A Robust STAR-RIS-Assisted MU-MIMO System for Integrated Sensing and Communications

Recently, integrated sensing and communications (ISAC) technology has attracted significant attention due to its potential to support various new applications in upcoming wireless networks. Nonetheless, the effectiveness of radar sensing and wireless communication in ISAC networks is often compromised by unpredictable electromagnetic environments. In this study, we explore an innovative, simultaneously transmitting and reflecting-reconfigurable intelligent surface (STAR-RIS)-assisted ISAC framework to maximize overall spectral efficiency for cellular users while maintaining the minimum required quality-of-service (QoS) of each user and ensuring the minimum signal-to-interference-plus-noise ratio (SINR) of the echo signal received at the dual-function radar and communication base-station (DFRC-BS) from targets. In particular, we formulate a robust sum-rate maximization problem for single-antenna multiple users by jointly optimizing the active beamforming vectors at the DFRC-BS and passive beamforming matrices at the STAR-RIS under norm-bounded imperfect channel state information (ICSI). To address the formulated non-convex resource allocation design problem, we employ an alternating optimization (AO) method, which iteratively solves the robust i) active beamforming vectors design at the DFRC-BS and ii) passive beamforming matrices at the STAR-RIS by exploiting S-procedure, semi-definite relaxation (SDR), and penalty convex-concave programming (CCP) methods which acquire a suboptimal solution to the framework. Furthermore, simulation results illustrate the efficacy of the proposed robust STAR-RIS-assisted ISAC systems, achieving approximately 30% higher spectral efficiency in comparison to the conventional reflecting-only RIS (R-RIS)-assisted ISAC systems under the specified target sensing constraints. Moreover, the results show that the time-splitting mode outperforms other operating modes of the STAR-RIS in ISAC performance.