Proposal on rain attenuation prediction method using convolutional neural network

被引：0
|
作者：
Komatsuya, Yuji [1 ]
Imai, Tetsuro [1 ]
Hirose, Miyuki [2 ]
机构：
[1] Tokyo Denki Univ, Dept Informat & Commun Engn, Adachi Ku, Tokyo 1208551, Japan
[2] Kyushu Inst Technol, Dept Elect Engn & Elect, Tobata Ku, Kitakyushu Shi, Fukuoka 8048550, Japan
来源：
IEICE COMMUNICATIONS EXPRESS | 2024年 / 13卷 / 06期
关键词：
rain attenuation; convolutional neural network; deep learning;
D O I：
10.23919/comex.2024SPL0015
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Recently, the practical application of HAPS (High Altitude Platform Station) as the next -generation communication platform is studied actively. HAPS employs adaptive rain attenuation countermeasure techniques such as site diversity methods, therefore it is ideal to predict rain attenuation on the path in real time. We proposed real-time rain attenuation prediction method by convolutional neural network that inputs image of rainfall rate and path distance. Result showed that prediction accuracy of our proposed method is better than a method using conventional formulas.
引用
收藏
页码：181 / 184
页数：4
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