LLM-Powered Agentic AI for 5G/6G Networks: A Tutorial and Survey on Architectures, Protocols, and Standardization
This paper presents a tutorial-and-survey on integrating agentic AI into Next-Generation Networks (NGNs), addressing the gap in protocol integration, evaluation, and standardization alignment.
Provides a comprehensive survey on integrating agentic AI into Next-Generation Networks, addressing the gap in protocol integration, evaluation, and standardization alignment.
Before reading this…
Applications
- →Next-Generation Networks
- →Autonomous telecommunications
To understand this paper, make sure you know these concepts first:
- Basic understanding of telecommunications networksfind papers →
- Familiarity with AI conceptsfind papers →
Abstract
More Like ThisAgentic 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.