毫米波大规模MIMO系统中均匀矩形阵列的信道跟踪

Haiyan Liu, Tiankui Zhang, Zhirui Hu, J. Loo, Youxiang Wang
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引用次数: 5

摘要

毫米波是满足5G高数据速率需求的一个有前途的选择。然而,严重的路径损耗需要通过提取信道状态信息(CSI)来补偿,以获得波束形成增益。在时变信道环境下,通过信道跟踪,可以获得信道CSI。针对毫米波大规模MIMO系统中URAs时变信道,提出了一种两级信道跟踪算法。两阶段信道跟踪算法的重点是获得准确的CSI。首先,基于扩展卡尔曼滤波,方便地估计方位角和仰角,得到物理信道矩阵;然后,提出矩阵分解$(\ mathm {M}\Gamma)$算法对信道进行校正,减小了EKF引起的估计误差。仿真结果证明了该算法的有效性。与传统的信道跟踪算法相比,所提出的信道跟踪算法可以降低符号错误率,增加跟踪时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Channel Tracking for Uniform Rectangular Arrays in mmWave Massive MIMO Systems
MmWave is a promising option for meeting the high data rate demand of 5G. However, the severe path loss needs to be compensated by extracting the channel state information (CSI) for beamforming gain. The CSI can be obtained by channel tracking in time-varying channel environment. In this paper, we present a two-stage channel tracking algorithm for time-varying channel of URAs in mmWave massive MIMO systems. The two-stage channel tracking algorithm focuses on obtaining accurate CSI. Firstly, the azimuth and elevation angles are easily estimated based on extending Kalman Filter to obtain the physical channel matrix. Then, the matrix factorization $(\mathrm{M}\Gamma)$ algorithm is proposed to calibrate the channel, which decrease the estimation error caused by EKF. Simulation results demonstrate that the performance of the proposed algorithm. The proposed channel tracking algorithm can reduce the symbol error rates and increase the tracking time compared with traditional channel tracking algorithms.
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