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基于高阶累积量和BP神经网络的数字调制识别

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针对非合作通信下低信噪比数字调制识别率低的问题,论文提出了一种基于高阶累积量和BP神经网络的调制识别方法。此方法借助二、四、六、八阶累积量构造出T1、T2两种特征值,这两种特征值可以在较低的信噪比下有效地识别2ASK、4ASK、2FSK、4FSK、2PSK、4PSK六种数字调制信号。经过Matlab仿真实验可以得出,当信噪比大于等于-3dB时,六种信号的识别率都可达到100%。
Digital Modulation Recognition Based on High Order Cumulant and BP Neural Network
To solve the problem of low recognition rate of digital modulation with low signal-to-noise ratio in non-cooperative communication,a modulation recognition method based on high-order cumulant and BP neural network is proposed in this paper.In this method,T1 and T2 are constructed by means of the second,fourth,sixth and eighth order cumulants.These two eigenvalues can effectively identify the six digital modulated signals of 2ASK,4ASK,2FSK,4FSK,2PSK and 4PSK under low signal-to-noise ratio.Through Matlab simulation experiment,it can be concluded that when the signal-to-noise ratio is greater than or equal to-3dB,the recognition rate of six kinds of signals can reach 100%.

modulation recognitionhigher order cumulantneural network

陈震峰、吴明、孙卫华

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中国船舶集团有限公司第七二二研究所 武汉 430205

调制识别 高阶累积量 神经网络

2024

舰船电子工程
中国船舶重工集团公司第709研究所 中国造船工程学会 电子技术学术委员会

舰船电子工程

CSTPCD
影响因子:0.243
ISSN:1627-9730
年,卷(期):2024.44(1)
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