Modular and Integrated AI Control Framework across Fiber and Wireless Networks for 6G
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Abstract (arXiv)
The rapid evolution of communication networks towards 6G increasingly incorporates advanced AI-driven controls across various network segments to achieve intelligent, zero-touch operation. This paper proposes a comprehensive and modular framework for AI controllers, designed to be highly flexible and adaptable for use across both fiber optical and radio networks. Building on the principles established by the O-RAN Alliance for near-Real-Time RAN Intelligent Controllers (near-RT RICs), our framework extends this AI-driven control into the optical domain. Our approach addresses the critical need for a unified AI control framework across diverse network transport technologies and domains, enabling the development of intelligent, automated, and scalable 6G networks.
Key facts. Cited by 2 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 Feb 2025.
Builds on
5 of 10 references.
References · 5
- 2023Machine Learning-based Early Attack Detection Using Open RAN Intelligent Controllercited by 5
- 2018Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Surveycited by 4
- 2024Cross-Domain AI for Early Attack Detection and Defense Against Malicious Flows in O-RANcited by 3
- 2024Demonstration of Cooperative Transport Interface using open-source 5G OpenRAN and virtualised PON networkcited by 2
- 2018A Variable Rate Fronthaul Scheme for Cloud Radio Access Networks (C-RAN)cited by 1
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.