基于CNN-LSTM的MIMO-OFDM信号盲调制识别算法  

Blind Modulation Recognition Algorithm for MIMO-OFDM Signal Based on CNN-LSTM

作　　者：张天骐[1] 邹涵 杨宗方 马焜然 ZHANG Tianqi;ZOU Han;YANG Zongfang;MA Kunran(School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications(CQUPT),Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《信号处理》2024年第4期747-756,共10页Journal of Signal Processing

基　　金：国家自然科学基金(61671095,61702065,61701067,61771085);信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003);重庆市自然科学基金项目(cstc2021jcyj-msxmX0836);重庆市教育委员会科研项目(KJ1600427,KJ1600429)。

摘　　要：无线通信信号的盲调制识别技术作为非协作通信的核心技术之一,在提高频谱利用效率以及未知信号解调中起着至关重要的作用。另外,非协作通信中存在着电磁环境未知,噪声干扰严重,信噪比低等问题,因此在非协作通信下进行未知信号的盲调制识别较为困难。为解决非协作通信中多输入多输出正交频分复用(MultipleInput Multiple-Output Orthogonal Frequency Division Multiplexing, MIMO-OFDM)信号在低信噪比下子载波盲调制识别的问题,本文使用CNN(Convolutional Neural Network,CNN)网络与LSTM(Long Short-Term Memory,LSTM)网络构建一维CNN-LSTM网络进行盲调制识别。鉴于I/Q数据具有很强特征表达能力,该算法选取I/Q数据作为第一输入特征直接输入网络。同时为了弥补噪声对I/Q数据的干扰,本文还选用抗噪声能力强的循环谱作为另一输入特征,为进一步提升循环谱的抗噪声能力,本文对循环谱进行切片累加操作得到抗噪声性能更好的循环谱切片累加序列作为第二输入特征。仿真结果表明,本文所提方法可以在SNR=2 dB条件下实现对{BPSK,QPSK,8PSK,16QAM,32QAM,128QAM}调制方式的识别,并且识别精度达到98%。As one of the core technologies of non-cooperative communication,blind modulation recognition technology for wireless communication signals plays a crucial role in improving spectrum utilization efficiency and the demodulation of un-known signals.In addition,non-cooperative communication experiences problems such as an unknown electromagnetic environ-ment,serious noise interference,and a low signal-to-noise ratio,which make it difficult to blindly modulate and identify un-known signals.In order to solve the problem of subcarrier blind modulation recognition of multiple-input multiple-output orthogo-nal frequency division multiplexing signals in non-cooperative communication at a low signal-to-noise ratio,this study used a convolutional neural network(CNN)and long short-term memory(LSTM)network to build a one-dimensional CNN-LSTM network for blind modulation identification.Because of the strong feature-expression ability of I/Q data,the algorithm used I/Q data as the first input feature and directly entered it into the network.In order to compensate for the interference of noise on I/Q data,a cyclic spectrum with strong noise immunity was also selected as another input feature.In order to further improve the noise immunity of the cyclic spectrum,a cyclic spectrum slice accumulation sequence with better noise immunity was used as the second input feature.Simulation results showed that the proposed method could recognize the{BPSK,QPSK,8PSK,16QAM,32QAM,128QAM}modulation mode under a signal-to-noise ratio of 2 dB,and the recognition accuracy reached 98%.

关 键 词：I/Q序列 神经网络 盲调制识别 循环谱 

分 类 号：TN911[电子电信—通信与信息系统]