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dc.contributor.authorBernardo Álvarez, Francisco
dc.contributor.authorAgustí Comes, Ramon
dc.contributor.authorPérez Romero, Jordi
dc.contributor.authorSallent Roig, José Oriol
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.identifier.citationBernardo, F. [et al.]. Temporal and spatial spectrum assignment in next generation OFDMA networks through reinforcement learning. A: IEEE Vehicular Technology Conference. "IEEE 69th Vehicular Technology Conference". 2009, p. 1-5.
dc.description.abstractThis paper proposes a Dynamic Spectrum Assignment strategy in the context of next generation multicell Orthogonal Frequency Division Multiple Access networks. The proposed strategy is able to dynamically find spectrum assignments per cell depending on the spatial and temporal distribution of the users over the scenario. Reinforcement Learning methodology has been employed to implement the strategy, which compared with other fixed and dynamic spectrum assignment strategies shows the best tradeoff between spectral efficiency and Quality-of-Service.
dc.format.extent5 p.
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshSignal theory (Telecommunication)
dc.subject.lcshOrthogonal frequency division multiplexing
dc.titleTemporal and spatial spectrum assignment in next generation OFDMA networks through reinforcement learning
dc.typeConference report
dc.subject.lemacSenyal, Teoria del (Telecomunicació)
dc.contributor.groupUniversitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/216248/EU/End-to-End Efficiency (E3)/E3
upcommons.citation.authorBernardo, F.; Agustí, R.; Pérez-Romero, J.; Sallent, J.
upcommons.citation.contributorIEEE Vehicular Technology Conference
upcommons.citation.publicationNameIEEE 69th Vehicular Technology Conference

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