Research On Modulation Recognition Technology Of Communication Signal Based On Machine Learning

Modulation signal recognition technology is a basic technology in the field of wireless communication,and also an important part of communication receiving system.It is between signal detection and signal demodulation.It mainly receives and processes the modulated signal intelligently.In order to obtain the communication information,the modulation mode of the received signal must be determined first,then the correct demodulation and subsequent information processing and analysis can be carried out.Today is an era of information technology changing with each passing day,and various communication technologies are constantly updated.The channel environment of wireless communication becomes more and more complex,and the modulation mode of communication signal correspondingly becomes more diverse and complex,which brings new challenges and problems to modulation signal recognition technology.In this paper,the modulation recognition algorithm of digital signal based on machine learning is studied:(1)This paper presents a modulation recognition algorithm based on LSSVM technology,which overcomes the high complexity of the algorithm.In the original algorithm,the SVM classifier is replaced by LSSVM and the modulation signals are classified.The simulation results show that the overall performance of the two algorithms is equivalent,but the modulation recognition algorithm based on LSSVM has lower complexity and faster computing speed.(2)A deep learning intelligent modulation recognition algorithm based on convolutional neural network model is proposed,which overcomes the shortcomings of traditional modulation recognition that feature extraction depends on artificial experience and the algorithm has poor performance in low SNR,and improves the accuracy of digital signal recognition in low SNR.The algorithm first preprocesses the received modulation signal,converts the sampling data of the communication signal into the gray image,takes it as the input of the neural network,uses the VGGNet network built under the deep learning architecture Py Torch for training,and automatically extracts and selects the characteristics of the digital modulation signal,thus realizing the automatic recognition of the digital modulation signal.The simulation results show that the recognition rate is more than 98% when the SNR is-2d B,which is better than the traditional modulation signal recognition algorithm,thus verifying the effectiveness of the method in the low SNR digital modulation signal recognition.(3)On the ARM development platform,the modulation recognition algorithm based on decision tree is simulated and tested,which provides a reference for the implementation of modulation recognition algorithm based on machine learning.