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References (12)

[1]
Distributed Precoding for Cell-free Massive MIMO in O-RAN: A Multi-agent Deep Reinforcement Learning Framework
2025M. Shokouhi, Vincent W. S. Wong
[2]
AgentRAN: An Agentic AI Architecture for Autonomous Control of Open 6G Networks
2025Maxime Elkael, Salvatore D’oro et al.
[3]
TailO-RAN: O-RAN Control on Scheduler Parameters to Tailor RAN Performance
2025Nicolò Longhi, Salvatore D’oro et al.
[4]
MX-AI: Agentic Observability and Control Platform for Open and AI-RAN
2025Ilias Chatzistefanidis, Andrea Leone et al.
[5]
Distributed Precoding for eMBB and URLLC Traffic in Cell-Free O-RAN: A Multi-Agent Reinforcement Learning Framework
2025M. Shokouhi, Vincent W. S. Wong
[6]
ALLSTaR: Automated LLM-Driven Scheduler Generation and Testing for Intent-Based RAN
2025Maxime Elkael, Michele Polese et al.
[7]
GreenRAN: A Channel-Aware Green O-RAN Framework for NextG Mobile Systems
2025Chaoqun You, Xingqiu He et al.
[8]
dApps: Enabling Real-Time AI-Based Open RAN Control
2025Andrea Lacava, Leonardo Bonati et al.
[9]
Qwen2.5 Technical Report
2024Qwen An Yang, Baosong Yang et al.
[10]
QLoRA: Efficient Finetuning of Quantized LLMs
2023Tim Dettmers, Artidoro Pagnoni et al.
[11]
The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games
2021Chao Yu, Akash Velu et al.
[12]
An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel
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Founder's Pitch

"Develop a multi-agent AI system for intent-driven optimization in cell-free O-RAN to improve energy efficiency."

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