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dc.contributor.authorVázquez Oliver, Miguel Ángel
dc.contributor.authorPérez Neira, Ana Isabel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2021-01-27T11:49:25Z
dc.date.available2021-01-27T11:49:25Z
dc.date.issued2020
dc.identifier.citationVázquez, M.; Pérez, A. Multigraph spectral clustering for joint content delivery and scheduling in beam-free satellite communications. A: IEEE International Conference on Acoustics, Speech and Signal Processing. "2020 IEEE International Conference on Acoustics, Speech, and Signal Processing: May 4-8, 2020 Centre de Convencions Internacional de Barcelona (CCIB), Barcelona, Spain: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 8802-8806. ISBN 978-1-5090-6631-5. DOI 10.1109/ICASSP40776.2020.9053805.
dc.identifier.isbn978-1-5090-6631-5
dc.identifier.urihttp://hdl.handle.net/2117/336089
dc.description.abstractThis paper tackles the problem of user scheduling in satellite content delivery networks with precoding. The clustering process has to consider two crucial and independent characteristics of the user terminals. On the one hand, users belonging to the same group shall have a reduced Euclidean norm between their channel vectors in order to obtain the maximum precoding gain. On the other hand, with the aim of exploiting the multicast capabilities of the system, user terminals grouped in the same cluster shall have requested the same content. The resulting clustering problem is formulated as a multigraph (also known as multiview) spectral clustering problem. The paper shows that this unsupervised learning framework is able to capture the different peculiarities of the mentioned problem. Two different techniques are introduced and validated in a close-to-real numerical simulation.
dc.description.sponsorshipThis work has received funding from the Spanish ministry of Science, Innovation and Universities under project TERESA-TEC2017-90093-C3-1-R (AEI/FEDER,UE), and by the Catalan Government under grant 2017-SGR01479.
dc.format.extent5 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços
dc.subject.lcshMachine learning
dc.subject.lcshGraph theory
dc.subject.lcshArtificial satellites in telecommunication
dc.subject.otherPrecoding
dc.subject.otherSatellite communication
dc.subject.otherTelecommunication computing
dc.subject.otherTelecommunication scheduling
dc.subject.otherUnsupervised learning
dc.subject.otherVectors
dc.titleMultigraph spectral clustering for joint content delivery and scheduling in beam-free satellite communications
dc.typeConference report
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacGrafs, Teoria de
dc.subject.lemacSatèl·lits artificials en telecomunicació
dc.identifier.doi10.1109/ICASSP40776.2020.9053805
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9053805
dc.rights.accessOpen Access
local.identifier.drac30356432
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2017-90093-C3-1-R/ES/INTERFAZ RADIO PARA SISTEMAS HIBRIDOS TERRESTRE%2FSATELITE DE 5G Y FUTUROS/
local.citation.authorVázquez, M.; Pérez, A.
local.citation.contributorIEEE International Conference on Acoustics, Speech and Signal Processing
local.citation.publicationName2020 IEEE International Conference on Acoustics, Speech, and Signal Processing: May 4-8, 2020 Centre de Convencions Internacional de Barcelona (CCIB), Barcelona, Spain: proceedings
local.citation.startingPage8802
local.citation.endingPage8806


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