Joint Energy and SINR Coverage Probability in UAV Corridor-assisted RF-powered IoT Networks

Harris K. Armeniakos, Petros S. Bithas, Konstantinos Maliatsos, Athanasios G. Kanatas
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Abstract

This letter studies the joint energy and signal-to-interference-plus-noise (SINR)-based coverage probability in Unmanned Aerial Vehicle (UAV)-assisted radio frequency (RF)-powered Internet of Things (IoT) networks. The UAVs are spatially distributed in an aerial corridor that is modeled as a one-dimensional (1D) binomial point process (BPP). By accurately capturing the line-of-sight (LoS) probability of a UAV through large-scale fading i) an exact form expression for the energy coverage probability is derived, and ii) a tight approximation for the overall coverage performance is obtained. Among several key findings, numerical results reveal the optimal number of deployed UAV-BSs that maximizes the joint coverage probability, as well as the optimal length of the UAV corridors when designing such UAV-assisted IoT networks.
无人机走廊辅助射频供电物联网网络中的联合能量和 SINR 覆盖概率
本文研究了无人机(UAV)辅助射频(RF)供电的物联网(IoT)网络中基于能量和信号干扰加噪声(SINR)的联合覆盖概率。无人机在空间上分布在空中走廊中,该走廊被建模为一维(1D)二叉点过程(BPP)。通过精确捕捉无人机通过大规模衰落的视距(LoS)概率,i)得出了能量覆盖概率的精确表达式,ii)获得了整体覆盖性能的精确近似值。在几项重要发现中,数值结果揭示了在设计此类无人机辅助物联网网络时,能使联合覆盖概率最大化的最佳部署无人机-BS 数量,以及无人机走廊的最佳长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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