Multi Feature Modulation Signal Recognition based on Deep Learning

Abstract

A new round of technological revolution, industrial revolution and information revolution are developing rapidly, and the development of communication technology is also facing challenges. Modulation signal recognition is a critical technology in the field of information and communication engineering. It is everywhere in both civil and military fields, such as online education, electronic intelligence support technology, etc. But as the electromagnetic environment becomes ever more complex, we also need to constantly take on new challenges. In this article, the author proposed a method for multi feature modulation recognition based on shallow convolutional neural network (CNN) to enhance the internal connection of various features extracted by features during modulation signal recognition, thereby improving the signal recognition effect. The simulation results in this paper show that the technology proposed in this paper improves the recognition rate of modulated signals under different signal-to-noise ratios(SNRs), which means that this method can effectively improve the recognition performance of modulated signals.