Joint Beamforming Design for RIS-Assisted Integrated Sensing and Communication Systems

TL;DR

This paper proposes a joint beamforming design for RIS-assisted integrated sensing and communication systems, optimizing performance by combining active and passive beamforming techniques with an efficient iterative algorithm.

Contribution

It introduces a novel joint beamforming optimization framework for RIS-assisted ISAC systems, integrating fractional programming, MM, and manifold optimization methods.

Findings

RIS deployment improves ISAC system performance

The proposed algorithm effectively maximizes sum-rate

Simulation results confirm the benefits of joint beamforming

Abstract

Integrated sensing and communication (ISAC) has been envisioned as a promising technology to tackle the spectrum congestion problem for future networks. In this correspondence, we investigate to deploy a reconfigurable intelligent surface (RIS) in an ISAC system for achieving better performance. In particular, a multi-antenna base station (BS) simultaneously serves multiple single-antenna users with the assistance of a RIS and detects potential targets. The active beamforming of the BS and the passive beamforming of the RIS are jointly optimized to maximize the achievable sum-rate of the communication users while satisfying the constraint of beampattern similarity for radar sensing, the restriction of the RIS, and the transmit power budget. An efficient alternating algorithm based on the fractional programming (FP), majorization-minimization (MM), and manifold optimization methods is developed to convert the resulting non-convex optimization problem into two solvable sub-problems and iteratively solve them. Simulation studies illustrate the advancement of deploying RIS in ISAC systems and the effectiveness of the proposed algorithm.