| 摘要: |
| 通过对观测样本进行非线性变换，提出了一种基于高阶累积量分级调制分类算法，有效解决
了频偏引起的相位旋转问题。仿真表明，在归一化频偏小于0.2时，算法具有
较好的分类性能。理论分析和仿真结果均证明了算法的正确性和有效性。 |
| 关键词: 调制分类 高阶累积量 频偏 分类性能 |
| DOI： |
|
| 基金项目: |
|
| Robust Hierarchical Modulation Classification Algorithm for Frequency Offsets |
| FENG Xiang,LIANG Wei-yang |
| (The First Aeronautical Institute of PLA Air Force, Xinyang 464000,China) |
| Abstract: |
| By the non-linear transformation to the observation sample, a higher-order cumul
ants based hierarchical modulation classification algorithm is prese
nted. The effect of frequency offsets on the performance of the hierarchical alg
orithm is eliminated by the transformation. The efficiency of the proposed class
ification algorithm is verified via theoretical analysis and extensive simulatio
ns. The simulations show that the algorithm presents better performance as the n
o
rmalized frequency is less than 0.2. |
| Key words: modulation classification higher-order cumulants frequency offsets classificatio
n performance |
《电讯技术》编辑部 