| 基于半监督聚类理论的MQAM信号的盲识别 |
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| 引用本文： | 李苹苹,孙钢灿,申金媛,刘润洁.基于半监督聚类理论的MQAM信号的盲识别[J].青岛化工学院学报(自然科学版),2014(4):405-409. |
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| 作者姓名： | 李苹苹 孙钢灿 申金媛 刘润洁 |
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| 作者单位： | 郑州大学信息工程学院,河南郑州450001 |
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| 基金项目： | 国家自然科学基金项目（U1204604,61172086）;中国博士后基金项目（2012M511587）;河南省博士后基金项目（2011829）;河南省青年骨干教师基金项目（2013GGJS-002）. |
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| 摘 要： | 在MQAM信号的调制识别中,传统聚类算法聚类效果差,误差平方和函数出现起伏且收敛慢.对此问题,提出由标记的样本点来指导隶属度及聚类中心的更新的半监督聚类理论重构MQAM信号星座图的方法.通过分析星座图,提出了基于星座图圆半径的识别方法,完成了对不同阶数MQAM信号调制方式的识别.仿真结果表明该方法提高了聚类准确度,误差平方和函数曲线平滑,且MQAM信号的识别率在90％以上.
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| 关 键 词： | 调制识别 MQAM信号 半监督聚类 星座图圆半径 |
Blind Recognition of MQAM Signals Based on Semi-supervised Clustering Theory |
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| LI Ping-ping,SUN Gang-can,SHEN Jin-yuan,LIU Run-jie.Blind Recognition of MQAM Signals Based on Semi-supervised Clustering Theory[J].Journal of Qingdao Institute of Chemical Technology(Natural Science Edition),2014(4):405-409. |
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| Authors: | LI Ping-ping SUN Gang-can SHEN Jin-yuan LIU Run-jie |
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| Institution: | (School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China) |
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| Abstract: | In the modulation classification of MQAM signals, traditional clustering algo- rithm results is poor, squared error function appears downs and slow convergence. To solve this problem, We proposed a method by the labeled samples to guide the membership degree and the clustering center update for reconstruction MQAM signal constella- tion based on semi supervised clustering theory. Through analysis the constellation, recognition method is proposed based on constellation radius, completed the recognition of the different orders of MQAM signal modulation. Simulation results show that this method improves the accuracy of clustering; the squared error function curve is smooth, and the recognition rate MQAM signals above 90%. |
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| Keywords: | modulation classification MQAM signals semi-supervised clustering con-stellation radius |
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