A blind detector for Rayleigh flat-fading channels with non-Gaussian interference via the particle learning algorithm

Authors:  Wenwei Ying, Yuzhong Jiang, Yueliang Liu, Puxuan Li

Abstract:
A blind particle learning detector (BPLD)is developed for signal detection in Rayleigh flat-fading channels with non-Gaussian interference. The parameters of the fading channel model and the noise model are all unknown. The impulsive noise is modeled as a mixture of Gaussian distributions, which is capable of representing a broad class of non-Gaussian noise. The particle learning algorithm is employed to simultaneously estimate signal and parameters of the fading channel model and the noise model. The delay weight method is used to improve the performance. Simulation results show that the performance of the BPLD proposed can follow closely the performance of the detector with known parameters of the fading channel model and the noise model.

Keywords:
Rayleigh flat-fading channel
Non-Gaussian noise
Blind signal detection
Particle learning

Published in: AEÜ-International Journal of Electronics and Communications (Volume 67, Issue 12, December  2013)

Publisher: Elsevier

ISSN Information: 1434-8411

A blind detector for Rayleigh flat-fading channels with non-Gaussian interference via the particle learning algorithm

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