摘要
N次方非线性变换方法是通信信号自动调制识别的常用方法,该方法对于相位键控(PSK)信号较为有效。但是,该方法要求的采样率通常要远高于Nyquist速率,这无疑给模拟数字转换器(ADC)带来了巨大的压力。本文利用相位键控(PSK)信号经过非线性变换后频谱的稀疏特性,提出了一种利用压缩采样数据实现PSK信号自动调制识别的方法。文中引入了压缩感知理论,并给出了利用压缩采样数据重构PSK信号非线性变换后频谱的方法,该重构频谱可用于自动调制识别及载频和符号率估计。
The Nth Power Nonlinear Transform(NPT) is a common method for automatic modulation classification, especially for Phase Shift Keying(PSK) signals. Nevertheless,the sampling rate required in the NPT method is typically much greater than Nyquist rate,which causes heavy burden for the Analog to Digital Converter(ADC). Taking advantage of the sparse property of Phase Shift Keying signals spectrum under NPT,the NPT method is developed for PSK signals with Sub-Nyquist rate samples. Combining the NPT method with Compressive Sensing(CS) theory,frequency spectrum reconstruction of the Nth Power Nonlinear Transform of PSK signals is presented, which can be further applied to Automation Modulation Recognition(AMR) and rough estimations of unknown carrier frequency and symbol rate.
出处
《太赫兹科学与电子信息学报》
2016年第1期88-92,共5页
Journal of Terahertz Science and Electronic Information Technology
关键词
压缩感知
相位键控
调制识别
N次方非线性变换
Compressive Sensing
Phase Shift Keying signals
modulation classification
Nth Power Nonlinear Transform
