论文标题
RIS辅助多用户误差通信中的平行因子分解通道估计
Parallel Factor Decomposition Channel Estimation in RIS-Assisted Multi-User MISO Communication
论文作者
论文摘要
可重构智能表面（RISS）最近被视为用于未来无线网络的节能解决方案，因为它们的快速和低功率配置可实现大规模连接性和低延迟通信。基于RIS的系统中的渠道估计是最关键的挑战之一，因为大量反射单元元素及其独特的硬件约束。在本文中，我们专注于RIS辅助多用户多用户多输入单输出（MISO）通信系统的下行链路，并提出了一种基于平行因子（PARAFAC）分解的方法，以展开所得的级联信道模型。提出的方法包括一种交替的最小二乘算法，以迭代估算基站和RI之间的通道以及RIS和用户之间的通道。我们的选择性仿真结果表明，所提出的迭代通道估计方法的表现优于使用Genie Aided信息的基准方案。我们还提供了有关不同RIS设置对拟议算法的影响的见解。
Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-efficient solution for future wireless networks due to their fast and low power configuration enabling massive connectivity and low latency communications. Channel estimation in RIS-based systems is one of the most critical challenges due to the large number of reflecting unit elements and their distinctive hardware constraints. In this paper, we focus on the downlink of a RIS-assisted multi-user Multiple Input Single Output (MISO) communication system and present a method based on the PARAllel FACtor (PARAFAC) decomposition to unfold the resulting cascaded channel model. The proposed method includes an alternating least squares algorithm to iteratively estimate the channel between the base station and RIS, as well as the channels between RIS and users. Our selective simulation results show that the proposed iterative channel estimation method outperforms a benchmark scheme using genie-aided information. We also provide insights on the impact of different RIS settings on the proposed algorithm.
