用视觉几何与稀疏采样建模太赫兹无线信道，提升6G通信效率
Terahertz Spatial Wireless Channel Modeling with Radio Radiance Field
- 基于视觉几何和稀疏测量重建连续无线电辐射场
- 少量训练样本即可捕捉关键传播路径，重构质量高
- 适合未来6G低功耗、可扩展的信道建模需求
太赫兹（THz）通信是6G系统的关键技术，提供超宽频带和前所未有的数据速率。然而，由于自由空间路径损耗严重、衍射能力弱、镜面反射显著以及散射突出，太赫兹信号传播特性与低频段差异显著，导致传统信道建模和基于导频的估计方法效率低下。本文探讨将无线电辐射场（RRF）框架应用于太赫兹频段的可行性。该方法利用基于视觉的几何信息和稀疏太赫兹射频测量，重建连续的无线电辐射场，实现无需密集采样的高效空间信道状态信息（Spatial-CSI）建模。我们首先构建精细的太赫兹仿真场景，随后重建RRF并评估其在重构质量和太赫兹通信有效性方面的表现。结果表明，即使使用稀疏训练样本，重建的RRF仍能准确捕捉关键传播路径。研究证实，RRF建模在太赫兹频段依然有效，为未来6G网络中可扩展、低成本的空间信道重建提供了有前景的方向。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。