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Data analytics for forecasting cell congestion on LTE networks

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dc.contributor.authorTorres, Pedro
dc.contributor.authorMarques, Paulo
dc.contributor.authorMarques, Hugo
dc.contributor.authorDionísio, Rogério Pais
dc.contributor.authorAlves, Tiago Ferreira
dc.contributor.authorPereira, Luis Miguel Cardoso
dc.contributor.authorRibeiro, Jorge Miguel Afonso
dc.date.accessioned2018-05-09T14:23:42Z
dc.date.available2018-05-09T14:23:42Z
dc.date.issued2017
dc.description“© © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”pt_PT
dc.description.abstractThis paper presents a methodology for forecasting the average downlink throughput for an LTE cell by using real measurement data collected by multiple LTE probes. The approach uses data analytics techniques, namely forecasting algorithms to anticipate cell congestion events which can then be used by Self-Organizing Network (SON) strategies for triggering network re-configurations, such as shifting coverage and capacity to areas where they are most needed, before subscribers have been impacted by dropped calls or reduced data speeds. The presented implementation results show the prediction of network behaviour is possible with a high level of accuracy, effectively allowing SON strategies to be enforced in time.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTORRES, P. [et al.] (2017) - Data analytics for forecasting cell congestion on LTE networks. In Network Traffic Measurement and Analysis Conference (TMA), Dublin, 21-23 junho. [S.l.]: IEEE. pp. 1-6.pt_PT
dc.identifier.doi10.23919/TMA.2017.8002917pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.11/6076
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relation17787 POCI-01-0247-FEDER-MUSCLESpt_PT
dc.relationMeasuring Mobile Broadband Networks in Europe
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8002917/pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/pt_PT
dc.subjectLTEpt_PT
dc.subjectSONpt_PT
dc.subjectMachine Learningpt_PT
dc.subjectForecastingpt_PT
dc.titleData analytics for forecasting cell congestion on LTE networkspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleMeasuring Mobile Broadband Networks in Europe
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/644399/EU
oaire.citation.conferencePlaceDublinpt_PT
oaire.citation.titleNetwork Traffic Measurement and Analysis Conference (TMA) 2017pt_PT
oaire.fundingStreamH2020
person.familyNameBAPTISTA TORRES
person.familyNameMarques
person.familyNameMarques
person.familyNamePAIS DIONÍSIO
person.givenNamePEDRO MIGUEL
person.givenNamePaulo
person.givenNameHugo
person.givenNameROGÉRIO
person.identifierK-5331-2015
person.identifier30skvuAAAAAJ
person.identifier.ciencia-id2711-E707-519C
person.identifier.ciencia-id6313-B906-ED27
person.identifier.ciencia-id2F1A-414F-368B
person.identifier.orcid0000-0003-4835-5022
person.identifier.orcid0000-0002-1788-651X
person.identifier.orcid0000-0001-5762-4912
person.identifier.orcid0000-0002-6810-2447
person.identifier.scopus-author-id56261515100
person.identifier.scopus-author-id7006399225
person.identifier.scopus-author-id25225486200
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameEuropean Commission
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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