A Stochastic Geometry Model of Backhaul and User Coverage in Urban UAV Networks

TL;DR

This paper develops a stochastic geometry model to analyze how UAV deployment parameters affect user coverage and backhaul in urban networks, identifying optimal UAV heights for maximizing service quality.

Contribution

It introduces an analytical model linking UAV parameters to coverage probability, including an optimal UAV height and adaptive height adjustment strategies.

Findings

Existence of an optimal UAV height for maximum coverage

Analytical expression for coverage probability based on UAV parameters

Adaptive UAV height adjustment improves coverage and backhaul requirements

Abstract

Wireless access points on unmanned aerial vehicles (UAVs) are being considered for mobile service provisioning in commercial networks. To be able to efficiently use these devices in cellular networks it is necessary to first have a qualitative and quantitative understanding of how their design parameters reflect on the service quality experienced by the end user. In this paper we model a network of UAVs operating at a certain height above ground to provide wireless service within coverage areas shaped by their directional antennas, with the UAVs using the existing terrestrial base station network for wireless backhaul. We provide an analytical expression for the coverage probability experienced by a typical user as a function of the UAV parameters. Using our derivations we demonstrate the existence of an optimum UAV height which maximises the end user coverage probability. We then explore a scenario where the UAVs adjust their individual heights to meet their backhaul requirements while at the same time attempting to maximise the coverage probability of the end user on the ground.