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.

中文翻译：

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RIS 辅助通信雷达共存：联合波束成形设计与分析


集成传感与通信（ISAC）被认为是未来无线通信最有前途的技术之一。然而，通信雷达共存系统中的相互干扰不容忽视。受可重构智能表面（RIS）研究的启发，我们提出了一种双RIS辅助共存系统，其中部署两个RIS来增强通信信号并抑制相互干扰。我们的目标是联合优化 RIS 和雷达的波束成形，以最大限度地提高通信性能，同时保持雷达检测性能。研究的问题具有挑战性，因此我们通过引入辅助变量将其转换为等效但更容易处理的形式。然后，我们提出了一种基于罚分对偶分解（PDD）的算法来解决由此产生的问题。此外，我们考虑两种特殊情况：大雷达发射功率场景和低雷达发射功率场景。对于前者，我们证明波束成形设计仅由通信信道决定，并且可以以封闭形式获得相应的最优联合波束成形策略。对于后者，我们通过块坐标下降（BCD）方法最小化相互干扰。通过结合这两种情况的解决方案，还开发了一种低复杂度算法。最后，仿真结果表明，基于 PDD 的算法和低复杂度算法均优于基准算法。