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

doi:10.1109/MWC.004.2200079

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

BA6402 Future communication networks

Lappeenranta-Lahti University of Technology LUT
Telecommunications Technological Center of Catalonia (CTTC)
Nokia, Germany
Universidade Federal de Lavras
Universidade Federal de Pernambuco
Aalborg University

Research output: Contribution to journal › Article › Scientific › peer-review

36 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	170-178
Number of pages	8
Journal	IEEE Wireless Communications
Volume	30
Issue number	5
DOIs	https://doi.org/10.1109/MWC.004.2200079
Publication status	Published - Oct 2023
MoE publication type	A1 Journal article-refereed

Funding

This article is partly supported by Academy of Finland via: FIREMAN consortium CHIST-ERA/n.326270, EnergyNet Research Fellowship n.321265/n.32886/n.352654, X-SDEN project n.349965, and 6G Flagship (n.346208). This research is also supported by the joint Baltic-Nordic Energy Research programme project “Guidelines for Next Generation Buildings as Future Scalable Virtual Management of MicroGrids [Next-uGrid]” (n.117766). The work of Charalampos Kalalas was supported by FIREMAN project CHIST-ERA-17-BDSI-003 funded by the Spanish National Foundation (PCI2019-103780). The work of Petar Popovski was, in part, supported by the Villum Investigator Grant “WATER” from the Velux Foundation, Denmark.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

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

Access to Document

10.1109/MWC.004.2200079

Cite this

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abstract = "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.",

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

Abstract

Funding

UN SDGs

Keywords

Access to Document

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