Radio signal modulation identification method based on deep learning model

The invention discloses a radio signal modulation identification method based on a deep learning model. The method comprises the following steps: 1, collecting a modulation signal as a data set, and dividing the data set into a training set and a test set; step 2, using the training set to train the established SA-DyCNN-DLSTM neural network model, and using the training set to train the SA-DyCNN-DLSTM neural network model; step 3, inputting the test set into the SA-DyCNN-DLSTM neural network model to realize identification of a radio signal modulation mode; according to the method, on the basis of an original model CNN-LSTM-DNN (CLDNN), an SA attention mechanism, a dynamic convolutional network and a pruning strategy are used for reducing calculation overload; analyzing effect factors from the aspect of identification precision by adjusting parameters of each network layer; according to the method, the modulation signal can be identified more quickly and accurately, and the identification accuracy is higher.