Active and Passive Beamforming for STAR-RIS Aided ISAC in IoT Networks

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and integrated sensing and communication (ISAC) are key technologies for the next-generation Internet-of-Things (IoT) networks. Compared with the reflecting-only RIS, STAR-RIS overcomes the limitation of half-space coverage, and provides more degrees-of-freedom (DoFs) for optimization and performance enhancement. In this paper, we study a STAR-RIS aided IoT network, where a base station (BS) serves several single-antenna downlink communication users and performs target sensing simultaneously. We aim to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all users by jointly optimizing the active and passive beamforming. The problem is nonconvex and challenging to tackle. We optimize the active and passive beamforming in an alternating fashion. In particular, we transform the max-min problem by the Dinkelbach method, and obtain the optimal active beamforming by SDR, and a rank-one solution for passive beamforming by the sequential rank-one constraint relaxation algorithm. Simulation results demonstrate the merits of the proposed approach over baseline schemes in maximizing the minimum SINR by up to 9.48 dB while guaranteeing the sensing performance.