Modelagem tensorial e processamento de sinais por sistemas de comunicaÃÃes de redes / Tensor modeling and signal processing for wireless communication systems

AUTOR(ES)
DATA DE PUBLICAÇÃO

2007

RESUMO

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 communication systems with more complex transmission structures, more realistic channel models and more efficient receiver signal processing. This thesis investigates tensor modeling 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. First, the block-constrained PARAFAC decomposition is applied for a uniÂed tensor modeling of oversampled, DS-CDMA and OFDM systems with application to blind multiuser equalization. This decomposition is also used for modeling 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 MIMO-CDMA transmission schemes combining spatial diversity and multiplexing. Blind symbol/code/channel recovery is discussed from the uniqueness properties of this decomposition. This thesis also studies new applications of 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 PARAFAC modeling approach for the parametric estimation of SIMO and MIMO multipath wireless channels with time-varying structure.

ASSUNTO(S)

wireless communication systems cdma transmission parafac detecÃÃo nÃo-supervisionada blind detection multi-antenna teleinformatica parafac channel estimation confac signal separation confac transmissÃo multi-antena mimo sistemas de comunicaÃÃo sem-fio estimaÃÃo de canal multiuser equalization equalizaÃÃo multi-usuÃria ofdm mimo cdma tensor modeling modelagem tensorial separaÃÃo de sinais

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