A New Method of Cognitive Signal Recognition Based on Hybrid Information Entropy and D-S Evidence Theory
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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, Rényi 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.
KeywordsAutomatic Modulation Recognition Information Entropy Dempster-Shafer Evidence Theory Normal Test
This work is supported by the National Natural Science Foundation of China (61771154,61301095), the Key Development Program of Basic Research of China (JCKY2013604B001), the Fundamental Research Funds for the Central Universities (GK2080260148 and HEUCF1508).
We gratefully thank of very useful discussions of reviewers.
Compliance with Ethical Standards
Conflict of Interest
Meantime, all the authors declare that there is no conflict of interests regarding the publication of this article.
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