Robust joint synchronization and channel estimation approach for frequency-selective environments
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/16692 |
Resumo: | Supporting spontaneous low-latency machine type communications requires fast synchronization and channel estimation at the receiver. The problems of synchronizing the received frame and estimating the channel coefficients are often addressed separately with the later one relying on accurate timing acquisition. While these conventional approaches can be adequate in flat fading environments, time dispersive channels can have a negative impact on both tasks and severely degrade the performance of the receiver. To circumvent this large degradation, in this paper we consider the use of a sparse based reconstruction approach for joint timing synchronization and channel estimation by formulating the problem in a form that is closely related to Compressive Sensing(CS) framework. Using modified versions of well-known sparse reconstruction techniques, which can take into account the additional signal structure in addition to sparsity, it is shown through numerical simulations that, even with short training sequences, excellent timing synchronization and channel estimation performance can be achieved, both in single user and multiuser scenarios. |
id |
RCAP_9bb549fc9714a867295a2b9bdb47109c |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/16692 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Robust joint synchronization and channel estimation approach for frequency-selective environmentsChannel estimationCompressive sensingSparse signal recoveryTime synchronizationSupporting spontaneous low-latency machine type communications requires fast synchronization and channel estimation at the receiver. The problems of synchronizing the received frame and estimating the channel coefficients are often addressed separately with the later one relying on accurate timing acquisition. While these conventional approaches can be adequate in flat fading environments, time dispersive channels can have a negative impact on both tasks and severely degrade the performance of the receiver. To circumvent this large degradation, in this paper we consider the use of a sparse based reconstruction approach for joint timing synchronization and channel estimation by formulating the problem in a form that is closely related to Compressive Sensing(CS) framework. Using modified versions of well-known sparse reconstruction techniques, which can take into account the additional signal structure in addition to sparsity, it is shown through numerical simulations that, even with short training sequences, excellent timing synchronization and channel estimation performance can be achieved, both in single user and multiuser scenarios.IEEE2018-10-18T16:40:51Z2018-01-01T00:00:00Z20182019-03-08T18:25:18Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/16692eng2169-353610.1109/ACCESS.2018.2871060Lopes, B.Catarino, S.Souto, N.Dinis, R.Cercas, F.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:48:33Zoai:repositorio.iscte-iul.pt:10071/16692Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:23:42.617867Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
title |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
spellingShingle |
Robust joint synchronization and channel estimation approach for frequency-selective environments Lopes, B. Channel estimation Compressive sensing Sparse signal recovery Time synchronization |
title_short |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
title_full |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
title_fullStr |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
title_full_unstemmed |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
title_sort |
Robust joint synchronization and channel estimation approach for frequency-selective environments |
author |
Lopes, B. |
author_facet |
Lopes, B. Catarino, S. Souto, N. Dinis, R. Cercas, F. |
author_role |
author |
author2 |
Catarino, S. Souto, N. Dinis, R. Cercas, F. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Lopes, B. Catarino, S. Souto, N. Dinis, R. Cercas, F. |
dc.subject.por.fl_str_mv |
Channel estimation Compressive sensing Sparse signal recovery Time synchronization |
topic |
Channel estimation Compressive sensing Sparse signal recovery Time synchronization |
description |
Supporting spontaneous low-latency machine type communications requires fast synchronization and channel estimation at the receiver. The problems of synchronizing the received frame and estimating the channel coefficients are often addressed separately with the later one relying on accurate timing acquisition. While these conventional approaches can be adequate in flat fading environments, time dispersive channels can have a negative impact on both tasks and severely degrade the performance of the receiver. To circumvent this large degradation, in this paper we consider the use of a sparse based reconstruction approach for joint timing synchronization and channel estimation by formulating the problem in a form that is closely related to Compressive Sensing(CS) framework. Using modified versions of well-known sparse reconstruction techniques, which can take into account the additional signal structure in addition to sparsity, it is shown through numerical simulations that, even with short training sequences, excellent timing synchronization and channel estimation performance can be achieved, both in single user and multiuser scenarios. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-10-18T16:40:51Z 2018-01-01T00:00:00Z 2018 2019-03-08T18:25:18Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/16692 |
url |
http://hdl.handle.net/10071/16692 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2169-3536 10.1109/ACCESS.2018.2871060 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134799207596032 |