LLM-powered agentic AI for 5G/6G networks: A tutorial and survey on architectures, protocols, and standardization

Ameur, Mazène; Mekrache, Abdelkader; Brik, Bouziane; Ksentini, Adlen
Submitted to ArXiV, 17 July 2026

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 covers the foundations of agentic systems: reasoning, planning, tool use, multi-agent coordination, and evaluation. Part II maps agentic capabilities onto 5G/6G control surfaces, standardization, and major 6G initiatives. Finally, it identifies open challenges shaping autonomous telecommunications.


Type:
Tutorial
Date:
2026-07-17
Department:
Communication systems
Eurecom Ref:
8889
Copyright:
© EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in Submitted to ArXiV, 17 July 2026 and is available at :

PERMALINK : https://www.eurecom.fr/publication/8889