摘要
针对传统频谱感知算法在较低信噪比和存在噪声不确定度时,检测性能降低的问题,提出了一种基于特征值极限分布的双判决门限频谱感知算法。由于利用了双门限和信号采样协方差矩阵的特征值进行判决,这种算法不但可以有效地克服噪声不确定度对检测性能的影响,而且不需要预先知道主用户信号的任何信息。与已有的最大最小特征值频谱感知算法相比,由于采用了双判决门限,因此该算法的检测性能更优。仿真结果表明,该方法不但可以有效地克服噪声不确定度,而且检测性能也优于最大最小特征值算法。
In order to improve the detection performance of the traditional spectrum sensing algorithm,a double threshold（DT） spectrum sensing algorithm is proposed.Since using the double threshold and the eigenvalue of the covariance matrix of the received signals,the proposed method exhibits a good performance and robustness against noise uncertainty without having to know any information of the primary signal.Compared with the maximum-minimum eigenvalue（MME） algorithm,the performance of DT is superior to MME since double threshold is used to detect the primary signal.Simulation results show that the proposed method provides a substantial improvement compared with the MME algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第3期588-591,共4页
Systems Engineering and Electronics
基金
国家自然科学基金项目(61171104)
中央高校基本科研业务费专项资金(G470415)资助课题
