Dynamic Metasurface Antennas Assisted Integrated Sensing and Communication

In this paper, we investigate an integrated sensing and communication (ISAC) system assisted by a dynamic metasurface antenna (DMA), where the base station (BS) simultaneously communicates with multiple users and performs target sensing. Specifically, this paper aims to maximize the radar signal-to-noise ratio (SNR) at the BS by jointly optimizing the beamforming matrix and the DMA weight matrix, subject to signal-to-interference-plus-noise ratio (SINR) constraints for the users, the maximum transmit power at the BS and the Lorentzian constraint associated with the DMA elements. To tackle this non-convex optimization problem, an alternating optimization (AO) algorithm is proposed. In this algorithm, semidefinite relaxation (SDR) is employed to optimize the beamforming matrix, while sequential rank-one constraint relaxation (SRCR) is used to optimize the DMA weight matrix. Additionally, the penalty dual decomposition (PDD) and successive convex approximation (SCA) techniques are utilized as an alternative approach to solve the DMA weight matrix. Simulation results demonstrate that the DMA-assisted ISAC system achieves favorable results. The impact of different parameters on the objective value is analyzed, which shows that the PDD method outperforms the SRCR method.