Joint Beamforming and Power Control for QoS Balancing in Full-Duplex MIMO-ISAC Systems

Abstract

We consider a full-duplex (FD) multiple-input-multiple-output (MIMO) integrated sensing and communication (ISAC) system, where a multi-antenna base station (BS) simultaneously performs downlink transmission, uplink reception, and radar sensing over the same spectral resources. To support these functions, the BS jointly designs its transmit waveform and receive processing to manage the multi-user, co-channel interference, and sensing-related interference. The design objective is to balance the quality of service of among all communication users using the max-min fairness criterion, subject to a predetermined radar sensing requirement and transmit-power constraints. The resulting problem is difficult to solve due to its nonconvexity and the strong coupling among the downlink beamformers, radar waveform, receive filters, and uplink powers. Furthermore, existing approaches for related FD MIMO-ISAC problems are not readily applicable to the considered problem. As the first step to tackling this problem, we eliminate the radar and uplink receive filters through their closed-form optimal expressions and reformulate the design in terms of transmit covariance matrices by means of the semidefinite relaxation (SDR) method. We then derive an iterative solution based on the successive convex approximation (SCA) technique, where suitable transformations and approximations are introduced to arrive at convex subproblems that can be handled directly by off-the-shelf convex solvers. We also show that rank-one downlink beamforming solutions can be recovered from the relaxed formulation without loss of optimality. Numerical results demonstrate that the proposed waveform design converges quickly, satisfies the sensing requirement, and achieves communication performance close to a communication-only benchmark with improved user fairness.