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

TL;DR

This paper analyzes the combined energy and SINR coverage probabilities in UAV-assisted RF-powered IoT networks, modeling UAV distribution in a corridor and deriving exact and approximate expressions for coverage metrics.

Contribution

It introduces a novel model of UAV distribution in a corridor and derives exact and approximate coverage probabilities, including optimal UAV deployment strategies.

Findings

Optimal number of UAV-BSs for maximum coverage

Optimal corridor length for UAV-assisted IoT networks

Derived exact and approximate coverage probability expressions

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.