[1] The novel and practical modified genetic algorithm (MGA)-autoregressive integrated moving average (ARIMA) model for forecasting real-time dynamic rain-induced attenuation has been established by combining genetic algorithm ideas with the ARIMA model. It is proved that due to the introduction of MGA into the ARIMA(1,1,7) model, the MGA-ARIMA model has the potential to be conveniently applied in every country or area by creating a parameter database used by the ARIMA (1,1,7) model. The parameter database is given in this paper based on attenuation data measured in Xi'an, China. The methods to create the parameter databases in other countries or areas are offered, too. Based on the experimental results, the MGA-ARIMA model has been proved practical for forecasting dynamic rain-induced attenuation in real time. The novel model given in this paper is significant for developing adaptive fade mitigation technologies at millimeter wave bands.

In the paper, the ARIMA model is used for analyzing and forecasting the short-term dynamic characteristics of raininduced attenuation. In this way, an ARIMA (Autoregressive Integrated Moving Average) model to forecast real-time dynamic rain-induced attenuation is established. The paper also analyses, evaluates and does the spectrum inspection to the model as well as the forecasting results. I. INTRODUCTIONOne principal technical difficulty for MMW technology is to evaluate and mitigate the attenuation induced by troposphere propagation environments, like rain, cloud, snow, fog, sand and storm. Among those, rain-induced attenuation is the severest attenuation. Many long-term statistical characteristics of rain-induced attenuation have been proposed.The long-term statistical characteristics can't reflect the influences of rain to the communication system completely, so some adaptive anti-fading technologies are developed. In order to evaluate the required speed of adaptive anti-fading system to track the attenuation changes, the adaptive antifading technology needs to study the real-time dynamic behaviour of rain-induced attenuation. Therefore, studying and forecasting the real-time dynamic characteristics of raininduced attenuation is very important for the development of adaptive anti-fading technology [1]- [3].In recent years, researchers have put forward many shortterm prediction models of rain-induced attenuation [1]- [5].The key to set up this kind of models is to gain the statistical measured data of rain-induced attenuation. An ARIMA forecasting model is established based on simulated data. The data are simulated according to on the probability density distribution function, which the real-time dynamic data of rain-induced attenuation are followed. The paper also analyses, evaluates and does the spectrum inspection to the model as well as the results of the forecast.

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