Ray Tracing Based Path Loss Modeling for UAV-to-Ground mmWave Channels in Campus Scenario

Yao, Mengtian; Chen, Xiaomin; Wang, Jian; Hua, Boyu; Zhong, Weizhi; Zhu, Qiuming; Yang, Jingwen

doi:10.1007/978-3-030-66785-6_50

Cited by 3 publications

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Traditional close-in (CI) model are only applicable for land mobile communications, and most of them do not consider the antenna height factor [25]. To address this problem, the UAV technique is used for spectrum mapping in this paper, in which UAV heights are considered when calculating the path losses [26].…”

Section: Propagation Channel Modelmentioning

confidence: 99%

UAV-Assisted Three-Dimensional Spectrum Mapping Driven by Spectrum Data and Channel Model

Zhu

Ding

et al. 2021

Symmetry

Self Cite

View full text Add to dashboard Cite

As the number of civil aerial vehicles increase explosively, spectrum scarcity and security become an increasingly challenge in both the airspace and terrestrial space. To address this difficulty, this paper presents an unmanned aerial vehicle-assisted (UAV-assisted) spectrum mapping system and a spectrum data reconstruction algorithm driven by spectrum data and channel model are proposed. The reconstruction algorithm, which includes a model-driven spectrum data inference method and a spectrum data completion method with uniformity decision mechanism, can reconstruct limited and incomplete spectrum data to a three-dimensional (3D) spectrum map. As a result, spectrum scarcity and security can be achieved. Spectrum mapping is a symmetry-based digital twin technology. By employing an uniformity decision mechanism, the proposed completion method can effectively interpolate spatial data even when the collected data are unevenly distributed. The effectiveness of the proposed mapping scheme is evaluated by comparing its results with the ray-tracing simulated data of the campus scenario. Simulation results show that the proposed reconstruction algorithm outperforms the classical inverse distance weighted (IDW) interpolation method and the tensor completion method by about 12.5% and 92.3%, respectively, in terms of reconstruction accuracy when the collected spectrum data are regularly missing, unevenly distributed and limited.

show abstract

Section: Propagation Channel Modelmentioning

confidence: 99%