AI Lifecycle-Aware Feasibility Framework for Split-RIC Orchestration in NTN O-RAN

1. 1Identify the constraints of integrating AI into NTN, such as satellite SWaP and feeder-link capacity
2. 2Develop a split-RIC architecture to distribute the O-RAN control hierarchy across Ground, LEO, and GEO segments
3. 3Compare deployment scenarios, including ground-centric control, LEO-centric control, and GEO-centric control
4. 4Evaluate the feasibility of each scenario using the proposed AI lifecycle-aware framework

This research benefits AI engineers, data scientists, and software engineers working on Non-Terrestrial Networks (NTN) and O-RAN, as it provides a framework for distributing control hierarchy across different segments

💡 Distributing O-RAN control hierarchy across different segments can help address the limitations of satellite SWaP and feeder-link capacity

💡 AI lifecycle-aware framework for split-RIC orchestration in NTN O-RAN to overcome satellite constraints