Covert Beamforming Design for Holographic Integrated Sensing and Communication With Imperfect CSI

In this paper, we propose a novel covert transmission scheme for reconfigurable holographic surface (RHS)-aided integrated sensing and communication (ISAC) system with imperfect channel state information (CSI). Considering full and partial channel uncertainty models, we jointly devise the digital and holographic beamforming along with the receive filter to maximize the worst-case and outage-constrained achievable rate (AR) of communication users while guaranteeing the sensing capability and covertness requirement. The resulting optimization problems are difficult to solve owing to the non-convexity caused by the semi-infinite constraints (SICs) and the coupled design variables. After approximating the worst-case and outage constraints by exploiting the S-procedure, successive convex approximation (SCA) and Bernstein-type inequality, we propose a secure solution that efficiently optimizes all variables by using convex optimization methods. To understand the proposed algorithm better, both the convergence and computational complexity are discussed. Simulation results show that by incorporating the RHS technique into the optimization design, the covert transmission performance of ISAC systems are improved while ensuring a certain level of sensing performance.