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Conference Paper: A robust subspace tracking algorithm for subspace-based blind multiuser detection in impulsive noise

TitleA robust subspace tracking algorithm for subspace-based blind multiuser detection in impulsive noise
Authors
Issue Date2002
PublisherIEEE.
Citation
The 14th International Conference on Digital Signal Processing, Santorini, Greece, 1-3 July 2002, v. 2, p. 1289-1292 How to Cite?
AbstractSubspace tracking is an efficient method to reduce the complexity in estimating the signal subspace required in subspace-based multiuser detection algorithm. Recursive least square (RLS)-based subspace tracking algorithms such as the PAST algorithm can be used to estimate the signal subspace adaptively with relatively low computational complexity. However, it is shown in this paper that subspace estimation using conventional autocorrelation matrix is very sensitive to impulse noise. A new robust correlation matrix, based on robust statistics, is proposed to overcome this problem. Moreover, a new robust PAST algorithm is developed, again using robust statistics, for robust subspace tracking. A new restoring mechanism is also proposed to handle long bursts of impulses, which sporadically occur in communications systems. Simulation results show that the proposed robust subspace tracking-based blind multiuser detector performs better than the conventional approach, especially under consecutive impulses. The adaptation of the proposed scheme in a dynamic multiple access channel, where users may enter and exit the shared mobile channel, is also found to be satisfactory.
Persistent Identifierhttp://hdl.handle.net/10722/46393

 

DC FieldValueLanguage
dc.contributor.authorWen, Yen_HK
dc.contributor.authorChan, SCen_HK
dc.contributor.authorHo, KLen_HK
dc.date.accessioned2007-10-30T06:48:54Z-
dc.date.available2007-10-30T06:48:54Z-
dc.date.issued2002en_HK
dc.identifier.citationThe 14th International Conference on Digital Signal Processing, Santorini, Greece, 1-3 July 2002, v. 2, p. 1289-1292en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46393-
dc.description.abstractSubspace tracking is an efficient method to reduce the complexity in estimating the signal subspace required in subspace-based multiuser detection algorithm. Recursive least square (RLS)-based subspace tracking algorithms such as the PAST algorithm can be used to estimate the signal subspace adaptively with relatively low computational complexity. However, it is shown in this paper that subspace estimation using conventional autocorrelation matrix is very sensitive to impulse noise. A new robust correlation matrix, based on robust statistics, is proposed to overcome this problem. Moreover, a new robust PAST algorithm is developed, again using robust statistics, for robust subspace tracking. A new restoring mechanism is also proposed to handle long bursts of impulses, which sporadically occur in communications systems. Simulation results show that the proposed robust subspace tracking-based blind multiuser detector performs better than the conventional approach, especially under consecutive impulses. The adaptation of the proposed scheme in a dynamic multiple access channel, where users may enter and exit the shared mobile channel, is also found to be satisfactory.en_HK
dc.format.extent403016 bytes-
dc.format.extent8028 bytes-
dc.format.extent27162 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofInternational Conference on Digital Signal Processing-
dc.rights©2002 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.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleA robust subspace tracking algorithm for subspace-based blind multiuser detection in impulsive noiseen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICDSP.2002.1028329en_HK
dc.identifier.hkuros82539-

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