Networks are becoming increasingly complex and distributed, requiring a large variety of technologies to operate. With 6G, which is now on the horizon for around 2030, it is essential to design, experiment and standardize new network architectures with more intelligence and automation.
In this context, the concept of Network Digital Twins (NDT) appears to be an ideal solution for testing a multitude of scenarios and architectural components before deploying them in the real world. However, to date, very few initiatives have focused on developing a reference architecture for NDT. Therefore, there is a need to take a major leap forward and propose new methods, simulation, and modelling tools around the concept of NDT and demonstrate their interest in tangible use cases. An important opening towards open communities is also needed to ensure these solutions' adoption and future exploitation.
In this context, 6G-TWIN will provide the foundation for the design, implementation and validation of an AI-native reference architecture for 6G systems that incorporates NDT as a core mechanism for the end-to-end, real-time optimisation, management and control of highly dynamic and complex network scenarios.