A NOVEL AUTOMATIC MODULATION CLASSIFICATION FOR M-QAM SIGNALS USING ADAPTIVE FUZZY CLUSTERING MODEL

被引：0
作者：
Zhang, Guo-Yu [1 ]
Yan, Xiao [1 ]
Wang, Shi-Hao [2 ]
Wang, Qian [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Aeronaut & Astronaut, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China
来源：
2018 15TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2018年
关键词：
Modulation classification; M-ary quadrature Amplitude modulation (M-QAM); Subtractive clustering; Adaptive neighborhood radius; Euclidean distance;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An automatic modulation classification (AMC) method for M-ary Quadrature Amplitude Modulation (M-QAM) signals using adaptive fuzzy clustering model is presented. In the proposed framework, the neighborhood radius of subtractive clustering algorithm is emphatically researched to satisfy different modulation orders. An adaptive construction mechanism of neighborhood radius is designed according to the amplitude component of M-QAM signals. Euclidean distance of the clustering center numbers between test signal and standard signals are utilized to identify the modulation types. Monte Carlo simulation results and theoretical analysis demonstrate that the proposed AMC method can provide promising performance.
引用
收藏
页码：45 / 48
页数：4
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