The Interplay of DMA and RIS for Near-Field Integrated Sensing and Symbiotic Radio Systems

This paper investigates a near-field integrated sensing and symbiotic radio (SR) communication system supported by a reconfigurable intelligent surface (RIS). In the near-field region, the base station (BS) leverages the RIS to realize symbiotic communication performance while simultaneously performing target sensing by analyzing echo signals. The BS antenna architecture encompasses both fully-digital and dynamic metasurface antenna (DMA) configurations. An optimization problem is developed to maximize the symbiotic transmission rate for the IoT devices, subject to constraints imposed by the Cram4er-Rao bound (CRB), the signal-to-noise ratio (SNR), the RIS phase shifts, the antenna parameters and system power. An alternating optimization (AO) framework with a semidefinite relaxation (SDR) is proposed to solve the problem, while for the Lorentz-constrained phase matrix of the frequency response of DMA surface elements, we propose to apply the Riemannian conjugate gradient (RCG) algorithm to solve it. Numerical results validate the efficiency of the proposed framework, demonstrating that the near-field approach enables accurate target localization. Furthermore, where the DMA configuration achieves higher symbiotic transmission rates with lower power consumption compared to fully-digital antennas.