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

Dick Carrillo, Charalampos Kalalas, Petra Raussi, Diomidis Michalopoulos, Demóstenes Rodríguez, Heli Kokkoniemi-Tarkkanen, Kimmo Ahola, Pedro Nardelli, Gustavo Fraidenraich, Petar Popovski

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)


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.
Original languageEnglish
Number of pages8
JournalIEEE Wireless Communications
Publication statusE-pub ahead of print - 22 Aug 2022
MoE publication typeA1 Journal article-refereed


  • 5G mobile communication
  • Business
  • Monitoring
  • Power systems
  • Reliability
  • Smart grids
  • Ultra reliable low latency communication


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