基于ICA和特征提取的MIMO信号调制识别算法

MIMO Signal Modulation Recognition Algorithm Based on ICA and Feature Extraction

针对非协作通信中多输入多输出(MIMO)信号的盲调制识别,该文提出一种基于独立分量分析(ICA)和特征提取的调制识别算法。根据空分复用MIMO系统各发送天线上信号的独立性,利用ICA算法从接收的混合信号中分离出发射信号。为实现全盲条件下的调制识别,在进行ICA分离前,利用最小描述长度(MDL)准则估计发射天线数。在得到发射信号之后,首先利用6阶累积量、循环谱和4次方谱算法构造4个特征参数,然后利用分层结构的神经网络分类器识别信号的调制类型。仿真结果表明,所提方法可在较低信噪比下对{2PSK,2ASK,2FSK,4PSK,4ASK,MSK,8PSK,16QAM}8种MIMO信号进行有效识别,当发送天线数为2、接收天线数为5、信噪比为2 dB时,识别率可达到98%以上。

For blind modulation recognition of Multiple Input Multiple Output(MIMO)signals in noncooperative communication,a modulation recognition method based on Independent Component Analysis(ICA)and feature extraction is proposed.According to the signal independence of each transmitting antenna in space division multiplexing MIMO system,the ICA algorithm is used to separate the transmitting signal from the received mixed signal.In order to realize modulation recognition under completely blind condition,the Minimum Description Length(MDL)criterion is used to estimate the number of transmitting antennas before ICA separation.After obtaining the transmitted signal,four characteristic parameters are constructed by using six-order cumulant,cyclic spectrum and fourth-power spectrum algorithm,and then the modulation type of the signal is identified by using hierarchical neural network classifier.The simulation results show that the proposed method can effectively recognize{2PSK,2ASK,2FSK,4PSK,4ASK,MSK,8PSK,16QAM}eight MIMO signals at low SNR.When the number of transmitting antennas is 2,the number of receiving antennas is 5 and the SNR is 2dB,the recognition rate can reach more than 98%.