IRS-Aided Covert Communications Over Correlated Fading Channels: Analysis and Optimization

This letter considers the spatial correlation between the channels related to the warder and receiver in an intelligent reflecting surface (IRS)-aided covert communication system. Based on this, to maximize the covert transmission rate, a joint transmit beamforming and IRS phase shift optimization problem is formulated. Due to the channel correlation, a closed-form expression for the Kullback-Leibler (KL) divergence, which is utilized to evaluate covertness, is not obtainable. Therefore, the Bernstein-type inequality is adopted to derive an upper bound for the KL divergence and reformulate the covert constraint. Further, an alternating optimization algorithm is proposed to solve this optimization problem, where the beamforming vector is obtained by the semi-definite programming with a simple projection approximation procedure in the subproblem, and the phase shift is obtained by the penalty successive convex approximation in another subproblem. Simulation results show that by adopting the proposed design that considers channel correlation, the transmission rate does not decrease but rather increases under high correlation.