Novel AntiNoiseUncertainty Spectrum Sensing Method Using the Component of Cramervon Mises

The performance of the existing spectrum sensing algorithm based on goodness of fit (GoF) test is excellent, however, is sensitive to the noise uncertainty. In this paper, the first component of Cramervon Mises, which is insensitive to variances shift, is used as test statistics in GOF test and a fast spectrum sensing based on component of Cramervon Mises is proposed; the probability density functions(PDF) of test statistic under free of frequency channel is derived and then theoretical threshold is given.Finally, with comparison to conventional GOF algorithm, the proposed method is free of noise uncertainty with lower complexity. Simulation results show the effectiveness of the proposed method.