Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
Por:
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.
Publicada:
1 oct 2023
Resumen:
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.
Filiaciones:
Carrillo D.:
Lappeenranta - Lahti University of Technology, Finland
Kalalas C.:
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Spain
Raussi P.:
Aalto University, Finland
Michalopoulos D.S.:
Nokia, Germany
Rodriguez D.Z.:
Federal University of Lavras, Brazil
Kokkoniemi-Tarkkanen H.:
VTT Technical Research Centre of Finland, Finland
Ahola K.:
VTT Technical Research Centre of Finland, Finland
Nardelli P.H.J.:
Lut University, Finland
University of Oulu, Finland
Fraidenraich G.:
UNICAMP, Brazil
Popovski P.:
Aalborg University, Denmark
Green Submitted, All Open Access; Green Open Access
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