RIS-Assisted Near-Field Integrated Sensing and Symbiotic Radio Systems

To facilitate the growth of Internet of Things (IoT), future networks are promising to offer sensing capabilities and provide support for low-power communications. This paper investigates a reconfigurable intelligent surface (RIS) assisted near-field integrated sensing and symbiotic radio (SR) communication system, in which the base station (BS) not only improves symbiotic communication quality by RIS, but also performs target sensing based on the detection of target echo signals, and the BS antenna considers fully-digital and DMA architecture. An optimization problem is formulated under constraints of Cramer-Rao Bound (CRB) and signal to interference plus noise ratio (SINR) for decoding the signals of the primary user and IoT devices. An alternating optimization (AO) algorithmic framework based on semidefinite relaxation (SDR) is proposed to solve the problem, while for the matrix of the DMA, we choose the Riemannian Manifold Optimisation (RMO) algorithm to solve it. Numerical results show that near-field framework enables accurate location and DMA requires less transmission power than fully-digital antennas.