Beamforming design for RIS-aided MIMO ISAC Systems based on Mutual Information

In this paper, we investigate reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) systems based on sensing mutual information (MI). With the deployment of the RIS, the base station (BS) can perceive the sensing target via the reflected sensing link created by the RIS and communicate with users simultaneously, and the channel between the BS and the RIS is considered as a light-of-sight (LoS) channel. Our aim is to maximize the sensing MI, subject to the quality of service (QoS) constraints of different users, power constraint of the BS, and the unit-modulus constraint of the RIS. Although the formulated nonconvex optimization problem with quartic objective function is difficult to solve, we propose an iterative algorithm based on rank-1 projection, majorization-minimization (MM), eigenvalue decomposition (EVD), and convex-concave procedure (CCP) methods. We also prove that the dedicated sensing beamformer can improve the sensing MI unless the BS-users link is blocked by some obstacles. Numerical results demonstrate that our proposed algorithm outperforms the other benchmarks on the performance of sensing MI and beampattern.