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Article: Superimposed training-based channel estimation and data detection for OFDM amplify-and-forward cooperative systems under high mobility

TitleSuperimposed training-based channel estimation and data detection for OFDM amplify-and-forward cooperative systems under high mobility
Authors
KeywordsAmplify-and-forward
Orthogonal frequency division multiplexing (OFDM)
Time-varying channels
Issue Date2012
PublisherIEEE
Citation
IEEE Transactions on Signal Processing, 2012, v. 60 n. 1, p. 274-284 How to Cite?
AbstractIn this paper, joint channel estimation and data detection in orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) cooperative systems under high mobility is investigated. Unlike previous works on cooperative systems in which a number of subcarriers are solely occupied by pilots, partial data-dependent superimposed training (PDDST) is considered here, thus preserving the spectral efficiency. First, a closed-form channel estimator is developed based on the least squares (LS) method with Tikhonov regularization and a corresponding data detection algorithm is proposed using the linear minimum mean square error (LMMSE) criterion. In the derived channel estimator, the unknown data is treated as part of the noise and the resulting data detection may not meet the required performance. To address this issue, an iterative method based on the variational inference approach is derived to improve performance. Simulation results show that the data detection performance of the proposed iterative algorithm initialized by the LMMSE data detector is close to the ideal case with perfect channel state information. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/155718
ISSN
2015 Impact Factor: 2.624
2015 SCImago Journal Rankings: 2.004
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grant CouncilHKU 7154/08E
GRFHKU 7191/11E
U.S. National Science FoundationCNS-09-05398
Funding Information:

The work was supported in part by the General Research Fund (GRF) from Hong Kong Research Grant Council (Project No.: HKU 7154/08E), by the GRF (Project No. HKU 7191/11E), and by the U.S. National Science Foundation by Grant CNS-09-05398.

References

 

DC FieldValueLanguage
dc.contributor.authorHe, Len_HK
dc.contributor.authorWu, YCen_HK
dc.contributor.authorMa, Sen_HK
dc.contributor.authorNg, TSen_HK
dc.contributor.authorPoor, HVen_HK
dc.date.accessioned2012-08-08T08:34:59Z-
dc.date.available2012-08-08T08:34:59Z-
dc.date.issued2012en_HK
dc.identifier.citationIEEE Transactions on Signal Processing, 2012, v. 60 n. 1, p. 274-284en_HK
dc.identifier.issn1053-587Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/155718-
dc.description.abstractIn this paper, joint channel estimation and data detection in orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) cooperative systems under high mobility is investigated. Unlike previous works on cooperative systems in which a number of subcarriers are solely occupied by pilots, partial data-dependent superimposed training (PDDST) is considered here, thus preserving the spectral efficiency. First, a closed-form channel estimator is developed based on the least squares (LS) method with Tikhonov regularization and a corresponding data detection algorithm is proposed using the linear minimum mean square error (LMMSE) criterion. In the derived channel estimator, the unknown data is treated as part of the noise and the resulting data detection may not meet the required performance. To address this issue, an iterative method based on the variational inference approach is derived to improve performance. Simulation results show that the data detection performance of the proposed iterative algorithm initialized by the LMMSE data detector is close to the ideal case with perfect channel state information. © 2006 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE-
dc.relation.ispartofIEEE Transactions on Signal Processingen_HK
dc.rightsIEEE Transactions on Signal Processing. Copyright © IEEE-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAmplify-and-forwarden_HK
dc.subjectOrthogonal frequency division multiplexing (OFDM)en_HK
dc.subjectTime-varying channelsen_HK
dc.titleSuperimposed training-based channel estimation and data detection for OFDM amplify-and-forward cooperative systems under high mobilityen_HK
dc.typeArticleen_HK
dc.identifier.emailWu, YC: ycwu@hkucc.hku.hken_HK
dc.identifier.emailMa, S: sdma@eee.hku.hken_HK
dc.identifier.emailNg, TS: tsng@eee.hku.hken_HK
dc.identifier.authorityWu, YC=rp00195en_HK
dc.identifier.authorityMa, S=rp00153en_HK
dc.identifier.authorityNg, TS=rp00159en_HK
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1109/TSP.2011.2169059en_HK
dc.identifier.scopuseid_2-s2.0-84555218309en_HK
dc.identifier.hkuros208108-
dc.identifier.hkuros209636-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84555218309&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume60en_HK
dc.identifier.issue1en_HK
dc.identifier.spage274en_HK
dc.identifier.epage284en_HK
dc.identifier.isiWOS:000298294600023-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridHe, L=36084228000en_HK
dc.identifier.scopusauthoridWu, YC=7406894786en_HK
dc.identifier.scopusauthoridMa, S=8553949000en_HK
dc.identifier.scopusauthoridNg, TS=7402229975en_HK
dc.identifier.scopusauthoridPoor, HV=7102187242en_HK
dc.customcontrol.immutablejt 130321-

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