Toward Ubiquitous and Flexible Coverage of UAV-IRS-Assisted NOMA Networks

TL;DR

This paper explores how UAV-mounted intelligent reflecting surfaces can enhance the coverage and flexibility of NOMA networks, providing analytical insights and optimal power allocation strategies for large-scale aerial communication systems.

Contribution

It introduces a novel 3D point process model for UAV deployment and derives coverage probabilities for UAV-IRS-assisted NOMA, advancing understanding of aerial IRS benefits.

Findings

UAV-IRS significantly improves network coverage.

Optimal power allocation enhances NOMA performance.

Analytical results validated by simulations.

Abstract

This paper studies how to achieve a high and flexible coverage performance of a large-scale cellular network that enables unmanned aerial vehicles (UAVs) for non-orthogonal multiple access (NOMA) transmission to simultaneously serve multiple users. The considered cellular network consists of a tier of base stations and a tier of UAVs. Each UAV is mounted with an intelligent reflecting surface (IRS) in order to serve as an aerial IRS reflecting signals between a base station and a user in the network. All the UAVs in the network are deployed based on a newly proposed three-dimensional (3D) point process that leads to a tractable and accurate analysis of the association statistics, which is traditionally difficult to analyze due to the mobility of UAVs. In light of this, we are able to analyze the downlink coverage of UAV-IRS-assisted NOMA transmission for two users and derive the corresponding coverage probabilities. Our coverage analyses shed light on the optimal allocations of transmit power between NOMA users and UAVs to accomplish the goal of ubiquitous and flexible NOMA transmission. We also conduct numerical simulations to validate our coverage analytical results while demonstrating the improved coverage performance achieved by aerial IRSs.