Published October 16, 2023 | Version 1.0
Project deliverable Open

D3.4 Hybrid Deterministic/Stochastic Raytracing based Channel Model for Multiband Analysis in Industry Scenario

Description

The present report introduces the results on channel modelling at sub-6 GHz, mmWave, and sub-THz in the industrial scenarios discussed in 6G BRAINS. This model is a quasi-deterministic approach based on raytracing (RT) simulations from precise maps obtained from 3D laser scans plus stochastic components derived from extensive radiofrequency (RF) measurements in the same scenarios. The laser and RF measurements were conducted in a Bosch factory and a machine room in the facilities of FhG, both in Germany. The acquisition of the 3D CAD models was discussed in Deliverable D3.1, the RF measurement results in Deliverable D3.3, and in the present deliverable we validate the RT model by direct comparison between the simulations and measurements, while introducing the stochastic parameters extracted from the RF measurements. This raytracing model allows simulations with spatial consistency over the different bands of interest in 6G BRAINS, providing an accurate geometrical representation of the environment from the propagation properties for precise localization applications.

Files

D3.4 Hybrid deterministic-stochastic ray-tracing based channel model for multiband analysis in industry scenario_v1.1.pdf

Additional details

Funding

6G BRAINS – Bring Reinforcement-learning Into Radio Light Network for Massive Connections 101017226
European Commission

Dates

Submitted
2023-10-16