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6G Arrow

6GARROW is a consortium between South Korea and several European countries focused on developing next-generation 6G wireless technologies.

This project covers a broad range of technical topics related to future 6G wireless communication networks, including device-level algorithms, AI-native network design, and advanced RAN and Core Network technologies.

AI-Native Architecture

A central part of the project is the development of a communication architecture in which Artificial Intelligence is embedded into the foundational layers of the network rather than being added on top of existing systems. This enables real-time intelligence, energy-efficient optimization, and new types of services that rely on network-integrated AI capabilities.

AI for and on Device

Another focus area concerns algorithms and communication protocols running directly on devices. Since 6G devices are expected to operate with stricter limitations, these algorithms must satisfy tighter constraints:

  • Low energy consumption

  • Low hardware cost​

  • Minimal heat generation

These requirements apply to many device categories, including sensors, wearables, robots, and energy-constrained IoT units.

AI for and on RAN/Core

The project also investigates algorithms and solutions for both the Radio Access Network (RAN) and the Core Network.
The RAN covers all wireless interactions between devices and radio infrastructure, while the Core Network includes mobility handling, authentication, session management, security, and traffic coordination.

6G Arrow Vision

6GARROW integrates these areas into a unified 6G research framework:​

  • Devices perform lightweight AI processing and interact efficiently with the RAN. 

  • The RAN uses AI to optimize radio resources, predict channel conditions, and improve user-experience-driven scheduling.  

  • The Core Network applies AI for mobility management, anomaly detection, traffic forecasting, and autonomous operation.  

  • End-to-end communication is supported by an AI-native architecture rather than a conventional network with external AI modules.

This coordinated design ensures that intelligence flows seamlessly from devices to the RAN and from the RAN to the Core Network.​

Robotic & Mobile Networks Laboratory

School of Electrical & Electronic Engineering, Yonsei University, 

50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea

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