为了解决噪声不确定环境下的盲频谱感知问题,提出一种基于接收信号格拉姆-施密特正交变换的快速盲频谱感知算法(Blind sensing method based on the Gram-Schmidt Orthogonalization,BS-GSO)。先通过多天线接收获得的采样矩阵来构造统...为了解决噪声不确定环境下的盲频谱感知问题,提出一种基于接收信号格拉姆-施密特正交变换的快速盲频谱感知算法(Blind sensing method based on the Gram-Schmidt Orthogonalization,BS-GSO)。先通过多天线接收获得的采样矩阵来构造统计协方差矩阵,利用似然比准则和施密特正交变换构造检验统计量并获得判决表达式,再应用中心极限定理和泰勒展开式推导出非渐进的判决门限。蒙特卡洛实验仿真结果表明,BS-GSO算法有效、稳健,且计算复杂度较低。展开更多
In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorith...In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.展开更多
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)
文摘为了解决噪声不确定环境下的盲频谱感知问题,提出一种基于接收信号格拉姆-施密特正交变换的快速盲频谱感知算法(Blind sensing method based on the Gram-Schmidt Orthogonalization,BS-GSO)。先通过多天线接收获得的采样矩阵来构造统计协方差矩阵,利用似然比准则和施密特正交变换构造检验统计量并获得判决表达式,再应用中心极限定理和泰勒展开式推导出非渐进的判决门限。蒙特卡洛实验仿真结果表明,BS-GSO算法有效、稳健,且计算复杂度较低。
基金National Natural Science Foundation of China(61362018)Hunan Provincial Department of Education(16A174)+1 种基金Doctor Recruitment Project in Jishou UniversityProject of Exploratory Learning and Innovative Experiment for College Students of Hunan Province(2016[283])
基金Projects(61362018,61861019)supported by the National Natural Science Foundation of ChinaProject(1402041B)supported by the Jiangsu Province Postdoctoral Scientific Research Project,China+1 种基金Project(16A174)supported by the Scientific Research Fund of Hunan Provincial Education Department,ChinaProject([2016]283)supported by the Research Study and Innovative Experiment Project of College Students,China
文摘In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.
