Blind identification of multiuser nonlinear channels using tensor decomposition and precoding
type: Item
instance of: scholarly article
title: Blind identification of multiuser nonlinear channels using tensor decomposition and precoding
zbMATH Open document ID: 1197.94049
author: Gérard Favier
author: J. C. M. Mota
author: Carlos Estêvão R. Fernandes
published in: Signal Processing
publication date: 2010-09-27T00:00:00Z
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 5791813
zbMATH Keywords: blind nonlinear channel identification
zbMATH Keywords: Markov chain
zbMATH Keywords: multiuser channel
zbMATH Keywords: PARAFAC decomposition
zbMATH Keywords: Volterra model
MaRDI profile type: Publication
full work available at URL: j.sigpro.2009.05.012
OpenAlex ID: W2090147074
cites work: Some further results on blind identification of MIMO FIR channels via second-order statistics
cites work: Channel identification for high speed digital communications
cites work: Jacobi Angles for Simultaneous Diagonalization
cites work: PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization
cites work: Blind spatial signature estimation via time-varying user power loading and parallel factor analysis
cites work: Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization
cites work: Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics
DOI: 10.1016/J.SIGPRO.2009.05.012
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description: scientific article; zbMATH DE number 5791813