Optimal Resource Allocation Design for Wideband ISAC Systems with Discrete True-Time Delayers

This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. We aim to minimize the Cramér-Rao Bound (CRB) for target estimation by jointly optimizing subcarrier allocation, digital beamforming matrices, and frequency-independent and frequency-dependent analog beamforming matrices at the base station (BS) adopting a hybrid beamforming structure. We formulate the optimization design as a non-convex mixed-integer nonlinear programming (MINLP) problem, subject to the transmit power budget constraint of the BS, the rate quality-of-service (QoS) constraints for users, and the discrete nature of the analog beamformer. To achieve a globally optimal solution for the complicated design problem, an iterative resource allocation algorithm is proposed by exploiting the generalized Bender's decomposition (GBD) method. Our simulation results demonstrate the crucial importance of simultaneously optimizing all available degrees-of-freedom (DoFs) in wideband ISAC systems jointly and optimally. Besides, our results unveil that deploying true-time-delayer (TTD) units with limited bit-resolution time delays can achieve substantial gains in both communication and sensing performances.