摘要
基于拟合优度检验的频谱感知算法检测性能较好但易受到噪声不确定度的影响。该文利用对方差偏离不敏感的Cramer-von Mises(CM)统计量第一分量,设置了新的检验统计量,并推导了频谱空闲时检验统计量的概率密度函数和判决门限,从而提出了利用CM分量的频谱感知算法。在减小拟合优度检验(Go F)中的CM算法复杂度的同时,克服了噪声不确定度对CM算法性能的影响。仿真结果表明所提算法有效解决了噪声不确定度对算法的影响。
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 Mi- ses 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.
出处
《信号处理》
CSCD
北大核心
2016年第8期945-950,共6页
Journal of Signal Processing
基金
国家自然科学基金资助项目(61271276
61301091)
国家863项目(014AA01A705)
关键词
认知无线电
频谱感知
拟合优度检验
CM统计量分量
cognitive radio
spectrum sensing
goodness of fit test
component of Cramer-von Mises
