Integrated Sensing and Communication With Reconfigurable Distributed Antenna and Reflecting Surface: Joint Beamforming and Mode Selection

Abstract

This article presents a novel integrated sensing and communication (ISAC) framework that leverages recent advancements in reconfigurable distributed antennas and reflecting surfaces (RDARS). RDARS is a programmable structure composed of numerous elements, each of which can be flexibly configured to operate in either reflection mode, resembling a passive reconfigurable intelligent surface (RIS), or connected mode, functioning as a remote transmit or receive antenna. Our RDARS-aided ISAC framework effectively mitigates the adverse effects of multiplicative fading compared to passive RIS-aided counterparts and reduces costs and energy consumption relative to active RIS-aided systems. Within this framework, we address a radar output signal-to-noise ratio (SNR) maximization problem by jointly optimizing the active transmit beamforming matrix, the reflection and mode selection matrices of RDARS, and the receive filter, while ensuring communication requirements are met. To tackle the inherent nonconvexity and mixed-integer optimization challenges, we propose an efficient penalty-based iterative algorithm with guaranteed convergence based on the majorization-minimization (MM) framework. Additionally, we present some interesting insights about the mode selection of RDARS by considering a RDARS-aided sensing system. Numerical results demonstrate the superior performance of our framework compared to existing structures, attributed to the distribution, reflection, and selection gains provided by the dynamically configured RDARS.