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Collaborative Insights on Explainable AI in O-RAN Published in IEEE Communications Surveys & Tutorials!
We are thrilled to announce the publication of our paper titled “Explainable AI in 6G O-RAN: A Tutorial and Survey on Architecture, Use Cases, Challenges, and Future Research” in IEEE Communications Surveys & Tutorials 2024, with an impressive Impact Factor of 34.4!
This paper represents a collaborative effort between the SUNRISE-6G and 6G-BRICKS projects, showcasing joint innovation in advancing research on 6G networks.
The paper delves into the transformative potential of Explainable AI (#XAI) within the 6G O-RAN architecture, addressing the critical trust gap between human operators and AI/ML-driven decision-making systems. As O-RAN evolves with disaggregated architecture, open interfaces, and hierarchical closed-loop control via RAN Intelligent Controllers (#RICs), the role of XAI becomes pivotal in fostering trust and transparency.
Key highlights of the paper:
- Overview of XAI methods and metrics.
- Analysis of XAI deployment in O-RAN architecture and its core building blocks.
- Exploration of diverse O-RAN use cases enhanced by XAI.
- Discussion on the automation of XAI pipelines and associated security considerations.
- Insights into challenges and future research directions for integrating XAI into AI/ML-based O-RAN management.
Access the full publication here.