Radio signal modulation recognition algorithm based on convolutional neural network

Abstract

In modern communications, it is often necessary to correctly identify the modulation of a signal with almost zero a priori knowledge as a non-collaborator for subsequent work such as demodulation and analysis. This paper is based on the convolutional neural network algorithm to study the modulation recognition algorithm of radio signals. Firstly, this paper studies the format, parameters and channel model of the radio signal dataset, and constructs a dataset in the format of I/Q data. Then, this article uses Convolutional Neural Network (CNN) algorithm to identify and classify the signal. Finally, to address the defects and training time problems in the classical convolutional neural network recognition method, this paper proposes an improved convolutional neural network named X-CNN. The X-CNN is optimised in terms of connection structure, enhancement mechanism and pooling method to improve the recognition rate and the overall fitting ability of the network.