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Ns3 meets Sionna: Using Realistic Channels in Network Simulation

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arxiv 2412.20524 v1 pith:7NRATPMP submitted 2024-12-29 cs.NI

Ns3 meets Sionna: Using Realistic Channels in Network Simulation

classification cs.NI
keywords channelnetworkaccuratelyns-3ns3sionnapropagationdeviceindoor
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Network simulators are indispensable tools for the advancement of wireless network technologies, offering a cost-effective and controlled environment to simulate real-world network behavior. However, traditional simulators, such as the widely used ns-3, exhibit limitations in accurately modeling indoor and outdoor scenarios due to their reliance on simplified statistical and stochastic channel propagation models, which often fail to accurately capture physical phenomena like multipath signal propagation and shadowing by obstacles in the line-of-sight path. We present Ns3Sionna, which integrates a ray tracing-based channel model, implemented using the Sionna RT framework, within the ns-3 network simulator. It allows to simulate environment-specific and physically accurate channel realizations for a given 3D scene and wireless device positions. Additionally, a mobility model based on ray tracing was developed to accurately represent device movements within the simulated 3D space. Ns3Sionna provides more realistic path and delay loss estimates for both indoor and outdoor environments than existing ns-3 propagation models, particularly in terms of spatial and temporal correlation. Moreover, fine-grained channel state information is provided, which could be used for the development of sensing applications. Due to the significant computational demands of ray tracing, Ns3Sionna takes advantage of the parallel execution capabilities of modern GPUs and multi-core CPUs by incorporating intelligent pre-caching mechanisms that leverage the channel's coherence time to optimize runtime performance. This enables the efficient simulation of scenarios with a small to medium number of mobile nodes.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. VaN3Twin: the Multi-Technology V2X Digital Twin with Ray-Tracing in the Loop

    cs.NI 2025-05 conditional novelty 7.0

    VaN3Twin integrates ray-tracing into a full-stack V2X simulator to enable accurate multi-technology coexistence modeling and reports 50-70% better agreement with field measurements than prior tools.

  2. Predicting Networks Before They Happen: Experimentation on a Real-Time V2X Digital Twin

    cs.NI 2026-01 conditional novelty 6.0

    A real-time V2X digital twin predicts RSSI with 1.01 dB average error and LoS transitions within 250 ms latency by integrating live mobility data with deterministic ray-tracing simulation.