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

arXiv: https://arxiv.org/abs/2603.23252 · HTML: https://mlsanity.com/paper/2603.23252/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 20 references that are in the map.
- First posted on arXiv 24 Mar 2026.

## Builds on (most cited first, 4 of 4)

- [Machine Learning-based xApp for Dynamic Resource Allocation in O-RAN Networks](https://mlsanity.com/paper/2401.07643/) (2024)
- [Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications](https://mlsanity.com/paper/2403.07763/) (2024)
- [RAN Functional Split Options for Integrated Terrestrial and Non-Terrestrial 6G Networks](https://mlsanity.com/paper/2310.17317/) (2023)
- [An In-Depth Survey on Virtualization Technologies in 6G Integrated Terrestrial and Non-Terrestrial Networks](https://mlsanity.com/paper/2312.01895/) (2023)

## Abstract (arXiv)

Integrating Artificial Intelligence (AI) into Non-Terrestrial Networks (NTN) is constrained by the joint limits of satellite SWaP and feeder-link capacity, which directly impact O-RAN closed-loop control and model lifecycle management. This paper studies the feasibility of distributing the O-RAN control hierarchy across Ground, LEO, and GEO segments through a Split-RIC architecture. We compare three deployment scenarios: (i) ground-centric control with telemetry streaming, (ii) ground--LEO Split-RIC with on-board inference and store-and-forward learning, and (iii) GEO--LEO multi-layer control enabled by inter-satellite links. For each scenario, we derive closed-form expressions for lifecycle energy and lifecycle latency that account for training-data transfer, model dissemination, and near-real-time inference. Numerical sensitivity analysis over feeder-link conditions, model complexity, and orbital intermittency yields operator-relevant feasibility regions that delineate when on-board inference and non-terrestrial learning loops are physically preferable to terrestrial offloading.