基于多特征融合的MIMO-OFDM系统单-混信号调制识别算法

Single-mixed signal modulation and recognition algorithm for MIMO-OFDM system based on multi-feature fusion

为解决非协作通信中多输入多输出正交频分复用(multiple-input multiple-output orthogonal frequency division multiplexing, MIMO-OFDM)系统的单-混信号调制识别问题,提出一种基于多特征融合和决策融合的调制识别方法。首先,利用特征矩阵的联合近似对角化(joint approximate diagonalization of eigenvalue matrix, JADE)算法从接收端恢复发送信号;然后,提取恢复后信号的四次方谱、循环谱和高阶累积量作为输入样本,利用多特征融合网络对输入样本进行训练;最后,使用决策融合策略根据每条支路输出得到最终判决结果。仿真实验结果表明,所提方法可以对MIMO-OFDM系统中的7种信号进行有效识别,在信噪比为10 dB时识别精度可达99.4%。

In order to solve the modulation recognition problem of single-mixed signal under multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)system in non-cooperative communication,this paper proposes a modulation and recognition method based on multi-feature fusion and decision fusion.Firstly,the joint approximate diagonalization of eigenvalue matrix(JADE)algorithm is used to recovery the transmitted signal from the receiving end.The quartic spectrum,cyclic spectrum and higher-order cumulants of the recovery signal are then extracted as input samples.Secondly,the multi-feature fusion network is used to train the input samples.Finally,the decision fusion strategy is used to obtain the final judgment result according to the output of each branch.Simulation result shows that the proposed method can effectively identify seven signals in MIMO-OFDM system,and the recognition accuracy can reach 99.4%at a signal-to-noise ratio of 10 dB.