The Use of Artificial Neural Networks in the Estimation of Coverage Digital TV Signal / A Utilização de Redes Neurais Artificiais na Estimação da Cobertura do Sinal de Televisão Digital

AUTOR(ES)

Douglas Dias da Silva

DATA DE PUBLICAÇÃO

2009

RESUMO

THIS works presents information about signal intensity obtained on field and from simulations for one-seg and full-seg receptions, the city of Goiania. The values obtained from measurements were used for a comparisson among propagation models that are presented in literature, and the goal is to determine the real condition of digital TV signal in the region of Goiania. The propagation models presented are available in literature and can be implemented in digital transmission system. The studied models were Free Space model, Log-Distance model, Hata model and ITU-R P.1546-1 method, and the objective was to determine the signal intensity of digital television transmission in the city of Goiania (RAPPAPORT, 1996) (UNION, 2003). Focusing on the development of a tool for signal intensity estimation, some researches were done about neural networks theory and its applications. Perceptron and Multilayer Perceptron were the analised architectures, emphasyzing on the last one and on its supervisioned trainning through the backpropagation error algorithm (HAYKIN, 2001). The Brazilian Digital Television System was described by reference rules made by Associacao Brasileira de Normas Tecnicas, which has detailed its transmission system and reception devices (TECNICAS, 2008a) (TECNICAS, 2008h). Measurements of signal intensity for one-seg and full-seg reception methods were made on field in the region of Goiania. These measurements followed the sugestions presented by Report ITU-R BT. 2035-1 and it used a radiofrequency analyzer and a Global Positioning System (GPS). With the obtained data, the digital signal covering situation in the city of Goiania was mapped, which revealed a lower intensity level to the studied models. A tool for signal intensity estimation was developed using Artificial Neural Networks, which was trained with the dada obtained from the performed measurements. This tool was used to obtain the signal intensity for several proposed scenarios. The signal intensity estimation for the scenario that has tree density and target absence distinguished as the one that was closest to the reality of Goiania, which is a consequence of high density of trees.

ASSUNTO(S)

digital television computabilidade e modelos de computacao 1.televisão digital; 2.redes neurais artificiais (rna); 3. telecomunicações redes neurais artificiais televisão digital telecomunicações artificial neural networks, telecommunications

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