Recognition of digital phase modulation signal in wireless communication

Digital modulation signal is an important field of wireless communication. With the continuous development of wireless communication technology, the recognition technology of digital signal is also advancing. In this paper, the recognition technology of digital phase-modulation signal is studied, and the received MPSK signal is converted into an isopotential horoscope through data processing. Based on deep learning theory, three deep learning models such as ResNet, VGG16 and Mobilenet are selected to carry out feature extraction and recognition of the isopotential constellation of MPSK signal, and the accuracy of recognition is compared.