Development of channel model to predict rain rate and attenuation for FMT applications

Abstract

A new model is presented to predict rain rate serially during a rain event at a tropical location. The model is based on the Gaussian distribution of the conditional occurrence of rain rate with a particular value of the rain rate occurring before. The mean and standard deviation of the distribution are modeled with the measured data. The rain rate at a particular time instant is predicted from the knowledge of previous samples. The predictor has tested well with a mean error within 10% for rain rates above 20 mm/hr for 10 sec time interval. The same technique is also successfully applied to predict time series of rain attenuation. The practical application of channel predictor is also shown in this paper for FMT simulation.