PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization
From MaRDI portal
Publication:970678
DOI10.1016/j.sigpro.2005.12.014zbMath1186.94412OpenAlexW2054032793MaRDI QIDQ970678
André L. F. de Almeida, Gérard Favier, João Cesar M. Mota
Publication date: 19 May 2010
Published in: Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.sigpro.2005.12.014
subspacewireless communicationsblind equalizationoversamplingmulticarrier modulationalternating least squaresparallel factor analysistensor modelingantenna arraysdirect-sequence spreadingfrequency-selective multipath
Related Items (11)
Further results for \(Z\)-eigenvalue localization theorem for higher-order tensors and their applications ⋮ A seminorm regularized alternating least squares algorithm for canonical tensor decomposition ⋮ $(L_r,L_r,1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials ⋮ PARAFAC-based channel estimation and data recovery in nonlinear MIMO spread spectrum communication systems ⋮ Tensor decompositions with banded matrix factors ⋮ A tensor-based approach for frequency-selective MIMO channel equalization ⋮ Blind identification of multiuser nonlinear channels using tensor decomposition and precoding ⋮ Subtracting a best rank-1 approximation may increase tensor rank ⋮ Blind equalization of nonlinear channels using a tensor decomposition with code/space/time diversities ⋮ Constrained Tucker-3 model for blind beamforming ⋮ Tensor ranks on tangent developable of Segre varieties
This page was built for publication: PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization
