Abstract
The received signal at the ground station for a satellite link is
affected by the stochastic nature of atmospheric channel. Adverse
weather events such as rain not only attenuates the signal but also
increases noise, scintillation fading and multipath effects that cause
rapid variations in the received signal at the ground station. In order
to analyze the stochastic effects of weather phenomenon on the link
performance on short-term basis, both the slowly changing signal
attenuation and the rapid variations caused by channel at the receiver
has to be studied. In this work, we first analyze the short-term effects
of rain on the statistical and spectral properties of fast varying
signal component affecting the link performance. Following this, we
model such parameters using several features extracted from the slowly
varying signal component with support vector machine (SVM). We show an
interesting result that the statistical and spectral properties of fast
varying signal under rainy channel conditions can be predicted with very
high accuracy using SVM. The prediction of such parameters will lead to
receiver design adaptive to varying channel dynamics affecting the link
performance under rainy conditions.