Terahertz channel modeling based on surface sensing characteristics

The dielectric properties of environmental surfaces, including walls, floors and the ground, etc., play a crucial role in shaping the accuracy of terahertz (THz) channel modeling, thereby directly impacting the effectiveness of communication systems. Traditionally, acquiring these properties has relied on methods such as terahertz time-domain spectroscopy (THz-TDS) or vector network analyzers (VNA), demanding rigorous sample preparation and entailing a significant expenditure of time. However, such measurements are not always feasible, particularly in novel and uncharacterized scenarios. In this work, we propose a new approach for channel modeling that leverages the inherent sensing capabilities of THz channels, specifically by obtaining channel measurement data through the analysis of refractive indices. By comparing the results obtained through channel sensing with that derived from THz-TDS measurements, we demonstrate the its ability to yield dependable surface property information. Integrating it into a ray-tracing algorithm for channel modeling in both a miniaturized cityscape scenario and an indoor environment, the results show consistency with experimental measurements, thereby validating its effectiveness in real-world settings.