Correction of the Algorithm of Joint Estimation of SIMO Channels and Transmitting Symbols by Oblique Projections

作者: 颜海梅 , 孙闽红 :杭州电子科技大学通信工程学院,杭州;

关键词: 单输入多输出信道信道估计符号估计斜投影SIMO Channel Estimation of Channels Estimation of Symbols Oblique Projections

摘要: 本文分析了基于斜投影算子的单输入多输出(SIMO)有限冲激响应(FIR)滤波器信道中信道与发射符号联合盲估计算法原理,改正了算法中存在的两处错误,即斜投影算子的计算公式和Q矩阵的构造公式,并采用Matlab软件仿真实现了该算法。仿真实验表明,改正的算法能同时给出信道矩阵与发射符号的正确估计,算法估计量的MSESNR的增加而单调减小,验证了改正后算法的正确性和有效性。

Abstract: The principle of the algorithm of joint estimation of single-input-multi-output (SIMO) channels and transmitting symbols by oblique projections is analyzed. Corrections of computation of the oblique projectors and construction of a Q matrix in the algorithm are performed. Simulation based on Matlab software is carried out to realize the algorithm. The experimental results show that the corrected algorithm can give right estimations of the channel matrix and the symbols, and the mean square error (MSE) of the two estimators decrease with the increase of the signal to noise ratio (SNR). Hence, the correctness and the validity of the corrected algorithm are verified.

文章引用: 颜海梅 , 孙闽红 (2012) SIMO信道与发射符号联合估计斜投算法修正。 无线通信, 2, 51-55. doi: 10.12677/hjwc.2012.23010


[1] C. Y. Peng, X. D. Zhang and Q. T. Cai. A block-adaptive subspace method using oblique projection for blind separation of convolutive mixtures. Advances in Neural Networks, Berlin- Heidelberg: Springer-Verlag, 2005: 526-531.

[2] 孙季丰, 张志勇. 用于MIMO-OFDM系统盲信道估计的斜投影子空间法[J]. 华南理工大学学报, 2010, 38(5): 2-3.

[3] 黄如浩, 何培宇, 于文君, 高勇. MIMO系统中基于斜投影的盲空时多用户检测算法[J]. 系统工程与电子技术, 2011, 33(3): 670-672.

[4] 尚鹏. 无线通信系统中的多用户分集及预编码研究[D]. 武汉: 华中科技大学, 2009.

[5] D. Moulines, P. Duhamel, J. F. Cardoso and S. Mayrargue. Subspace methods for the blind identification of multichannel FIR filters. IEEE Transactions on Signal Processing, 1995, 43(2): 516-525.

[6] S. Abdallah. Widely linear versus conventional subspace-based estimation of SIMO flat-fading channels: Mean squared error analysis. IEEE Transactions on Signal Processing, 2012, 60(3): 1307-1318.

[7] D. Schmid, G. Enzner. Cross-relation-based blind SIMO identifiability in the presence of near-common zeros and noise. IEEE Transactions on Signal Processing, 2012, 60(1): 60-72.

[8] Q. Zhao, L. Tong. Adaptive blind channel estimation by least squares smoothing. IEEE Transactions on Signal Processing, 1999, 47(11): 3000-3012.

[9] A. van der Veen, S. Talwar and A. Paulraj, A subspace approach to blind space-time signal processing for wireless communication systems. IEEE Transactions on Signal Processing, 1997, 45: 173-190.

[10] X. Yu, L. Tong. Joint channel and symbol estimation by oblique projections. IEEE Transactions on Signal Processing, 2001, 49(12): 3074-3080.

[11] P. Vandaele, M. Moonen. Two deterministic blind channel estimation algorithms based on oblique projections. Signal Processing, 2000, 80(3): 481-495.

[12] 张贤达. 矩阵分析与应用[M]. 北京: 清华大学出版社, 2004.