The Impact of Terrain Sampling Density on 5G NR-V2X Downlink Channel Modeling Using Various Propagation Models at the 3.6 GHz Band

Abstract

This study investigates the sensitivity of radio wave propagation models to terrain sampling density in a 5G New Radio Vehicle-to-Everything downlink scenario at 3.6 GHz. Four widely used models are analysed: the empirical ITU-R P.1546-6, the deterministic Parabolic Equation Method, and the hybrid ITU-R P.1812-6 and ITU-R P.452-16. Real terrain profiles from Hungary are considered at multiple resolutions, allowing a systematic assessment of how accuracy degrades as the representation of terrain becomes oarser. The analysis reveals a consistent ranking across nvironments: the empirical model is the least affected by esolution changes, while deterministic and hybrid methods re significantly more sensitive. To interpret these differences, the study introduces a spectral complexity measure of errain profiles and establishes its strong relationship with error growth through regression analysis. This provides a novel ramework for explaining and quantifying the impact of terrain detail on model behaviour. The findings highlight both he methodological contribution of linking spectral complexity to propagation accuracy and the practical implications or optimising the trade-off between computational efficiency nd prediction reliability in vehicular network planning.