Integrated Sensing and Communications for Reconfigurable Intelligent Surface-Aided Cell-Free Networks

This work explores a cell-free integrated sensing and communication (CF-ISAC) framework in which distributed access points work together to support communication users (UEs) with assistance from multiple reconfigurable intelligent surfaces (RISs) while simultaneously performing target sensing. An effective strategy is introduced for the joint optimization of communication parameters, sensing beamforming designs, and reflecting coefficients, with the goal of enhancing the minimum signal-to-interference-plus-noise ratio (SINR) among all UEs. To address the complexity of this non-convex optimization problem, a robust alternating optimization method is designed. The numerical results confirm that the proposed approach significantly boosts the minimum SINR in CF-ISAC systems, demonstrating the advantages of utilizing RISs.