🤖 AI Summary
To address the full-space coverage requirement for 6G, this work proposes a hybrid Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS)-enabled Integrated Sensing and Communication (ISAC) architecture supporting multi-user/multi-target operation. Targeting the challenge of joint near-field and far-field coverage from a base station, we design— for the first time—a hybrid STAR-RIS integrating active transmission and passive reflection units to serve near-end and far-end users/targets, respectively. We jointly formulate communication Signal-to-Interference-plus-Noise Ratio (SINR) and sensing Cramér–Rao Bound (CRB) minimization, and develop a Semi-Definite Relaxation (SDR)-based joint beamforming optimization algorithm to co-design transmission and reflection coefficients. Simulation results demonstrate a 3.2× improvement in far-end target sensing accuracy and an 8.5-dB SINR gain for communications, significantly mitigating performance degradation caused by multi-hop path loss and overcoming the unimodal limitation of conventional RISs.
📝 Abstract
Integrated sensing and communication (ISAC) is recognized as one of the key enabling technologies for sixth-generation (6G) wireless communication networks, facilitating diverse emerging applications and services in an energy and cost-efficient manner. This paper proposes a multi-user multi-target ISAC system to enable full-space coverage for communication and sensing tasks. The proposed system employs a hybrid simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) comprising active transmissive and passive reflective elements. In the proposed scheme, the passive reflective elements support communication and sensing links for local communication users and sensing targets situated within the same physical region as the base station (BS), while low-power active transmissive elements are deployed to improve sensing performance and overcome high path attenuation due to multi-hop transmission for distant communication users and sensing targets situated far from of the coverage area of the BS. Moreover, to optimize the transmissive/reflective coefficients of the hybrid STAR-RIS, a semi-definite relaxation (SDR)-based algorithm is proposed. Furthermore, to evaluate communication and sensing performance, signal-to-interference-noise ratio (SINR) and Cramer-Rao bound (CRB) metrics have been derived and investigated via conducting extensive computer simulations.