LTE's peak data rate for downlink and uplink can reach 326.4 and 86.4 Mbps, respectively [2], while LTE-A significantly enhances these specifications: it increases peak rates, achieving 3 Gbps for downlink and 1.5 Gbps for uplink; for such, it requires a bandwidth up to 100 MHz [3].A Hybrid Path Loss Prediction Model based on Artificial Neural Networks using Empirical Models for LTE And LTE-A at 800 MHz and 2600 MHz Bruno J. Cavalcanti, Gustavo A. CavalcanteFederal Institute of Education, Science and Technology Paraíba Campus Campina Grande, Brazil, bruno.cavalcanti@ifpb.edu.br, gustavo.cavalcante@ifpb.edu.br LaércioFederal University of Rio Grande do Norte, Caixa Postal 1655, CEP: 59078-970, Natal, RN, Brazil, laercio@ct.ufrn.br, gabrielmocan@bct.ect.ufrn.br, marcelo_medeiros_5@yahoo.com.br, adaildo@ct.ufrn.br, Journal of Microwaves, Optoelectronics and Electromagnetic Applications, Vol. 16, No. 3, September 2017 Path loss models are important for predicting coverage area, interference analysis, frequency assignments, and cell parameters -basic components for the network-planning process in the project of a mobile communications system [4]. Understanding the radio channel for the network deployment is utmost, being the modelling of the radio channel using the most appropriate path loss model, an essential factor.Propagation models can be classified [5,6] as: deterministic, empirical, and physical/statistical. The first ones can be considered the most accurate method. They are based on the behavior of radio waves propagated in space, calculating propagation losses mathematically, based on theoretical formulation.For such, accurate information is necessary, not only about buildings and terrains, but also about reflection and diffraction coefficients of the surfaces which are in the propagation path.Meanwhile, empirical models do not accurately predict the radio waves comportment, depending more on field strength from that specific environment to give an approximation based on measurements. Lastly, physical/statistical models combines empirical and statistic information about the environment, aiming to decrease computational cost.In order to make the communications systems more accurate -to have a more efficient planning, many efforts have been made towards the development of coverage prediction simulation methods and tools able to accurately estimate on measured data. In this sense, some techniques can help to provide more efficient simulation methods, reducing errors and providing more trustworthy results. The problem in path loss prediction between two points can be interpreted as a solution to obtain a function of several inputs and a single output, where the inputs contain information like locations of the transmitter and receiver, frequency and surrounding buildings.Thus, the prediction of path loss can be described as the transformation of an input vector containing topographical and morphological information about the environment to the desired output value [11]. Since neural networks can be effe...