STARS Enabled Full-Space Integrated Sensing and Communications

Abstract

A simultaneously transmitting and reflecting surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where a novel bi-directional sensing-STARS architecture is devised to facilitate the full-space communication and sensing. Based on the proposed framework, a joint optimization problem is formulated, where the Cramer-Rao bound (CRB) for estimating the 2-dimension direction-of-arrival of the sensing target is minimized. An alternating optimization algorithm is proposed. In particular, the maximum number of deployable sensors is obtained in the closed-form expressions. Simulation results validate that: 1) STARS was capable of providing superior sensing performance compared to the conventional reconfigurable intelligent surface, and 2) the maximum likelihood estimator can be adopted in the proposed strategy to achieve high-quality sensing.