驯服智能体化RAN：O-RAN中自治AI智能体的稳定性保证仲裁
Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN
- Department of Electrical and Computer Engineering Worcester Polytechnic Institute（伍斯特理工学院电气与计算机工程系）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对O-RAN中多智能体冲突导致资源偏移的问题，提出AURA仲裁层，通过可行性不变量、驻留时间和死区约束动作，证明收敛性，实验减少偏移一个数量级并消除吞吐量匮乏。
AI中文摘要：
O-RAN控制平面正变得智能体化：由不同供应商以rApp形式部署的自治AI智能体，独立地在共享无线资源上闭合控制环路。我们在一个实时O-RAN系统上证明，这种独立性是不安全的。两个各自目标正确的智能体，一个保护延迟SLA，另一个最大化利用率以实现能效，共同驱动共享资源分区的周期性相反偏移，而单独任何一个都不会产生这种偏移。现有的冲突缓解机制假定应用群体是静态已知的，无法治理在运行时行为涌现的智能体。我们提出AURA，一个轻量级仲裁层，仅当智能体动作满足可行性不变量、每变量驻留时间和死区时才予以接纳，并证明仲裁系统收敛到可行工作点。在OpenAirInterface（OAI）测试平台上实现，并测量单向延迟和吞吐量，AURA将周期性共享状态偏移减少了一个数量级以上（从8.4降至0.4 PRB幅度），并几乎消除了跨切片吞吐量匮乏（从40-55%降至0.3%），同时保持受保护切片自身的延迟合规性不变，这一权衡由收敛保证明确化。
英文摘要：
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.
