Blind identification of multiuser nonlinear channels using tensor decomposition and precoding

Carlos Alexandre Rolim Fernandes; Gérard Favier; João Mota

doi:10.1016/j.sigpro.2009.05.012

Blind identification of multiuser nonlinear channels using tensor decomposition and precoding

Carlos Alexandre Rolim Fernandes ^{1, 2} Gérard Favier ¹ João Mota ²

1 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SIGNAL

Laboratoire I3S - SIS - Signal, Images et Systèmes

2 UFC - GTEL - Grupo de Pesquisa em Telecomunicações Sem Fio

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

keyword : Blind nonlinear channel identification Markov chain Multiuser channel PARAFAC decomposition Volterra model

Type de document :

Article dans une revue

Signal Processing, Elsevier, 2009, 89 (12), pp.2644-2656. 〈10.1016/j.sigpro.2009.05.012〉

Domaine :

Sciences de l'ingénieur [physics] / Traitement du signal et de l'image

Informatique [cs] / Traitement du signal et de l'image

Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00417569
Contributeur : Thomas Bouilloc <>
Soumis le : mercredi 16 septembre 2009 - 11:15:35
Dernière modification le : lundi 5 novembre 2018 - 15:52:01

Blind identification of multiuser nonlinear channels using tensor decomposition and precoding

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