An accurate neural network approach in modeling an UWB channel in an underground mine

Author

Zaarour, Nour ; Kandil, Nahi ; Hakem, N.

Author_Institution

Lab. de Rech. Telebec en Commun. Souterraines, Univ. du Quebec en Abitibi-Temiscamingue, Val-d´Or, QC, Canada

fYear

2013

fDate

7-13 July 2013

Firstpage

1608

Lastpage

1609

Abstract

Modeling an ultra-wideband (UWB) channel is an important and challenging task in wireless communications. Modeling a channel in an underground mine environment presents additional challenges and difficulties. Many researchers and techniques have treated this subject. In this paper we will present a new approach in modeling the channel in an underground mine by using artificial neural networks (ANN) of type RBF (Radial basis function) focusing on the change of the path loss attenuation as a function of distance and frequency. Results presented show the accuracy of this method.

Keywords

neural nets; radio networks; telecommunication computing; ultra wideband communication; wireless channels; ANN; RBF; UWB channel; artificial neural networks; neural network approach; radial basis function; ultra wideband channel; underground mine environment; wireless communications; Accuracy; Artificial neural networks; Bandwidth; Biological neural networks; Frequency measurement; Loss measurement; RBFN model; UWB channel modeling; mine environment; path loss; testing phase; training phase;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium (APSURSI), 2013 IEEE

Conference_Location

Orlando, FL

ISSN

1522-3965

Print_ISBN

978-1-4673-5315-1

Type

conf

DOI

10.1109/APS.2013.6711463

Filename

6711463