基于阈值优化的频谱感知算法  

Spectrum sensing algorithm based on optimal threshold

作　　者：魏苗[1] 练秋生[1] 

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004

出　　处：《燕山大学学报》2011年第2期157-161,共5页Journal of Yanshan University

基　　金：河北省自然科学基金资助项目(F2010001294)

摘　　要：协方差绝对值(Covariance Absolute Value,CAV)感知算法使用固定阈值和固定虚警概率的频谱感知策略,无法保证在任何时候都能使频谱感知性能达到最优。提高频谱感知性能包括降低对主用户的干扰概率并提高空闲频谱的利用率,即最大限度地降低漏检概率与虚警概率。为此,本文对协方差绝对值感知算法进行改进,提出了不同信噪比下自适应阈值的优化方法使频谱感知误差(漏检概率与虚警概率的代数和)达到最小。实验结果表明,本文算法有效降低了频谱感知误差,提高了检测概率,特别是在信噪比较低的情况下性能改善较为明显。Covariance absolute value sense algorithm（CAV） use the spectrum sensing strategy of the fixed threshold and fixed false alarm probability,so it can not guarantee at any time to achieve optimal spectrum sensing performance.To improve the spectrum sensing performance,it contains reducing interference probability with primary user and increasing the utilization of idle spectrum,namely,to reduce false alarm probability and missed probability at most.Therefore,covariance absolute value sense algorithm is improved that it proposes the optimization method of the adaptive threshold under different signal to noise ratio so that the value of spectrumsensing error（the sumofmissed detection probability and false alarmprobability） is at the minimum.Simulation results show that the proposed scheme effectively reduce the spectrum sensing error and increase the detection probability, particularly in the case of low SNR,the spectrum sensing performance improvements are significant.

关 键 词：认知无线电 频谱感知 自适应阈值 DTV信号 

分 类 号：TN912[电子电信—通信与信息系统]