Spectrum Anomalies Autonomous Detection in Cognitive Radio Using Hidden Markov Models

摘要：

　　The precisely detection of electromagnetic spectrum anomaly is important and crucial for increasing demand on spectrum security,especially in the condition of complex electromagnetic environment and lack of pre-knowledge information about frequency use.There were many research methods of anomalies detection to conquer malicious radio events.In this paper,we proposed a spectrum anomalies autonomous detection and classification method based on spectrum amplitude probability and Hidden Markov Model (HMM) to cover the shortage of passive spectrum anomaly detection on site at present.We trained and tested the method through experiments using real spectrum measurement data.The experimental results show that new approach performs well for recognizing different kinds of spectrum anomalies with rather high accuracy.

关键词： hidden Markov model anomalies detection spectrum monitoring Cognitive radio Introduction

作者: Wei Honghao Jia Yunfeng Wang Lei

作者单位: School of Electronic and Information Engineering Beihang University Beijing, China

会议类型: 国际会议

会议名称: 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference(IAEAC 2015)(2015 IEEE先进信息技术,电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 388-392

在线出版日期: 2015-12-19（万方平台首次上网日期，不代表论文的发表时间）