Generative Twin for 6G and Beyond 5G Networks: Vision, Challenges and Architecture

Within the current 6G and beyond 5G research, digital twins have become an indispensable asset for network management. These digital twins offer real-time and dynamic system representations, enabling precise decision-making and comprehensive testing in simulation environments before deployment. Going further, we introduce the novel concept of 'Generative Twin', an approach enabling the automatic generation system configurations and test system situations using Generative Artificial Intelligence (AI) and surpassing the limitations of human administrators. Our work reaches further, presenting a high-level architecture that outlines the additional functional elements and interfaces required to enhance the digital twins for 5G networks. We also demonstrate a mock-up simulation of information generation using the Large Language Model (LLM) ChatGPT and a best-practices digital twin based on the Open5GCore toolkit. Furthermore, we present a practical implementation roadmap, offering guidance for effective integration of generative twins and the technology challenges that necessitate further research, highlighting the very large potential of leveraging generative AI as an integral part of network management.