Publication:
Quadrature permutation matrix modulation

dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.kuauthorÖzpoyraz, Burak
dc.contributor.kuauthorBaşar, Ertuğrul
dc.contributor.kuauthorAydın, Atalay
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2026-02-26T07:12:57Z
dc.date.available2026-02-25
dc.date.issued2026
dc.description.abstractThis paper introduces the in-phase and quadrature (IQ) extension to the permutation matrix modulation (PMM) technique and proposes the quadrature PMM (QPMM) scheme for higher spectral efficiency without any expense in RF chains. Assuming a single-user MIMO (SU-MIMO) system model with all antennas activated, the proposed QPMM scheme utilizes the permutation matrices as the spatial indexing unit for both the IQ components of the complex symbol vector. Furthermore, a low-complex detector, conditional maximum likelihood detector (C-MLD), that achieves the same bit error rate (BER) performance as the optimal joint MLD is presented. In addition to the low-complex C-MLD detector, a deep learning (DL) based detector, called FusionDet, is also proposed for the QPMM scheme. This DL-based detector provides a trade-off between complexity and BER performance. The BER performance of the QPMM scheme and the complexities of the detectors are examined. The provided computer simulations reveal that the proposed QPMM scheme outperforms the conventional PMM method for different MIMO setups and modulation levels. In addition, the complexity analysis shows that C-MLD attains the same BER performance as the optimal joint MLD with significantly lower complexity. Finally, FusionDet is observed to further decrease detector complexity in exchange for sub-optimal detection performance.
dc.description.fulltextYes
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessHybrid OA
dc.description.peerreviewstatusN/A
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.versionN/A
dc.identifier.doi10.1109/TWC.2025.3581483
dc.identifier.eissn1558-2248
dc.identifier.embargoNo
dc.identifier.endpage118
dc.identifier.issn1536-1276
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-105009432320
dc.identifier.startpage107
dc.identifier.urihttps://doi.org/10.1109/TWC.2025.3581483
dc.identifier.urihttps://hdl.handle.net/20.500.14288/32477
dc.identifier.volume25
dc.identifier.wos001659564100048
dc.keywordsReceiving antennas
dc.keywordsTransmitting antennas
dc.keywordsSymbols
dc.keywordsDetectors
dc.keywordsComplexity theory
dc.keywordsMultiple-input multiple-output (MIMO)
dc.keywordsModulation
dc.keywordsBit error rate (BER)
dc.keywordsVectors
dc.keywordsPrecoding
dc.keywordsIndex modulation (IM)
dc.keywordsDeep learning (DL)
dc.keywordsNeural network (NN)
dc.language.isoeng
dc.publisherIEEE
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofIEEE Transactions on Wireless Communications
dc.relation.openaccessYes
dc.rightsCC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
dc.rights.uriAttribution, Non-commercial, No Derivative Works (CC-BY-NC-ND)
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleQuadrature permutation matrix modulation
dc.typeJournal Article
dspace.entity.typePublication
relation.isOrgUnitOfPublication21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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