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Researcher profile

Rohit Singh

Rohit Singh contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Networking and Internet Architectureeess.SPMachine LearningArtificial IntelligenceComputer Science and Game TheoryCryptography and SecurityDatabasesEmerging Technologies

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Published work

7 published item(s)

preprint2026arXiv

Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance

To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cases the use of AI/ML techniques (AI/ML beam management and mobility procedures) have been proposed. These techniques rely heavily on data that are most often simulated for various scenarios and do not accurately reflect real deployment behavior or user traffic patterns. Therefore, there is an utmost need for realistic datasets under various conditions. This work presents a dataset collected from a commercially deployed network across various modes of mobility (pedestrian, bike, car, bus, and train) and at multiple speeds to depict real time UE mobility. When collecting the dataset, we focused primarily on handover (HO) scenarios, with the aim of reducing the HO interruption time and maintaining continuous throughput during and immediately after HO execution. To support this research, the dataset includes timing advance (TA) measurements at various signaling events such as RACH trigger, MAC CE, and PDCCH grant which are typically missing in existing works. We cover a detailed description of the creation of the dataset; experimental setup, data acquisition, and extraction. We also cover an exploratory analysis of the data, with a primary focus on mobility, beam management, and TA. We discuss multiple use cases in which the proposed dataset can facilitate understanding of the inference of the AI/ML model. One such use case is to train and evaluate various AI/ML models for TA prediction.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Investigating the impact of BTI, HCI and time-zero variability on neuromorphic spike event generation circuits

Neuromorphic computing refers to brain-inspired computers, that differentiate it from von Neumann architecture. Analog VLSI based neuromorphic circuits is a current research interest. Two simpler spiking integrate and fire neuron model namely axon-Hillock (AH) and voltage integrate, and fire (VIF) circuits are commonly used for generating spike events. This paper discusses the impact of reliability issues like Bias Temperature instability (BTI) and Hot Carrier Injection (HCI), and timezero variability on these CMOS based neuromorphic circuits. AH and VIF circuits are implemented using HKMG based 45nm technology. For reliability analysis, industry standard Cadence RelXpert tool is used. For time-zero variability analysis, 1000 Monte-Carlo simulations are performed.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Consenting to Internet of Things Across Different Social Settings

Devices connected to the Internet of Things (IoT) are rapidly becoming ubiquitous across modern homes, workplaces, and other social environments. While these devices provide users with extensive functionality, they pose significant privacy concerns due to difficulties in consenting to these devices. In this work, we present the results of a pilot study that shows how users consent to devices in common locations at a friends house in which the user is a guest attending a party. We use this pilot study to indicate a direction for a larger study, which will capture a more granular understanding of how users will consent to a variety of devices placed in different social settings (i.e. a party house owned by a friend, an office space for the user and some 40 other employees, the bathroom of a department store). Our final contribution of this work will be to build a probability distribution which will indicate how probable a given user is to consent to a device given what sensors it has, where it is, and the awareness and preferences of each user.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

An Analytical Model for Efficient Indoor THz Access Point Deployment

Ultra-densification of user equipment (UE) and access points (APs) are anticipated to take a toll on the future spectrum needs. Higher frequency bands, such as mmWave ($30$-$300GHz$) and THz spectrum ($0.3$-$10THz$), can be used to cater to the high-throughput needs of ultra-dense networks. These high-frequency bands have a tremendous amount of \textit{green-filed contiguous spectrum}, ranging in hundreds of $GHz$. However, these bands, especially the THz bands, face numerous challenges, such as high spreading, absorption, and penetration losses. To combat these challenges, the THz-APs need to be either equipped with high transmit power, high antenna gains (i.e., narrow antenna beams), or limit the communication to short-ranges. All of these factors are bounded due to technical or economic challenges, which will result in a \textit{"distance-power dilemma"} while deciding on the deployment strategy of THz-APs. In this paper, we present an analytical model to deploy THz-APs in an indoor setting efficiently. We further show through extensive numerical analysis, the optimal number of APs and optimal room length for different blocks of the THz spectrum. Furthermore, these THz-APs need to be efficiently packed to avoid outages due to handoffs, which can add more complexity to the dilemma. To mitigate the packing problem, we propose two solutions over the optimal solution: (a) Radius Increase, and (b) Repeater Assistance, and present an analytical model for each.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Green Security Game with Community Engagement

While game-theoretic models and algorithms have been developed to combat illegal activities, such as poaching and over-fishing, in green security domains, none of the existing work considers the crucial aspect of community engagement: community members are recruited by law enforcement as informants and can provide valuable tips, e.g., the location of ongoing illegal activities, to assist patrols. We fill this gap and (i) introduce a novel two-stage security game model for community engagement, with a bipartite graph representing the informant-attacker social network and a level-$κ$ response model for attackers inspired by cognitive hierarchy; (ii) provide complexity results and exact, approximate, and heuristic algorithms for selecting informants and allocating patrollers against level-$κ$ ($κ<\infty$) attackers; (iii) provide a novel algorithm to find the optimal defender strategy against level-$\infty$ attackers, which converts the problem of optimizing a parameterized fixed-point to a bi-level optimization problem, where the inner level is just a linear program, and the outer level has only a linear number of variables and a single linear constraint. We also evaluate the algorithms through extensive experiments.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

SHINE (Strategies for High-frequency INdoor Environments) with Efficient THz-AP Placement

The increasing demand for ultra-high throughput in ultra-dense networks might take a toll on 5G capacity. Moreover, with Internet-of-Things (IoT) and the growing use-cases for indoor killer-applications, it will be necessary to look beyond 5G technologies. One such promising technology is to move higher in the frequencies, such as the THz ($300$ $GHz$-$10$ $THz$) spectrum. THz has a massive number of greenfield-contiguous channels ranging from $10$ $GHz$ to $200$ $GHz$ (best case), which was not available in the traditional radio frequency (RF) or millimeter wave (mmWave) bands. Although THz has immense potential to cater to such demands, it comes with numerous challenges revolving around hardware, link budget, mobility, blockages, scheduling, and deployment. Terahertz access points (THz-APs) are sensitive to deployment and can critically impact a system\textquotesingle s dynamics (i.e., coverage, throughput, and efficiency). In this paper, we present Strategies for High-frequency INdoor Environments or SHINE, which focuses on efficient AP deployment in the THz spectrum and draws motivation from approaches used indoor to improve lighting conditions. Due to THz\textquotesingle s limited coverage area of a few meters, the number of THz-APs required to satisfy a densely populated room will be higher compared to today&#39;s single router/box/AP model. This increased number of THz-APs will not only increase the operational costs, but also (in some cases) can make the system inefficient. Through SHINE, we explore the deployment-related challenges and propose strategies to mitigate the same.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Ultra-dense Low Data Rate (UDLD) Communication in the THz

In the future, with the advent of Internet of Things (IoT), wireless sensors, and multiple 5G killer applications, an indoor room might be filled with $1000$s of devices demanding low data rates. Such high-level densification and mobility of these devices will overwhelm the system and result in higher interference, frequent outages, and lower coverage. The THz band has a massive amount of greenfield spectrum to cater to this dense-indoor deployment. However, a limited coverage range of the THz will require networks to have more infrastructure and depend on non-line-of-sight (NLOS) type communication. This form of communication might not be profitable for network operators and can even result in inefficient resource utilization for devices demanding low data rates. Using distributed device-to-device (D2D) communication in the THz, we can cater to these Ultra-dense Low Data Rate (UDLD) type applications. D2D in THz can be challenging, but with opportunistic allocation and smart learning algorithms, these challenges can be mitigated. We propose a 2-Layered distributed D2D model, where devices use coordinated multi-agent reinforcement learning (MARL) to maximize efficiency and user coverage for dense-indoor deployment. We show that densification and mobility in a network can be used to further the limited coverage range of THz devices, without the need for extra infrastructure or resources.

0 citations0 reviewsNo code linkedOpen access