IRS-Aided Secure Communications with Linear Precoding: Performance Analysis and System Design

Intelligent reflecting surface (IRS) has been shown effective in improving the security of communication systems, but the difficulty in acquiring instantaneous channel state information at the IRS makes the implementation of IRS-aided systems challenging. In this paper, we consider a two-timescale design for IRS-aided secure MISO communication where linear precoding schemes such as regularized zero-forcing (RZF) and zero-forcing (ZF) are adopted due to their low complexity and ability to suppress information leakage. To this end, we first derive the closed-form expression for the ergodic secrecy sum rate (ESSR) of IRS-aided MISO systems, considering both the uncommon and common correlation structures. Then, based on the evaluation results, we propose a two-timescale algorithm to maximize the ESSR by alternatively optimizing the regularization factor of the RZF precoder and phase shifts of the IRS. Simulation results validate the accuracy of the theoretical analysis and the effectiveness of the proposed algorithm.