突发QAM信号盲识别算法

摘要

For the modulation recognition of seven kinds of Quadrature Amplitude Modulation (QAM) in non-cooperative communication, a new blind identification algorithm was proposed based on combined features. Based on the discussion and analysis of the cyclostationarity and the instantaneous amplitude distribution of the QAM signals, the algorithm used the combined features which were cyclostationary detection feature, fourth-order zero-conjugate cyclic accumulation feature and instantaneous envelope feature. The algorithm used the binary tree support vector machine as classifier to classify the seven Intermediate Frequency (IF) QAM signals. The simulation results show that the correct recognition rate of the algorithm reaches over 90% when the number of symbols is 1000 and the Signal-to-Noise Ratio (SNR) is more than 6 dB.%针对非协作通信中的7种正交幅度调制(QAM)方式识别问题,提出一种新的基于联合特征的盲识别算法.该算法在对信号的循环平稳性以及QAM瞬时幅度分布特点讨论和分析基础上,采用基于循环平稳检测、四阶零次共轭循环累积量以及瞬时包络的联合特征,并选择二叉树支持向量机作为识别分类器,完成了对7种中频QAM信号的识别.仿真实验表明,该算法在码元数目为1000,信噪比大于6 dB时,正确识别率可达到90％以上.