摘要
在多天线感知场景中噪声不确定和信号相关现象可能同时存在,经典的基于能量检测(ED)感知性能将急剧恶化。利用多天线接收信号存在的相关特性,提出一种基于取样协方差矩阵(SCM)特征值的盲频谱感知方法。新方法无需噪声方差、主信号和无线信道的信息参与感知过程。与经典的能量检测方法相比,由于无需噪声方差参与感知节点的判决过程,新方法的感知性能对噪声不确定性具有良好的鲁棒性。利用多元统计理论和随机矩阵理论(RMT)获得了相应的理论判决门限。仿真结果表明新算法比基于ED的感知算法具有更好的误警性能和更可靠的检测性能。
In the multiantenna sensing scenarios, the sensing performance of the classical ED method can be degraded drastically because both the noise uncertainty and the correlation between the signal samples may be present simultaneously. Using the correlation characteristics of the multiple antenna received signal, a blind algorithm based on all the eigenvalues of the sample covariance matrix （SCM） is proposed. The new method can execute spectrum sensing without information about the noise variance, the primary signal and the wireless channel. Compared with the ED method, the sensing performance of the proposed method is robust to noise uncertainty because it does not need noise variance to help the sensing node to make a right decision. The multivariate statistical theory and the random matrix theory （RMT） are used to obtain the theoretical decision threshold. Simulation results show that the proposed algorithm has better false alarm performance and more reliable detection performance than the ED method when there exists noise uncertainty.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2012年第7期1549-1554,共6页
Journal of System Simulation
基金
The National Natural Science Foundation of China(Grant No.61102089)
the Scientific Research Fund of Hunan Provincial Education Department(Grant No.11C1058)
the New Courses Project of Jishou University(Grant No.2011KCB03)
关键词
盲频谱感知算法
噪声不确定性
盲特征值检测
能量检测
取样协方差矩阵
多元统计理论
随机矩阵理论
blind spectrum sensing algorithm
noise uncertainty
blind eigenvalues detection （BESD）
energy detection （ED）
sample covariance matrix （SCM）
multivariate statistical theory
random matrix theory （RMT）
