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Automatic modulation recognition algorithm based on MSCNN-BiGRU network

In this paper, we propose an automatic modulation recognition (AMR) algorithm based on multi-scale convolutional neural network cascaded bidirectional gated recurrent unit (MSCN-BiGRU) network. Firstly, the network extracts and fuse the multi-scale features of the raw signal I/Q data. and then obtain the global features of the fused features at a larger scale through the BiGRU network. Finally, the softmax classifier is used to complete the recognition. The experimental results show that the average recognition accuracy of the algorithm on the RML2018.01A dataset is 62.42%, surpassing CNN by 3.89% and ResNet by 2.8%, and the maximum recognition accuracy can reach 97.5%.