Terahertz Spatial Wireless Channel Modeling with Radio Radiance Field

TL;DR

This paper explores using radio radiance fields to model the complex THz wireless channel, enabling efficient spatial channel estimation with sparse data for future 6G systems.

Contribution

It introduces applying the RRF framework to THz channels, demonstrating effective reconstruction and modeling with sparse measurements, a novel approach for 6G wireless communication.

Findings

RRF captures key propagation paths with sparse samples

Reconstructed RRF shows high quality in simulations

Effective for scalable THz channel modeling

Abstract

Terahertz (THz) communication is a key enabler for 6G systems, offering ultra-wide bandwidth and unprecedented data rates. However, THz signal propagation differs significantly from lower-frequency bands due to severe free space path loss, minimal diffraction and specular reflection, and prominent scattering, making conventional channel modeling and pilot-based estimation approaches inefficient. In this work, we investigate the feasibility of applying radio radiance field (RRF) framework to the THz band. This method reconstructs a continuous RRF using visual-based geometry and sparse THz RF measurements, enabling efficient spatial channel state information (Spatial-CSI) modeling without dense sampling. We first build a fine simulated THz scenario, then we reconstruct the RRF and evaluate the performance in terms of both reconstruction quality and effectiveness in THz communication, showing that the reconstructed RRF captures key propagation paths with sparse training samples. Our findings demonstrate that RRF modeling remains effective in the THz regime and provides a promising direction for scalable, low-cost spatial channel reconstruction in future 6G networks.