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Diffusion Maximum Correntropy Criterion Based Robust Spectrum Sensing in Non-Gaussian Noise Environments

by Xiguang Xu 1,*, Hua Qu 1,2, Jihong Zhao 1,2,3, Feiyu Yan 1 and Weihua Wang 1
1
School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
2
Suzhou Caiyun Network Technologies Co., Ltd., Suzou 215123, China
3
School of Telecommunication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(4), 246; https://doi.org/10.3390/e20040246
Received: 21 March 2018 / Revised: 29 March 2018 / Accepted: 30 March 2018 / Published: 3 April 2018
Spectrum sensing is the most important task in cognitive radio (CR). In this paper, a new robust distributed spectrum sensing approach, called diffusion maximum correntropy criterion (DMCC)-based robust spectrum sensing, is proposed for CR in the presence of non-Gaussian noise or impulsive noise. The proposed distributed scheme, which does not need any central processing unit, is characterized by an adaptive diffusion model. The maximum correntropy criterion, which is insensitive to impulsive interference, is introduced to deal with the effect of non-Gaussian noise. Simulation results show that the DMCC-based spectrum sensing algorithm has an excellent robust property with respect to non-Gaussian noise. It is also observed that the new method displays a considerably better detection performance than its predecessor (i.e., diffusion least mean square (DLMS)) in impulsive noise. Moreover, the mean and variance convergence analysis of the proposed algorithm are also carried out. View Full-Text
Keywords: robust spectrum sensing; maximum correntropy criterion (MCC); diffusion scheme; non-Gaussian noise; cognitive radio networks robust spectrum sensing; maximum correntropy criterion (MCC); diffusion scheme; non-Gaussian noise; cognitive radio networks
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Xu, X.; Qu, H.; Zhao, J.; Yan, F.; Wang, W. Diffusion Maximum Correntropy Criterion Based Robust Spectrum Sensing in Non-Gaussian Noise Environments. Entropy 2018, 20, 246.

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