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Updated: Sep 12, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
Published on: February 3, 2021
Toward standardization of GenAI-driven agentic architectures for radio access networks
Zeinab Nezami1,2, Syed Ali Raza Zaidi1, Maryam Hafeez1
1School of Electronic and Electrical Engineering, University of Leeds, Leeds, United Kingdom.
Abstract:
The adoption of Generative Artificial Intelligence (GenAI) in Radio Access Networks (RAN) presents new opportunities for automation and intelligence across network operations. GenAI-powered agents, leveraging Large Language Models (LLMs), can enhance planning, execution, and decision-making for orchestration and real-time optimisation of 6G networks. Standardizing the implementation of the Agentic architecture for RAN is now essential to establish a unified framework for RANOps and AgentOps. One of the key challenges is to develop a blueprint that incorporates best practices for memory integration, tool generation, multi-agent orchestration, and performance benchmarking. This study highlights key areas requiring standardization, including agent tool specifications, RAN-specific LLM fine-tuning, validation frameworks, and AI-friendly documentation. We propose a dedicated research initiative on GenAI-for-RAN and GenAI-on-RAN to address these gaps and advance AI-driven network automation.
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