Blind equalization of nonlinear channels using a tensor decomposition with code/space/time diversities

Abstract : In this paper, we consider the blind equalization problem for nonlinear channels represented by means of a Volterra model. We first suggest a precoding scheme inducing a three-dimensional (3-D) structure for the received data due to code, space, and time diversities. The tensor of received data admits a PARAFAC (parallel factors) decomposition with finite alphabet and Vandermonde structure constraints. We derive a uniqueness result taking such constraints into account. When one of the matrix factors, the code matrix, is known or belongs to a known finite set of matrices, we give new uniqueness results and three equalization algorithms are proposed. The performances of these algorithms are illustrated by means of simulation results.
Type de document :
Article dans une revue
Signal Processing, Elsevier, 2009, 89 (2), pp.133-143
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https://hal.archives-ouvertes.fr/hal-00417609
Contributeur : Thomas Bouilloc <>
Soumis le : mercredi 16 septembre 2009 - 13:32:48
Dernière modification le : mardi 24 mars 2015 - 10:54:54

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  • HAL Id : hal-00417609, version 1

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Alain Y. Kibangou, Gérard Favier. Blind equalization of nonlinear channels using a tensor decomposition with code/space/time diversities. Signal Processing, Elsevier, 2009, 89 (2), pp.133-143. <hal-00417609>

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