Study of Prediction of Propagation Loss Models in LTE and Advanced-LTE Communications Systems Using Artificial Intelligence Techniques
Propagation Models, Neural Networks, Genetic Algorithms, Long Term Evolution (LTE), Long Term Evolution Advanced (LTE-A), Measurement Campaign.
In this thesis is made a careful analysis of the main propagation loss models for Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A) communication networks using artificial intelligence techniques such as neural networks and genetic algorithms in environments urban, suburban and rural areas of mid-sized cities in northeastern Brazil. The methodological procedures performed initially consisted of simulation of the Hata and Ericsson 9999 models, along with their optimized versions. They were then compared with measured values obtained from a measurement campaign. The results obtained through simulations, optimizations and measurements, showed good metric agreement. The main contribution of this thesis is that by employing these improved propagation models, we can estimate propagating signals closer to reality, avoiding errors in the planning and implementation of LTE and LTE-A wireless networks.