基于字典的张量分解辅助毫米波MU-MIMO系统时变信道估计

Tongtong Weng, Wuyang Zhou
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引用次数: 0

摘要

本研究主要针对多输入多输出(MIMO)毫米波系统的上行时变信道估计问题。我们将混合波束形成结构中的时变信道估计转换为考虑到达/离开角(AoA/AoDs)、多普勒频移和路径增益的参数估计问题。我们还提出了一种两阶段信道估计方法。我们在初始阶段将接收信号描述为三阶张量,并提供了一种结合匹配追踪(MP)和称为基于字典的张量分解的交替最小二乘(ALS)的算法来估计AoA/ aod。在第二阶段,我们使用估计的AoA/ aod恢复多普勒频移和路径增益。最后恢复了整个时变信道。仿真结果表明,该方法在复杂度和估计精度方面都优于传统方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dictionary-Based Tensor Decomposition-Aided Time-Varying Channel Estimation for Millimeter Wave MU-MIMO Systems
This research focuses on the multiple-input multiple-output (MIMO) mmWave systems' uplink time-varying channel estimation challenge. We convert the time-varying channel es-timation in the hybrid beamforming structure into a param-eter estimation problem that takes angles of arrival/departure (AoA/AoDs), Doppler shift, and path gains into account. We also suggest a two-stage channel estimation method. We describe the receiving signals as a third-order tensor in the initial stage and provide an algorithm that combines Matching Pursuit (MP) and Alternating Least Squares (ALS) called Dictionary-based Tensor Decomposition to estimate AoA/AoDs. In the second stage, we recover the Doppler shifts and paath gains using the estimated AoA/AoDs. The entire time-varying channel is finally restored. The simulation results demonstrate that the suggested method performs better than the traditional approach in terms of complexity and estimation accuracy.
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