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3D Wi-Fi Signal Measurement in Realistic Digital Twin Testbed Environments Using Ray Tracing

Mengyuan Wang, Haopeng Wang, Haiwei Dong, Abdulmotaleb El Saddik

TL;DR

A digital twin–based measurement system that integrates real-world 3D environment reconstruction with deterministic ray tracing (RT) for physically grounded electromagnetic modeling and offers interactive 3D visualization and on-demand data extraction, highlighting its potential for digital twin–driven wireless system design and optimization.

Abstract

Accurate and efficient modeling of indoor wireless signal propagation is crucial for the deployment of next-generation Wi-Fi. This paper presents a digital twin-based measurement system that integrates real-world 3D environment reconstruction with deterministic ray tracing for physically grounded electromagnetic modeling. Building geometry is obtained through LiDAR scanning, followed by object segmentation and assignment of ITU-R standard material parameters. The propagation process is simulated with a GPU-accelerated ray-tracing engine that generates path-level channel attributes, including delay, power, angular dispersion, and Ricean K-factor. Under identical runtime constraints, the proposed system is evaluated against a commercial measurement simulator, demonstrating up to 21 dB higher path gain and consistently improved signal-to-interference-plus-noise ratio in line-of-sight conditions. Additionally, experiments against onsite RSSI measurements confirm a high spatial correlation of 0.98 after calibration, proving the system's fidelity in real-world settings. Furthermore, coverage analysis across 2.4 GHz, 5 GHz, and 6 GHz bands demonstrates the capability of system to model frequency-dependent material attenuation for Wi-Fi 6E/7 networks. Finally, the system offers interactive 3D visualization and on-demand data extraction, highlighting its potential for digital twin-driven wireless system design and optimization.

3D Wi-Fi Signal Measurement in Realistic Digital Twin Testbed Environments Using Ray Tracing

TL;DR

A digital twin–based measurement system that integrates real-world 3D environment reconstruction with deterministic ray tracing (RT) for physically grounded electromagnetic modeling and offers interactive 3D visualization and on-demand data extraction, highlighting its potential for digital twin–driven wireless system design and optimization.

Abstract

Accurate and efficient modeling of indoor wireless signal propagation is crucial for the deployment of next-generation Wi-Fi. This paper presents a digital twin-based measurement system that integrates real-world 3D environment reconstruction with deterministic ray tracing for physically grounded electromagnetic modeling. Building geometry is obtained through LiDAR scanning, followed by object segmentation and assignment of ITU-R standard material parameters. The propagation process is simulated with a GPU-accelerated ray-tracing engine that generates path-level channel attributes, including delay, power, angular dispersion, and Ricean K-factor. Under identical runtime constraints, the proposed system is evaluated against a commercial measurement simulator, demonstrating up to 21 dB higher path gain and consistently improved signal-to-interference-plus-noise ratio in line-of-sight conditions. Additionally, experiments against onsite RSSI measurements confirm a high spatial correlation of 0.98 after calibration, proving the system's fidelity in real-world settings. Furthermore, coverage analysis across 2.4 GHz, 5 GHz, and 6 GHz bands demonstrates the capability of system to model frequency-dependent material attenuation for Wi-Fi 6E/7 networks. Finally, the system offers interactive 3D visualization and on-demand data extraction, highlighting its potential for digital twin-driven wireless system design and optimization.
Paper Structure (26 sections, 20 equations, 10 figures, 7 tables)

This paper contains 26 sections, 20 equations, 10 figures, 7 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Wireless Propagation Simulation Method
  4. Digital Twin Reconstruction
  5. Digital Twin Processing
  6. Environment Segmentation
  7. Radio Materials Assignment
  8. Ray-Tracing Based Propagation Modeling
  9. Experimental Setup
  10. Scenario Description and Parameter Setup
  11. Simulation Configuration
  12. Evaluation Metrics
  13. Error Metrics and Normalization
  14. Results and Analysis
  15. 3D Environment Reconstruction
  16. ...and 11 more sections

Figures (10)

  • Figure 1: The architecture of the proposed wireless propagation simulation. It begins with capturing real-world environments using a LiDAR-based scanning camera, followed by digital twin reconstruction. The electromagnetic materials are assigned to segmentated objects based on ITU-R P.2040-3 parameters, then, scene loaded into the simulation pipeline, where transmitters and receivers are added along with configurable parameters. Using a GPU-accelerated ray-tracing engine, both per-path channel characteristics and coverage metrics are computed and visualized.
  • Figure 2: Multipath interactions in an indoor wireless scene, including line-of-sight (LOS) transmission, floor and wall reflections, non-line-of-sight (NLOS) diffraction around corners, and diffuse scattering due to surface roughness and irregular objects.
  • Figure 3: Reconstructed 3D digital twin environment: it shows the front view, top view, side view and back view.
  • Figure 4:
  • Figure 5:
  • ...and 5 more figures