Short-Term Rainfall Attenuation Prediction for Wireless Communication

被引：0

作者：

Li, Tansheng ^{[1
]}

Suzuki, Kazuya ^{[1
]}

Nishioka, Jun ^{[1
]}

Mizukoshi, Yasuhiro ^{[1
]}

Hasegawa, Yohei ^{[1
]}

机构：

[1] NEC Corp Ltd, Cloud Syst Labs, Kawasaki, Kanagawa, Japan

来源：

2015 IEEE 16TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT) | 2015年

关键词：

Rain attenuation; Radio attenuation prediction; K-nearest neighbor; Artificial neural network;

D O I：

暂无

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：

This paper describes a method for predicting short-tenn rain attenuation for ground wire less communications. We propose machine learning methods using the k-nearest neighbour (KNN) and artificial neural network (ANN). We used a time-series of link attenuation calculated from a set of high-precision rainfall radar maps as training data. These two methods were verified with data from a different rainfall event. The results show that the two methods provide rainfall attenuation for wireless communications with sufficient accuracy.

引用

页码：615 / 619

页数：5

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