Multi-parameter identification of power line communication channel model based on matching pursuit

Authors: Pei-ling Zhang, Hong-xin Zhang, Li-yu Huang, He Peng-fei

Abstract:
The over-complete atom dictionary is designed on the basis of typical multi-path transmission function of power line communication (PLC) channel, and matching pursuit (MP) algorithm is used for multiparameter identification of the channel. First, the sampling data were obtained from the measured result of low-voltage PLC channel within the range from 300 kHz to 6000 kHz, which help us to develop a model for the PLC channel. Then, in order to reduce the computation complexity of MP algorithm to identify the multi-parameter of PLC, genetic algorithm (GA) is applied to effectively search for the best atom at each step of MP in the dictionary of atoms. From the multi-parameter identification result with three or four paths channel models, it demonstrates that the combined algorithm based on MP and GA can acquire more evaluation precision of PLC channel than that of GA and particle swarm optimization (PSO) algorithm respectively. Meanwhile,the more numbers of channel paths in the process of multi-parameter identification, the better will be the curve fitting result compared to the experiment. The experimental results have validated the efficiency of the combined MP–GA algorithm that proposed in this paper.

Keywords:
Low-voltage power line communication
Matching pursuit (MP)
Genetic algorithm (GA)
Parameter identification
Particle swarm optimization (PSO)

Published in: AEÜ-International Journal of Electronics and Communications (Volume 67, Issue 8, August  2013)

Publisher: Elsevier

ISSN Information: 1434-8411

Multi-parameter identification of power line communication channel model based on matching pursuit

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