Modulation recognition of radio signals plays a vital role in radio monitoring and spectrum management. As the deep learning network in artificial neural network has the powerful ability of representation learning which can automatically extract various complex features from the original data, exploring the modulation identification of radio signals based on deep learning is one of the main development trends in the field of radio monitoring. This paper introduces some application results and existing problems of deep learning in radio signal modulation recognition. Combined with the actual needs of the work, this review puts forward some ideas for deep learning in the modulation recognition of radio signals, such as further improving the recognition range and the recognition accuracy, especially at low SNR; seeking some new deep learning hybrid architecture for radio signal modulation recognition.