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Research Letters in Signal Processing
Volume 2008 (2008), Article ID 539139, 5 pages
Research Letter

On Blind MIMO System Identification Based on Second-Order Cyclic Statistics

1Laboratoire d'Analyse des Signaux & des Processus Industriels, Université Jean Monnet, Institut Universitaire de Technology de Roanne, Roanne 42332, France
2Laboratoire GSCM-LRIT, Faculté des Sciences, Université Mohammed V, B.P. 1014 Rabat-Agdal, Morocco

Received 10 September 2007; Accepted 26 January 2008

Academic Editor: Ling Guan

Copyright © 2008 K. Sabri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This letter introduces a new frequency domain approach for either MIMO System Identification or Source Separation of convolutive mixtures in cyclostationary context. We apply the joint diagonalization algorithm to a set of cyclic spectral density matrices of the measurements to identify the mixing system at each frequency up to permutation and phase ambiguity matrices. An efficient algorithm to overcome the frequency dependent permutations and to recover the phase, even for non-minimum-phase channels, based on cyclostationarity is also presented. The new approach exploits the fact that each input has a different and specific cyclic frequency. A comparison with an existing MIMO method is proposed.