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

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.

I. Introduction

The future wireless communication system will develop towards high data rate and intelligentization to provide better services [1]. To enable high data rate transmission, there are two mainstream solutions. One is to push the wireless communication spectrum towards the higher frequency, such as millimeter waves [2] and even Terahertz waves [3]; the other is to share frequency bandwidth with other systems. Meanwhile, to realize the intelligent wireless communication system, artificial intelligence (AI) is regarded as one of the most potential techniques [7], [8], and massive sensing data are necessary for designing and training the AI network. Further, the data can be obtained via deploying radar systems in communication systems. Due to the above two demands, integrated sensing and communication (ISAC) [4]–[6] has recently attracted widespread attention in both academia and industry since it can collect sensing data and improve spectrum efficiency simultaneously. Specifically, the studies of ISAC focus on two aspects: 1) the dual-functional radar and communication (DFRC) system [9]–[11], in which radar and communication devices share the same hardware; 2) the communication radar coexistence system [12], [13], in which radar and communication devices are separated and share the same frequency bandwidth. In this paper, we focus on the latter, and existing relevant works mainly aim at suppressing the mutual interference between two systems via joint radar and communication beamforming design.