Sensing Performance Enhancement for Reconfigurable Intelligent Surface Empowered Integrated Sensing and Communications

Integrated Sensing and Communication (ISAC) technology has become a research hotspot for future sixthgeneration (6G) mobile networks, as it integrates communication and sensing functions into a single platform, significantly enhancing wireless resource utilization and supporting foreseeable applications, such as smart cities and autonomous driving. However, the implementation of ISAC systems faces numerous challenges, particularly in optimizing both communication and sensing performance simultaneously in complex wireless propagation environments. This paper proposes a novel Reconfigurable Intelligent Surface (RIS)-assisted ISAC system, where sensing units are embedded in the RIS to reduce multihop attenuation during the sensing procedure, thereby improving sensing accuracy. Specifically, a beamforming design is proposed for joint sensing and multi-user communication in the case of a single target. By imposing signal-to-interference-plus-noise-ratio (SINR) constraints on multiple users, an optimization problem is formulated to minimize the Cramer-Rao Bound (CRB) of the target's two-dimensional (2D) direction-of-arrivals (DOAs) estimation. To address the formulated problem, a dual-loop iterative algorithm based on a penalty dual decomposition (PDD) framework is proposed. Furthermore, two different methods, i.e., the semidefinite programming (SDP) method and the physically implementable sequential phase-shift rotation (SPR) method, are developed to optimize the phase shifts at RIS. Finally, numerical results validate the convergence performance of the proposed algorithm, where both methods achieves superior estimation performance and provides ideal sensing accuracy.