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Energy-Efficient Massive IoT Shared Spectrum Access over UAV-enabled Cellular Networks

Data aggregation has become an emerging paradigm to support massive Internet-of-things (IoT), a new and critical use case for fifth-generation new radio (5G-NR). Indeed, data aggregators can complement cellular base stations and process IoT traffic to reduce network congestion. In this paper, we consider using mobile data aggregators, e.g., drones, that collect IoT traffic and aggregate them to the network. Specifically, we first discuss how the spectrum can be shared between cellular users (UEs) and IoT devices in the presence of drones, proposing a time-division duplexing protocol. We use stochastic geometry to analyze this protocol, comparing it to the standard spectrum sharing and orthogonal allocation protocols. We then formulate a stochastic optimization problem to optimize the nominal IoT transmit power, maximizing the average energy-efficiency (EE) of the IoT device subject to interference constraints to protect UEs. Simulations are presented to validate the theoretical insights and the effectiveness of the proposed protocol. It is shown that using drones, to aggregate IoT traffic, improves the EE of IoT devices, yet the EE degrades as their altitudes increases. Equally important, optimizing the transmit power is critical to further improve the EE, while ensuring fair coexistence with UEs.

preprint2020arXivOpen access
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