AI-based Autonomous Control, Management, and Orchestration in 5G: from Standards to Algorithms

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dc.contributor.author Bega, Dario
dc.contributor.author Gramaglia, Marco
dc.contributor.author Pérez, Ramón
dc.contributor.author Fiore, Marco
dc.contributor.author Banchs Roca, Albert
dc.contributor.author Costa-Pérez, Xavier
dc.date.accessioned 2021-01-25T13:26:39Z
dc.date.available 2021-01-25T13:26:39Z
dc.date.issued 2020-12-02
dc.identifier.bibliographicCitation IEEE network, 34(6), Pp. 14-20
dc.identifier.issn 0890-8044
dc.identifier.issn 1558-156X (online)
dc.identifier.uri http://hdl.handle.net/10016/31770
dc.description.abstract While the application of Artificial Intelligence (AI) to 5G networks has raised a strong interest, standard solutions to bring AI into 5G systems are still in their infancy and have a long way to go before they can be used to build an operational system. In this paper, we contribute to bridging the gap between standards and a working solution, by defining a framework that brings together the relevant standard specifications and complements them with additional building blocks. We populate this framework with concrete AI-based algorithms that serve different purposes towards developing a fully operational system. We evaluate the performance resulting from applying our framework to control, management and orchestration functions, showing the benefits that AI can bring to 5G systems.
dc.description.sponsorship This work was supported by the H2020 5G-TOURS European project (Grant Agreement No. 856950).
dc.format.extent 7
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2020 IEEE.
dc.subject.other Artificial intelligence
dc.subject.other Forecasting
dc.subject.other Engines
dc.subject.other Prediction algorithms
dc.subject.other History
dc.subject.other Data analysis
dc.subject.other 3GPP
dc.title AI-based Autonomous Control, Management, and Orchestration in 5G: from Standards to Algorithms
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi https://doi.org/10.1109/MNET.001.2000047
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/856950/5G-TOURS
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 14
dc.identifier.publicationissue 6
dc.identifier.publicationlastpage 20
dc.identifier.publicationtitle IEEE NETWORK
dc.identifier.publicationvolume 34
dc.identifier.uxxi AR/0000025931
dc.contributor.funder European Commission
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