RIS-Assisted Communication Radar Coexistence: Joint Beamforming Design and Analysis

TL;DR

This paper proposes a RIS-assisted joint beamforming design for integrated sensing and communication systems to enhance communication performance and suppress mutual interference in radar-communication coexistence scenarios.

Contribution

It introduces a double-RIS-assisted system with a novel optimization framework and algorithms for joint beamforming, addressing mutual interference and radar detection performance.

Findings

The proposed algorithms outperform benchmarks in simulations.

Closed-form solution for high radar power scenario.

Low-complexity algorithm effectively handles low radar power case.

Abstract

Integrated sensing and communication (ISAC) has been regarded as one of the most promising technologies for future wireless communications. However, the mutual interference in the communication radar coexistence system cannot be ignored. Inspired by the studies of reconfigurable intelligent surface (RIS), we propose a double-RIS-assisted coexistence system where two RISs are deployed for enhancing communication signals and suppressing mutual interference. We aim to jointly optimize the beamforming of RISs and radar to maximize communication performance while maintaining radar detection performance. The investigated problem is challenging, and thus we transform it into an equivalent but more tractable form by introducing auxiliary variables. Then, we propose a penalty dual decomposition (PDD)-based algorithm to solve the resultant problem. Moreover, we consider two special cases: the large radar transmit power scenario and the low radar transmit power scenario. For the former, we prove that the beamforming design is only determined by the communication channel and the corresponding optimal joint beamforming strategy can be obtained in closed-form. For the latter, we minimize the mutual interference via the block coordinate descent (BCD) method. By combining the solutions of these two cases, a low-complexity algorithm is also developed. Finally, simulation results show that both the PDD-based and low-complexity algorithms outperform benchmark algorithms.