Reconfigurable intelligent surface-aided dual-function radar and communication systems with MU-MIMO communication^☆

Abstract

In this paper, we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication (ISAC) system. Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming. Specifically, the weighted minimum mean-square error method is first used to reformulate the original problem into an equivalent one. Then, we utilize an alternating optimization algorithm to decouple the optimization variables and decompose this challenging problem into two subproblems. Given reflecting coefficients, a penalty-based algorithm is utilized to deal with the non-convex radar Signal-to-Noise Ratio (SNR) constraints. For the given beamforming matrix of the base station, we apply majorization-minimization to transform the problem into a Quadratic Constraint Quadratic Programming (QCQP) problem, which is ultimately solved using a Semi-Definite Relaxation (SDR) based algorithm. Simulation results illustrate the advantage of deploying reconfigurable intelligent surface in the considered multi-user Multiple-Input Multiple-Output (MIMO) ISAC systems.

Keywords

Integrated sensing and communication / Reconfigurable intelligent surface / Dual-function radar-communication

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