Alpha稳定分布噪声背景下衰落信号的调制识别方法

Modulation Recognition Method of Fading Signals under Alpha Stable Distribution Noise Background

在Alpha稳定分布噪声背景下,针对基于传统循环统计量的衰落信号调制识别方法失效的问题,通过引入归一化压缩函数形成一类新型广义循环统计量,提出一种新的调制识别方法。提取各信号广义循环平稳特征作为判决标准,利用树形分类器实现了Alpha稳定分布噪声背景衰落信道中FSK、PSK、MSK等信号的调制识别。仿真结果表明,该方法在Alpha稳定分布噪声背景的多径衰落和单径等多种信道中均有良好的性能;相较于其他基于非线性变换的广义循环统计量方法,灵活性更强、性能更优且复杂度更低。

Under Alpha stable distribution noise background, the existing fading-signal modulation recognition methods based on traditional cyclic statistics were always invalid. To solve this problem, a new modulation recognition method is proposed, by introducing normalized compression function to generate a series of novel generalized cyclic statistics. Firstly, the general- ized cyclostationary feature of the signals are extracted as decision criterion; and then the tree classifier is used to achieve modulation recognition of signals such as FSK, PSK and MSK in fading channels under Alpha stable distribution noise back- ground. Finally, simulation results show that the proposed method has good performance in different channels with single or multiple propagation paths under Alpha stable distribution noise background. Moreover, it exhibits higher flexibility, better performance but lower complexity than other methods based on generalized cyclic statistics using non-linear transform.