Modular and Integrated AI Control Framework across Fiber and Wireless Networks for 6G
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Digital twins for the design, interactive control, and deployment of modular, fiber-reinforced soft continuum arms
Soft continuum arms (SCAs) promise versatile manipulation through mechanical compliance, for assistive devices, agriculture, search applications, or surgery. However, the strong nonlinear coupling between materials, morp…
A Modular Edge Device Network for Surgery Digitalization
Future surgical care demands real-time, integrated data to drive informed decision-making and improve patient outcomes. The pressing need for seamless and efficient data capture in the OR motivates our development of a m…
Decision MakingPose TrackingBab_Sak Robotic Intubation System (BRIS): A Learning-Enabled Control Framework for Safe Fiberoptic Endotracheal Intubation
Endotracheal intubation is a critical yet technically demanding procedure, with failure or improper tube placement leading to severe complications. Existing robotic and teleoperated intubation systems primarily focus on …
Depth EstimationAI-Native Network Controller: A Modular Framework for Safe Agentic Control of Multi-Domain Network Infrastructure
The convergence of multiple network domains, including radio access, optical transport, and core networks, under unified intelligent control is a fundamental requirement for future 6G systems. This is important because e…
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation
White matter fiber clustering is an important strategy for white matter parcellation, which enables quantitative analysis of brain connections in health and disease. In combination with expert neuroanatomical labeling, d…
AnatomyClusteringComputational EfficiencyRepresentation Learning+1