发表机构
Universitat Politècnica de Catalunya (UPC)（加泰罗尼亚理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一个FR3频段UAV基站信道知识图谱数据集，并设计可解释的高度感知衰减模型，在未见城市上达到1.93 dB误差，为FR3部署提供数据与物理基准。
AI 中文摘要
本文介绍了一个密集的上中频段（FR3）信道知识图谱（CKM）数据集，该数据集针对搭载机载基站（UxNB）的无人飞行器（UAV）设计。数据集包含来自66个城市3236个城市位置的16180个CKM样本，频率为7.125 GHz，UxNB高度可达500米。每个513x513样本存储建筑几何、视距（LOS）状态、衰减、延迟扩展、角度扩展以及可变发射机高度。作为聚焦的首个用例，我们提出了一种可解释的高度感知衰减模型。其LOS分支结合了自由空间损耗、双射线项和紧凑的基于数据的高度/距离校准。其非视距（NLOS）分支结合了COST 231-Hata基线与局部环境特定的线性校准。所提出的模型在14个未见城市的超过500个独特位置（共2590个样本）上达到了1.93 dB的整体均方根误差，其中LOS为1.74 dB，NLOS为3.54 dB。该结果为FR3 UxNB部署提供了衰减数据，并为未来FR3建模工作提供了物理锚点。
英文摘要
This paper introduces a dense upper mid-band Frequency Range (FR3) Channel Knowledge Map (CKM) dataset for Uncrewed Aerial Vehicles (UAVs) with an on-board base station (UxNB). It contains 16,180 CKM samples from 3,236 urban locations in 66 cities at 7.125 GHz and UxNB heights of up to 500 meters. Every 513x513 sample stores the building geometry, the line-of-sight (LOS) state, attenuation, delay spread, angular spread, and variable transmitter height. As a focused first use-case, we propose an interpretable height-aware attenuation model. Its LOS branch combines free-space loss, two-ray term, and compact data-based height/range calibration. Its non-LOS (NLOS) branch combines a COST 231-Hata basis with local environment-specific linear calibration. The proposed model reaches 1.93 dB overall root mean square error, with 1.74 dB in LOS and 3.54 dB in NLOS on over 500 unique locations in 14 unseen cities (2,590 samples in total). The result provides attenuation data for FR3 UxNB deployments and a physical anchor for future FR3 modeling efforts.
Comments6 pages, accepted for IEEE Globecom'26 Workshops
