PARAFAC-based channel estimation and data recovery in nonlinear MIMO spread spectrum communication systems

DOI10.1016/j.sigpro.2010.07.010zbMath1203.94028OpenAlexW2090251286MaRDI QIDQ612602

Gérard Favier, Carlos Estêvão R. Fernandes, João Cesar M. Mota

Publication date: 29 December 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2010.07.010

zbMATH Keywords

channel estimationdirect sequence spread spectrumdata recoveryMIMO Volterranonlinear channelPARAFAC decompositionradio over fiber

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Cites Work

• A comparison of algorithms for fitting the PARAFAC model
• PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization
• Some further results on blind identification of MIMO FIR channels via second-order statistics
• Blind equalization of nonlinear channels using a tensor decomposition with code/space/time diversities
• Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics
• Blind identification of multiuser nonlinear channels using tensor decomposition and precoding
• Space-time spreading MIMO-CDMA downlink systems using constrained tensor modeling
• A Link between the Canonical Decomposition in Multilinear Algebra and Simultaneous Matrix Diagonalization

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