中文摘要：

研究低压电力线载波通信信号调制识别技术对建立相关通信领域的规范化测试标准具有重要意义。通过采集电力线载波芯片发送的调制信号样值,经预处理后提取信号四类特征参数,并利用BP神经网络结合双特征参数阈值判决法对特征参数进行判决归类,从而实现调制类型的自动识别。仿真及实测数据结果表明,提出的特征参数集和基于双特征参数阈值判决的神经网络分类器能够有效识别低压电力线载波BFSK、BPSK和QPSK调制信号,在信噪比大于10d B的情况下,该方法的识别正确率可达95%以上。

英文摘要：

Research on the low voltage power line carrier communication ( PLC) modulation recognition technology is of great importance for establishing PLC physical layer standard test method .In this paper , a novel modulation recog-nition scheme with double feature parameters-threshold judgment method for narrowband PLC is proposed .The PLC modulated signal is sampled and pre-processed .With the four decision criterias derived from these samples , the BP neural network is applied to recognize and classify different modulated signals automatically .From the simulation and experiment results , it can be seen that the proposed method based on double feature parameters-threshold judgment can effectively recognize PLC narrowband modulation signals of BFSK , BPSK and QPSK .When the SNR is above 10dB, the successful recognition rate is above 95%.