Published July 9, 2025
| Version v1
Conference paper
Open
6G-MIRAI-HARMONY: Machine Intelligence based Radio Access Infrastructure
Contributors
Researchers:
Description
The 6G-MIRAI-HARMONY project is funded as part of the European Union’s Smart Networks and Services (SNS) Joint Undertaking (JU) initiative. The project represents a collaborative effort between leading European and Japanese academic institutions and industry experts which has launched in April 2025. 6G-MIRAI-HARMONY is addressing the mounting demands for higher data rates, reduced latency, and improved reliability in wireless communication systems. These challenges are intensified by the increasing range of applications such as collaborative robotics, full industrial automation, real-time digital twinning, and immersive virtual reality, all while ensuring economic and ecological sustainability. To meet these demands, 6G-MIRAI aims to: develop advanced multi-antenna technologies like user-centric cell-free massive MIMO, address the practical limitations of AI/ML implementation in wireless communications and enable scalable, energy-efficient network solutions.
6G-MIRAI-HARMONY is structured around five Research and Technology Items (RTIs) to achieve its objectives:
- Develop realistic models and datasets to serve as the foundation for innovative technological solutions.
- Focus on enabling AI/ML techniques for key physical layer components, ensuring reliability, robustness, and scalability.
- Explore AI-driven solutions for efficient coordination of physical layer components, higher-layer functions, and control planes, especially in cell-free networks.
- Provide design guidelines for AI-ready 6G-RAN architectures
- Investigate methodologies for data management, testing, and validation
The presentation will given an overview of the project (consortium partners, objectives) and outline the project’s research & standards baselines and target landing zones.
Files
Henning Sanneck 260625.pdf
Files
(2.3 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:7a25be80c1bf44df20874728e6e3a01a
|
2.3 MB | Preview Download |