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Reference Scenarios and Key Performance Indicators for 5G Ultra-dense Networks

2020-11-10Preprint Open access
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dc.contributor.authorCampos, Luís Miguel
dc.contributor.authorRibeiro, Luís
dc.contributor.authorKarydis, Ioannis
dc.contributor.authorKaragiannis, Stelios
dc.contributor.authorPedro, Dário
dc.contributor.authorMartins, Jorge
dc.contributor.authorMarques, Carlos
dc.contributor.authorArmada, Ana García
dc.contributor.authorPerez Leal, Raquel
dc.contributor.authorLópez-Morales, Manuel José
dc.contributor.authorVelez, Fernando J.
dc.contributor.authorSebastião, Pedro
dc.contributor.authorRamos, Anderson
dc.date.accessioned2020-07-13T14:59:20Z
dc.date.available2020-07-13T14:59:20Z
dc.date.issued2020-11-10
dc.description.abstractThe so-called 5G will revolutionize the way we live, and work. In order to demonstrate the profound changes, we can expect to experience within the next 5 to 10 years, we present use cases for the planned research within the TeamUp5G project. Some use cases are strongly linked to the network layer and aim at developing solutions capable of optimizing the main promising benefits of 5G: extremely low latency and extremely high bandwidth (e.g., handle video streams, traffic congestion, user profiles), in the most efficient way possible. Other use cases focus on commercial applications that make use of middleware applications to enhance their performance. The latter fall into two main areas: real-time virtual reality and live video streaming, which are extremely demanding in terms of latency and bandwidth to provide an acceptable QoE/QoS to multiple users. The use cases presented are built assuming that 5G is essential for their support with appropriate QoE/QoS. Key performance indicators and their range of variation are also identified.pt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.doi10.1109/CSNDSP49049.2020.9249513
dc.identifier.urihttp://hdl.handle.net/10400.6/10375
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationInstituto de Telecomunicações
dc.relationNew RAN TEchniques for 5G UltrA-dense Mobile networks
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subject5Gpt_PT
dc.subjectUse casespt_PT
dc.subjectDeployment scenariospt_PT
dc.subjectKPIspt_PT
dc.subjectCharacterization parameterspt_PT
dc.titleReference Scenarios and Key Performance Indicators for 5G Ultra-dense Networkspt_PT
dc.typepreprint
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardTitleNew RAN TEchniques for 5G UltrA-dense Mobile networks
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50008%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/813391/EU
oaire.citation.conferencePlacePorto, Portugalpt_PT
oaire.citation.titleCSNDSP - 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processingpt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamH2020
person.familyNameGarcía Armada
person.familyNameVelez
person.familyNameRocha Ramos
person.givenNameAna
person.givenNameFernando J.
person.givenNameAnderson
person.identifier.ciencia-id1510-E247-C9DB
person.identifier.ciencia-id1610-0333-F898
person.identifier.orcid0000-0002-8495-6151
person.identifier.orcid0000-0001-9680-123X
person.identifier.ridD-9561-2011
person.identifier.scopus-author-id6505978276
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
rcaap.rightsopenAccesspt_PT
rcaap.typepreprintpt_PT
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relation.isAuthorOfPublicationeb831c87-4af4-4978-ba42-43d4d55dbe1f
relation.isAuthorOfPublication49541ff0-7298-49b9-bd6a-01f03cb7d300
relation.isAuthorOfPublication.latestForDiscoveryeb831c87-4af4-4978-ba42-43d4d55dbe1f
relation.isProjectOfPublication5a9bd4c8-57a9-46c4-95dc-a5e5c220c117
relation.isProjectOfPublication2bece073-0fd1-4f5e-a978-e2709b1c5713
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