Communication signal modulation mode identification method based on convolutional neural network

Abstract

The invention discloses a modulation mode identification system and method based on a convolutional neural network, which solve the problems of complex feature extraction steps and low identificationrate under a low signal-to-noise ratio in the prior art. The simple feature in the identification system is constructed as a simple feature using a co-directional component and a quadrature componentof a baseband signal as signals, and the simple feature is sent to a convolutional neural network module for identification. The identification method comprises the steps of: modulating a transmittedsignal and performing pulse shaping; performing up-conversion on the transmitted signal and then transmitting the transmitted signal through an additive white Gaussian noise channel; performing pre-processing first by a receiving end to obtain the co-directional component r(t) of the analyzed signal; constructing the simple feature, i.e., constructing the co-directional component r(t) and the quadrature component of the analyzed signal into a two-dimensional matrix; performing feature learning and classification by the convolutional neural network; and sending a modulation method to a demodulation end to obtain a demodulated signal. The method is low in feature design complexity, avoids explicit feature extraction, has high classification correctness, and can be applied to communication systems having high recognition performance requirements.

Description

technical field [0001] The invention belongs to the field of communication technology, mainly relates to the technical field of communication signal identification and deep learning, specifically a communication signal modulation method identification method based on convolutional neural network, which is used for cognitive radio, interference identification, spectrum management, electronic countermeasures, etc. field. Background technique [0002] Communication signal modulation identification is an intermediate step in signal detection and demodulation. It has important research value in both military and civilian fields, and is widely used in cognitive radio, interference identification, spectrum management, electronic countermeasures and other fields. [0003] At present, in the literature on modulation recognition that has been published at home and abroad, the modulation recognition methods can be divided into two categories: decision pattern recognition and statistica...

AI Technical Summary

Problems solved by technology

The algorithm of this method is complicated, and it is difficult to achieve real-time modulation identification

[0005] Although many achievements have been made in the modulation mode identification algorithm, these advances cannot cover up the shortcomings in its development: the feature extraction steps of the existing modulation mode identification algorithm are complicated, and the features required for system identification are almost all manually designed. Low recognition rate under noise ratio

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