Una visión basada en QoE para algoritmo MRO en redes LTE

dc.centroE.T.S.I. Telecomunicaciónen_US
dc.contributor.authorMarí-Altozano, María Luisa
dc.contributor.authorMwanje, Stephen S.
dc.contributor.authorLuna-Ramírez, Salvador
dc.contributor.authorToril-Genovés, Matías
dc.contributor.authorGijón-Martín, Carolina
dc.date.accessioned2020-09-11T09:29:57Z
dc.date.available2020-09-11T09:29:57Z
dc.date.created2020-09
dc.date.issued2020-09-11
dc.departamentoIngeniería de Comunicaciones
dc.description.abstractDue to the huge increase in traffic and services in mobile networks, network management has changed its main focus from Quality of Service (QoS) to a Quality of Experience (QoE) perspective. In addition, SON (Self organization Networks) techniques have been developed to automate network management, being Mobility Robustness Optimization a key use case. Traditionally, Mobility Robustness Optimization aims to improving Handover performance by reducing too-early, too-late and ping-pong handovers. Nevertheless, these techniques may fail when pursuing maximum user QoE at cell edge. In this work, a novel Mobility Robustness Optimization algorithm is proposed to reach maximum QoE at cell edge in a realistic LTE network with a file download service.en_US
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.en_US
dc.identifier.urihttps://hdl.handle.net/10630/19751
dc.language.isospaen_US
dc.relation.eventdate2/9/2020en_US
dc.relation.eventplaceMálaga (España) - Onlineen_US
dc.relation.eventtitleURSI 2020en_US
dc.rights.accessRightsopen accessen_US
dc.subjectSistemas de comunicaciones inalámbricosen_US
dc.subjectAlgoritmos computacionalesen_US
dc.subject.otherQoEen_US
dc.subject.otherOptimizaciónen_US
dc.subject.otherLTEen_US
dc.subject.otherAlgoritmo MROen_US
dc.titleUna visión basada en QoE para algoritmo MRO en redes LTEen_US
dc.typeconference outputen_US
dspace.entity.typePublication
relation.isAuthorOfPublicationc062c7f9-a73f-4f6e-8d25-d8258916a967
relation.isAuthorOfPublication014c95aa-41da-4fb1-b41d-1e297ff0ecb6
relation.isAuthorOfPublication.latestForDiscoveryc062c7f9-a73f-4f6e-8d25-d8258916a967

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
ursi2020_riuma_mlma.pdf
Size:
97.42 KB
Format:
Adobe Portable Document Format
Description:
Resumen de la contribución al congreso
Download

Description: Resumen de la contribución al congreso