The DMT Power Line Channel Sparse Bayesian Regression Estimation Based on Communication System

Yi Pei Huang; Ya Jun Han; Bao Fan Chen

doi:10.4028/www.scientific.net/AMR.960-961.1308

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 960-961The DMT Power Line Channel Sparse Bayesian...

The DMT Power Line Channel Sparse Bayesian Regression Estimation Based on Communication System

Abstract:

This paper introduces the power line communications channel estimation method based on sparse Bayesian regression, it is through the use of Bayesian learning framework that provides a sparse model in the presence of noise accurate channel estimation model. Improved channel estimation using the power line for the system to consider the frequency domain equalization (FREQ) transmitter and receiver, the bit error rate and comparing the two methods for generating various channel estimation techniques, and (BER) performance curves simulation the results show that the performance of the method is better than the previous method of least squares technique.

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Periodical:

Advanced Materials Research (Volumes 960-961)

Pages:

1308-1311

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.960-961.1308

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Online since:

June 2014

Authors:

Yi Pei Huang, Ya Jun Han, Bao Fan Chen

Keywords:

Channel Estimation, DMT, Regression Analysis, RVM, SBL

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References

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