MQAM信号调制方式自动识别方法

doi:10.11959/j.issn.1000-436x.2019168

摘要/Abstract

摘要：

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。

关键词: 四阶累积量, 零中心归一化瞬时幅度紧致性, 减法聚类, MQAM, 自动识别

Abstract:

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.

Key words: fourth-order cumulant, compactness of zero center normalized instantaneous amplitude, MQAM, automatic recognition

中图分类号:

TN911

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.

图/表 29

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表9

32QAM信号在2种邻域半径下的聚类点数以及密度值之和"

邻域半径	聚类点数	密度值之和
$\frac{L}{5}$	32	4 540.3
$\frac{L}{11}$	32	3 875.5

表9

图10

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表10

64QAM信号在2种邻域半径下的聚类点数以及密度值之和"

邻域半径	聚类点数	密度值之和
$\frac{L}{7}$	64	4 529 6
$\frac{L}{15}$	65	3 7028

表10

图12

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表11

128QAM信号在2种邻域半径下的聚类点数以及密度值之和"

邻域半径	聚类点数	密度值之和
$\frac{L}{5}$	38	4.3055e+003
$\frac{L}{11}$	128	4.5390e+003

表11

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表12

256QAM信号在2种邻域半径下的聚类点数以及密度值之和"

邻域半径	聚类点数	密度值之和
$\frac{L}{7}$	64	4332.6
$\frac{L}{15}$	256	4484.5

表12

表13

表14

参考文献 17

[1]	曹桂芹, 赵宪臣, 姜士强 ,等. 全数字128QAM 调制解调器的实现与分析[J]. 数字通信技术, 2016(1): 329-331.
	CAO G Q , ZHAO X C , JIANG S Q ,et al. Implementation and analysis of the 128 QAM digital modulator and demodulator[J].,2016(1)：329-331. Digital Communications Technology, 2016(1): 329-331.
[2]	李杰 . 无线通信中的高阶QAM实现技术研究[D]. 成都:电子科技大学, 2016:15.
	LI J . Communication ＆ information system[D]. Chengdu：University of Electronic Science and Technology of China, 2016:15.
[3]	褚衍杰, 胡年福, 巢凯今 ,等. 通带MQAM信号调制方式识别方法[J]. 西安电子科技大学学报(自然科学版), 2008,35(5): 932-937.
	CHU Y J , HU N F , CHAO K J ,et al. Modulation recognition of MQAM signals in the passband[J]. Journal of Xi’dian University, 2008,35(5): 932-937.
[4]	张弛, 吴瑛 . 方形 QAM 信号的识别算法[J]. 计算机工程与设计, 2009,30(18): 4155-4157.
	ZHANG C , WU Y . Method of square QAM signals recognition[J]. Computer Engineering and Design, 2009,30(18): 4155-4157.
[5]	刘聪杰, 彭华, 吴迪 ,等. 突发自适应调制信号的调制识别算法研究[J]. 信号处理, 2012,28(3): 417-424.
	LIU C J , PENG H , WU D ,et al. Modulation recognition algorithm of burst adaptive modulation signal[J]. Signal Processing, 2012,28(3): 417-424.
[6]	张路平, 王建新 . MQAM信号调制方式盲识别[J]. 电子与信息学报, 2011,33(2): 332-336.
	ZHANG L P , WANG J X . Blind modulation recognition algorithm for MQAM signals[J]. Journal of Electronics ＆ Information Technology, 2011,33(2): 332-336.
[7]	李东波, 欧阳喜 . 一种抗频偏的常见幅相调制信号识别算法[J]. 信息工程大学学报, 2018,19(1): 42-46.
	LI D B , OUYANG X . Anti-frequency-offset algorithm for modulation recognition of common amplitude-phase modulated signals[J]. Journal of Information Engineering University, 2018,19(1): 42-46.
[8]	XIAO D M , XU Z , ZHAO X Y ,et al. Modulation classification of MQAM signals based on higher-order cumulant and subtractive clustering[C]// 2016 International Conference on Computer Engineering,Information Science and Internet Technology (CII 2016). 2016: 66-73.
[9]	曹颖, 周丽丽, 王晓亚 . 高阶QAM信号调制样式识别算法研究[J]. 火控雷达技术, 2013,42(2): 23-26.
	CAO Y , ZHOU L L , WANG X Y . Blind modulation recognition algorithm for MQAM signals[J]. Fire Control Radar Technology, 2013,42(2): 23-26.
[10]	MU X D , ZENG X , YI Z X ,et al. Modulation classification of MQAM signals based on higher-order cumulant and subtractive clustering[C]// 2016 International Conference on Computer Engineering,Information Science and Internet Technology(CII 2016).ISBN:978-1-60595-348-9: 66-73.
[11]	张华娣, 楼华勋, .一种QAM信号类内识别新方法[C]// 2017全国电子战学术交流大会论文集. 2017: 427-432.
	ZHANG H D , LOU H X . A new modulation classification method of the QAM signal[C]// Proceedings of China Academic Exchange on Electronic Warfare. 2017: 427-432.
[12]	杨杰, 刘珩, 卜祥元 ,等. 通信信号调制识别原理与算法[M]. 北京: 人民邮电出版社, 2014: 85-86.
	YANG J , LIU H , PO X Y ,et al. Modulation recognition for communication signals[M]. BeiJing: Posts ＆ Telecom PressPress, 2014: 85-86.
[13]	赵雄文, 郭春霞, 李景春 . 基于高阶累积量和循环谱的信号调制方式混合识别算法[J]. 电子与信息学报, 2016,38(3): 674-680.
	ZHAO X W , GUO C X , LI J C . Mixed recognition algorithm for signal modulation schemes by high-order cumulants and cyclic spectrum[J]. Journal of Electronics ＆ Information Technology, 2016,38(3): 674-680.
[14]	范海波, 杨志俊, 曹志刚 . 卫星通信常用调制方式的自动识别[J]. 通信学报, 2004,25(1): 140-149.
	FAN H B , YANG Z J , CAO Z G . Automatic recognition for common used modulations in satellite communication[J]. Journal on Communications, 2004,25(1): 140-149.
[15]	王彬, 葛临东, 徐立清 . 一种多径信道中的调制识别算法[J]. 数据采集与处理, 2007,22(4): 440-446.
	WANG B , GE L D , XU L Q . Algorithm for modulation classification in multi-path channels[J]. Journal of Data Acquisition＆Processing, 2007,22(4): 440-446.
[16]	张东坡, 陈允锋, 李新付 ,等. 基于星座图的 QAM 信号调制方式识别[J]. 通信对抗, 2006(1): 8-11.
	ZHANG D P , CHEN Y F , LI X F ,et al. The recognition of QAM signal based on constellation diagram[J]. Communication Countermeasures, 2006(1): 8-11.
[17]	詹亚锋, 曹志刚, 马正新 . M-QAM 信号的调制制式识别[J]. 通信学报, 2004,25(2): 68-74.
	ZHAN Y F , CAO Z G , MA Z X . Modulation classification of M-QAM signals[J]. Journal on Communications, 2004,25(2): 68-74.

信号类型	\|C₂₀\|	\|C₄₀\|	\|C₄₂\|	\|C₆₃\|
16QAM	0.000 0	0.680 0	0.680 0	2.080 0
32QAM	0.000 0	0.190 0	0.690 0	2.110 0
64QAM	0.000 0	0.619 0	0.619 0	1.797 2
128QAM	0.000 0	0.181 4	0.657 4	1.959 4
256QAM	0.000 0	0.604 7	0.604 7	1.734 5

幅度	概率分布
0.333 3	0.25
0.745 4	0.5
1.000 0	0.25

幅度	概率分布
0.142 8	0.064 7
0.319 4	0.124 3
0.428 6	0.061 3
0.515 1	0.119 6
0.589 0	0.124 5
0.714 3	0.186 0
0.769 4	0.121 8
0.869 0	0.131 3
1.000 0	0.066 4

幅度	概率分布
0.066 7	0.015 6
0.149 1	0.031 3
0.200 0	0.015 6
0.240 4	0.031 3
0.274 9	0.031 3
0.333 0	0.046 9
0.359 0	0.031 3
0.405 5	0.031 3
0.426 9	0.031 3
0.447 2	0.031 3
0.466 7	0.015 6
0.485 3	0.031 3
0.520 7	0.031 3
0.537 5	0.062 5
0.569 6	0.031 3
0.600 0	0.015 6
0.614 6	0.062 5
0.628 9	0.031 3
0.656 6	0.031 3
0.670 0	0.031 3
0.696 0	0.031 3
0.708 7	0.031 3
0.721 1	0.031 3
0.733 3	0.015 6
0.745 4	0.062 5
0.780 3	0.031 3
0.802 8	0.031 3
0.824 6	0.031 3
0.866 7	0.015 6
0.876 9	0.031 3
0.935 7	0.031 3
1.000 0	0.015 6

信号类型	频率粗估计值/MHz	频率精确估计值/MHz	带宽估计值/MHz	特征参数F
16QAM	0.951 8	0.999 995	0.284 73	0.983 5
32QAM	1.009 5	1.000 002	0.288 15	0.287 3
64QAM	1.030 0	1.000 000	0.293 58	1.018 7
128QAM	1.046 0	0.999 996	0.291 75	0.215 7
256QAM	1.077 6	0.999 999	0.286 93	0.983 0