Methodologies for path loss prediction in LTE-1.8 GHz networks using neuro-fuzzy and ANN

The goal of this paper is to predict the propagation loss of 4G signals by means of a static empirical approach, which lists the data obtained through a measurement campaign conducted at Castanhal City, located in the state of Pará (northern Brazil), which it was obtained through the power of the LTE signal transmitted at a frequency of 1.8 GHz. With the use of computational intelligence Artificial Neural Networks (ANN) and Neuro-Fuzzy System (NFS) techniques. The input parameters was distance between Tx and Rx, height and gain of the transmitting antenna in order to predict the path loss on a specific point. And thus to compare the Root Mean Square Error (RMSE) rate obtained with some existing classical path loss models in the literature: Cost 231-Hata, Ikegami-Walfisch and ITU-R P.1546-4.