RIS-Aided Beamforming Design for Dual Functional Radar and Communications

Dual functional radar and communications (DFRC) and reconfigurable intelligent surface (RIS) serve as two promising paradigms for enhancing the system capacity in the next-generation wireless communications. However, coordinating RIS and DFRC to improve system communication and detection performance is a complex problem involving multiple interrelated variables such as the RIS phase shift matrix and the DFRC beamforming vector etc. In this paper, we investigate the RIS-aided beamforming design in the DFRC system, which aims to maximize the radar detection probability while maintaining the user communication performance. Due to the coupling of the RIS phase shift matrix and the DFRC beamforming vector and the non-convex unit modulus constraint, the optimization problem is highly non-convex, which is difficult to solve directly. To tackle the issue, we develop a two-stage alternating algorithm by splitting the problem into a series of subproblems. Specifically, we adopt semidefinite relaxing (SDR) to optimize the DFRC beamforming vector, while the majorization-minimization (MM) framework is utilized for RIS phase shift design. Simulation results show the proposed scheme can enhance the radar detection performance compared to the benchmark methods.