Tutorial 4 - Digital Twin Networks: Toward Intelligent and Autonomous Networking

Digital Twin Networks (DTNs) have emerged as a key enabling paradigm for future 6G communication systems by establishing real-time virtual representations of physical networks with bidirectional interactions. By integrating network sensing, data-driven modeling, and intelligent decision-making, DTNs enable self-optimization, self-adaptation, and self-configuration, thereby providing a promising foundation for endogenous network intelligence and autonomous network evolution. Furthermore, Digital Twin Edge Networks (DITENs) extend the DTN paradigm toward distributed edge environments by tightly integrating digital twins with edge computing, enabling intelligent resource orchestration, adaptive service provisioning, and efficient network optimization. This tutorial aims to provide communications and networking professionals and academics with a comprehensive overview of recent advances, emerging applications, and future challenges in DTN-based intelligent network modeling, optimization, and control for future wireless systems. The tutorial will first introduce the vision, architecture, and fundamental principles of DTNs, including key components, enabling technologies, and closed-loop network control mechanisms. Then, AI-empowered DTNs will be presented, with emphasis on the integration of machine learning (ML), generative artificial intelligence (AI), and reinforcement learning (RL) for predictive modeling, intelligent optimization, and adaptive network operation. Finally, emerging applications and open challenges of DTNs and DTENs will be discussed, covering intelligent vehicular networks, unmanned aerial vehicle (UAV) networks, industrial Internet of Things (IoT), edge intelligence, and integrated sensing and communication (ISAC) systems. The tutorial will conclude with a discussion of future research directions and open issues toward fully autonomous, intelligent, and adaptive 6G networks enabled by digital twin technologies.

  • Corresponding Author Information
    Yan Zhang, University of Electronic Science and Technology of China, China
    Prof. Yan Zhang is currently a Full Professor with the University of Electronic Science and Technology of China. Previously, he was full professor at University of Oslo, Norway. His research interests include next-generation wireless networks leading to 6G, green and secure cyber-physical systems. He is a fellow of the IET; and an Elected Member of the Academia Europaea (MAE), the Royal Norwegian Society of Sciences and Letters (DKNVS), and the Norwegian Academy of Technological Sciences (NTVA). He was a recipient of the Global Clarivate Analytics "Highly Cited Researcher" Award (Web of Science top 1 most cited worldwide). He is the Co-EiC of IEEE Transactions on Industrial Informatics, an Area Editor of IEEE Transactions on Green Communications and Networking, a Senior Editor of IEEE Systems Journal, and an associate editor of several IEEE Transactions/magazine.

  • Speaker 1: Yan Zhang, University of Electronic Science and Technology of China, China
  • Title: Digital Twin Networks: Vision, Architecture and Fundamentals
    Prof. Yan Zhang is currently a Full Professor with the University of Electronic Science and Technology of China. Previously, he was full professor at University of Oslo, Norway. His research interests include next-generation wireless networks leading to 6G, green and secure cyber-physical systems. He is a fellow of IET and an Elected Member of the Academia Europaea (MAE), the Royal Norwegian Society of Sciences and Letters (DKNVS), and the Norwegian Academy of Technological Sciences (NTVA). He was a recipient of the Global Clarivate Analytics "Highly Cited Researcher" Award (Web of Science top 1 most cited worldwide). He is the Co-EiC of IEEE Transactions on Industrial Informatics, an Area Editor of IEEE Transactions on Green Communications and Networking, a Senior Editor of IEEE Systems Journal, and an associate editor of several IEEE Transactions/magazine.

  • Speaker 2: Yunlong Lu, Beijing Jiaotong University, China
  • Title: AI-Empowered Digital Twin Networks: Intelligence and Optimization
    Prof. Yunlong Lu received the Ph.D. degree in computer science from Beijing University of Posts and Telecommunications, Beijing, China, in 2020. From 2018 to 2019, he was a Visiting Ph.D. Student at the University of Oslo, Norway. He is currently a Full Professor with the School of Electronic and Information Engineering and the State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, China. His research interests include edge intelligence, wireless communications, and trustworthy mobile networks. He is a recipient of the IEEE Vehicular Technology Society Daniel E. Noble Fellowship Award, the IEEE Best Vehicular Electronics Paper Award, and the Capital Frontier Academic Achievement Award of China. He was selected for the China Association for Science and Technology (CAST) Young Elite Scientists Sponsorship Program and the Beijing Nova Program. He has served as an Editor and Guest Editor for several journals and as a Chair and Technical Program Committee Member for multiple IEEE conferences, including IEEE ICC, GLOBECOM, and VTC.

  • Speaker 3: Yaru Fu, Hong Kong Metropolitan University, China
  • Title: Digital Twin Networks: Emerging Applications and Future Directions
    Prof. Yaru Fu is an Associate Professor and Head of the Centre for Research in Advanced Network Technologies (CRANT) at Hong Kong Metropolitan University, Hong Kong, China. She received her Ph.D. degree in Electronic Engineering from the City University of Hong Kong in 2018. Her research interests include B5G/6G technologies, digital twins, and machine learning. She has published over 130 papers in leading IEEE journals and conferences. Dr. Fu serves on the editorial boards of several IEEE journals, including IEEE Communications Surveys & Tutorials, IEEE Transactions on Cognitive Communications and Networking, and IEEE Internet of Things Journal. She has received several prestigious awards, including the IEEE WCL Best Editor Award (2021), IEEE GLOBECOM Best Paper Award (2024), and IEEE TCNC Exemplary Editor Award (2025). She has also been recognized among the World's Top 2% Scientists by Stanford University (2023–2025) and as a 2025 N2Women Rising Star.