广西师范大学学报（自然科学版） ›› 2016, Vol. 34 ›› Issue (2): 35-45.doi: 10.16088/j.issn.1001-6600.2016.02.006

• • 上一篇    下一篇

一种新的基于小波变换的QPSK信号解调方法

陈锦, 罗晓曙   

  1. 广西师范大学电子工程学院,广西桂林541004
  • 收稿日期:2015-12-10 出版日期:2016-06-25 发布日期:2018-09-14
  • 通讯作者: 罗晓曙(1961—),男,湖北应城人,广西师范大学教授,博士。E-mail:lxs@mailbox.gxnu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(11262004)

A Novel QPSK Signal Demodulation Method Based on Wavelet Transform

CHEN Jin, LUO Xiaoshu   

  1. College of Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004,China
  • Received:2015-12-10 Online:2016-06-25 Published:2018-09-14

PDF (PC)

250

摘要： 本文根据小波变换具有时频分析的特点,提出一种通信系统中QPSK(quadrature phase shift keying)信号解调的新方法。该信号解调新方法与传统的QPSK相干解调方式不同之处在于,首先它是直接对接收到的QPSK信号中的频率和相位(相当于瞬时值)进行提取和判决,是一种具有多分辨特性的时频分析检波方法;其次,发送端信号和接收端信号之间不需要严格同步,是一种“盲检测”方法。仿真结果表明:该新的信号解调方法在抗噪声性能和抗复杂信道的鲁棒性等方面具有比传统解调方法更优异的性能。

关键词: 小波变换, 时频分析, QPSK, 盲检测, 鲁棒性。

Abstract: According to the characteristics of the time-frequency analysis of the wavelet transform, a novel QPSK(quadrature phase shift keying) signal demodulation method in the communication system is proposed. The novel demodulation method for QPSK signal is different from the traditional demodulation method. First of all, it can directly extract and decide the frequency and phase (equivalent to the instantaneous value) of the received QPSK signal and it is a time-frequency detection method which has the multi-resolution properties; second, it is a "blind detection" method without strict synchronization between the transmitter signal and receiver signal. The computer simulation results show that the novel signal demodulation method has better performance than the traditional one in anti-noise property and robustness of anti complex channel.

Key words: wavelet transform, time-frequency analysis, QPSK, blind detection, robustness

中图分类号: 

  • TN911
[1] 陈健,阔永红,李建东,等.基于小波变换的数字调制信号识别方法的研究[J].电子与信息学报, 2006, 28(11): 2026-2029.
[2] 高勇,黄振,陆建华.基于小波变换的MDPSK信号盲解调算法[J].清华大学学报(自然科学版),2009,49(8): 1172-1175. DOI:10.16511/j.cnki.qhdxxb.2009.08.018.
[3] 王红星,王洪利,毛忠阳.基于时频分布的扩展的二元相移键控信号解调算法[J].吉林大学学报(工学版), 2011, 41(5): 1491-1496. DOI:10.13229/j.cnki.jdxbgxb2011.05.024.
[4] GAO Yong, LI Mu, HUANG Zhen, et al. A symbol rate estimation algorithm based on Morlet wavelet transform and autocorrelation [C]//IEEE Youth Conference on Information, Computing and Telecommunication. Piscataway, NJ: IEEE Press, 2009: 239-242. DOI:10.1109/YCICT.2009.5382378.
[5] HOSSEN A, AL-WADAHI F. A two-stage network for modulation classification based on entropy of wavelet transform[C]//Proceedings of 3rd International Conforence: Sciences of Electronic,Technologies of Information and Telecommunications,TUNISIA,2005,27-31.
[6] MENG Lingling, SI Xiujie. An improved algorithm of modulation classification for digital communication signals based on wavelet transform[C]//2007 International Conference on. Wavelet Analysis and Pattern Recognition: Volume 3. Piscataway, NJ:IEEE Press, 2007: 1226-1231. DOI:10.1109/ICWAPR.2007.4421621.
[7] HO K M. Automatic recognition and demodulation of digitally modulated communications signals using wavelet- domain signatures[D]. New Brunswick, NJ: Rutgers University, 2010. DOI:10.7282/T3XS5VJT.
[8] 袁晔, 梅文博. 基于时频域特征和分层决策的通信信号调制识别[J]. 系统工程与电子技术, 2005, 27(6): 991-994.
[9] 冯旭哲, 杨俊, 罗飞路. 基于小波变换的通信信号码元速率估计[J]. 系统仿真学报, 2008, 20(5): 1259-1261, 1320. DOI:10.16182/j.cnki.joss.2008.05.023.
[10] HO K C, PROKOPIW W, CHAN Y T. Modulation identification of digital signals by the wavelet transform[J].IEE Proceedings: Radar, Sonar and Navigation, 2000, 147(4): 169-176. DOI:10.1049/ip-rsn:20000492.
[11] 欧鑫, 黄小蔚, 袁晓, 等. 类 Haar 小波与数字信号调制识别[J]. 四川大学学报(工程科学版), 2004, 36(4): 95-98.
[12] WANG Long, ZHANG Gengxin, BIAN Dongming, et al. Blind symbol rate estimation of satellite communication signal by Haar wavelet transform[J]. Journal of Electronics (China), 2011, 28(2): 198-203. DOI:10.1007/s11767-011-0592-y.
[13] ZHANG Damin, WANG Xu. MPSK signal modulation recognition based on wavelet transformation[C]//2009 International Conference on Networking and Digital Society: Volume 1. Piscataway, NJ: IEEE Press, 2009: 202-205. DOI:10.1109/ICNDS.2009.56.
[14] HO K C, PROKOPIW W, CHAN Y T. Modulation identification by the wavelet transform[C]//1995 Conference Record of IEEE Military Communications Conference: Volume 2. Piscataway, NJ:IEEE Press, 1995: 886-890. DOI:10.1109/MILCOM.1995.483654.
[15] HONG L, HO K C. Identification of digital modulation types using the wavelet transform[C]//1999 IEEE Military Communications Conference Proceedings: Volume 1. Piscataway, NJ:IEEE Press, 1999: 427-431. DOI:10.1109/MILCOM.1999.822719.
[16] 陈锦,张晗博,殷奕,等.一种新的小波阈值去噪方法研究[J].信息化研究,2014,40(3):13-17.
[17] PRANKASAM P, MADHESWARAN M. Automatic modulation identification of QPSK and GMSK using wavelet transform for adaptive demodulator in SDR[C]//2007 International Conference on Signal Processing, Communications and Networking. Piscataway, NJ: IEEE Press, 2007: 507-511. DOI:10.1109/ICSCN.2007.350651.
[18] CHEN Jian, KUO Yonghong, LI Jiandong, et al. Digital modulation identification by wavelet analysis[C]//Proceedings of Sixth International Conference on Computational Intelligence and Multimedia Applications. Los Alamitos, CA:IEEE Computer Society Press, 2005: 29-34. DOI:10.1109/ICCIMA.2005.23.
[19] 苏志金, 许建华, 韩民. 基于小波变换的MPSK 短信号符号率估计[J]. 电子测量与仪器学报, 2013, 27(2): 140-144. DOI: 10.3724/SP.J.1187.2013.00140.
[1] 许伦辉, 陈凯勋. 基于改进萤火虫算法优化BP神经网络的路网速度分布预测[J]. 广西师范大学学报（自然科学版）, 2019, 37(2): 1-8.
[2] 周克良, 邢素林, 聂丛楠. 基于自适应阈值小波变换的心音去噪方法[J]. 广西师范大学学报（自然科学版）, 2016, 34(1): 19-25.
[3] 胡沁春, 何怡刚, 何静. 基于开关电流电路的时域高斯类小波变换实现[J]. 广西师范大学学报（自然科学版）, 2013, 31(4): 18-22.
[4] 周炎岩, 冯嘉礼. 基于定性映射的数字音频水印算法[J]. 广西师范大学学报（自然科学版）, 2011, 29(2): 200-204.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 广西师范大学学报（自然科学版）编辑部
地址：广西桂林市三里店育才路15号　邮编：541004
电话：0773-5857325　E-mail: gxsdzkb@mailbox.gxnu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发