认知无线电中一种非高斯背景下的协同频谱感知方案
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摘要
在认知无线电系统中,由于需要对一定频谱范围内的认知用户进行频谱检测,而传统经典的检测方法无法满足复杂多变的检测环境,基于此,文章研究了在实际情况中更为普遍的非高斯噪声情况下认知用户的频谱检测问题.由于传统的广义似然比检测计算量较大而且实际工程中较难实现,文章采用广义似然比的一种近似形式即Rao检测.通过采用矩估计方法对系统模型的混合系数等进行参数估计,并在拟合非高斯噪声的背景下应用于认知用户的频谱检测,推导出非高斯噪声中Rao检测的检测统计量和检测性能公式,分析比较了非高斯噪声中Rao检测与高斯Rao检测的性能.仿真结果表明,在虚警概率一定的情况下,基于Rao检测的频谱检测方法能有效地提高认知无线电网络中非高斯噪声背景下认知用户的检测性能.
In cognitive radio system,due to the need for cognitive users within a certain range of the spectrum for spectral detection but the classic detection methods cannot meet the complex testing environment.For this reason,this paper studies the spectrum sensing problem which more cognitive users in non Gauss noise generally under in actual situation.Because the traditional generalized likelihood ratio test which the large amount of calculation and difficult to implement in practical engineering,this paper uses generalized likelihood ratio test 's approximate forms,that is Rao detection.By using the method of moments estimate mixing coefficient system model parameter estimation and fitting spectrum detection applied to cognitive users under non- Gaussian noise background,deducing the non-Gaussian noise test statistic Rao detection and detection performance formula,analysis and comparison of the non-Gaussian Rao noise detection and Gaussian Rao detection performance.The simulation showed that,under certain circumstances the probability of false alarm,spectrum sensing method based on Rao detection can effectively improve the detection performance of cognitive users under No-Gauss noise background in cognitive radio networks.
In cognitive radio system,due to the need for cognitive users within a certain range of the spectrum for spectral detection but the classic detection methods cannot meet the complex testing environment.For this reason,this paper studies the spectrum sensing problem which more cognitive users in non Gauss noise generally under in actual situation.Because the traditional generalized likelihood ratio test which the large amount of calculation and difficult to implement in practical engineering,this paper uses generalized likelihood ratio test 's approximate forms,that is Rao detection.By using the method of moments estimate mixing coefficient system model parameter estimation and fitting spectrum detection applied to cognitive users under non- Gaussian noise background,deducing the non-Gaussian noise test statistic Rao detection and detection performance formula,analysis and comparison of the non-Gaussian Rao noise detection and Gaussian Rao detection performance.The simulation showed that,under certain circumstances the probability of false alarm,spectrum sensing method based on Rao detection can effectively improve the detection performance of cognitive users under No-Gauss noise background in cognitive radio networks.
引文
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[11]姜微.基于能量检测的频谱检测技术研究[D].哈尔滨:哈尔滨工程大学,2010.JIANG W.Research on spectrum detection technology based on energy detection[D].Harbin:Harbin Engineeing University,2010.
[12]褚御芝,郑宝玉,季薇.协同频谱感知中的融合策略[J].南京邮电大学学报,2010,30(3):39-45.CHU Y Z,ZHENG B Y,JI W.Research on fushion strategy in cooperative spectrum sensing[J].Journal of Nanjing University of Posts and Telecommuntcations,2010,30(3):39-45.
[2]QUAN Z,CUI S G,SAYED A H.Optimal linear cooperation for spectrum sensing in cognitive radio networks[J].IEEE Journal of Selected Topics in Signal Processing,2008,2(1):28-40.
[3]刘雪梅.基于循环平稳特征的频谱感知算法概述[J].通信技术,2011,44(12):21-23.LIU X M.Summany of spectrum sensing algorithm based on cyclostationary characteristic[J].Conmunication Technology,2011,44(12):21-23.
[4]EDWARDP,LIANG Y C.Optimization for cooperative sensing in cognitive radio networks[C].Proceedings of WCNC2007,Kowloon,China,2007:27-32.
[5]漆春梅.认知无线电中的频谱感知技术研究[D].成都:电子科技大学,2009.QI C M.Research on spectrum sensing in cognitive radio[D].Chengdu:University of Electronic Scionco and Technology of China,2009.
[6]STEVEN M K.Fundamentals of statistical signal processing volumeⅠ:Estimation theory[M].Beijing:Publishing House of Electronics Industry,2003.
[7]GANESAN G.Cooperative spectrum sensing in cognitive radio rartⅠ:Two user Networks[J].IEEE Transactions on Wireless Communication,2007,6(6):2 204-2 212.
[8]韩昭芳.认知无线电中协作频谱感知策略优化的研究[D].北京:北京邮电大学,2011.HAN Z F.Research on spectrum sensing strategy optimization in cognitive radio[D].Beijing:University of Posts and Telecommuntcatins,2011.
[9]DIGHAM F.F-ALOUINI M S.On the energy sensing of unknown signals over fading channels[J].IEEE Transactions on Communications,2007,55(1):21-24.
[10]CIUONZO D,PAPA G,ROMANO G,et al.One-Bit decentralized detection with a Rao test for multisensor fusion[J].IEEE Signal Processing Society,2013,20(9):861-864.
[11]姜微.基于能量检测的频谱检测技术研究[D].哈尔滨:哈尔滨工程大学,2010.JIANG W.Research on spectrum detection technology based on energy detection[D].Harbin:Harbin Engineeing University,2010.
[12]褚御芝,郑宝玉,季薇.协同频谱感知中的融合策略[J].南京邮电大学学报,2010,30(3):39-45.CHU Y Z,ZHENG B Y,JI W.Research on fushion strategy in cooperative spectrum sensing[J].Journal of Nanjing University of Posts and Telecommuntcations,2010,30(3):39-45.