DocumentCode :
2582570
Title :
HOS-based impulsive noise detection technique for power line communication systems
Author :
Oliveira, Thiago Rodrigues ; De Sá, Pedro Correia ; de Paula Barbosa, Sérgio Luis ; Ribeiro, Moises Vidal ; Marques, Cristiano Augusto Gomes
Author_Institution :
Telecommun. & Signal Process. Lab., Fed. Univ. of Juiz de Fora, Juiz de Fora, Brazil
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
125
Lastpage :
130
Abstract :
This paper discusses a detection technique for impulsive noise in power line cables. Essentially, a reduced set of features (signature vector), which is selectively extracted from the power line signal feeds a detection technique. The features are higher-order statistics and the Fisher´s discriminant ratio is the selection technique. The designed detectors are a multilayer perceptron neural network and a Bayes implemented according the maximum likelihood criterium. Simulation results indicate that improved performance can be attained if multilayer perceptron neural network is considered as a nonlinear detector. Also, the results reveal that higher-order statistics is a very interesting technique to extract a reduced and representative signature vector of impulsive noise.
Keywords :
carrier transmission on power lines; higher order statistics; impulse noise; maximum likelihood detection; multilayer perceptrons; telecommunication computing; Bayes method; Fisher discriminant ratio; HOS-based impulsive noise detection technique; higher order statistics; maximum likelihood criterium; multilayer perceptron neural network; nonlinear detector; power line cables; power line communication systems; Communication cables; Detectors; Feeds; Higher order statistics; Maximum likelihood detection; Multi-layer neural network; Multilayer perceptrons; Neural networks; Power line communications; Signal detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Line Communications and Its Applications (ISPLC), 2010 IEEE International Symposium on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-5009-1
Electronic_ISBN :
978-1-4244-5010-7
Type :
conf
DOI :
10.1109/ISPLC.2010.5479884
Filename :
5479884
Link To Document :
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