Adaptive equalization of a communication channel in a non-Gaussian noise environment

The subject of adaptive filters constitutes an important part of statistical signal processing. Adaptive filters are successfully applied in such diverse fields as communications, control, radar, sonar, and biomedical engineering. In this paper we study the use of the particle filter for adaptive eq...

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Published inThe 3rd International IEEE-NEWCAS Conference, 19-22 June, 2005, Quebec City, Canada : conference proceedings = Troisième conférence internationale IEEE-NEWCAS, 19 au 21 juin 2005, Ville de Québec, Canada : compte rendu de conférence : NEWCAS 2005 pp. 395 - 398
Main Authors Kamel, H., Badawy, W.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Adaptive equalizers
Adaptive filters
Adaptive signal processing
Biomedical signal processing
Communication channels
Communication system control
Particle filters
Radar signal processing
Signal processing algorithms
Working environment noise
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Summary:The subject of adaptive filters constitutes an important part of statistical signal processing. Adaptive filters are successfully applied in such diverse fields as communications, control, radar, sonar, and biomedical engineering. In this paper we study the use of the particle filter for adaptive equalization of a linear dispersive channel that produces (unknown) distortion. The performance of the adaptive filter is compared to that of least-mean-square (LMS) and recursive-least-square (RLS) algorithms. The main advantage of the particle filter when compared to other algorithms is its robustness when dealing with non-Gaussian noise. The particle filter showed better performance in convergence speed and root-mean-square (rms) error in case of low signal-to-noise ratio.
ISBN:9780780389342
0780389344
DOI:10.1109/NEWCAS.2005.1496705