Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/55338
Título: Boosting 5G on smart grid communication: a smart RAN slicing approach
Palavras-chave: Smart grids
5G mobile communication
Monitoring
Business
Ultra reliable low latency communication
Reliability
Power systems
Redes elétricas inteligentes
Rede 5G
Comunicação móvel
Comunicação ultra confiável e de baixa latência
Sistemas de energia
Data do documento: Ago-2022
Editor: Institute of Electrical and Electronics Engineers (IEEE)
Citação: CARRILLO, D. et al. Boosting 5G on smart grid communication: A smart RAN slicing approach. IEEE Wireless Communications, [S. I.], 2022. DOI: 10.1109/MWC.004.2200079.
Resumo: Fifth-generation (5G) and beyond systems are expected to accelerate the ongoing transformation of power systems towards the smart grid. However, the inherent heterogeneity in smart grid services and requirements pose significant challenges towards 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 (AI) 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 selfhealing use case. Our research outcomes advocate the adoption of emerging AI-native approaches for RAN slicing in beyond- 5G systems, and lay the foundations for differentiated service provisioning in the smart grid.
URI: https://ieeexplore.ieee.org/document/9864325
http://repositorio.ufla.br/jspui/handle/1/55338
Aparece nas coleções:DCC - Artigos publicados em periódicos

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