Publication:
Neural network based digital pre-distorter design for DCO-OFDM visible light communications

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dc.contributor.coauthorNarmanlıoğlu, Ömer
dc.contributor.coauthorUysal, Murat
dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.departmentN/A
dc.contributor.kuauthorErgen, Sinem Çöleri
dc.contributor.kuauthorTuran, Buğra
dc.contributor.kuprofileFaculty Member
dc.contributor.kuprofilePhD Student
dc.contributor.otherDepartment of Electrical and Electronics Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.yokid7211
dc.contributor.yokidN/A
dc.date.accessioned2024-11-09T23:37:56Z
dc.date.issued2022
dc.description.abstractDirect current biased optical orthogonal frequency division multiplexing (DCO-OFDM) is an appealing modulation scheme for reliable, high-speed optical transmissions and foreseen to be used in the upcoming IEEE 802.11bb visible light communication (VLC) standard. However, non-linear characteristics of light emitting diodes (LEDs) as VLC transmitters degrade the bit error rate (BER) performance of DCO-OFDM due to its high peak-to-average-power ratio. In this paper, we propose neural network based digital pre-distorter (DPD) to mitigate non-linear LED response for DCO-OFDM transmission. The proposed scheme extends the reliable transmission range by 1.75 m and 1.8 cm for non-compensated LED response and Memory Polynomial based DPD, respectively.
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.identifier.doi10.1109/MeditCom55741.2022.9928724
dc.identifier.isbn9781-6654-9825-8
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85142220865&doi=10.1109%2fMeditCom55741.2022.9928724&partnerID=40&md5=3aa0db38feb287ac36c667afc56ad728
dc.identifier.scopus2-s2.0-85142220865
dc.identifier.urihttps://dx.doi.org/10.1109/MeditCom55741.2022.9928724
dc.identifier.urihttps://hdl.handle.net/20.500.14288/12907
dc.keywordsDCO-OFDM
dc.keywordsDigital pre-distorter
dc.keywordsLinearization
dc.keywordsNeural network
dc.keywordsVisible light communication
dc.keywordsBit error rate
dc.keywordsIEEE Standards
dc.keywordsLight
dc.keywordsLight emitting diodes
dc.keywordsLight transmission
dc.keywordsOrthogonal frequency division multiplexing
dc.keywordsDigital pre-distort
dc.keywordsDirect current biased optical orthogonal frequency division multiplexing
dc.keywordsDirect-current
dc.keywordsLight emitting diode
dc.keywordsLinearisation
dc.keywordsModulation schemes
dc.keywordsNetwork-based
dc.keywordsNeural-networks
dc.keywordsOptical orthogonal frequency division multiplexing
dc.keywordsPredistorters
dc.keywordsVisible light communication
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.source2022 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2022
dc.subjectEngineering
dc.subjectTelecommunications
dc.subjectOptics
dc.titleNeural network based digital pre-distorter design for DCO-OFDM visible light communications
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0002-7502-3122
local.contributor.authorid0000-0001-9438-5113
local.contributor.kuauthorErgen, Sinem Çöleri
local.contributor.kuauthorTuran, Buğra
relation.isOrgUnitOfPublication21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0

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