Thèse soutenue

Modélisation et traitement tensoriel du signal pour les systèmes de communication sans-fil

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Auteur / Autrice : André Lima Ferrer de Almeida
Direction : Gérard FavierJoão Cesar M. Mota
Type : Thèse de doctorat
Discipline(s) : Automatique, traitement du signal et des images
Date : Soutenance en 2007
Etablissement(s) : Nice
Ecole(s) doctorale(s) : École doctorale Sciences et technologies de l'information et de la communication (Sophia Antipolis, Alpes-Maritimes)

Résumé

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In several signal processing applications for wireless communications, the received signal is multidimensional in nature and may exhibit a multilinear algebraic structure. In this context, the PARAFAC tensor decomposition has been the subject of several works in the past six years. However, generalized tensor decompositions are necessary for covering a wider class of wireless communications systems with more complex transmission structures, more realistic channel models and more efficient receiver signal processing. This thesis investigates tensor modelling approaches for multiple-antenna systems, channel equalization, signal separation and parametric channel estimation? New tensor decompositions, namely, the block-constrained PARAFAC and CONFAC decompositions are developed and studied in terms of identifiability. Fist, the block-constrained PARAFAC decompositions applied for a unified tensor modelling of oversampled, DS-CDMA and OFDM systems applications to blind multiuser equalization. This decomposition is also used for modelling multiple-antenna (MIMO) transmission systems with block space-time spreading and blind detection, which generalizes previous tensor-based MIMO transmission models. The CONFAC decomposition is then exploited for designing new uniqueness properties of this decomposition? This thesis also studies new applications f third-order PARAFAC decomposition? A new space-time-frequency spreading system is proposed for multicarrier multiple-access systems, where this decomposition is used as a joint spreading and multiplexing tool at the transmitter using tridimensional spreading code with trilinear structure. Finally, we present a PARAC modelling approach for the parametric estimation of SIMO and MIMO multipath wireless channels with time-varying structure.