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6G Digital Twin Networks: From Theory to Practice
Open accessAbstract
Digital twin networks (DTNs) are real-time replicas of physical networks. They are emerging as a powerful technology for design, diagnosis, simulation, what-if-analysis, and artificial intelligence (AI)/ machine learning (ML) driven real-time optimization and control of the sixth generation (6G) wireless networks. Despite the great potential of what digital twins can offer for 6G, realizing the desired capabilities of DTNs requires tackling many design aspects including data, models, and interfaces. In this article we provide an overview of DTNs by presenting prominent use cases and their service requirements, describing a reference architecture, and discussing fundamental design aspects. We also present a real-world example to illustrate how DTNs can be built upon and operated in a real-time reference development platform - Omniverse.
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Cites
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391
Cited by
NVIDIA AI Aerial: AI-Native Wireless Communications
Cohen-Arazi, K., Roe, M., Hu, Z., Chavan, R., Ptasznik, A., Lin, J., Morais, J., Boccuzzi, J., & Balercia, T. (2025) · arXiv · doi:10.48550/arxiv.2510.01533 · Cited by 7
Metadata
- Authors
- Lin, X., Kundu, L., Dick, C., Obiodu, E., Mostak, T., & Flaxman, M.
- Venue
- IEEE Communications Magazine
- Published
- 2023-11
- Volume
- 61
- Issue
- 11
- Pages
- 72-78
- ISSN
- 0163-6804 (ISSN-L)
- 1558-1896
- OpenAlex
- W4380303648
- Cited by
- 171
- References
- 1
- FWCI
- 19.20
- Type
- journal article
- Language
- en
- Open access
- green
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- Lin, X., Kundu, L., Dick, C., Obiodu, E., Mostak, T., & Flaxman, M. (2023). 6G Digital Twin Networks: From Theory to Practice. IEEE Communications Magazine. https://doi.org/10.1109/mcom.001.2200830
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