Fair Beamforming Design in Near-Field Integrated Sensing and Communication Systems

In this paper, we investigate the fair beamforming design for a near-field integrated sensing and communication (lSAC) system with multi-user and multi-target scenarios using a uniform circular array (UCA) configuration. To simultaneously ensure both network capacity and users’ fairness, we formulated the geometric mean rate (GMR) maximization problem under the sensing metric constraint based on joint distance and angle estimation Cramér-Rao Bound (CRB) for multiple targets. To solve the formulated complex and non-convex problem, we utilize the successive convex approximation (SCA) and the semidefinite relaxation (SDR) methods to obtain the globally optimal solution, and then propose a suboptimal solution based on the zero-forcing (ZF) algorithm to reduce complexity. Simulation results indicated that this scheme improves system fairness index by 5% to 10%, while ensuring both communication capacity and sensing performance.