Dictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array

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dc.authorid0000-0003-3375-0310
dc.authorid0000-0001-9474-7372
dc.contributor.authorNazzal, Mahmoud
dc.contributor.authorAygül, Mehmet Ali
dc.contributor.authorGörçin, Ali
dc.contributor.authorArslan, Hüseyin
dc.date.accessioned2020-01-02T11:27:00Z
dc.date.available2020-01-02T11:27:00Z
dc.date.issued2019
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü
dc.descriptionConference: 15th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC) Location: Tangier, MOROCCO Date: JUN 24-28, 2019 Book Series: International Wireless Communications and Mobile Computing Conference
dc.description.abstractRecent research considers the application of a lens antenna array in order to provide efficient beam selection in beamspace massive MIMO. Achieving the advantages of this beam selection paradigm requires efficient channel estimation in the beamspace. Along this line, beamspace sparsity is an efficient regularizer to this problem. In this paper, we propose using a dictionary trained over a set of example beam selection matrices, as a beam selection tool. In this context, a learned dictionary can more effectively guarantee the sparsity of the representation at the specified sparsity level, owing to the dictionary learning process. This means that it gives a better sparse representation, and, consequently, a better channel estimation quality. Simulations validate that using a trained dictionary improves the quality of channel estimation, as tested over two channel models with different operating scenarios.
dc.description.sponsorshipIEEE; IEEE Morocco Section; Mohammed V University of Rabaten_US
dc.identifier.citationNazzal, M., Aygül, M. A., Görçin, A. ve Arslan, H. (2019). Dictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array. 15th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC) içinde (20-25. ss.). Tangier, Morocco, June 24-28, 2019. http://doi.org/10.1109/IWCMC.2019.8766499
dc.identifier.doi10.1109/IWCMC.2019.8766499
dc.identifier.endpage25
dc.identifier.isbn9781538677476
dc.identifier.scopusqualityN/A
dc.identifier.startpage20
dc.identifier.urihttp://doi.org/10.1109/IWCMC.2019.8766499
dc.identifier.urihttps://hdl.handle.net/20.500.12511/4863
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof15th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.relation.tubitakinfo:eu-repo/grantAgreement/TUBITAK/SOBAG/116E078
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectBeamspace Channel Estimation
dc.subjectBeam Selection
dc.subjectMillimeter-Waves
dc.subjectMassive MIMO
dc.subjectSparse Coding
dc.subjectDictionary Learnin
dc.titleDictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array
dc.typeConference Object

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