O-RAN

Monotone FedNAM, a physically constrained federated additive model, eliminates all monotonicity violations in SLA-risk prediction for O-RAN, raising constrained shape consistency from 0.71 to 1.00 and…

Agentic AI systems are being explored to enhance Open RAN operations, offering explicit planning and self-management for network slice lifecycle and radio resource management. Research shows agentic p…

Researchers developed a Q-learning-based adaptive retraining method to address traffic drift in Open Radio Access Networks (O-RAN), reducing retraining overhead while maintaining forecasting accuracy.…