Secrecy Rate Optimization for Multi-User Secure Communication Assisted by Intelligent Reflecting Surfaces (IRS) Under Imperfect CSI Conditions

Abstract

This paper investigates the application of intelligent reflecting surfaces (IRS) in secure wireless communication under multi-user and multi-eavesdropper scenarios, focusing on addressing the challenges posed by imperfect channel state information (CSI). In this context, multiple users receive confidential information via a multi-antenna access point (AP), while the eavesdroppers' channels may be stronger than the legitimate communication channels and exhibit spatial correlation. To improve secure communication efficiency, a unified optimization method is introduced, combining AP signal direction adjustments and IRS reflection control to boost the confidentiality rate of authorized communication pathways. Considering the challenges of imperfect CSI and the presence of multiple users and eavesdroppers, the paper employs alternating optimization and semidefinite relaxation (SDR) methods, combined with an iterative hybrid optimization (IHO) algorithm, to solve the optimization problem and obtain high-quality suboptimal solutions. Simulation outcomes reveal that the suggested approach markedly enhances confidentiality rates in multi-user and multi-eavesdropper scenarios compared to traditional benchmark models, effectively mitigating the impact of imperfect CSI.