摘要
基于信息论准则的宽带频谱感知方法由于很好地克服了噪声不确定性问题而获得了广泛研究.但该类算法的推导需要假定接收数据向量在统计上独立同分布、背景噪声须为高斯白噪声,且其实现复杂度较高.针对这些不足,本文提出一种基于秩准则的宽带盲频谱感知算法.该算法将接收信号的取样协方差矩阵分解成秩为q的'理想'矩阵和'扰动'矩阵之和,利用秩准则函数寻求q值的最优解,然后根据该最优值确定被占用信道的个数及位置.新方法无需依赖噪声功率、信道及主用户信号的统计特征参与感知判决过程,具有广泛的适用性;同时相对于基于信息论准则的宽带频谱感知方法,新方法具有感知判决量表达式简单、计算复杂度低的优点,同时新方法在色噪声场景下表现出优良的感知性能.仿真结果表明了新方法的有效性.
Wideband spectrum sensing methods based on information theory criterion (ITC) solve the problem of noise uncertainty, so it has been extensively studied. But deducing the sensing decision rule u- sing the information theory needs to assume that the received data vectors are statistical independent, and that the noise is Gaussian white noise. Meanwhile, this kind of methods possesses high implementation complexity. To overcome these limitations, this paper presented a new wideband blind spectrum sensing method based on the rank criterion. This proposed method firstly divides the sample covariance matrix of received signal into the "ideal" matrix having rank of q and the "disturbance" matrix, the rank criterion function is then used to search the optimal q value, which is used to determine the numbers and the locations of the occupied channels. The new method requires no a priori knowledge about the noise power, the statistical characteristics of the wireless channel and the primary user signal. Compared with the existing ITC based wideband sensing methods, the proposed method has a more concise decision expression and then has lower computational complexity. In addition, the new method shows excellent performance in colored noise sensing scenarios. Simulation results verified the effectiveness of the proposed method.
出处
《湖南大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2016年第2期150-156,共7页
Journal of Hunan University:Natural Sciences
基金
国家自然科学基金资助项目(61362018
61102039
61102089)
湖南省自然科学基金资助项目(14JJ7029)
湖南省教育厅优秀青年项目(13B093)
湖南省科技计划项目(2015GK3032)
中央高校基本科研业务费专项资金资助项目
江苏省博士后科研资助计划项目(1402041B)~~
关键词
认知无线电
宽带盲频谱感知
秩准则
信号子空间
噪声子空间
cognitive radio
wideband blind spectrum sensing
rank criterion
signal subspace
noise subspace