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Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach

The problem of channel estimation for multicarrier communications is addressed. We focus on systems employing the Discrete Cosine Transform Type-I (DCT1) even at both the transmitter and the receiver, presenting an algorithm which achieves an accurate estimation of symmetric channel filters using on...

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Detalles Bibliográficos
Autores principales: Domínguez-Jiménez, María Elena, Luengo, David, Sansigre-Vidal, Gabriela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4629058/
https://www.ncbi.nlm.nih.gov/pubmed/26568981
http://dx.doi.org/10.1155/2015/151370
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author Domínguez-Jiménez, María Elena
Luengo, David
Sansigre-Vidal, Gabriela
author_facet Domínguez-Jiménez, María Elena
Luengo, David
Sansigre-Vidal, Gabriela
author_sort Domínguez-Jiménez, María Elena
collection PubMed
description The problem of channel estimation for multicarrier communications is addressed. We focus on systems employing the Discrete Cosine Transform Type-I (DCT1) even at both the transmitter and the receiver, presenting an algorithm which achieves an accurate estimation of symmetric channel filters using only a small number of training symbols. The solution is obtained by using either matrix inversion or compressed sensing algorithms. We provide the theoretical results which guarantee the validity of the proposed technique for the DCT1. Numerical simulations illustrate the good behaviour of the proposed algorithm.
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spelling pubmed-46290582015-11-15 Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach Domínguez-Jiménez, María Elena Luengo, David Sansigre-Vidal, Gabriela ScientificWorldJournal Research Article The problem of channel estimation for multicarrier communications is addressed. We focus on systems employing the Discrete Cosine Transform Type-I (DCT1) even at both the transmitter and the receiver, presenting an algorithm which achieves an accurate estimation of symmetric channel filters using only a small number of training symbols. The solution is obtained by using either matrix inversion or compressed sensing algorithms. We provide the theoretical results which guarantee the validity of the proposed technique for the DCT1. Numerical simulations illustrate the good behaviour of the proposed algorithm. Hindawi Publishing Corporation 2015 2015-10-18 /pmc/articles/PMC4629058/ /pubmed/26568981 http://dx.doi.org/10.1155/2015/151370 Text en Copyright © 2015 María Elena Domínguez-Jiménez et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Domínguez-Jiménez, María Elena
Luengo, David
Sansigre-Vidal, Gabriela
Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title_full Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title_fullStr Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title_full_unstemmed Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title_short Estimation of Symmetric Channels for Discrete Cosine Transform Type-I Multicarrier Systems: A Compressed Sensing Approach
title_sort estimation of symmetric channels for discrete cosine transform type-i multicarrier systems: a compressed sensing approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4629058/
https://www.ncbi.nlm.nih.gov/pubmed/26568981
http://dx.doi.org/10.1155/2015/151370
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