Joint Beamforming and Reflection Design for RIS-assisted ISAC Systems

TL;DR

This paper explores how reconfigurable intelligent surfaces can enhance integrated sensing and communication systems by jointly optimizing beamforming and reflection to improve performance.

Contribution

It introduces a novel joint design framework for RIS-assisted ISAC systems, including an efficient algorithm to optimize beamforming, reflection, and filtering.

Findings

Proposed scheme outperforms traditional methods in simulations.

The joint optimization improves communication sum-rate and radar SNR.

The algorithm effectively solves the non-convex optimization problem.

Abstract

In this paper, we investigate the potential of employing reconfigurable intelligent surface (RIS) in integrated sensing and communication (ISAC) systems. In particular, we consider an RIS-assisted ISAC system in which a multi-antenna base station (BS) simultaneously performs multi-user multi-input single-output (MU-MISO) communication and target detection. We aim to jointly design the transmit beamforming and receive filter of the BS, and the reflection coefficients of the RIS to maximize the sum-rate of the communication users, while satisfying a worst-case radar output signal-to-noise ratio (SNR), the transmit power constraint, and the unit modulus property of the reflecting coefficients. An efficient iterative algorithm based on fractional programming (FP), majorization-minimization (MM), and alternative direction method of multipliers (ADMM) is developed to solve the complicated non-convex problem. Simulation results verify the advantage of the proposed RIS-assisted ISAC scheme and the effectiveness of the developed algorithm.