The Paradigm of Digital Twin Communications
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Abstract (arXiv)
With the fast evolving of cloud computing and artificial intelligence (AI), the concept of digital twin (DT) has recently been proposed and finds broad applications in industrial Internet, IoT, smart city, etc. The DT builds a mirror integrated multi-physics of the physical system in the digital space. By doing so, the DT can utilize the rich computing power and AI at the cloud to operate on the mirror physical system, and accordingly provides feedbacks to help the real-world physical system in their practical task completion. The existing literature mainly considers DT as a simulation/emulation approach, whereas the communication framework for DT has not been clearly defined and discussed. In this article, we describe the basic DT communication models and present the open research issues. By combining wireless communications, artificial intelligence (AI) and cloud computing, we show that the DT communication provides a novel framework for futuristic mobile agent systems.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2021.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 3; 2025: 1.
8 papers.
- 2022A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systemscited by 18
- 2024Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challengescited by 10
- 2023LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computationcited by 4
- 2023Digital Twin-Aided Learning for Managing Reconfigurable Intelligent Surface-Assisted, Uplink, User-Centric Cell-Free Systemscited by 3
- 2024A Survey on Privacy Attacks Against Digital Twin Systems in AI-Roboticscited by 3
- 2024Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?cited by 2
- 2025Accurate AI-Driven Emergency Vehicle Location Tracking in Healthcare ITS Digital Twincited by 1
- 2021Learning Based Task Offloading in Digital Twin Empowered Internet of Vehiclescited by 0
- 2025Accurate AI-Driven Emergency Vehicle Location Tracking in Healthcare ITS Digital Twin5 Feb 2025
- 2024A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics27 Jun 2024
- 2024Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges12 Jun 2024
- 2024Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?16 Feb 2024
- 2023LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computation17 Dec 2023
- 2023Digital Twin-Aided Learning for Managing Reconfigurable Intelligent Surface-Assisted, Uplink, User-Centric Cell-Free Systems10 Feb 2023
- 2022A Bayesian Framework for Digital Twin-Based Control, Monitoring, and Data Collection in Wireless Systems2 Dec 2022
- 2021Learning Based Task Offloading in Digital Twin Empowered Internet of Vehicles28 Dec 2021