AI 中文总结
针对6G空天地数字孪生的大面积位置特定信道建模难题，提出基于遥感的增强型射线追踪框架，经实测验证可降低信道参数预测误差。
AI 中文摘要
位置特定信道模型对6G空天地一体化通信系统的无线数字孪生至关重要。然而，大范围区域内难以获取3D地图，这限制了大面积位置特定信道建模的应用。为解决该问题，本文提出一种基于遥感的增强型射线追踪（RT）信道建模框架，该框架包含确定性RT分支、测量统计分支和RT增强分支。为克服大面积3D地图获取困难，确定性RT分支从卫星遥感影像重建3D RT场景，并利用实测路径损耗校准其电磁材料参数。为提供RT增强所需的统计参数，测量统计分支建立信道参数的边际分布和参数间依赖模型；具体而言，在4.60 GHz开展了无人机（UAV）宽带信道测量活动，所提多径估计方法估算出被测多径的复幅度、时延和多普勒频移。为弥合RT预测与实测间的差距，RT增强分支将RT多径组织为视距（LoS）、视距尾（LoS-tail）和非视距（NLoS）分量，生成额外的短时延LoS-tail路径，并在保留RT总接收功率的前提下，根据测量得到的统计数据重新分配分量和路径功率。验证结果表明，所提框架将路径损耗均方根误差（RMSE）从5.45 dB降至4.35 dB；相较于校准后的RT，其均方根时延扩展和归一化多普勒扩展的RMSE分别降低53.03和26.48（注：原文未明确单位，按原文保留数值）。该框架为6G空天地一体化数字孪生研究提供了一种位置特定信道建模方法。
英文摘要
Site-specific channel models are essential for wireless digital twins of 6G space--air--ground communication systems. However, 3D maps are difficult to obtain over wide areas, which limits large-area site-specific channel modeling. To address this issue, this paper proposes a remote-sensing-based augmented ray-tracing channel modeling framework. The framework comprises a deterministic RT branch, a measurement-statistical branch, and an RT augmentation branch. To overcome the difficulty of acquiring large-area 3D maps, the deterministic RT branch reconstructs a 3D RT scene from satellite remote-sensing imagery and calibrates its electromagnetic material parameters using measured path loss. To provide the statistical parameters required for RT augmentation, the measurement-statistical branch establishes the marginal distributions and interparameter dependence models of the channel parameters. Specifically, a wideband UAV channel measurement campaign is conducted at 4.60 GHz, and a proposed multipath estimation method estimates the complex amplitudes, delays, and Doppler shifts of the measured multipath. To bridge the gap between RT predictions and measurements, the RT augmentation branch organizes the RT multipath into LoS, LoS-tail, and NLoS components, generates additional short-delay LoS-tail paths, and reallocates the component and path powers according to the measurement-derived statistics while preserving the total RT received power. The validation results show that the proposed framework reduces the path loss RMSE from 5.45 to 4.35 dB and, relative to calibrated RT, decreases the RMS delay spread and normalized Doppler spread RMSEs by 53.03 and 26.48, respectively. The proposed framework provides a site-specific channel modeling approach for 6G space--air--ground digital-twin studies.
Comments17 pages, 23 figures, 4 tables
