Network intelligence in 6G: challenges and opportunities

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Association for Computing Machinery
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The success of the upcoming 6G systems will largely depend on the quality of the Network Intelligence (NI) that will fully automate network management. Artificial Intelligence (AI) models are commonly regarded as the cornerstone for NI design, as they have proven extremely successful at solving hard problems that require inferring complex relationships from entangled, massive (network traffic) data. However, the common approach of plugging "vanilla" AI models into controllers and orchestrators does not fulfil the potential of the technology. Instead, AI models should be tailored to the specific network level and respond to the specific needs of network functions, eventually coordinated by an end-to-end NI-native architecture for 6G. In this paper, we discuss these challenges and provide results for a candidate NI-driven functionality that is properly integrated into the proposed architecture: network capacity forecasting.
Proceeding of: the 16th ACM Workshop on Mobility in the Evolving Internet Architecture (in conjunction with MobiCom 2021: The 27th Annual International Conference On Mobile Computing And Networking, January 31-February 04, 2022, New Orleans, United States)
Network intelligence, Mobile networks, Network design principles, Networks architectures, 6G communications
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MobiArch'21: Proceedings of the 16th ACM Workshop on Mobility in the Evolving Internet Architecture. New York, 2022. Pp.: 7-12.