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
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〉
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https://hal.archives-ouvertes.fr/hal-00417569
Contributeur : Thomas Bouilloc <>
Soumis le : mercredi 16 septembre 2009 - 11:15:35
Dernière modification le : mercredi 31 janvier 2018 - 10:24:05

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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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