基于复数网络与注意力机制的信号调制识别

Communication signal modulation recognition method based on complex network and attention mechanism

摘要:

通信信号调制识别作为管理、监测电磁频谱的重要手段，具有重要的研究价值和应用前景。本文利用调制信号的频域信息，提出一种基于复数神经网络的信号调制识别方法。首先将I、Q两路信号组合成复信号，经过快速傅里叶变换(FFT)后把得到的实部和虚部组合起来作为输入网络的数据集。其次，设计了一种复数神经网络结构，并引入了注意力机制对网络结构进行改良。仿真结果表明，本文提出的方法可以有效识别9种调制方式，在信噪比为6 dB时，平均正确识别率达到96.33%。

Abstract:

As an important means of managing and monitoring the electromagnetic spectrum, communication signal modulation recognition shows important research value and application prospects. A signal modulation recognition method based on complex neural network is proposed by using the frequency domain information of modulated signals for modulation recognition. Firstly, the I and Q signals are combined into complex signals, and the real and imaginary parts obtained are combined as the data set of the input network after Fast Fourier Transform(FFT). Secondly, a complex neural network structure is designed, and an attention mechanism is introduced to improve the network structure. Finally, the simulation results show that the proposed method can effectively identify nine modulation modes, and the average correct recognition rate reaches 96.33% when the signal-to-noise ratio is 6 dB.