PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization

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

zbMATH Keywords

subspace wireless communications blind equalization oversampling multicarrier modulation alternating least squares parallel factor analysis tensor modeling antenna arrays direct-sequence spreading frequency-selective multipath

Mathematics Subject Classification ID

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

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

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