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1. 中国电子科技集团公司第三十六研究所,浙江 嘉兴 314033
2. 通信信息控制和安全技术重点实验室,浙江 嘉兴 314033
[ "张华娣(1978- ),女,广东湛江人,中国电子科技集团公司第三十六研究所高级工程师,主要研究方向为信号处理。" ]
[ "楼华勋(1981- ),男,浙江永康人,中国电子科技集团公司第三十六研究所高级工程师,主要研究方向为信号处理原型产品开发。" ]
网络出版日期:2019-08,
纸质出版日期:2019-08-25
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张华娣, 楼华勋. MQAM信号调制方式自动识别方法[J]. 通信学报, 2019,40(8):200-211.
Huadi ZHANG, Huaxun LOU. Automatic modulation recognition algorithm for MQAM signal[J]. Journal on communications, 2019, 40(8): 200-211.
张华娣, 楼华勋. MQAM信号调制方式自动识别方法[J]. 通信学报, 2019,40(8):200-211. DOI: 10.11959/j.issn.1000-436x.2019168.
Huadi ZHANG, Huaxun LOU. Automatic modulation recognition algorithm for MQAM signal[J]. Journal on communications, 2019, 40(8): 200-211. DOI: 10.11959/j.issn.1000-436x.2019168.
提出了一种实现MQAM信号调制方式自动识别的方法。首先通过四阶累积量构造特征参数F,实现方形QAM和十字形QAM的识别,通过计算零中心归一化瞬时幅度紧致性,把16QAM从方形QAM中识别出来。然后,通过信号包络平方的频谱估算出波特率,结合定时同步,消除ISI码间干扰,恢复出较理想的星座图。接着,针对32QAM和128QAM设置不同的聚类半径,用减法聚类算法求出聚类点及其密度值,通过计算不同半径下的聚类点密度值的差异进行类型判断,同理,进行64QAM和256QAM信号的分类。所提方法不需要载频和波特率等先验信息,能完成16QAM、32QAM、64QAM、128QAM、256QAM信号的自动识别,并且没有复杂的迭代过程,可以应用于实际信号的调制识别。
An automatic modulation recognition algorithm for MQAM signal was proposed.Firstly
the feature parameter F based on the fourth order cumulants was constructed to classify the square QAM and the cross QAM.Secondly
the compactness of zero center normalized instantaneous amplitude was calculated to identify the 16QAM from the square QAM.Thirdly
the baud rate was estimated by frequency spectrum of amplitude square
and timing was synchronized to delete the ISI and resume the relatively ideal constellations.And aiming at the 32QAM and the 128QAM
two different clustering radii were set
and clustering point density was got respectively by the subtractive clustering algorithm
and then the 32QAM and the 128QAM was classified depending on the difference of density value.In the same way
the 64QAM and the 256QAM were classified.The proposed algorithm can recognize five kinds of QAM signals,including 16QAM signals
32QAM signals
64QAM signals
128QAM signal and 256QAM signal without prior knowledge of frequency and baud rate.Furthermore
the proposed algorithm does not need complex iterative process
which can be applied in practical signal recognition.
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