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arXiv 2402.04532eess.SP
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双主动可重构智能表面辅助雷达-通信共存系统的联合波束成形设计

Joint Beamforming Design for Double Active RIS-assisted Radar-Communication Coexistence Systems

Mengyu Liu, Hong Ren, Cunhua Pan, Boshi Wang, Zhiyuan Yu, Ruisong Weng, Kangda Zhi, Yongchao He

AI总结:

针对雷达-通信共存系统中无源RIS乘性衰落限制性能的问题,提出双主动RIS辅助系统,通过PDD与BCD联合优化波束成形与反射系数,在满足雷达约束下最大化通信速率,仿真验证其优于单主动和双无源方案。

摘要:

集成感知与通信(ISAC)技术已被视为下一代无线通信系统中的关键候选技术之一。然而,当雷达与通信设备在同一系统中共存,即雷达-通信共存(RCC)时,通信系统对雷达的干扰可能很大且不可忽视。近年来,可重构智能表面(RIS)被引入RCC系统以降低干扰。然而,无源RIS引入的“乘性衰落”效应限制了其性能。为解决这一问题,我们考虑一个双主动RIS辅助的RCC系统,该系统聚焦于雷达波束成形向量和主动RIS反射系数矩阵的设计,以最大化通信系统的可达数据速率。所考虑的系统需满足雷达检测约束以及雷达和RIS处的功率预算。由于该问题是非凸的,我们提出了一种基于惩罚对偶分解(PDD)框架的算法。具体而言,我们首先引入辅助变量将耦合变量重构为等式约束,并通过PDD框架将这些约束纳入目标函数。然后,我们通过块坐标下降(BCD)方法将等价问题解耦为若干子问题。此外,我们采用拉格朗日对偶方法交替优化这些子问题。仿真结果验证了所提算法的有效性。此外,结果还表明,在相同功率预算下,在RCC系统中部署双主动RIS比部署单主动RIS和双无源RIS能实现更高的数据速率。

英文摘要:

Integrated sensing and communication (ISAC) technology has been considered as one of the key candidate technologies in the next-generation wireless communication systems. However, when radar and communication equipment coexist in the same system, i.e. radar-communication coexistence (RCC), the interference from communication systems to radar can be large and cannot be ignored. Recently, reconfigurable intelligent surface (RIS) has been introduced into RCC systems to reduce the interference. However, the "multiplicative fading" effect introduced by passive RIS limits its performance. To tackle this issue, we consider a double active RIS-assisted RCC system, which focuses on the design of the radar's beamforming vector and the active RISs' reflecting coefficient matrices, to maximize the achievable data rate of the communication system. The considered system needs to meet the radar detection constraint and the power budgets at the radar and the RISs. Since the problem is non-convex, we propose an algorithm based on the penalty dual decomposition (PDD) framework. Specifically, we initially introduce auxiliary variables to reformulate the coupled variables into equation constraints and incorporate these constraints into the objective function through the PDD framework. Then, we decouple the equivalent problem into several subproblems by invoking the block coordinate descent (BCD) method. Furthermore, we employ the Lagrange dual method to alternately optimize these subproblems. Simulation results verify the effectiveness of the proposed algorithm. Furthermore, the results also show that under the same power budget, deploying double active RISs in RCC systems can achieve higher data rate than those with single active RIS and double passive RISs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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