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MIMO Semi-blind Channel Estimation by using Tikhonov Regularized MMSE and MAP Algorithms with Householder Transformation based QR Decomposition
Radioelectronics and Communications Systems Pub Date : 2021-06-19 , DOI: 10.3103/s0735272721040014
Payal Saxena , Sagar B. Patel , Jaymin K. Bhalani

Abstract

In this paper, we present novel semi-blind channel estimation schemes for Rayleigh fading Multi-Input Multi-Output (MIMO) channel. Here channel matrix H is decomposed as an upper triangular matrix R, which can be estimated blindly using the Householder transformation based QR decomposition of received output covariance matrix and Q matrix, which can be estimated using the Tikhonov regularization-based MAP (maximum a posteriori) and MMSE (minimum mean square error) techniques with the help of singular value decomposed orthogonal pilot symbols. Simulation results in terms of BER performance obtained for BPSK and 4-PSK data modulation schemes using Alamouti coded 2×6 (2 transmitter and 6 receiver antennas) and 2×8 (2 transmitter and 8 receiver antennas) cases by choosing different values of regularization parameter λ. Appropriate choice of regularization parameter can be calculated using discrepancy principles that gives better performance in terms of BER. The paper proposes the novel semi-blind channel estimation approach using the Householder QR decomposition based blind estimation of R and Tikhonov regularized based MMSE and MAP algorithms using pilot symbols for estimation of Q will yield good results in channel estimation methods.



中文翻译:

基于二维码分解的 Tikhonov 正则化 MMSE 和 MAP 算法的 MIMO 半盲信道估计

摘要

在本文中,我们提出了用于瑞利衰落多输入多输出 (MIMO) 信道的新型半盲信道估计方案。这里信道矩阵H被分解为上三角矩阵R,可以使用基于 Householder 变换的接收输出协方差矩阵的 QR 分解和Q进行盲估计矩阵,可以使用基于 Tikhonov 正则化的 MAP(最大后验)和 MMSE(最小均方误差)技术在奇异值分解正交导频符号的帮助下进行估计。通过选择不同的正则化值,使用 Alamouti 编码的 2×6(2 个发射机和 6 个接收机天线)和 2×8(2 个发射机和 8 个接收机天线)情况下 BPSK 和 4-PSK 数据调制方案获得的 BER 性能仿真结果参数λ。Appropriate choice of regularization parameter can be calculated using discrepancy principles that gives better performance in terms of BER. 本文提出了一种新的半盲信道估计方法,该方法使用基于 Householder QR 分解的R盲估计和 Tikhonov 基于正则化的 MMSE 和 MAP 算法使用导频符号来估计Q将在信道估计方法中产生良好的结果。

更新日期:2021-06-19
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