Blind identification of convolutive MIMO systems with 3 sources and 2 sensors

Authors:
Binning Chen;Athina P. Petropulu;Lieven De Lathauwer
Affiliations:
Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA;Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA;Équipe Traitement des Images et du Signal, École Nationale Supérieure d'Électronique et de ses Applications, Université de Cergy-Pontoise, Cergy-Pontoise, France
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2002

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Abstract

We address the problem of blind identification of a convolutive Multiple-Input Multiple-Output (MIMO) system with more inputs than outputs, and in particular, the 3-input 2-output case. We assume that the inputs are temporally white, non-Gaussian distributed, and spatially independent. Solutions for the scalar MIMO case, within scaling and permutation ambiguities, have been proposed in the past, based on the canonical decomposition of tensors constructed from higher-order cross-cumulants of the system output. In this paper, we look at the problem in the frequency domain, where, for each frequency we construct a number of tensors based on cross-polyspectra of the output. These tensors lead to the system frequency response within frequency dependent scaling and permutation ambiguities. We propose ways to resolve these ambiguities, and show that it is possible to obtain the system response within a scalar and a linear phase.