Multi-user ISAC through Stacked Intelligent Metasurfaces: New Algorithms and Experiments
Ziqing Wang, Hongzheng Liu, Jianan Zhang, Rujing Xiong, Kai Wan, Xuewen Qian, Marco Di Renzo, Robert C. Qiu
Abstract
This paper investigates a stacked intelligent metasurfaces (SIM)-assisted integrated sensing and communications (ISAC) system. An extended target model is considered, where the base station (BS) aims to estimate the complete target response matrix relative to the SIM. Under the constraints of minimum signal-to-interference-plus-noise ratio (SINR) for the communication users (CUs) and maximum transmit power, we jointly optimize the transmit beamforming at the BS and the end-to-end transmission matrix of the SIM, to minimize the Cramér-Rao bound (CRB) for target estimation. Effective algorithms such as alternating optimization (AO) and semidefinite relaxation (SDR) are employed to solve the non-convex SINR-constrained CRB minimization problem. Finally, we design and build a hardware platform for SIM, and experimentally evaluate the performance of SIM-aided communication and sensing tasks.