基于非负矩阵分解的频谱感知技术研究  

Research on Spectrum Sensing in Cognitive Radios Based on Nonnegative Matrix Factorization

作　　者：张梦阳[1] 孙学斌[1] 李斌[1] 周正[1] 张梦阳 孙学斌[1] 李斌[1] 周正[1] 

机构地区：[1]北京邮电大学信息与通信工程学院,北京100876

出　　处：《无线电工程》2013年第11期1-3,7,共4页Radio Engineering

基　　金：中央高校基本科研业务费专项资金资助(2012RC0103);国家自然科学基金资助(60902046;60972079;61271180);国家科技重大专项资助(2011ZX03005-002;2012ZX03001022)

摘　　要：为了提高认知无线电系统中低信噪比条件下的频谱感知性能,提出了基于非负矩阵分解的频谱感知方法。在无需知道被感知信号的先验信息的条件下,将原始信号进行短时傅里叶变换后,利用非负矩阵分解的噪声与信号之间的特征矩阵存在的差异性,将特征矩阵作为检测统计量进行频谱感知。仿真结果表明,基于非负矩阵分解的频谱感知方法在低信噪比条件下,具有较传统的能量检测方法与循环平稳检测方法更优的感知性能。To improve the performance of spectrum sensing of cognitive radio system in low SNR,a spectrum sensing based on nonnegative matrix factorization is proposed. After transforming the original signal by STFT,by using the differences between signal and noise of basis matrices,the basis matrices can be used as test statistics to perform the spectrum sensing,without knowing the prior information of sensed signal. The simulation results show the proposed method has better performance compared with the traditional methods of Energy Detection and Cyclostationary Feature Detection in low SNR.

关 键 词：认知无线电 频谱感知 非负矩阵分解 特征矩阵 

分 类 号：TN911.7[电子电信—通信与信息系统]