ABSTRACT: Rain attenuation is one of the important impairments that affects RF signal at Ku and Ka band frequencies. The forecasting of the rainfall and rain attenuation plays a vital role in the fields of communications, agriculture, military services, etc. The paper shows the results of experimentally measured rain attenuation of earthspace link in Kondapalli operating at 11.07 GHz. Auto-Regressive Integrated Moving Average (ARIMA) model is used to predict and generate the time series values for rain attenuation over a long period. The predicted values obtained using ARIMA model is compared with measured values of rain attenuation for different set of parameters of the model and analysis is done in terms of prediction error which could be used for the validation of the method. Keywords: Rain attenuation, ARIMA model, ITU-R model, Time series, ccdf. I.INTRODUCTION Satellite communication systems operating at and above Ku band frequencies must overcome the problem of propagation impairments which includes fading due to rain, clouds, snow, gases, and amplitude scintillations, for obtaining the required performance. Among all impairments, rain is the predominant factor that affects the signal most and the mechanism involved is absorption and scattering of the signal energy. The estimation of attenuation on the slant path to a satellite is essential to the process of establishing a margin in the link budget that ensures the required availability of the link is met Number of models have been proposed and developed for prediction and generation of time series data of rain attenuation based on auto-regressive moving average processes A. ITU-R Rain Attenuation Prediction Model Rain attenuation is the significant propagation impairment at Ku and Ka band frequencies. In ITU-R rain attenuation prediction model, the rain intensity at 0.01% probability level is the rain related input to the model. The model has been derived on the basis of the log-normal distribution where both point rain intensity and path attenuation distributions conform to the log-normal distribution. The model is applicable across the frequency range 4 to 35 GHz and percentage probability range 0.001% to 10%. The input parameters to this model are: point rainfall rate for 0.01% of an average year (in mm/hr) with 1-min integration time, altitude of the location above mean sea level (in Km), elevation angle of the receiver (in degrees)