Agentic AI for Intent-driven Optimization in Cell-free O-RAN

Researchers propose an agentic AI framework using multiple LLM-based agents to optimize cell-free Open RAN networks through intent-driven automation. The system reduces active radio units by 42% in energy-saving mode while cutting memory usage by 92% through parameter-efficient fine-tuning.