Prediction of slant path rain attenuation based on artificial neural network

Hongwei Yang Hongwei Yang,Chen He Chen He,Wentao Song Wentao Song,Hongwen Zhu Hongwen Zhu

doi:10.1109/iscas.2000.857049

Hongwei Yang Hongwei Yang, Chen He Chen He + Show 2 more

https://doi.org/10.1109/iscas.2000.857049

Copy DOI

Export

Save

Cite

Abstract
Full-Text
Similar Papers

Abstract

Listen

Rain attenuation is predicted in various compositions of the frequency, the elevation angle, the rain-fall rate, the percent of the time, the polarization angle, the altitude of the earth station and the latitude of the earth station by means of artificial neural network in this paper. The rain attenuation prediction model of millimeter waves based on an artificial neural network is proposed for the first time, and the predicted results are compared with the CCIR recommendation model. The results show that the artificial neural network can obtain the nonlinear relation of the rain attenuation and the other factors that affect millimeter wave propagation attenuation and improve the accuracy of rain attenuation prediction with a 1.3 dB increase on average. It is a useful approach to construct the rain attenuation prediction model of millimeter wave with artificial neural network.

Full Text