摘要
针对认知无线电系统中传统数字调制识别方法在非高斯Alpha稳定分布噪声下识别性能差、计算复杂度高的问题,提出了一种基于分数低阶循环谱相关系数的数字调制识别新方法。该方法提取分数低阶循环谱截面和频率谱截面以及其投影面的5个相关系数作为识别特征参数,并采用判决树分类器,实现了非高斯噪声下数字调制信号识别。仿真结果表明,在非高斯Alpha稳定分布噪声下,该识别方法不仅具有较高的识别率和良好的稳健性并且计算复杂度更低,更适合于认知无线电系统。
In cognitive radio system, the traditional methods of digital modulation signals recognition with Alpha stable distribution noise have the problems of poor performance and high computation complexity. A novel recognition method based on correlation coefficient of fractional lower order cyclic spectrum was proposed to solve this problem. The method extracts the recognition characteristic parameters which are five correlation coefficients of the fractional lower order cyclic spectrum＇s section and frequency spectrum＇s section and projection planes of both, and then decision tree was used as a classifier to achieve digital modulation signals recognition. Simulation results show that the proposed method not only has higher recognition rates and better robustness but also has lower computation complexity in an Al- pha stable distribution noise environment, which is more suitable for cognitive radio system.
出处
《通信学报》
EI
CSCD
北大核心
2014年第1期82-88,共7页
Journal on Communications
基金
国家自然科学基金资助项目(61271299,61102057)
国家重点基础研究发展计划(“973”计划)基金资助项目(2009CB320404)
高等学校学科创新引智计划基金资助项目(B08038)~~
关键词
认知无线电
调制识别
ALPHA稳定分布
分数低阶循环谱
相关系数
cognitive radio
modulation recognition
Alpha stable distribution
fractional lower order cyclic spectrum
correlation coefficient
