Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach

Fifth-generation (5G) and beyond systems are expected to accelerate the ongoing transformation of power systems toward the smart grid. However, the inherent heterogeneity in smart grid services and requirements pose significant challenges toward the definition of a unified network architecture. In t...

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Autores: Carrillo D., Kalalas C., Raussi P., Michalopoulos D.S., Rodriguez D.Z., Kokkoniemi-Tarkkanen H., Ahola K., Nardelli P.H.J., Fraidenraich G., Popovski P.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Repositorio:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
OAI Identifier:oai:cttc.fundanetsuite.com:p8329
Acceso en línea:https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8329
Access Level:acceso abierto
Palabra clave:Smart grids
5G mobile communication
Monitoring
Business
Ultra reliable low latency communication
Reliability
Power systems
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spelling Boosting 5G on Smart Grid Communication: A Smart RAN Slicing ApproachCarrillo D.Kalalas C.Raussi P.Michalopoulos D.S.Rodriguez D.Z.Kokkoniemi-Tarkkanen H.Ahola K.Nardelli P.H.J.Fraidenraich G.Popovski P.Smart grids5G mobile communicationMonitoringBusinessUltra reliable low latency communicationReliabilityPower systemsFifth-generation (5G) and beyond systems are expected to accelerate the ongoing transformation of power systems toward the smart grid. However, the inherent heterogeneity in smart grid services and requirements pose significant challenges toward the definition of a unified network architecture. In this context, radio access network (RAN) slicing emerges as a key 5G enabler to ensure interoperable connectivity and service management in the smart grid. This article introduces a novel RAN slicing framework which leverages the potential of artificial intelligence (Al) to support IEC 61850 smart grid services. With the aid of deep reinforcement learning, efficient radio resource management for RAN slices is attained, while conforming to the stringent performance requirements of a smart grid self-healing use case. Our research outcomes advocate the adoption of emerging Al-native approaches for RAN slicing in beyond-5G systems, and lay the foundations for differentiated service provisioning in the smart grid.Institute of Electrical and Electronics Engineers Inc.2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8329IEEE WIRELESS COMMUNICATIONSISSN: 15361284ISSNe: 15580687reponame:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)instname:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)Inglésinfo:eu-repo/semantics/openAccessoai:cttc.fundanetsuite.com:p83292026-06-17T11:44:47Z
dc.title.none.fl_str_mv Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
title Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
spellingShingle Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
Carrillo D.
Smart grids
5G mobile communication
Monitoring
Business
Ultra reliable low latency communication
Reliability
Power systems
title_short Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
title_full Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
title_fullStr Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
title_full_unstemmed Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
title_sort Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
dc.creator.none.fl_str_mv Carrillo D.
Kalalas C.
Raussi P.
Michalopoulos D.S.
Rodriguez D.Z.
Kokkoniemi-Tarkkanen H.
Ahola K.
Nardelli P.H.J.
Fraidenraich G.
Popovski P.
author Carrillo D.
author_facet Carrillo D.
Kalalas C.
Raussi P.
Michalopoulos D.S.
Rodriguez D.Z.
Kokkoniemi-Tarkkanen H.
Ahola K.
Nardelli P.H.J.
Fraidenraich G.
Popovski P.
author_role author
author2 Kalalas C.
Raussi P.
Michalopoulos D.S.
Rodriguez D.Z.
Kokkoniemi-Tarkkanen H.
Ahola K.
Nardelli P.H.J.
Fraidenraich G.
Popovski P.
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Smart grids
5G mobile communication
Monitoring
Business
Ultra reliable low latency communication
Reliability
Power systems
topic Smart grids
5G mobile communication
Monitoring
Business
Ultra reliable low latency communication
Reliability
Power systems
description Fifth-generation (5G) and beyond systems are expected to accelerate the ongoing transformation of power systems toward the smart grid. However, the inherent heterogeneity in smart grid services and requirements pose significant challenges toward the definition of a unified network architecture. In this context, radio access network (RAN) slicing emerges as a key 5G enabler to ensure interoperable connectivity and service management in the smart grid. This article introduces a novel RAN slicing framework which leverages the potential of artificial intelligence (Al) to support IEC 61850 smart grid services. With the aid of deep reinforcement learning, efficient radio resource management for RAN slices is attained, while conforming to the stringent performance requirements of a smart grid self-healing use case. Our research outcomes advocate the adoption of emerging Al-native approaches for RAN slicing in beyond-5G systems, and lay the foundations for differentiated service provisioning in the smart grid.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8329
url https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8329
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv IEEE WIRELESS COMMUNICATIONS
ISSN: 15361284
ISSNe: 15580687
reponame:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
instname:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
instname_str Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
reponame_str r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
collection r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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