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Modular and Integrated AI Control Framework across Fiber and Wireless Networks for 6G

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arxiv 2502.15731 v1 pith:6J6JG4D2 submitted 2025-02-03 cs.NI cs.AI

classification cs.NIcs.AI
keywords acrossframeworknetworkscontrolintelligentai-drivencontrollersfiber
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AI-Native Network Controller: A Modular Framework for Safe Agentic Control of Multi-Domain Network Infrastructure

    cs.NI 2026-04 conditional novelty 4.0 of 10

    The AI-Native Network Controller (AI-NNC) is a modular, protocol-agnostic framework enabling safe agentic AI control across heterogeneous network domains via validated command pipelines.

  2. Multi Part Deployment of Neural Network

    cs.LG 2025-06 reject novelty 2.0 of 10

    A high-level proposal to partition a neural network across servers using neuron-level remote calls and a shared NFS model, without any validation.

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