Signal Classification based on Cyclostationary Spectral Analysis and HMM/SVM in Cognitive Radio

摘要：

Distinction of the type of modulated signals is very important in cognitive radio system. In this paper, a novel approach to signal classification is proposed for cognitive radio. Combining the spectral cyclostationary features, embed SVM into the framework of HMM to construct a hybrid HMM/SVM classifier for signal recognition. The simulation results show that the high performance and robustness of the proposed approach, even in low SNR of-5dB. Compared to the conventional methods including the classifiers based on HMM or ANN, the proposed approach has a rather higher recognition rate of signals.

关键词： Cognitive Radio Signal Classification Cyclostationary HMM SVM

作者: Xinying He Zhimin Zeng Caili Guo

作者单位: School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing, China

会议类型: 国际会议

会议名称: 2009 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2009)(2009年检测技术与机电自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 309-312

在线出版日期: 2009-04-11（万方平台首次上网日期，不代表论文的发表时间）