Title :
The blind deconvolution of the multi-channel based on the higher order statistics
Author :
Yang, Janghoon ; Nikias, Chrysostomos L.
Author_Institution :
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
fDate :
Oct. 29 2000-Nov. 1 2000
Abstract :
We have proposed a source separation algorithm of the convolutive mixtures based on the maximization of the auto-kurtosis and minimization of the cross-kurtosis with the constraint on the output power. As an iterative method, we suggest a nontrivial extension of the generalized eigenvector algorithm for blind equalization (GEnEVA) to the blind deconvolution of the multi-input multi-output (MIMO) systems. The application of the proposed algorithm on the 64-QAM signal separations shows that it can achieve excellent performance and it is robust to the broad range of the noise levels.
Keywords :
MIMO systems; blind equalisers; deconvolution; eigenvalues and eigenfunctions; higher order statistics; iterative methods; minimisation; quadrature amplitude modulation; telecommunication channels; 64-QAM signal separation; GEnEVA algorithm; MIMO systems; auto-kurtosis maximization; blind equalization; blind multichannel deconvolution; convolutive mixtures; cross-kurtosis minimization; generalized eigenvector algorithm; higher order statistics; iterative method; multi-input multi-output systems; noise levels; output power constraint; source separation algorithm; Blind equalizers; Deconvolution; Iterative algorithms; Iterative methods; MIMO; Minimization methods; Noise level; Noise robustness; Power generation; Source separation;
Conference_Titel :
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-6514-3
DOI :
10.1109/ACSSC.2000.910752
