About the project

By leveraging artificial intelligence (AI) technologies at the heart of radio access networks (RAN) and integrating devices seamlessly into network architectures, we can unlock new levels of efficiency, flexibility, and performance.

Illustration of puzzle pieces represaenting European Union and the Republic of Korea joined together

6G AI-Native Integrated RAN-Core Networks

6GARROW is a SNS international project fostering collaboration between the European Union and the Republic of Korea. The primary focus is on advancing Radio Access Networks and pioneering integrated device-network approaches. These innovations will serve as the foundational elements for the development of future AI-native RANs, paving towards future 6G mobile networks.

6GARROW builds on the foundations of established EU-ROK research collaboration including 5G-CHAMPION project that demonstrated 5G technology in the 2018 Winter Olympics in PyeongChan, PriMO-5G project that demonstrated end-to-end 5G system providing immersive video services for moving objects such as drones and 5G-ALLSTAR project that showcased smooth integration of 5G terrestrial and satellite systems.

Consortium partners
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EU Member States
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Asian Affiliated partners
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WHAT

Enable seamless integration of AI/ML functions and capabilities across devices, terminals and networks

Enable Native Exposure of AI Services and Functions to Terminals

  • Seamless integration of AI/ML capabilities across devices, terminals and networks.
  • Focus on real-time decision-making, optimization, and adaptation.

Definition of AI-Driven Architecture and Interoperability Framework

  • Framework to ensure AI-native and network-integrated functionalities.
  • Interoperability between device and network to streamline performance.

Investigate Impact of Semantic Communications on Native AI Systems

  • Semantic communication to prioritize meaning over raw data in AI-native systems.
  • Enhancing understanding, reasoning, and goal-oriented communication.

WHY

Device Performance Optimization

  • Maximizing user experience while minimizing complexity, energy consumption, and signaling.
  • Critical to ensure new 6G services run efficiently on terminals without draining resources.

Network Performance Optimization

  • Support for self-organizing, adaptive, and resilient networks.
  • AI-driven solutions for radio resource control, mobility management, and system orchestration.

Support for Semantic Communication

  • Efficient semantic data extraction to improve decision-making and context-aware networking.
  • Reducing unnecessary data transmission while focusing on goal-relevant information.

Addressing Technical Feasibility

  • Testbed implementations and real-world data collection needed to prove AI-native integration viability.

HOW

Enhance Device Performance with AI/ML

  • Development of AI/ML algorithms for terminals to manage energy consumption and complexity.
  • Ensuring seamless interaction between user terminals and network infrastructure.

Optimize RAN and Core Network Using AI/ML Solutions

  • Use AI to manage radio resources, automate base station control, optimize mobility, and recover from failures.
  • Focus on energy efficiency and maximizing network robustness.

Leverage Semantic Communication for AI-Driven Optimization

  • Apply semantic/goal-oriented communications to enhance AI reasoning and network automation.
  • AI systems to interpret and act on semantically relevant information, leading to efficient connect-compute resource use.

Develop Experimental Testbeds and Proof of Concept Platforms

  • Implement experimental testbeds to validate new AI-native and semantic communication concepts in 6G networks.
  • Demonstrate innovations like EE base station management and AI-driven semantic communication adaptation.