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Modulation Classification for M-ary CPM Signals: Based on PAM Decomposition and Phase Detection Methods

机译:基于MAM CPM信号的调制分类:基于PAM分解和相位检测方法

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We study new modulation classification methods for M-ary CPM signals based on the average likelihood ratio test (ALRT) approach. It is well-known that the M-ary CPM signal can be decomposed into the superposition of multiple PAM waveforms. In this paper, we apply the decomposed PAM waveforms for CPM classification through ALRT. However, to detect the CPM signals costs a high complexity because the PAM decomposition method requires multiple filters to match the PAM waveforms. Hence, we propose a new phase detection method which has lower complexity. In addition, we analyze the phase noise in the phase detection method to insure the prerequisite of applying the ALRT approach for modulation classification. Simulation results show that the new M-ary CPM classification method has satisfying probability of correct classification when SNR is beyond 0 dB.
机译:我们基于平均似然比检验(ALRT)方法研究了Mary CPM信号的新调制分类方法。众所周知,Mary CPM信号可以分解为多个PAM波形的叠加。在本文中,我们通过ALRT将分解后的PAM波形应用于CPM分类。但是,由于CAM分解方法需要多个滤波器来匹配PAM波形,因此检测CPM信号的成本很高。因此,我们提出了一种具有较低复杂度的新的相位检测方法。另外,我们在相位检测方法中分析相位噪声,以确保应用ALRT方法进行调制分类的前提。仿真结果表明,当信噪比超过0 dB时,新的M进制CPM分类方法具有令人满意的正确分类概率。

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