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Artificial Intelligence
arXiv (cs.AI) · July 17, 2026

LLM-Powered Agentic AI for 5G/6G Networks: A Tutorial and Survey on Architectures, Protocols, and Standardization

Mazene Ameur, Abdelkader Mekrache, Bouziane Brik +1 more

Running a mobile network has been rule-based automation: conditions are detected, predefined responses fire. Agentic AI proposes something different, systems given goals that decide for themselves how to reach them, and next-generation networks are an obvious candidate because their configuration space long ago outgrew what people can hand-tune.

The authors note that existing surveys cover the two fields separately, which leaves the connective tissue unexamined: how agents would integrate with network protocols, how their behaviour should be evaluated, and how any of it aligns with standardisation.

Those gaps are where the difficulty actually lives. Telecoms runs on interoperability agreements between vendors and operators, so an autonomous controller that cannot be specified in a standard, or whose behaviour cannot be evaluated against one, does not get deployed regardless of how well it performs in a lab.

From the arXiv (cs.AI) abstract

Agentic Artificial Intelligence (AI), enabled by Large Language Models, marks a shift from rule-based automation toward autonomous, goal-driven control of Next-Generation Networks (NGNs). Existing surveys treat the two domains in isolation, leaving protocol integration, evaluation, and standardization alignment underexplored. To address this gap, a two-part tutorial-and-survey is presented. Part I formalises the control, management, and AI-native planes of 5G and 6G. It then…


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