TY - JOUR
T1 - Boosting 5G on Smart Grid Communication: A Smart RAN Slicing Approach
AU - Carrillo, Dick
AU - Kalalas, Charalampos
AU - Raussi, Petra
AU - Michalopoulos, Diomidis
AU - Rodríguez, Demóstenes
AU - Kokkoniemi-Tarkkanen, Heli
AU - Ahola, Kimmo
AU - Nardelli, Pedro
AU - Fraidenraich, Gustavo
AU - Popovski, Petar
PY - 2023/10
Y1 - 2023/10
N2 - 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.
AB - 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.
KW - 5G mobile communication
KW - Business
KW - Monitoring
KW - Power systems
KW - Reliability
KW - Smart grids
KW - Ultra reliable low latency communication
UR - http://www.scopus.com/inward/record.url?scp=85137564466&partnerID=8YFLogxK
U2 - 10.1109/MWC.004.2200079
DO - 10.1109/MWC.004.2200079
M3 - Article
SN - 1536-1284
VL - 30
SP - 170
EP - 178
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 5
ER -