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dc.contributor.authorMoysen Cortes, Jessica
dc.contributor.authorGiupponi, Lorenza
dc.contributor.authorMangues Bafalluy, Josep
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2017-10-31T10:29:51Z
dc.date.available2017-10-31T10:29:51Z
dc.date.issued2017-02-05
dc.identifier.citationMoysen, J., Giupponi, L., J. M. A mobile network planning tool based on data analytics. "Mobile information systems", 5 Febrer 2017, vol. 2017, núm. ID 6740585, p. 1-16.
dc.identifier.issn1574-017X
dc.identifier.urihttp://hdl.handle.net/2117/109446
dc.description.abstractPlanning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity of layers, applications, and Radio Access Technologies (RAT). In this context, a network planning tool capable of dealing with this complexity is highly convenient. The objective is to exploit the information produced by and already available in the network to properly deploy, configure, and optimise network nodes. This work presents such a smart network planning tool that exploits Machine Learning (ML) techniques. The proposed approach is able to predict the Quality of Service (QoS) experienced by the users based on the measurement history of the network. We select Physical Resource Block (PRB) per Megabit (Mb) as our main QoS indicator to optimise, since minimizing this metric allows offering the same service to users by consuming less resources, so, being more cost-effective. Two cases of study are considered in order to evaluate the performance of the proposed scheme, one to smartly plan the small cell deployment in a dense indoor scenario and a second one to timely face a detected fault in a macrocell network.
dc.format.extent16 p.
dc.language.isoeng
dc.publisherHINDAWI
dc.rightsAttribution 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica
dc.subject.lcshMachine learning
dc.subject.lcshMobile communication systems
dc.subject.otherMachine learning
dc.subject.otherGenetic algorithm
dc.subject.otherData analytics
dc.subject.otherQuality of service
dc.subject.otherMinimization of drive test
dc.subject.otherNetwork planning
dc.subject.otherSmall cell deployment
dc.subject.otherCell outage compensation
dc.titleA mobile network planning tool based on data analytics
dc.typeArticle
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacComunicacions mòbils, Sistemes de
dc.contributor.groupUniversitat Politècnica de Catalunya. WiComTec - Grup de recerca en Tecnologies i Comunicacions Sense Fils
dc.identifier.doi10.1155/2017/6740585
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.hindawi.com/journals/misy/2017/6740585/
dc.rights.accessOpen Access
local.identifier.drac21225179
dc.description.versionPostprint (published version)
local.citation.authorMoysen, J.; Giupponi, L.; Mangues-Bafalluy, Josep
local.citation.publicationNameMobile information systems
local.citation.volume2017
local.citation.numberID 6740585
local.citation.startingPage1
local.citation.endingPage16


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Attribution 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution 3.0 Spain