrum sensing performance is analyzed. Closed-form expressions for the probabilities of false alarm and detection are derived. Numerical results show that the multiple status changes of the primary user cause considerable degradation in the sensing performance. This degradation depends on the number of changes, the primary user traffic model, the primary user traffic intensity and the signal-to-noise ratio of the received signal. Numerical results also show that the amount of degradation decreases when the number of changes increases, and converges to a minimum sensing performance due to the limited sensing period and primary holding time.

preprint2012arXiv

Performance of Amplify-and-Forward Multihop Transmission over Relay Clusters with Different Routing Strategies

We Consider a multihop relay network in which two terminals are communicating with each other via a number of cluster of relays. Performance of such networks depends on the routing protocols employed. In this paper, we find the expressions for the average symbol error probability (ASEP) performance of amplify-and-forward (AF) multihop transmission for the simplest routing protocol in which the relay transmits using the channel having the best symbol to noise ratio (SNR). The ASEP performance of a better protocol proposed in [1] known as the adhoc protocol is also analyzed. The derived expressions for the performance are a convenient tool to analyze the performance of AF multihop transmission over relay clusters. Monte-Carlo simulations verify the correctness of the proposed formulation and are in agreement with analytical results. Furthermore, we propose new generalized protocols termed as last-n-hop selection protocol, the dual path protocol, the forward- backward last-n-hop selection protocol, and the forward-backward dual path protocol, to get improved ASEP performances. The ASEP performance of these proposed schemes is analysed by computer simulations. It is shown that close to optimal performance can be achieved by using the last-n-hop selection protocol and its forward-backward variant. The complexity of the protocols is also studied.

preprint2012arXiv

Power Allocation Strategies for Fixed-Gain Half-Duplex Amplify-and-Forward Relaying in Nakagami-m Fading

In this paper, we study power allocation strategies for a fixed-gain amplify-and-forward relay network employing multiple relays. We consider two optimization problems for the relay network: 1) optimal power allocation to maximize the end-to-end signal-to-noise ratio (SNR) and 2) minimizing the total consumed power while maintaining the end-to-end SNR over a threshold value. We investigate these two problems for two relaying protocols of all-participate relaying and selective relaying and multiple cases of available channel state information (CSI) at the relays. We show that the SNR maximization problem is concave and the power minimization problem is convex for all protocols and CSI cases considered. We obtain closed-form expressions for the two problems in the case for full CSI and CSI of all the relay-destination links at the relays and solve the problems through convex programming when full CSI or CSI of the relay-destination links are not available at the relays. Numerical results show the benefit of having full CSI at the relays for both optimization problems. However, they also show that CSI overhead can be reduced by having only partial CSI at the relays with only a small degradation in performance.

preprint2011arXiv

A Novel Unified Expression for the Capacity and Bit Error Probability of Wireless Communication Systems over Generalized Fading Channels

Analysis of the average binary error probabilities (ABEP) and average capacity (AC) of wireless communications systems over generalized fading channels have been considered separately in the past. This paper introduces a novel moment generating function (MGF)-based \emph{unified expression} for the ABEP and AC of single and multiple link communication with maximal ratio combining. In addition, this paper proposes the hyper-Fox's H fading model as a unified fading distribution of a majority of the well-known generalized fading models. As such, we offer a generic unified performance expression that can be easily calculated and that is applicable to a wide variety of fading scenarios. The mathematical formalism is illustrated with some selected numerical examples that validate the correctness of our newly derived results.

preprint2011arXiv

Hadamard Upper Bound (HUB) on Optimum Joint Decoding Capacity of Wyner Gaussian Cellular MAC

This paper has been withdrawn by the authors.

preprint2011arXiv

Secure Diversity-Multiplexing Tradeoff of Zero-Forcing Transmit Scheme at Finite-SNR

In this paper, we address the finite Signal-to-Noise Ratio (SNR) Diversity-Multiplexing Tradeoff (DMT) of the Multiple Input Multiple Output (MIMO) wiretap channel, where a Zero-Forcing (ZF) transmit scheme, that intends to send the secret information in the orthogonal space of the eavesdropper channel, is used. First, we introduce the secrecy multiplexing gain at finite-SNR that generalizes the definition at high-SNR. Then, we provide upper and lower bounds on the outage probability under secrecy constraint, from which secrecy diversity gain estimates of ZF are derived. Through asymptotic analysis, we show that the upper bound underestimates the secrecy diversity gain, whereas the lower bound is tight at high-SNR, and thus its related diversity gain estimate is equal to the actual asymptotic secrecy diversity gain of the MIMO wiretap channel.

preprint2011arXiv

Technical Report: Multi-Carrier Position-Based Packet Forwarding Protocol For Wireless Sensor Networks

Beaconless position-based forwarding protocols have recently evolved as a promising solution for packet forwarding in wireless sensor networks. However, as the node density grows, the overhead incurred in the process of relay selection grows significantly. As such, end-to-end performance in terms of energy and latency is adversely impacted. With the motivation of developing a packet forwarding mechanism that is tolerant to node density, an alternative position-based protocol is proposed in this paper. In contrast to existing beaconless protocols, the proposed protocol is designed such that it eliminates the need for potential relays to undergo a relay selection process. Rather, any eligible relay may decide to forward the packet ahead, thus significantly reducing the underlying overhead. The operation of the proposed protocol is empowered by exploiting favorable features of orthogonal frequency division multiplexing (OFDM) at the physical layer. The end-to-end performance of the proposed protocol is evaluated against existing beaconless position-based protocols analytically and as well by means of simulations. The proposed protocol is demonstrated in this paper to be more efficient. In particular, it is shown that for the same amount of energy the proposed protocol transports one bit from source to destination much quicker.

preprint2010arXiv

A New Formula for the BER of Binary Modulations with Dual-Branch Selection over Generalized-K Composite Fading Channels

Error performance is one of the main performance measures and derivation of its closed-form expression has proved to be quite involved for certain systems. In this letter, a unified closed-form expression, applicable to different binary modulation schemes, for the bit error rate of dual-branch selection diversity based systems undergoing independent but not necessarily identically distributed generalized-K fading is derived in terms of the extended generalized bivariate Meijer G-function.

preprint2010arXiv

A Unified MGF-Based Capacity Analysis of Diversity Combiners over Generalized Fading Channels

Unified exact average capacity results for L-branch coherent diversity receivers including equal-gain combining (EGC) and maximal-ratio combining (MRC) are not known. This paper develops a novel generic framework for the capacity analysis of $L$-branch EGC/MRC over generalized fading channels. The framework is used to derive new results for the Gamma shadowed generalized Nakagami-m fading model which can be a suitable model for the fading environments encountered by high frequency (60 GHz and above) communications. The mathematical formalism is illustrated with some selected numerical and simulation results confirming the correctness of our newly proposed framework.

preprint2010arXiv

An MGF-based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered Random Variables

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks (Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels.

preprint2010arXiv

Extended Generalized-K (EGK): A New Simple and General Model for Composite Fading Channels

In this paper, we introduce a generalized composite fading distribution (termed extended generalized-K (EGK)) to model the envelope and the power of the received signal in millimeter wave (60 GHz or above) and free-space optical channels. We obtain the first and the second-order statistics of the received signal envelope characterized by the EGK composite fading distribution. In particular, expressions for probability density function, cumulative distribution function, level crossing rate and average fade duration, and fractional moments are derived. In addition performance measures such as amount of fading, average bit error probability, outage probability, average capacity, and outage capacity are offered in closed-form. Selected numerical and computer simulation examples validate the accuracy of the presented mathematical analysis.

preprint2007arXiv

Rate and Power Allocation for Discrete-Rate Link Adaptation

Link adaptation, in particular adaptive coded modulation (ACM), is a promising tool for bandwidth-efficient transmission in a fading environment. The main motivation behind employing ACM schemes is to improve the spectral efficiency of wireless communication systems. In this paper, using a finite number of capacity achieving component codes, we propose new transmission schemes employing constant power transmission, as well as discrete and continuous power adaptation, for slowly varying flat-fading channels. We show that the proposed transmission schemes can achieve throughputs close to the Shannon limits of flat-fading channels using only a small number of codes. Specifically, using a fully discrete scheme with just four codes, each associated with four power levels, we achieve a spectral efficiency within 1 dB of the continuous-rate continuous-power Shannon capacity. Furthermore, when restricted to a fixed number of codes, the introduction of power adaptation has significant gains with respect to ASE and probability of no transmission compared to a constant power scheme.

Mohamed-Slim Alouini

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214 published item(s)

AUV Trajectory Learning for Underwater Acoustic Energy Transfer and Age Minimization

From Ground to Sky: Architectures, Applications, and Challenges Shaping Low-Altitude Wireless Networks

Frontiers of Generative AI for Network Optimization: Theories, Limits, and Visions

Label-Efficient School Detection from Aerial Imagery via Weakly Supervised Pretraining and Fine-Tuning

Low-Complexity RSS-based Underwater Localization with Unknown Transmit Power

On Performance of Integrated Satellite HAPS Ground Communication: Aerial IRS Node vs Terrestrial IRS Node

On the Uplink SINR Meta Distribution of UAV-assisted Wireless Networks

Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network

A New Analytical Approximation of the Fluid Antenna System Channel

Bridging the Urban-Rural Connectivity Gap through Intelligent Space, Air, and Ground Networks

Conditional Contact Angle Distribution in LEO Satellite-Relayed Transmission

Energy Efficiency Analysis of Charging Pads-powered UAV-enabled Wireless Networks

Evaluating the Accuracy of Stochastic Geometry Based Models for LEO Satellite Networks Analysis

High-Rate Uninterrupted Internet-of-Vehicle Communications in Highways: Dynamic Blockage Avoidance and CSIT Acquisition

Joint Trajectory Design and User Scheduling of Aerial Cognitive Radio Networks

Laser-Powered UAVs for Wireless Communication Coverage: A Large-Scale Deployment Strategy

Maritime Communications: A Survey on Enabling Technologies, Opportunities, and Challenges

Max-Min Data Rate Optimization for RIS-aided Uplink Communications with Green Constraints

On Secure NOMA-CDRT Systems with Physical Layer Network Coding

On the Asymptotic Performance Analysis of the k-th Best Link Selection over Non-identical Non-central Chi-square Fading Channels

On the Performance Optimization of Two-way Hybrid VLC/RF based IoT System over Cellular Spectrum

Performance Analysis of Charging Infrastructure Sharing in UAV and EV-involved Networks

Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

Proactive Traffic Offloading in Dynamic Integrated Multi-Satellite Terrestrial Networks

Stochastic Geometry-based Analysis of Multi-Purpose UAVs for Package and Data Delivery

Stochastic Geometry-Based Low Latency Routing in Massive LEO Satellite Networks

Technical Report: Development of an Ultrahigh Bandwidth Software-defined Radio Platform

Toward Sustainable Transportation: Accelerating Vehicle Electrification with Dynamic Charging Deployment

Towards 6G Holographic Localization: Enabling Technologies and Perspectives

Charging Techniques for UAV-assisted Data Collection: Is Laser Power Beaming the Answer?

Data-Driven State Estimation for Light-Emitting Diode Underwater Optical Communication

Establishing and Maintaining a Reliable Optical Wireless Communication in Underwater Environment

On the Performance of Spectrum Sharing Backscatter Communication Systems

Smart Buildings Enabled by 6G Communications

Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks

Terahertz-Band MIMO-NOMA: Adaptive Superposition Coding and Subspace Detection

Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing

A 6G White Paper on Connectivity for Remote Areas

A Journey from Improper Gaussian Signaling to Asymmetric Signaling

A PHY Layer Security Analysis of a Hybrid High Throughput Satellite with an Optical Feeder Link

A Survey on Design and Performance of Higher-Order QAM Constellations

A Tutorial on Clique Problems in Communications and Signal Processing

Accurate Closed-Form Approximations to Channel Distributions of RIS-Aided Wireless Systems

Adaptive Acquisition Schemes for Photon-Limited Free-Space Optical Communications

Aerial Base Stations Deployment in 6G Cellular Networks using Tethered Drones: The Mobility and Endurance Trade-off

Analog Versus Hybrid Precoding for Multiuser Massive MIMO with Quantized CSI Feedback

Asymptotic Analysis of an Ensemble of Randomly Projected Linear Discriminants

Backflash Light as a Security Vulnerability in Quantum Key Distribution Systems

Beam Tracking with Photon-Counting Detector Arrays in Free-Space Optical Communications

Beamforming Through Reconfigurable Intelligent Surfaces in Single-User MIMO Systems: SNR Distribution and Scaling Laws in the Presence of Channel Fading and Phase Noise

Classes of Full-Duplex Channels with Capacity Achieved Without Adaptation

Climate Monitoring using Internet of X-Things

CubeSat Communications: Recent Advances and Future Challenges

Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

Deep Learning in Industrial Internet of Things: Potentials, Challenges, and Emerging Applications

Efficient Importance Sampling for the Left Tail of Positive Gaussian Quadratic Forms

Energy-Efficient Fixed-Gain AF Relay Assisted OFDM with Index Modulation

Enhanced Huffman Coded OFDM with Index Modulation

Exploiting Randomly-located Blockages for Large-Scale Deployment of Intelligent Surfaces

Flying Car Transportation System: Advances, Techniques, and Challenges

Free-Space Optical MISO Communications With an Array of Detectors

GMD-Based Hybrid Beamforming for Large Reconfigurable Intelligent Surface Assisted Millimeter-Wave Massive MIMO

High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model

Intelligent Reflecting Surface Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design

Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques

Joint Reflecting and Precoding Designs for SER Minimization in Reconfigurable Intelligent Surfaces Assisted MIMO Systems

Latency-Aware Offloading in Integrated Satellite Terrestrial Networks

Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

Modeling of Viral Aerosol Transmission and Detection

Nearest Neighbor and Contact Distance Distribution for Binomial Point Process on Spherical Surfaces

Next Generation Terahertz Communications: A Rendezvous of Sensing, Imaging, and Localization

On Integrated Access and Backhaul Networks: Current Status and Potentials

On Secure Mixed RF-FSO Systems With TAS and Imperfect CSI

On the Performance of Dual-Hop Systems over Mixed FSO/mmWave Fading Channels