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Toward standardization of GenAI-driven agentic architectures for radio access networks

  • 0School of Electronic and Electrical Engineering, University of Leeds, Leeds, United Kingdom.
Frontiers in Artificial Intelligence +

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August 6, 2025

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August 6, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Generative Artificial Intelligence (GenAI) in Radio Access Networks (RAN) offers new automation potential. Standardizing GenAI agent architecture is crucial for intelligent 6G network operations and optimization.

Area Of Science

  • Telecommunications Engineering
  • Artificial Intelligence
  • Network Automation

Background

  • Generative Artificial Intelligence (GenAI) adoption in Radio Access Networks (RAN) presents opportunities for enhanced automation and intelligence.
  • Large Language Models (LLMs) are key to developing GenAI-powered agents for network planning, execution, and real-time optimization.

Purpose Of The Study

  • To highlight the necessity of standardizing the Agentic architecture for RAN to create a unified framework for Radio Access Network Operations (RANOps) and Agent Operations (AgentOps).
  • To identify key challenges and propose best practices for memory integration, tool generation, multi-agent orchestration, and performance benchmarking within GenAI for RAN.

Main Methods

  • Literature review and conceptual framework development focusing on GenAI applications in RAN.
  • Identification of critical areas for standardization, including agent tool specifications, LLM fine-tuning for RAN, validation frameworks, and AI-friendly documentation.

Main Results

  • Key standardization areas identified: agent tool specifications, RAN-specific LLM fine-tuning, validation frameworks, and AI-friendly documentation.
  • The study underscores the need for a blueprint incorporating best practices for memory, tool generation, and multi-agent orchestration.

Conclusions

  • Standardizing GenAI agent architecture in RAN is essential for advancing AI-driven network automation in 6G.
  • A dedicated research initiative on GenAI-for-RAN and GenAI-on-RAN is proposed to address identified gaps and foster innovation.

Keywords:

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