New Blind Recognition Method of SCLD and OFDM in Alpha-Stable Noise  

作　　者：Junlin Zhang Bin Wang Yang Wang 

机构地区：[1]National Digital Switching System Engineering and Technological R&D Centre, Zhengzhou, China

出　　处：《International Journal of Communications, Network and System Sciences》2017年第5期240-251,共12页通讯、网络与系统学国际期刊（英文）

摘　　要：This paper deals with modulation classification under the alpha-stable noise condition. Our goal is to discriminate orthogonal frequency division multiplexing (OFDM) modulation type from single carrier linear digital (SCLD) modulations in this scenario. Based on the new results concerning the generalized cyclostationarity of these signals in alpha-stable noise which are presented in this paper, we construct new modulation classification features without any priori information of carrier frequency and timing offset of the received signals, and use support vector machine (SVM) as classifier to discriminate OFDM from SCLD. Simulation results show that the recognition accuracy of the proposed algorithm can be up to 95% when the mix signal to noise ratio (MSNR) is up to ?1 dB.This paper deals with modulation classification under the alpha-stable noise condition. Our goal is to discriminate orthogonal frequency division multiplexing (OFDM) modulation type from single carrier linear digital (SCLD) modulations in this scenario. Based on the new results concerning the generalized cyclostationarity of these signals in alpha-stable noise which are presented in this paper, we construct new modulation classification features without any priori information of carrier frequency and timing offset of the received signals, and use support vector machine (SVM) as classifier to discriminate OFDM from SCLD. Simulation results show that the recognition accuracy of the proposed algorithm can be up to 95% when the mix signal to noise ratio (MSNR) is up to ?1 dB.

关 键 词：MODULATION Recognition GENERALIZED SECOND-ORDER CYCLIC STATISTICS OFDM Alpha-Stable Noise 

分 类 号：TN91[电子电信—通信与信息系统]