# Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN

arXiv: https://arxiv.org/abs/2609.18857 · HTML: https://mlsanity.com/paper/2609.18857/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Agentic AI for wireless networks, one of 16 directions in LLM agents and tool use.
- Builds on 5 of its 15 references that are in the map.
- First posted on arXiv 16 Sep 2026.

## Placed in

- LLM agents and tool use / [Agentic AI for wireless networks](https://mlsanity.com/agents/agentic-ai-for-wireless-networks/)

## Builds on (most cited first, 5 of 5)

- [NetLLM: Adapting Large Language Models for Networking](https://mlsanity.com/paper/2402.02338/) (2024)
- [PACIFISTA: Conflict Evaluation and Management in Open RAN](https://mlsanity.com/paper/2405.04395/) (2024)
- [Conflict Mitigation Framework and Conflict Detection in O-RAN Near-RT RIC](https://mlsanity.com/paper/2305.07117/) (2023)
- [ORANSlice: An Open-Source 5G Network Slicing Platform for O-RAN](https://mlsanity.com/paper/2410.12978/) (2024)
- [Mitigating xApp conflicts for efficient network slicing in 6G O-RAN: a graph convolutional-based attention network approach](https://mlsanity.com/paper/2504.17590/) (2025)

## Abstract (arXiv)

The O-RAN control plane is becoming agentic: autonomous AI agents, deployed as rApps by different vendors, independently close control loops over shared radio resources. We demonstrate on a live O-RAN system that this independence is unsafe. Two agents with individually correct objectives, one protecting a latency SLA and one maximizing utilization for energy efficiency, jointly drive recurring opposing excursions of the shared resource partition that neither produces alone. Existing conflict-mitigation mechanisms presume a statically known application population and cannot govern agents whose behavior emerges at run time. We present AURA, a lightweight arbitration layer that admits agent actions only when they satisfy feasibility invariants, per-variable dwell times, and a deadband, and we prove the arbitrated system converges to a feasible operating point. Implemented on an OpenAirInterface (OAI) testbed with measured one-way latency and throughput, AURA reduces recurring shared-state excursions by more than an order of magnitude (from 8.4 to 0.4 PRB amplitude) and virtually eliminates cross-slice throughput starvation (from 40-55% to 0.3%), while leaving the protected slice's own latency compliance unchanged, a trade-off the convergence guarantee makes explicit.