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Sistema para la detección y clasificación de patrones de celdas en redes móviles
dc.contributor.author | Trujillo, José Antonio | |
dc.contributor.author | De la Bandera Cascales, Isabel | |
dc.contributor.author | Palacios, David | |
dc.contributor.author | Barco-Moreno, Raquel | |
dc.date.accessioned | 2020-09-18T11:53:05Z | |
dc.date.available | 2020-09-18T11:53:05Z | |
dc.date.created | 2020 | |
dc.date.issued | 2020-09-18 | |
dc.identifier.uri | https://hdl.handle.net/10630/19803 | |
dc.description.abstract | The new 5th generation (5G) mobile networks will bring multiple services and heterogeneous scenarios that will provide large amount of data. In this context, automatic solutions to analyze such amount of data will allow operators to manage nerworks more efficiently. Management actions might be applied in a different way depending on the characteristics of each cell. This paper proposes an automatic framework based on machine learning to analyze and classify cells based on Key Performance Indicators (KPI) from a live network. | en_US |
dc.description.sponsorship | Ministerio de Economía y Competitividad de España, en el marco del acuerdo de subvención RTC-2017-6661-7 (NEREA). | en_US |
dc.language.iso | spa | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Sistemas de comunicaciones móviles | en_US |
dc.subject.other | SOM | en_US |
dc.subject.other | Random Forest | en_US |
dc.subject.other | Patrón de celda | en_US |
dc.subject.other | KPI | en_US |
dc.subject.other | 5G | en_US |
dc.title | Sistema para la detección y clasificación de patrones de celdas en redes móviles | en_US |
dc.type | info:eu-repo/semantics/conferenceObject | en_US |
dc.centro | E.T.S.I. Telecomunicación | en_US |
dc.relation.eventtitle | XXXV Simposio Nacional de la Unión Científica Internacional de Radio, URSI 2020 | en_US |
dc.relation.eventplace | Málaga (Remoto), España | en_US |
dc.relation.eventdate | 2/9/2020 | en_US |