International Journal of Engineering and Technology

TPredicting the behavior of the primary user in cognitive radio networks enables significant reduction of the interference level caused by the secondary user during his change of channel. Therefore, the purpose of this article is to present a comparative evaluation of the models for time series: AR, MA and ARMA that can predict the behavior of the primary user as well as the spectral opportunities for cognitive radio networks in the GSM frequency band. The performance of the three models for time series will be contrasted with a purely reactive model (non-predictive) under two scenarios, two traffic levels and six evaluation metrics. The results obtained show that the moving average model has the best performance in general. However, it is not the best in all four testing scenarios.