AI/ML-Driven Optimization for 6G Radio Access Networks
DRIVING-6G (AI/ML-Driven Framework for Joint Dynamic Optimization of Sensing, Computation, Frequency/resource Allocation in 6G RANs) is a collaborative research project labeled under the CELTIC-NEXT framework.
About the project
The project aims to develop and validate an advanced AI/ML-driven framework designed for the joint dynamic optimization of real-time sensing, computation offloading, communication, and frequency/resource allocation in 6G Radio Access Networks (RANs). By leveraging cross-layer coordination protocols and decoupling machine learning algorithms from underlying RAN functions, DRIVING-6G delivers solutions for multi-objective, real-time optimizations through integrated AI-powered cognition and collaborative intelligence.
Business Impact & Value Creation
At the PHY/MAC layers, these joint optimizations orchestrate signal processing across transmitter and receiver chains, enhancing system sustainability and computational feasibility to support high throughput and ultra-low latency. Furthermore, integrating sensing techniques with PHY layer optimizations creates a trustworthy, ML-driven resource allocation framework for multi-user environments, unlocking significant business value, reducing operational costs (OPEX/CAPEX) for telecom operators, and enabling novel use cases across autonomous systems, smart manufacturing, and immersive experiences.
key facts
- Project duration: 30 months
- Dates: July 2026 – December 2028
- Partners: 12 organizations
- Countries: 8
- Total budget: €3,032.24K
- Effort: 35.44 person-years
- Project ID: C2024/2-7
- Coordinator: Peter Lindgren, CGC ApS
- Project status: Set-up
key technicals highlight
01. Decoupled ML Framework
Decoupling ML algorithms from underlying RAN functions to create a more flexible and adaptable network architecture.
02. Joint PHY/MAC Layer Optimization
AI/ML-driven orchestration of signal processing across transmitter and receiver chains to support high throughput and low latency.
03. Sensing & PHY Layer Integration
Combining sensing techniques with physical layer optimizations to establish a trustworthy, ML-driven resource allocation framework.
04. Collaborative Intelligence
Intelligence sharing among sensors enhances overall sensing capabilities and supports coordinated decision-making.
05. Multi-Dimensional Business Models
Parallel development and validation of technological innovations and business models can enable customized services, reduced OPEX/CAPEX and new revenue streams.
06. Demo Site Validation
Technological solutions and business models will be tested and validated through Vestel’s demo site to accelerate commercial adoption.
partners
12 partners. 8 countries. One shared vision.
DRIVING-6G brings together telecommunications, research and industrial expertise from across Europe to develop, test and validate the project’s technological and business innovations.
- Czech Republic
- Denmark
- Germany
- Ireland
- Poland
- Portugal
- Turkey
- United Kingdom