No prior recognition method of modulation mode by partition-fractal and SVM learning method

Shanshan Li, Qi Zhang*, Xiangjun Xin, Ran Gao, Sitong Zhou, Ying Tao, Yufei Shen, Huan Chang, Qinghua Tian, Feng Tian, Yongjun Wang, Leijing Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A modulation classification method in combination with partition-fractal and support-vector machine (SVM) learning methods is proposed to realize no prior recognition of the modulation mode in satellite laser communication systems. The effectiveness and accuracy of this method are verified under nine modulation modes and compared with other learning algorithms. The simulation results show when the signal-to-noise ratio (SNR) of the modulated signal is more than 8 dB, the classifier accuracy based on the proposed method can achieve more than 98%, especially when in binary phase shift keying and quadrature amplitude shift keying modes, and the classifier achieves 100% identification whatever the SNR changes to. In addition, the proposed method has strong scalability to achieve more modulation mode identification in the future.

Original languageEnglish
Article number111404
JournalChinese Optics Letters
Volume18
Issue number11
DOIs
Publication statusPublished - 10 Nov 2020

Keywords

  • Free-space optical communication
  • Modulation
  • Pattern recognition

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