Volume 41 Issue 6
Nov.  2021
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Article Navigation >  Chinese Journal of Space Science  > 2021  >  41(6): 968-975
YAN Wenkang, YAN Yi, FAN Yanan, YAO Xiujuan, GAO Xiang, SUN Wen. A Modulation Recognition Algorithm Based on Wavelet Transform Entropy and High-order Cumulant for Satellite Signal Modulation[J]. Chinese Journal of Space Science, 2021, 41(6): 968-975. doi: 10.11728/cjss2021.06.968
Citation: YAN Wenkang, YAN Yi, FAN Yanan, YAO Xiujuan, GAO Xiang, SUN Wen. A Modulation Recognition Algorithm Based on Wavelet Transform Entropy and High-order Cumulant for Satellite Signal Modulation[J]. Chinese Journal of Space Science, 2021, 41(6): 968-975. doi: 10.11728/cjss2021.06.968
shu

A Modulation Recognition Algorithm Based on Wavelet Transform Entropy and High-order Cumulant for Satellite Signal Modulation

doi: 10.11728/cjss2021.06.968 cstr: 32142.14.cjss2021.06.968

  • 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;

  • 2. University of Chinese Academy of Sciences, Beijing 100049

  • Received Date: 2020-07-13
  • Rev Recd Date: 2021-03-31
  • Publish Date: 2021-11-15
    Abstract
  • Modulation recognition is the key link of signal detection and demodulation. Aiming at MAPSK, MQAM, MFSK and MPSK modes used in satellite modulation, a joint modulation recognition algorithm is proposed, which calculates the entropy of wavelet transform and combines highorder cumulant. According to the characteristics of the wavelet transform pair frequency sensitive information, different modulation method to distinguish the results of the calculation of higher-order cumulant and the modulation signal of different complexity entropy results, the calculation results of the above four 4 kinds of modulation signal are analyzed, and entropy is proposed based on wavelet transform and higher-order cumulants joint satellite signal modulation recognition algorithm. Based on the calculated wavelet coefficients of modulation signals, the classification of modulation signals is realized by calculating the entropy value, and the signal classification within the class is realized by using the high-order cumulant. Through simulation analysis, the recognition effect of 0.9 above 8 dB can be achieved. In addition, the method has reference significance for high order (64 order modulation) signals.

     

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