Optimization of the propagation model choice by measuring field and artificial intelligence

  • Alberto Leonardo Penteado Botelho Léo do Rosário Botelho Junior

Abstract

The propagation model to be chosen in the design of a digital terrestrial broadcast station is a critical point for predicting the coverage area. There are several models, with specific characteristics that may be better than others in certain situations. This paper presents a study of the choice of propagation model, through the use of artificial intelligence (AI). A brief review of the most widely used propagation models in the literature, field measurements and simulations by the Progira coverage prediction software, which operates on the ArcGIS geoprocessing platform are presented. Using the propagation model criterion that presents the smallest error between the field measurement and the software simulation, an AI method of classification learning was developed. The objective of this method can choose, with the smallest error, the best propagation model in the entire study area, not restricted to the Sites measured in the field.

Published
May 15, 2019
How to Cite
BOTELHO, Alberto Leonardo Penteado. Optimization of the propagation model choice by measuring field and artificial intelligence. SET INTERNATIONAL JOURNAL OF BROADCAST ENGINEERING, [S.l.], v. 4, p. 9, may 2019. ISSN 2446-9432. Available at: <http://revistaeletronica.set.org.br/index.php?journal=ijbe&page=article&op=view&path%5B%5D=155>. Date accessed: 25 aug. 2019.
Section
Transmission, propagation, reception, re-distribution of broadcast signals AM, F