Trajectory and Transmit Power Optimization for IRS-Assisted UAV Communication under Malicious Jamming

TL;DR

This paper proposes an optimization framework for IRS-assisted UAV communication systems to enhance data rates under jamming, by jointly optimizing transmit power, IRS beamforming, and UAV trajectory, using an alternating optimization algorithm.

Contribution

It introduces a novel joint optimization approach for IRS-assisted UAV communication under jamming, employing AO, SCA, and SDR techniques for improved performance.

Findings

The proposed algorithm significantly outperforms benchmark algorithms.

IRS deployment location depends on jamming power and IRS size.

Joint optimization enhances UAV communication robustness against jamming.

Abstract

In this letter, we investigate an unmanned aerial vehicle (UAV) communication system, where an intelligent reflecting surface (IRS) is deployed to assist in the transmission from a ground node (GN) to the UAV in the presence of a jammer. We aim to maximize the average rate of the UAV communication by jointly optimizing the GN's transmit power, the IRS's passive beamforming and the UAV's trajectory. However, the formulated problem is difficult to solve due to the non-convex objective function and the coupled optimization variables. Thus, to tackle it, we propose an alternating optimization (AO) based algorithm by exploiting the successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Simulation results show that the proposed algorithm can significantly improve the average rate compared with the benchmark algorithms. Moreover, it also shows that when the jamming power is large and the number of IRS elements is relatively small, deploying the IRS near the jammer outperforms deploying it near the GN, and vice versa.