STAR-RIS Aided Secure Integrated Sensing and Communication

Integrated sensing and communication (ISAC) has attracted considerable interest owing to its capacity to mitigate spectrum congestion and hardware efficiency. Nevertheless, there is a certain risk of leaking communication information, if sensing waveform includes communication data. In this paper, we integrate a secure transmission problem in an ISAC network with simultaneously transmitting and reflecting intelligent surface (STAR-RIS), which divides the whole space into two regions: the reflection space R and the transmission space T. The reflection space contains a radar sensing target, which we consider as a possible eavesdropper that attempts to intercept the communication transmission. The transmission space has a single communication user. The base station (BS) simultaneously sends messages to the single-antenna user and performs target detection with the help of STAR-RIS. In addition, to further increase the secrecy capacity, BS simultaneously generates artificial noise (AN) to interfere with the eavesdropper. We jointly optimize the transmission and reflected beam formation of BS and STAR-RIS, and consider the communication and perceptual power ratio to maximize the user secrecy capacity, On the basis of satisfying the minimum level of perception. The reference points-based evolutionary algorithm (RPEA) genetic algorithm is used to solve the non-convex problem. The simulation results demonstrate the effectiveness of the proposed scheme and AN can increase the user's capacity for confidentiality.