Abstract
The automatic modulation recognition of communication signal has been widely used in many fields. However, it is very difficult to recognize the modulation in low SNR. Based on information entropy features and Dempster-Shafer evidence theory, a novel automatic modulation recognition methods is proposed in this paper. Firstly, Renyi entropy and singular entropy is used to obtain the modulation feature. Secondly, based on the normal test theory, a novel basic probability assignment function(BPAF) is presented. Finally, Dempster-Shafer evidence theory is used as a classifier. Experiment results indicate that the new approach can obtain a higher recognition result in low SNR.
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