# xApp Distillation: AI-based Conflict Mitigation in B5G O-RAN

arXiv: https://arxiv.org/abs/2407.03068 · HTML: https://mlsanity.com/paper/2407.03068/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 10 references that are in the map.
- First posted on arXiv 3 Jul 2024.

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

- [Policy Distillation](https://mlsanity.com/paper/1511.06295/) (2015)
- [Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks](https://mlsanity.com/paper/2012.01263/) (2020)
- [ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms](https://mlsanity.com/paper/2112.09559/) (2021)
- [Team Learning-Based Resource Allocation for Open Radio Access Network (O-RAN)](https://mlsanity.com/paper/2201.07385/) (2022)
- [Actor-Critic Network for O-RAN Resource Allocation: xApp Design, Deployment, and Analysis](https://mlsanity.com/paper/2210.04604/) (2022)

## Built on by (most cited first, 3 of 3)

- [O-RAN Xapps Conflict Prediction Using Graph Convolutional Networks](https://mlsanity.com/paper/2503.03523/) (2025)
- [ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunities](https://mlsanity.com/paper/2604.01239/) (2026)
- [ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps](https://mlsanity.com/paper/2605.22306/) (2026)

## Abstract (arXiv)

The advancements of machine learning-based (ML) decision-making algorithms created various research and industrial opportunities. One of these areas is ML-based near-real-time network management applications (xApps) in Open-Radio Access Network (O-RAN). Normally, xApps are designed solely for the desired objectives, and fine-tuned for deployment. However, telecommunication companies can employ multiple xApps and deploy them in overlapping areas. Consider the different design objectives of xApps, the deployment might cause conflicts. To prevent such conflicts, we proposed the xApp distillation method that distills knowledge from multiple xApps, then uses this knowledge to train a single model that has retained the capabilities of Previous xApps. Performance evaluations show that compared conflict mitigation schemes can cause up to six times more network outages than xApp distillation in some cases.