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常用多进制数字调制信号的识别方法 被引量:1

Recognition of Commonly-used M-ary Digital Modulations
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摘要 针对常用的多进制数字调制信号,设计了一通用的数字调制识别方案:先用三个时频域特征参数进行调制的大类识别,再利用各自算法估计信号调制阶数,修正了MFSK信号功率谱谱峰个数的估计算法,并提出了MASK/MQAM基于时域的调制阶数识别算法。仿真结果表明,在信噪比大于6dB时,该识别结构和识别算法对MFSK、MPSK、MASK调制信号的正确识别率不低于92%,MQAM识别算法则要求较高的信噪比。 A general digital modulation recognition method is proposed for common M-ary digital modulations. A coarse recognition is executed, then different algorithms are used to estimate the order of modulation. Estimation on the number of spectrum peaks is modified and a novel recognition algorithm for modulation order of MASK and MQAM is presented. Simulations results show that the recognition rate for this recognition structure and algorithm can reach 92% for MFSK, MPSK and MASK when the SNR is above 6 dB, and for MQAM, a higher SNR is required.
出处 《通信技术》 2008年第10期41-43,共3页 Communications Technology
关键词 调制识别 瞬时特征 谱特征 判决器 modulation recognition instantaneous feature spectrum feature decision tree
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  • 1[1]NANDI A K, AZZOUZ E E. Automatic analogue modulation recognition[J]. Signal Processing 1995,46(2):211-222.
  • 2[2]NANDI A K, AZZOUZ E E. Algorithms for automatic modulation recognition of communication siganls[J]. IEEE Trans Commun, 1998, 46(4): 431-436.
  • 3[3]SWAMI A, SADLER B M. Hierarchical digital modulation classification using cumulates[J]. IEEE Trans Commun, 2000, 48(3): 416-429.
  • 4[4]GARDNER W A, SPOONER C M. Cyclic-spectral analysis for signal detection and modulation recognition[A]. MILCOM'88[C]. 1988. 419-424.
  • 5[5]DUBUC C, BOUDREAU D. An automatic modulation recognition algorithm for spectrum monitoring applications[A]. IEEE International Conference on Communications (ICC'99)[C]. Vancouver, Canaada, 1999.732-736.
  • 6[6]CHLAN Y T, GADBOIS L G Identification of the modulation type of a signal[J]. Signal Processing, 1989,16(2):149-154.
  • 7Nandi A K,Azzouz E E.Algorithms for automatic modulation recognition of communication signals[J].IEEE Trans Comm,1998,46(4):431-436.
  • 8Wong M L D,Nandi A K.Automatic digital modulation recognition using spectral and statistical features with multi-layer perceptrons[A].In Proc of Sixth International Symposium on Signal Processing and its Applications (ISSPA' 01)[C].Kuala Lumpur,Malaysia,13-16 vol.2:August,2001.390-393.
  • 9Zhao Y Q,Ren G H,Wang X X,et al.Automatic digital modulation recognition using artificial neural networks[A].In Proc of IEEE Int Conf Neural Networks & Signal Processing[C].Nanjing,China,Dec.14-17,2003.257-260.
  • 10Dubuc C,Boudreau D.An automatic modulation recognition algorithm for spectrum monitoring applications[A].In Proc of IEEE International Conference on Communications (ICC' 99)[C].Vancouver,Canada,1999.732-736.

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  • 1YIN C Y, LI B B, LI Y L. Modulation Classifi-cation of MQAM Signals from their ConstellationUsing Clustering [C] / / the 2nd InternationalConference on Communications Software andNetworks. Singapore:IEEE, 2010:303-306.
  • 2YANG Y, LIU C H, S00NG T W. A Log-1 ikelihoodFunction-based Algorithm for QAM SignalClassification[J]. Signal Processing, 1998, 70(01):61-71.
  • 3MOBASSERI B G. Digital Modulation ClassificationUsing Constellation Shape[J]. Signal Processing,2000,80(02) :251-277.
  • 4HELMY M 0,ZAKI F ff. Identification of LinearBi-dimentional Digital Modulation Schemes ViaClustering Algorithms[C]//the InternationalConference on Computer Engineering & Systems.Cario, Egypt: IEEE, 2009:385-390.
  • 5AHMADI N, BERANGI R. Modulation Classificationof QAM and PSK from their Constellation UsingGenetic Algorithm and Hierarchical ClusteringfC]//the 3rd International Conference on Informationand Communication Technologies: From Theory toApplications. Damascus, Syrima: IEEE, 2008:1-5.
  • 6FRISCH M, MESSER H. The Use of the WaveletTransform in the Detection of an UnknownTransient Signal[J]. IEEE Trans, on InformationTheory, 1992,38(02) :892-897.
  • 7XU J, WANG F P, WANG Z J. The Improvement ofSymbol Rate Estimation by the WaveletTransform[C]// Proc. of the InternationalConference on Communications, Circuits andSystems. Atlanta, GA, USA: IEEE, 2005:100-103.
  • 8CHIU S. Fuzzy Model Identification based onCluster Estimation[J]. Journal of Intelligentand Fuzzy system, 1994,2(03) :267-278.
  • 9侯健,王华奎.一种基于星座图聚类的MQAM识别方法[J].无线电通信技术,2009,35(3):35-38. 被引量:12
  • 10徐斌,雷菁,李保国.一种数字信号调制方式识别方法[J].通信技术,2011,44(11):23-24. 被引量:5

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