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,Adaildo G D’Assunção,Marcelo M.M De Oliveira,Gabriel M Cantanhede,Gustavo A Cavalcante,Laércio M De Mendonça

doi:10.1590/2179-10742017v16i3925

Abstract

This article presents the development and analysis of a hybrid, error correction-based, neural network to predict the path loss for suburban areas at 800 MHz and 2600 MHz, obtained by combining empirical propagation models, ECC-33, Ericsson 9999, Okumura Hata, and 3GPP's TR 36.942, with a backpropagation Artificial Neural Network (ANN). The network performance was tested along with two optimization techniques - Genetic Algorithm (GA) and Least Mean Square (LMS). Results were compared with data obtained by measurements performed in the vicinity of the Federal University of Rio Grande do Norte (UFRN), in the city of Natal, Brazil. In the end, the hybrid neural network presented the best results, indicating greater similarity with experimental data. The results developed in this research will help to achieve better signal estimation, reducing errors in planning and implementation of LTE and LTE-A systems.

Highlights

IntroductionTo reach the conditions for fulfilling the Long Term Evolution (LTE) and LTE Advanced (LTE-A) requisites [2], an efficient and accurate network planning during the preliminary system deployment is necessary, where accurate propagation characteristics of the environment should be known
ANALYSIS OF RESULTS The performance of the HNN model, along with the Simple Neural-Network (SNN) was obtained by comparing Root Mean Squared Error (RMSE) and applying the Wilcoxon rank-sum test
From the beginning of the course of measurements in route 1, up to 500 meters, ECC model predictions, which obtained a RMSE of 10.33 dB, were positioned far from most measured points

Summary

Introduction

To reach the conditions for fulfilling the LTE and LTE-A requisites [2], an efficient and accurate network planning during the preliminary system deployment is necessary, where accurate propagation characteristics of the environment should be known. 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. 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

Objectives

Results

Conclusion