Design of a Communication Signal Modulation Recognition System Based on Deep Learning
The article designs a deep learning-based communication signal modulation recognition system,aiming to overcome the limitations of traditional modulation recognition methods in complex electromagnetic environments.The system has four modules:signal preprocessing,feature extraction,modulation classification and post-processing decision.ConvolutionalNeural Networks(CNN)are used for feature extraction,and Support Vector Machine(SVM)is used for feature extraction.The experimental results show that the system exhibits high recognition accuracy under a variety of channel conditions,especially under complex channels and low Signal Noise Ratio(SNR).The research results of the article validate the value of deep learning techniques in communication signal processing,and provide new technical means for the field of wireless communication and electronic countermeasures.
communication signalmodulation recognitiondeep learning
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