期刊名称：International Journal of Wireless & Mobile Networks
印刷版ISSN：0975-4679
电子版ISSN：0975-3834
出版年度：2014
卷号：6
期号：6
页码：57
DOI：10.5121/ijwmn.2014.6605
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In this paper, the performance assessment of five different detection techniques from spectrum sensingperspective in cognitive radio networks is proposed and implemented using the realistic implementationoriented model (R-model) with signal processing operations. The performance assessment of the differentsensing techniques in the existence of unknown or imprecisely known impulsive noise levels is done byconsidering the signal detection in cognitive radio networks under a non-parametric multisensory detectionscenario. The examination focuses on performance comparison of basic spectrum sensing mechanisms as,energy detection (ED) and cyclostationary feature detection (CSFD) along with the eigenvalue-baseddetection methods namely, Maximum-minimum eigenvalue detection (MMED), Roy’s largest Root Test(RLRT) which requires knowledge of the noise variance and Generalized Likelihood Ratio Test (GLRT)which can be implemented as a test of the largest eigenvalues vs. Maximum-likelihood estimates a noisevariance. From simulation results it is observed that the detection performance of the GLRT method isbetter than the other techniques in realistic implementation oriented model.
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