Journal
COMPUTER NETWORKS
Volume 237, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.comnet.2023.110044
Keywords
AI/ML; Data analytics; Intelligent networks; Network automation
Ask authors/readers for more resources
This article surveys the application of artificial intelligence and machine learning in 5G and 6G mobile communications. It introduces the key technologies of AI/ML in network planning and optimization, service request, data collection and distribution, and summarizes the main AI/ML algorithms. The article also discusses the standardization and open source activities of AI/ML, as well as the challenges that need to be addressed in using AI/ML for automation.
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 networkcentric. 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available