RIS辅助MIMO系统中基于Kronecker和张量分解的结构化信道参数估计

中文摘要 AI 辅助

本文针对采用均匀矩形阵列、在视距传播条件下的可重构智能表面（RIS）辅助多输入多输出（MIMO）系统，提出了结构化的信道参数估计器。通过利用级联信道的Kronecker和多线性结构，我们引入了连续Kronecker分解（SKF）以及两种三阶张量参数估计（TOPE）方法：TOPE-ALS和TOPE-HOSVD。这些估计器从导频滤波后的信号矩阵中恢复空间特征，然后解耦相应的水平和垂直空间频率。这种结构化方法在降低计算复杂度的同时达到了基准估计精度，为RIS辅助系统提供了一种高效的解决方案。

英文摘要

This paper proposes structured channel-parameter estimators for reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) systems employing uniform rectangular arrays under line-of-sight propagation. By exploiting the Kronecker and multilinear structures of the cascaded channel, we introduce the Successive Kronecker Factorization (SKF) alongside two Third-Order Tensor Parameter Estimation (TOPE) methods: TOPE-ALS and TOPE-HOSVD. These estimators recover spatial signatures from the pilot-filtered signal matrix, and then decouple the corresponding horizontal and vertical spatial frequencies. This structured formulation achieves benchmark estimation accuracy while reducing computational complexity, offering a efficient solution for RIS-aided systems.

发表机构

• Federal University of Ceará (UFC)（塞阿拉联邦大学）

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