Adaptive Constant Modulus Algorithm based oncomplex Givens rotations

This paper deals with adaptive Constant Modulus Algorithm (CMA) for the blind separation of communication signals. Ikhlef et al. proposed in 2010 an efficient block implementation of the CMA using Givens rotations. We introduce herein a fast adaptive implementation of this method which exploits recent developments on whitening techniques together with appropriate updating of the used statistics and efficient selection of the Givens rotation parameters. The proposed algorithm shows significantly improved performance with respect to existing techniques as illustrated by the simulation results.

[1]  Phillip A. Regalia,et al.  On the equivalence between the Godard and Shalvi-Weinstein schemes of blind equalization , 1999, Signal Process..

[2]  Constantinos B. Papadias,et al.  Globally convergent blind source separation based on a multiuser kurtosis maximization criterion , 2000, IEEE Trans. Signal Process..

[3]  Aïssa Ikhlef,et al.  On the Constant Modulus Criterion: A New Algorithm , 2010, 2010 IEEE International Conference on Communications.

[4]  Lin He,et al.  A hybrid adaptive blind equalization algorithm for QAM signals in wireless communications , 2004, IEEE Transactions on Signal Processing.

[5]  Amir Leshem,et al.  Constant Modulus Beamforming , 2005 .

[6]  Thierry Chonavel,et al.  Min-norm based alphabet-matching algorithm for adaptive blind equalisation of high-order QAM signals , 2013, Trans. Emerg. Telecommun. Technol..

[7]  D. Godard,et al.  Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems , 1980, IEEE Trans. Commun..

[8]  Asoke K. Nandi,et al.  An Adaptive Constant Modulus Blind Equalization Algorithm and Its Stochastic Stability Analysis , 2010, IEEE Signal Processing Letters.

[9]  Pierre Comon,et al.  Handbook of Blind Source Separation: Independent Component Analysis and Applications , 2010 .

[10]  Karim Abed-Meraim,et al.  Sliding window adaptive Constant Modulus Algorithm based on complex Hyperbolic Givens rotations , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

[11]  V. Yang,et al.  A vector constant modulus algorithm for shaped constellation equalization , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[12]  J. Treichler,et al.  A new approach to multipath correction of constant modulus signals , 1983 .

[13]  Karim Abed-Meraim,et al.  Low complexity adaptive algorithms for Principal and Minor Component Analysis , 2013, Digit. Signal Process..

[14]  H. Vincent Poor,et al.  IEEE Workshop on Statistical Signal Processing, SSP 2014, Gold Coast, Australia, June 29 - July 2, 2014 , 2014, Symposium on Software Performance.

[15]  Constantinos B. Papadias,et al.  Blind source separation with randomized Gram-Schmidt orthogonalization for short burst systems , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.