RIS-Assisted Integrated Sensing and Communication System With Physical Layer Security Enhancement by DRL Approach

Reconfigurable intelligent surfaces (RIS) play a crucial role in enhancing the security of integrated sensing and communication (ISAC) systems. In this paper, RIS is explored to assist the secure transmission of user data in ISAC system. Through the joint design of the transmit beamforming and RIS discrete phase shifter, we aim to maximize user's secure rates while ensuring target sensing performance. Due to the coupling of optimization variables, conventional optimization methods are hard to address this formulated problem. Therefore, a deep reinforcement learning (DRL) scheme by utilizing the soft actorcritic (SAC) and alternating optimization (AO) algorithms is employed to design the transmit beamforming and the RIS discrete phase shifter, respectively. Simulation results indicate that the problem scheme could obtain a significant improvement in enhancing user secure rates compared to other benching schemes.