Minimum secrecy rate maximization for intelligent reflecting surface assisted multi-user communication system

Intelligent reflecting surface (IRS) has recently received considerable attention from the wireless communications research community. In this paper, we investigate a secure communication system aided by an IRS, comprising multi-user and a single eavesdropper. Specifically, under the unit modulus constraint at the IRS and the transmit power constraint at the access point (AP), we maximize the minimum secrecy rate by jointly optimizing the beamforming vectors at the multi-antenna AP and the phase shift matrix of the IRS. In order to solve the non-convex optimization problem, we propose an alternating optimization (AO) algorithm and obtain a suboptimal solution. Firstly, to optimize the beamforming vectors, the semidefinite relaxation (SDR) technique is employed. Secondly, with the aim of addressing the issue of phase shift matrix optimization at the IRS, the successive convex approximation (SCA) method is applied. Simulation results demonstrate that our proposed scheme performs better than the benchmark schemes in terms of both algorithm convergence and secrecy rate performance.