Coverage Analysis for Energy-Harvesting UAV-assisted mmWave Cellular Networks

TL;DR

This paper analyzes the coverage and performance of UAV-assisted mmWave cellular networks with energy harvesting, considering both downlink and uplink phases, and optimizes key system parameters for improved network efficiency.

Contribution

It provides a comprehensive joint analysis of downlink and uplink coverage in UAV-assisted mmWave networks with energy harvesting, including new expressions for coverage probabilities and optimization of system parameters.

Findings

Smaller user clusters improve network performance.

Optimal UAV height enhances coverage and throughput.

Proper power splitting and time division multiplexing maximize efficiency.

Abstract

In this paper, we jointly consider the downlink simultaneous wireless information and power transfer (SWIPT) and uplink information transmission in unmanned aerial vehicle (UAV)-assisted millimeter wave (mmWave) cellular networks, in which the user equipment (UE) locations are modeled using Poisson cluster processes (e.g., Thomas cluster processes or Mat\'ern cluster processes). Distinguishing features of mmWave communications, such as different path loss models for line-of-sight (LOS) and non-LOS (NLOS) links and directional transmissions are taken into account. In the downlink phase, the association probability, and energy coverages of different tier UAVs and ground base stations (GBSs) are investigated. Moreover, we define a successful transmission probability to jointly present the energy and signal-to-interference-plus-noise ratio (SINR) coverages and provide general expressions. In the uplink phase, we consider the scenario that each UAV receives information from its own cluster member UEs. We determine the Laplace transform of the interference components and characterize the uplink SINR coverage. In addition, we formulate the average uplink throughput, with the goal to identify the optimal time division multiplexing between the donwlink and uplink phases. Through numerical results we investigate the impact of key system parameters on the performance. We show that the network performance is improved when the cluster size becomes smaller. In addition, we analyze the optimal height of UAVs, optimal power splitting value and optimal time division multiplexing that maximizes the network performance.