Traffic Prediction Method for GEO Satellites Combining ARIMA Model and Grey Model

An accurate traffic prediction on various service is of great importance to the channel resource management of geostationary earth orbit (GEO) satellites. Therefore, a traffic prediction method for GEO satellites combining autoregressive integrated moving average (ARIMA) model and grey model is proposed. First, the traffic prediction methods based on ARIMA model and grey model are introduced respectively. Second, a combined model is given, in which according to the results of the historical prediction of ARIMA model and grey model, those two models are combined with different weights. Third, the combined model is applied to a multi-service access and the access probability of each kind of service is calculated based on the prediction results. Finally, the simulation experiments indicate that the combined model has better prediction stability and higher average prediction accuracy than either of the separated models. Moreover, the proposed access strategy based on the combined model performs better than other similar strategies.