Intelligent Reflecting Surface Aided Secure UAV Communications

TL;DR

This paper proposes an optimization framework for enhancing physical-layer security in UAV communications aided by an intelligent reflecting surface, achieving higher secrecy rates through joint phase shift, power, and location optimization.

Contribution

It introduces a novel joint optimization approach for IRS-assisted UAV security, employing fractional programming and convex approximation techniques to solve a complex non-convex problem.

Findings

Proposed algorithm significantly improves secrecy rate over benchmarks.

Closed-form solutions for phase shifts and power at each iteration.

Simulation results validate the effectiveness of the IRS-aided secure UAV communication scheme.

Abstract

In this letter, we study the secure communication problem in the unmanned aerial vehicle (UAV) enabled networks aided by an intelligent reflecting surface (IRS) from the physical-layer security perspective. Specifically, the IRS is deployed to assist the wireless transmission from the UAV to the ground user in the presence of an eavesdropper. The objective of this work is to maximize the secrecy rate by jointly optimizing the phase shifts at the IRS as well as the transmit power and location of the UAV. However, the formulated problem is difficult to solve directly due to the non-linear and non-convex objective function and constraints. By invoking fractional programming and successive convex approximation techniques, the original problem is decomposed into three subproblems, which are then transformed into convex ones. Next, a low-complexity alternating algorithm is proposed to solve the challenging non-convex problem effectively, where the closed-form expressions for transmit power and phase shifts are obtained at each iteration. Simulations results demonstrate that the designed algorithm for IRS-aided UAV communications can achieve higher secrecy rate than benchmarks.