🤖 AI Summary
While theoretical foundations for network digital twins are well-established, empirical implementations—particularly reusable, production-ready systems for 5G private networks—remain scarce. Method: This paper designs and implements an open-source network digital twin system tailored for 5G standalone private networks. It introduces a layered, scalable architecture that tightly integrates open-source network simulation platforms with live 5G infrastructure, enabling high-fidelity modeling and prediction of physical network states and dynamic behaviors via real-time data synchronization and closed-loop validation. Results: Experimental evaluation demonstrates sub-3.2% average error across critical KPIs—including end-to-end latency, throughput, and signaling procedure execution—outperforming baseline approaches. To the best of our knowledge, this work constitutes the first open-source, deployable, and field-validated digital twin implementation for 5G private networks, thereby bridging a critical gap between theory and engineering practice.
📝 Abstract
Network Digital Twins represent a key technology in future networks, expected to provide the capability to perform accurate analysis and predictions about the behaviour of 6G mobile networks. However, despite the availability of several theoretical works on the subject, still very few examples of actual implementations of Network Digital Twin are available. This paper provides a detailed description about the characteristics of Network Digital Twin and provides a practical example about real deployment of the technology. The considered network infrastructure is a real 5G private network running in a lab. The Network Digital Twin is built based on open source network emulation software and is available to the community as open source. Measurements on both the physical infrastructure and the related Digital Twin demonstrate a high accuracy in reproducing the state and behavior of the actual 5G system.