Movable Antenna-Aided Dynamic Beamforming for ISAC Systems

This paper explores an integrated sensing and communication (ISAC) system based on the movable antenna (MA) and hybrid architecture, where a base station (BS) adopts transmit MAs to achieve communication and sensing. Specially, we formulate communication and sensing signal models based on MAs and derive the Cramér-Rao bound (CRB) as the target sensing performance. The dynamic beamformer design problem is formulated to minimize the CRB, subject to constraints on the user communication rates, total power budget, analog beam-former hardware limitations, and MA movable regions. To address the intractability of this optimization problem, we propose an alternative optimization framework, where the penalty dual decomposition (PDD) is utilized to solve beamformers, and the gradient descent method (GDM) is utilized to generate optimal MAs positions. Numerical results demonstrate that our proposed approach outperforms traditional fixed-position antennas(FPA)-aided ISAC beamforming schemes in balancing performances and hardware.