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On the Optimum Detection of MIMO-SVD Signals With Strong Nonlinear Distortion Effects at the Transmitter

2024-12-23Artigo científico Acesso aberto
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dc.contributor.authorGonçalves, João
dc.contributor.authorNogueira, M. Teresa
dc.contributor.authorDinis, Daniel
dc.contributor.authorGuerreiro, João
dc.contributor.authorDinis, Rui
dc.contributor.institutionFaculdade de Ciências e Tecnologia (FCT)
dc.contributor.pblInstitute of Electrical and Electronics Engineers (IEEE)
dc.date.accessioned2025-05-21T21:16:15Z
dc.date.available2025-05-21T21:16:15Z
dc.date.issued2024-12-23
dc.descriptionFunding information: This work was supported in part by FCT—Fundação para a Ciência e Tecnologia, I.P. (DOI: https://doi.org/10.54499/UIDB/50008/2020) under Grant UIDB/50008/2020; in part by the project CELL-LESS6G (DOI: https://doi.org/10.54499/2022.08786.PTDC) under Grant 2022.08786.PTDC; and in part by the project COPELABS (DOI: https://doi.org/10.54499/UIDB/04111/2020) under Grant UIDB/04111/2020.
dc.description.abstractMultiple-Input Multiple-Output (MIMO) architectures are now widely adopted in wireless systems, providing substantial capacity benefits by harnessing spatial diversity and spatial multiplexing. Nonetheless, the large Peak-to-Average Power Ratio (PAPR) associated with common pre-processing techniques, like Singular Value Decomposition (SVD), increases the system's susceptibility to nonlinear distortion. Conventional receiver designs that mitigate this distortion often neglect the fact that it has useful information on the transmitted data. Maximum Likelihood (ML) detection offers the capability to take advantage of the nonlinear distortion, but its inherent complexity is prohibitively high. This paper introduces a new MIMO receiver design aimed at exploiting the diversity introduced by the transmitter nonlinearities. It also provides an approximate bound on the achievable ML Bit Error Rate (BER) performance. Our results indicate that the proposed receiver can have a performance close to the ML receiver with just a few iterations.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent12
dc.format.extent1290065
dc.identifier.doi10.1109/ACCESS.2024.3521513
dc.identifier.issn2169-3536
dc.identifier.otherPURE: 111455866
dc.identifier.otherPURE UUID: 123c56b6-f4b5-4c9f-834c-68cfd8f7fa58
dc.identifier.otherORCID: /0000-0001-5106-239X/work/174361888
dc.identifier.otherWOS: 001392836900032
dc.identifier.otherScopus: 85213240789
dc.identifier.otherORCID: /0000-0002-8520-7267/work/184528839
dc.identifier.urihttp://hdl.handle.net/10362/183290
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT
dc.relationInstituto de Telecomunicações
dc.relationCOPELABS - Cognitive and People-centric Computing R&D Unit
dc.subjectReceivers
dc.subjectMIMO
dc.subjectStreams
dc.subjectQuadrature amplitude modulation
dc.subjectPeak to average power ratio
dc.subjectVectors
dc.subjectPower amplifiers
dc.subjectNonlinear distortion
dc.subjectSymbols
dc.subjectSignal to noise ratio
dc.subjectNonlinear effects
dc.subjectMaximum likelihood detection
dc.subjectReceiver design
dc.subjectPerformance evaluation
dc.titleOn the Optimum Detection of MIMO-SVD Signals With Strong Nonlinear Distortion Effects at the Transmitteren
dc.typejournal article
degois.publication.firstPage3230
degois.publication.lastPage3241
degois.publication.titleIEEE Access
degois.publication.volume13
dspace.entity.typePublication
oaire.awardNumberUIDB/50008/2020
oaire.awardNumber2022.08786.PTDC
oaire.awardNumberUIDB/04111/2020
oaire.awardTitleInstituto de Telecomunicações
oaire.awardTitleCOPELABS - Cognitive and People-centric Computing R&D Unit
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Concurso de Projetos de I&D em Todos os Domínios Científicos - 2022/2022.08786.PTDC/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04111%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamConcurso de Projetos de I&D em Todos os Domínios Científicos - 2022
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication6b1f1825-8ab4-43f1-b6be-46ce73bd063a
relation.isProjectOfPublication40f847e1-36b9-4565-8da4-bbfc596b54b8
relation.isProjectOfPublication67639a80-0e51-4a24-9895-28ed2e7ea6e2
relation.isProjectOfPublication.latestForDiscovery40f847e1-36b9-4565-8da4-bbfc596b54b8

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