Robust and Real-Time Automatic Modulation Classification System Based on Deep Learning

Automatic modulation classification (AMC), whose main purpose is to recognize the received signal modulation mode under multi-signal environment and noise interference, provides the foundation for subsequent signal processing. In our paper, we propose a novel robust and real-time AMC implementation method based on deep learning (DL) and cognitive radio (CR), which can get faster recognition and higher accuracy. In this paper, it only needs 79.76us to recognize a set of data, and the accuracy is great than 90% at low signal-to-noise ratio.