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Pre Denoising Modulation Recognition Algorithm Based on CycleGAN

In order to solve the problem of mismatch of pre trained deep neural network model and sharp deterioration of system performance caused by large difference in SNR between modulation training data and test data, combined with Cycle-Consistent Adversarial Networks (CycleGAN), a pre denoising modulation recognition algorithm based on CycleGAN was proposed. Low SNR signals learn and imitate the IQ sequence characteristics of high SNR signals to achieve the pre denoising and improve the recognition. Simulation results show that compared with training on modulation training data, the recognition rate of direct test on test data is improved by 28.87%.