AI/ML for beyond 5G systems: Concepts, technology enablers & solutions

5G brought an evolution on the network architecture employing the service-based paradigm, enabling flexibility in realizing customized services across different technology domains. Such paradigm gives rise to the adoption of analytics and Artificial Intelligence/Machine Learning (AI/ML) in mobile co...

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Veröffentlicht in:Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2023-12, Vol.237, p.110044, Article 110044
Hauptverfasser: Taleb, Tarik, Benzaïd, Chafika, Addad, Rami Akrem, Samdanis, Konstantinos
Format: Artikel
Sprache:eng
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Zusammenfassung:5G brought an evolution on the network architecture employing the service-based paradigm, enabling flexibility in realizing customized services across different technology domains. Such paradigm gives rise to the adoption of analytics and Artificial Intelligence/Machine Learning (AI/ML) in mobile communications with the ease of collecting various measurements related to end-users and the network, which can be exposed towards consumers, including 3rd party applications. AI/ML may influence network planning and optimization considering the service life-cycle and introduce new operations provision, paving the way towards 6G. This article provides a survey on AI/ML considering the business, the fundamentals and algorithms across the radio, control, and management planes. It sheds light on the key technologies that assist the adoption of AI/ML in 3rd Generation Partnership Project (3GPP) networks considering service request, reporting, data collection and distribution and it overviews the main AI/ML algorithms characterizing them into user-centric and network-centric. Finally, it explores the main standardization and open source activities on AI/ML, highlighting the lessons learned and the further challenges that still need to be addressed to reap the benefits of AI/ML in automation for beyond 5G/6G mobile systems.
ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2023.110044