Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted wireless communication system and present two joint channel estimation and signal recovery schemes based on message passing algorithms in this paper. Specifically, the proposed bidirectional scheme applies the Taylor series expansion and Gaussian approximation to simplify the sum-product procedure in the formulated problem. In addition, the inner iteration that adopts two variants of approximate message passing algorithms is incorporated to ensure robustness and convergence. Two ambiguities removal methods are also discussed in this paper. Our simulation results show that the proposed schemes show the superiority over the state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed schemes.

中文翻译：

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RIS 授权的多用户通信的联合信道估计和信号恢复


可重构智能表面（RIS）最近被认为是未来无线网络中节能解决方案的有前途的候选者。它们的动态和低功耗配置可实现覆盖范围扩展、大规模连接和低延迟通信。由于涉及 RIS 单元元件和传输信号的大量未知变量，基于 RIS 的系统中的信道估计和信号恢复是最关键的技术挑战。为了解决这个问题，本文重点关注RIS辅助的无线通信系统，提出了两种基于消息传递算法的联合信道估计和信号恢复方案。具体来说，所提出的双向方案应用泰勒级数展开和高斯近似来简化公式化问题中的和积过程。此外，内部迭代采用了两种近似消息传递算法的变体，以确保鲁棒性和收敛性。本文还讨论了两种歧义消除方法。我们的模拟结果表明，所提出的方案显示出优于最先进的基准方法的优越性。我们还提供了不同 RIS 参数设置对所提出方案的影响的见解。