Cramer-Rao Bound Minimization for Movable Antenna-Assisted Multiuser Integrated Sensing and Communications

TL;DR

This paper proposes a joint beamforming and movable antenna positioning strategy for multiuser ISAC systems, minimizing sensing CRB and enhancing performance over fixed antennas using an AO framework with SDR and SCA techniques.

Contribution

It introduces a novel joint optimization framework for MA-assisted ISAC systems to minimize sensing CRB, addressing the NP-hard problem with advanced optimization techniques.

Findings

MA-assisted ISAC achieves lower CRB than fixed antennas

Proposed method effectively optimizes antenna positions and beamforming

Numerical results validate improved sensing performance

Abstract

This paper investigates a movable antenna (MA)-assisted multiuser integrated sensing and communication (ISAC) system, where the base station (BS) and communication users are all equipped with MA for improving both the sensing and communication performance. We employ the Cramer-Rao bound (CRB) as the performance metric of sensing, thus a joint beamforming design and MAs' position optimizing problem is formulated to minimize the CRB. However the resulting optimization problem is NP-hard and the variables are highly coupled. To tackle this problem, we propose an alternating optimization (AO) framework by adopting semidefinite relaxation (SDR) and successive convex approximation (SCA) technique. Numerical results reveal that the proposed MA-assisted ISAC system achieves lower estimation CRB compared to the fixed-position antenna (FPA) counterpart.