Publication:
Low complexity turbo-equalization: a clustering approach

dc.contributor.coauthorKim, Kyeongyeon
dc.contributor.coauthorChoi, Jun Won
dc.contributor.coauthorSinger, Andrew C.
dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.kuauthorKozat, Süleyman Serdar
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-10T00:06:29Z
dc.date.issued2014
dc.description.abstractWe introduce a low complexity approach to iterative equalization and decoding, or "turbo equalization", which uses clustered models to better match the nonlinear relationship that exists between likelihood information from a channel decoder and the symbol estimates that arise in soft-input channel equalization. The introduced clustered turbo equalizer uses piecewise linear models to capture the nonlinear dependency of the linear minimum mean square error (MMSE) symbol estimate on the symbol likelihoods produced by the channel decoder and maintains a computational complexity that is only linear in the channel memory. By partitioning the space of likelihood information from the decoder based on either hard or soft clustering and using locally-linear adaptive equalizers within each clustered region, the performance gap between the linear MMSE turbo equalizers and low-complexity least mean square (LMS)-based linear turbo equalizers can be narrowed.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue6
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipHanyang Univeristy [HY-2013]
dc.description.sponsorshipDiv of Electrical, Commun & Cyber Sys
dc.description.sponsorshipDirectorate For Engineering [1101338] Funding Source: National Science Foundation This research was funded by the research fund of Hanyang Univeristy (HY-2013). The associate editor coordinating the review of this paper and approving it for publication was K. K. Kuchi.
dc.description.volume18
dc.identifier.doi10.1109/LCOMM.2014.2316172
dc.identifier.eissn1558-2558
dc.identifier.issn1089-7798
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-84902124550
dc.identifier.urihttps://doi.org/10.1109/LCOMM.2014.2316172
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16621
dc.identifier.wos340115200042
dc.keywordsTurbo equalization
dc.keywordsPiecewise linear modelling
dc.keywordsHard clustering
dc.keywordsSoft clustering
dc.keywordsSelective channels
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofIEEE Communications Letters
dc.subjectTelecommunications
dc.titleLow complexity turbo-equalization: a clustering approach
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorKozat, Süleyman Serdar
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Electrical and Electronics Engineering
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relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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