Blind identification of multiuser nonlinear channels using tensor decomposition and precoding

Abstract : This paper presents two blind identification methods for nonlinear memoryless channels in multiuser communication systems. These methods are based on the parallel factor (PARAFAC) decomposition of a tensor composed of channel output covariances. Such a decomposition is possible owing to a new precoding scheme developed for phase-shift keying (PSK) signals modeled as Markov chains. Some conditions on the transition probability matrices (TPM) of the Markov chains are established to introduce temporal correlation and satisfy statistical correlation constraints inducing the PARAFAC decomposition of the considered tensor. The proposed blind channel estimation algorithms are evaluated by means of computer simulations
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Signal Processing, Elsevier, 2009, 89 (12), pp.2644-2656. <10.1016/j.sigpro.2009.05.012>
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Contributeur : Thomas Bouilloc <>
Soumis le : mercredi 16 septembre 2009 - 11:15:35
Dernière modification le : mardi 4 mai 2010 - 17:14:35

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Carlos Alexandre Rolim Fernandes, Gérard Favier, João Mota. Blind identification of multiuser nonlinear channels using tensor decomposition and precoding. Signal Processing, Elsevier, 2009, 89 (12), pp.2644-2656. <10.1016/j.sigpro.2009.05.012>. <hal-00417569>

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