Nonparametric Multicycle Spectrum Sensing Method by Segmented Data Processing for Cognitive Radio

Wang, Jun; Huang, Jiwei; Fan, Min; Wang, Hongjun

doi:10.1007/s00034-013-9628-x

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…Currently, there are several types of spectrum sensing methods [1,2], such as energy detection methods [3], multiple cumulants methods [4], cyclostationarity methods [5,6], and autocorrelation methods [7][8][9][10]. Energy detection methods are subject to the influence of noise uncertainty and lead to SNR wall phenomena.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sensing Based on Nonparametric Autocorrelation in Wireless Communication Systems under Alpha Stable Noise

Chen

Wang

Lin

et al. 2016

Mobile Information Systems

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Cognitive radio is regarded as a core technology to support wireless information systems. Spectrum sensing is one of the key steps to achieve cognitive radio technology. To address this problem in the presence of Alpha stable noise in wireless communication systems, we propose a nonparametric autocorrelation method, which takes advantages of the characteristics of signal autocorrelation and noise nonstationarity. The autocorrelated signal is distinguished from Alpha stable noise. As a result, the proposed method is immune from noise uncertainty. Simulation results show the validity of the proposed method under Alpha stable noise, for example, impulsive noise in wireless information systems.

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