mlsanityData to 7 Oct 2026

Toward Digital Network Twins: Integrating Sionna RT in ns-3 for 6G Multi-RAT Networks Simulations

arXiv 2501.00372 ↗First posted 31 Dec 2024cs.NI cs.SEcited by 6

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Abstract (arXiv)

The increasing complexity of 6G systems demands innovative tools for network management, simulation, and optimization. This work introduces the integration of ns-3 with Sionna RT, establishing the foundation for the first open source full-stack Digital Network Twin (DNT) capable of supporting multi-RAT. By incorporating a deterministic ray tracer for precise and site-specific channel modeling, this framework addresses limitations of traditional stochastic models and enables realistic, dynamic, and multilayered wireless network simulations. Tested in a challenging vehicular urban scenario, the proposed solution demonstrates significant improvements in accurately modeling wireless channels and their cascading effects on higher network layers. With up to 65% observed differences in application-layer performance compared to stochastic models, this work highlights the transformative potential of ray-traced simulations for 6G research, training, and network management.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Dec 2024.

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Citing papers per year: 2025: 4; 2026: 2.

6 papers.