Blind joint MIMO channel and data estimation based on regularized ML
International audience The problem of blind joint FIR-MIMO channel and data estimation is addressed in this paper. Based on a regularized DML (Deterministic Maximum Likelihood) formulation of the problem, a bilinear approach is used in order to estimate jointly the channel impulse responses and the...
Published in: | Digital Signal Processing |
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Main Authors: | , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2021
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Online Access: | https://imt-atlantique.hal.science/hal-03322591 https://imt-atlantique.hal.science/hal-03322591/document https://imt-atlantique.hal.science/hal-03322591/file/Elsevier_Regularized_Blind_joint_MIMO_channel_and_data_estimation_based_on_DML.pdf https://doi.org/10.1016/j.dsp.2021.103201 |
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Archives ouvertes Hal IMT Atlantique |
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ftimtatlantique |
language |
English |
topic |
Blind MIMO identification deterministic ML regularized estimation joint channel and data estimation sparsity simplicity [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
spellingShingle |
Blind MIMO identification deterministic ML regularized estimation joint channel and data estimation sparsity simplicity [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Lassami, Nacerredine Aissa El Bey, Abdeldjalil Abed-Meraim, Karim Blind joint MIMO channel and data estimation based on regularized ML |
topic_facet |
Blind MIMO identification deterministic ML regularized estimation joint channel and data estimation sparsity simplicity [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
description |
International audience The problem of blind joint FIR-MIMO channel and data estimation is addressed in this paper. Based on a regularized DML (Deterministic Maximum Likelihood) formulation of the problem, a bilinear approach is used in order to estimate jointly the channel impulse responses and the input data. This regularization is introduced as a penalty function added to the classical DML criterion representing the a priori information about the problem in order to enhance the accuracy of the estimation. Two types of priors information are considered for the transmitted data: the finite alphabet simplicity or the sparsity. The sparsity prior was also considered for channel impulse responses. The key advantage of the proposed criteria is their convexity when optimized alternatively over the channel and the input data. The proposed approach allows to improve further the estimation accuracy of such a blind estimation problem but suffers from a relatively high computational cost. Hence, a reduced complexity implementation of the latter has been proposed at the end of the paper, in an adaptive scheme for high dimensional or streaming data situations. |
author2 |
Département Mathematical and Electrical Engineering (IMT Atlantique - MEE) IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT) Equipe Communication System Design (Lab-STICC_COSYDE) Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT) Ecole Militaire Polytechnique Alger (EMP) Ministère de l'Enseignement Supérieur et de la Recherche Scientifique Algérie (MESRS)-Ministère de la Défense Nationale Algérie Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME) Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL) Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA) Ecole Polytechnique de l'Université d'Orléans Université d'Orléans (UO) |
format |
Article in Journal/Newspaper |
author |
Lassami, Nacerredine Aissa El Bey, Abdeldjalil Abed-Meraim, Karim |
author_facet |
Lassami, Nacerredine Aissa El Bey, Abdeldjalil Abed-Meraim, Karim |
author_sort |
Lassami, Nacerredine |
title |
Blind joint MIMO channel and data estimation based on regularized ML |
title_short |
Blind joint MIMO channel and data estimation based on regularized ML |
title_full |
Blind joint MIMO channel and data estimation based on regularized ML |
title_fullStr |
Blind joint MIMO channel and data estimation based on regularized ML |
title_full_unstemmed |
Blind joint MIMO channel and data estimation based on regularized ML |
title_sort |
blind joint mimo channel and data estimation based on regularized ml |
publisher |
HAL CCSD |
publishDate |
2021 |
url |
https://imt-atlantique.hal.science/hal-03322591 https://imt-atlantique.hal.science/hal-03322591/document https://imt-atlantique.hal.science/hal-03322591/file/Elsevier_Regularized_Blind_joint_MIMO_channel_and_data_estimation_based_on_DML.pdf https://doi.org/10.1016/j.dsp.2021.103201 |
genre |
DML |
genre_facet |
DML |
op_source |
ISSN: 1051-2004 EISSN: 1095-4333 Digital Signal Processing https://imt-atlantique.hal.science/hal-03322591 Digital Signal Processing, 2021, 117, pp.103201. ⟨10.1016/j.dsp.2021.103201⟩ https://www.sciencedirect.com/science/article/abs/pii/S1051200421002402#! |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dsp.2021.103201 hal-03322591 https://imt-atlantique.hal.science/hal-03322591 https://imt-atlantique.hal.science/hal-03322591/document https://imt-atlantique.hal.science/hal-03322591/file/Elsevier_Regularized_Blind_joint_MIMO_channel_and_data_estimation_based_on_DML.pdf doi:10.1016/j.dsp.2021.103201 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1016/j.dsp.2021.103201 |
container_title |
Digital Signal Processing |
container_volume |
117 |
container_start_page |
103201 |
_version_ |
1790599589225562112 |
spelling |
ftimtatlantique:oai:HAL:hal-03322591v1 2024-02-11T10:03:22+01:00 Blind joint MIMO channel and data estimation based on regularized ML Lassami, Nacerredine Aissa El Bey, Abdeldjalil Abed-Meraim, Karim Département Mathematical and Electrical Engineering (IMT Atlantique - MEE) IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT) Equipe Communication System Design (Lab-STICC_COSYDE) Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT) Ecole Militaire Polytechnique Alger (EMP) Ministère de l'Enseignement Supérieur et de la Recherche Scientifique Algérie (MESRS)-Ministère de la Défense Nationale Algérie Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique (PRISME) Université d'Orléans (UO)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL) Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA) Ecole Polytechnique de l'Université d'Orléans Université d'Orléans (UO) 2021-10 https://imt-atlantique.hal.science/hal-03322591 https://imt-atlantique.hal.science/hal-03322591/document https://imt-atlantique.hal.science/hal-03322591/file/Elsevier_Regularized_Blind_joint_MIMO_channel_and_data_estimation_based_on_DML.pdf https://doi.org/10.1016/j.dsp.2021.103201 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dsp.2021.103201 hal-03322591 https://imt-atlantique.hal.science/hal-03322591 https://imt-atlantique.hal.science/hal-03322591/document https://imt-atlantique.hal.science/hal-03322591/file/Elsevier_Regularized_Blind_joint_MIMO_channel_and_data_estimation_based_on_DML.pdf doi:10.1016/j.dsp.2021.103201 info:eu-repo/semantics/OpenAccess ISSN: 1051-2004 EISSN: 1095-4333 Digital Signal Processing https://imt-atlantique.hal.science/hal-03322591 Digital Signal Processing, 2021, 117, pp.103201. ⟨10.1016/j.dsp.2021.103201⟩ https://www.sciencedirect.com/science/article/abs/pii/S1051200421002402#! Blind MIMO identification deterministic ML regularized estimation joint channel and data estimation sparsity simplicity [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing info:eu-repo/semantics/article Journal articles 2021 ftimtatlantique https://doi.org/10.1016/j.dsp.2021.103201 2024-01-17T17:27:18Z International audience The problem of blind joint FIR-MIMO channel and data estimation is addressed in this paper. Based on a regularized DML (Deterministic Maximum Likelihood) formulation of the problem, a bilinear approach is used in order to estimate jointly the channel impulse responses and the input data. This regularization is introduced as a penalty function added to the classical DML criterion representing the a priori information about the problem in order to enhance the accuracy of the estimation. Two types of priors information are considered for the transmitted data: the finite alphabet simplicity or the sparsity. The sparsity prior was also considered for channel impulse responses. The key advantage of the proposed criteria is their convexity when optimized alternatively over the channel and the input data. The proposed approach allows to improve further the estimation accuracy of such a blind estimation problem but suffers from a relatively high computational cost. Hence, a reduced complexity implementation of the latter has been proposed at the end of the paper, in an adaptive scheme for high dimensional or streaming data situations. Article in Journal/Newspaper DML Archives ouvertes Hal IMT Atlantique Digital Signal Processing 117 103201 |