基于SNR均匀训练的幅频RRC脉冲信号分离
Separation of Signals Consisting of Amplitude and Instantaneous Frequency RRC Pulses Using SNR Uniform Training
摘要：
这项工作提出了样本均值和样本方差为基础的功能，区分连续相位FSK从QAM和PSK调制。根升余弦脉冲用于信号生成。采用支持向量机进行信号分离。它们仅针对一个SNR值进行训练，并用于从宽范围的SNR中对信号进行分类。放松了关于载波幅度、载波相位、载波偏移、滚降因子和初始符号相位的先验信息。通过观察加性高斯白噪声、载波偏移、符号和采样不同步以及快衰落的联合影响，验证了该方法的有效性。
英文摘要：
This work presents sample mean and sample variance based features that distinguish continuous phase FSK from QAM and PSK modulations. Root raised cosine pulses are used for signal generation. Support vector machines are employed for signals separation. They are trained for only one value of SNR and used to classify the signals from a wide range of SNR. A priori information about carrier amplitude, carrier phase, carrier offset, roll-off factor and initial symbol phase is relaxed. Effectiveness of the method is tested by observing the joint effects of AWGN, carrier offset, lack of symbol and sampling synchronization, and fast fading.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
