> [!ABSTRACT] > [6G-TWIN](https://6g-twin.eu/) is a European initiative focused on developing an **AI-native reference architecture for 6G systems**, integrating **[[Network Digital Twin]] (NDTs)** to optimise, manage, and control complex networks in real-time. > [!FACTSHEET] > - **Funding**: Horizon Europe, SNS JU > - **Duration**: 2024-2026 > - **My role**: Coordinator > - **Key partners**: Accelleran, Ericsson, IMEC, Politecnico di Bari, Proximus NXT, R2M Solution, TU Dresden, Ubiwhere, Université de Bourgogne, VIAVI Solutions   ## Context As digital transformation continues to reshape industries, the anticipated deployment of 6G networks by 2030 presents new opportunities to design intelligent, automated, and sustainable network architectures. The 6G-TWIN project addresses these challenges by introducing an AI-native reference architecture that integrates network digital twins (NDTs). These NDTs enable real-time optimisation, management, and control of complex network scenarios, making potential future [[6G and Beyond]] systems more efficient and adaptive. ## Key objectives The 6G-TWIN project focuses on the following primary objectives: 1. **Designing an AI-native 6G architecture**: Develop an open, federated architecture that incorporates NDTs to support intelligent analytics and real-time decision-making across diverse network domains. 2. **Creating federated, graph-based NDTs**: Build dynamic digital twins to model complex, evolving network environments, enhancing network planning, resource allocation, and operational control. 3. **Implementing a modelling and simulation framework**: Establish a secure, scalable framework for representing network scenarios, enabling the testing and validation of advanced 6G functionalities. These objectives represent the core ambitions of the project. Additional objectives may exist and can be clarified by consulting the [6G-TWIN project website](https://6g-twin.eu/). ## Outcomes The 6G-TWIN project is expected to deliver significant outcomes, including: - **Integration of AI and NDT technologies**: A robust, federated AI-native network architecture leveraging NDTs to optimise performance across multiple domains. - **Dynamic AI-orchestrated solutions**: Development of new AI methodologies for real-time network function orchestration and service optimisation. - **Energy efficiency improvements**: Demonstrating substantial reductions in energy consumption, with a target of at least 30% improvement in operational efficiency. These are just some examples of the project’s expected outcomes. ## Consortium 6G-TWIN unites **11 partners from 8 EU Member States and associated countries**, representing a multidisciplinary effort to advance 6G research in Europe. Visit the [6G-TWIN website](https://6g-twin.eu/) for more information. [](https://zenodo.org/communities/6g-twin/) [](https://www.linkedin.com/company/99314178/)