摘要
针对传统的Alpha稳定分布噪声下数字调制识别方法在低信噪比环境下识别性能较差的问题,提出了一种基于广义累积量和广义瞬时相位的数字调制信号识别的新方法.该方法首先构造广义累积量特征参数,并提取分数阶傅里叶变换的零中心归一化广义瞬时相位的谱密度最大值作为识别的特征参数,然后通过最小均方误差分类器和门限的设置来实现Alpha稳定分布噪声下数字调制信号的识别.仿真结果表明,在Alpha稳定分布噪声下,该方法不仅识别性能较好,而且计算复杂度较低.
The traditional methods for digital modulation signals recognition with Alpha stable distribution noise have the problem of poor performance. In this paper, a novel recognition method for digital modulation signals based on the generalized cumulant and generalized instantaneous phase is proposed to solve this problem. This method extracts the characteristic parameters which are the generalized cumulant and maximum of normalization and center generalized instantaneous phase spectral density based on fractional Fourier transform. And then the minimum mean square error classifier and the threshold are used to achieve modulation recognition of digital modulation signals with Alpha stable distribution noise. Simulation results show that the proposed method has not only better performance but also lower computation complexity than the traditional recognition methods in an Alpha stable distribution noise environment.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2015年第6期1-5,共5页
Journal of Xidian University
基金
国家自然科学基金资助项目(61501348
61271299)
国家博士后科学基金资助项目(2014M562372)
国家"863"高技术研究发展计划资助项目(2007AA01Z288)
高等学校学科创新引智计划资助项目(B08038)
关键词
调制识别
ALPHA稳定分布噪声
广义累积量
广义瞬时相位
最小均方误差
modulation recognition
Alpha-stable distribution noise
generalized cumulant
generalized instantaneous phase
minimum mean square error
