Digital Twin for Non-Terrestrial Networks: Vision, Challenges, and Enabling Technologies

This paper investigates the transformative potential of digital twin (DT) technology for non-terrestrial networks (NTNs). NTNs, comprising airborne and space-borne elements, face unique challenges in network control, management, and optimization. DT technology provides a novel framework for designing and managing complex cyber-physical systems with enhanced automation, intelligence, and resilience. By offering a dynamic virtual representation of the NTN ecosystem, DTs enable real-time monitoring, simulation, and data-driven decision-making. This paper explores the integration of DTs into NTNs, identifying technical challenges and highlighting some key enabling technologies. Emphasis is placed on technologies such as the Internet of Things (IoT), machine learning, generative AI, space-based clouds, quantum computing, and others, highlighting their potential to empower DT development for NTNs. To illustrate these concepts, we present a case study demonstrating the implementation of a data-driven DT model for enabling dynamic, service-oriented network slicing within an open radio access network (O-RAN) architecture tailored for NTNs. This work aims to advance the understanding and application of DT technology, contributing to the evolution of network control and management in the dynamic and rapidly changing landscape of non-terrestrial communication systems.