Radioelectric spectrum occupancy forecast has proven useful for the design of wireless systems able to harness spectrum opportunities like cognitive radio. This paper proposes the development of a model that identifies propagation losses and spectrum opportunities in a channel of a mobile cellular network for an urban environment using received signal power forecast. The proposed model integrates the Hata-Okumura (H-O) large-scale propagation model with a wavelet neural model. The model results, obtained through simulations, show that the wavelet neural model forecasts with a high degree of precision, which is consistent with the observed behavior in experiments carried out in wireless systems of this type
