Journal of Terahertz Science and Electronic Information Technology , Volume. 22, Issue 7, 710(2024)
Continuous phase modulation recognition algorithm based on fuzzy entropy
To address the recognition challenge of Multi-h Continuous Phase Modulation (Multi-h CPM) signals with varying modulation parameters, this paper proposes a modulation recognition algorithm grounded in fuzzy entropy theory. This theory transcends the binary approach of distance and count-based similarity in approximate entropy, opting for a membership function to assess similarity and more accurately reflect the complexity of time series. The algorithm separates and calculates the fuzzy entropy of the in-phase and quadrature components of the received signal, utilizing these values as classification features for a Support Vector Machine(SVM). Experiments demonstrate that the algorithm achieves 100% recognition accuracy for full-response rectangular shaped Multi-h CPM signals across various modulation index sets at signal-to-noise ratios above 6 dB, and enables modulation recognition with a minimal number of symbols.
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RUAN Guangxin, LIU Zheng. Continuous phase modulation recognition algorithm based on fuzzy entropy[J]. Journal of Terahertz Science and Electronic Information Technology , 2024, 22(7): 710
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Received: Jul. 11, 2022
Accepted: --
Published Online: Aug. 22, 2024
The Author Email: Zheng LIU (liuzheng@nudt.edu.cn)