Robust Secrecy Rate Maximization for IRS-Aided MISO Communication Systems

Currently, the intelligent reflecting surface (IRS) has been applied to improve the physical layer security (PLS) in wireless networks. However, obtaining perfect channel state information (CSI) of eavesdroppers is challenging due to the covert nature of eavesdroppers. Therefore, a robust beamforming design scheme based on the IRS-aided multi-user multiple-input single-output (MU-MISO) system is proposed, which aims to maximize system secrecy rate subject to the maximum transmit power of the base station under imperfect eavesdropper CSI. Since the optimization problem is non-convex and the optimization variables are strongly coupled, we propose an alternative optimization (AO) algorithm and semidefinite programming (SDP) relaxation to address this problem. Simulation results demonstrated the performance of the proposed method.