Please use this identifier to cite or link to this item:
Title in Portuguese: Tensor-based blind channel identification
Author: Fernandes, Carlos Estevão Rolim
Favier, Gérard
Mota, João César Moura
Issue Date: 2007
Publisher: IEEE International Conference on Communications
Citation: FERNANDES, C. E. R. ; FAVIER, G. ; MOTA, J. C. M. Tensor-based blind channel identification. In: IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2007, Glasgow. Anais... Glasgow: IEEE International Conference on Communications, 2007, p. 2728-2732
Abstract: We propose a blind FIR channel identification method based on the Parallel Factor (Parafac) analysis of a 3rd-order tensor composed of the 4-th order output cumulants. Our algorithm is based on a single-step least squares (LS) minimization procedure instead of using classical three-step Alternating Least Squares (ALS) methods. Using a Parafacbased decomposition, we avoid any kind of pre-processing such as the prewhitening operation, which is mandatory in most methods using higher-order statistics. Our method retrieves the channel vector without any permutation or scaling ambiguities. In addition, we establish a link between the cumulant tensor decomposition and the joint-diagonalization approach. Computer simulations illustrate the performance gains that our method provides with respect to other classical solutions. Initialization and convergence issues are also addressed.
metadata.dc.type: Artigo de Evento
Appears in Collections:DETE - Trabalhos apresentados em eventos

Files in This Item:
File Description SizeFormat 
2007_eve_cerfernandes tensor.pdf215,25 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.