Short-term rainfall attenuation prediction for wireless communication

This paper describes a method for predicting short-term rain attenuation for ground wireless 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.