Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Blind identification of MIMO-FIR systems: a generalized linear prediction approach
Signal Processing - Special issue on blind source separation and multichannel deconvolution
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
An efficient square-root algorithm for BLAST
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Globally convergent blind source separation based on a multiuser kurtosis maximization criterion
IEEE Transactions on Signal Processing
A blind signal separation method for multiuser communications
IEEE Transactions on Signal Processing
On subspace methods for blind identification of single-inputmultiple-output FIR systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing - Part I
The multimodulus blind equalization and its generalized algorithms
IEEE Journal on Selected Areas in Communications
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The problem of blind recovery of QAM and PSK signals for multiple-input multiple-output (MIMO) communication systems is investigated. We propose a simplified version of the well-known constant modulus algorithm (CMA), named simplified CMA (SCMA). The SCMA cost function consists in projection of the MIMO equalizer outputs on one dimension (either real or imaginary part). A study of stationary points of SCMA reveals the absence of any undesirable local stationary points, which ensures a perfect recovery of all signals and a global convergence of the algorithm. Taking advantage of the phase ambiguity in the solution of the new cost function for QAM constellations, we propose a modified cross-correlation term. It is shown that the proposed algorithm presents a lower computational complexity compared to the constant modulus algorithm (CMA) without loss in performances. Some numerical simulations are provided to illustrate the effectiveness of the proposed algorithm.