Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics

CHEN Hong; CAI Xiaoxia; XU Yun; LIU Wentao

doi:10.11999/JEIT150703

Volume 38 Issue 4

Apr. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(4): 863-869

CHEN Hong, CAI Xiaoxia, XU Yun, LIU Wentao. Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics[J]. Journal of Electronics & Information Technology, 2016, 38(4): 863-869. doi: 10.11999/JEIT150703

Citation:

CHEN Hong, CAI Xiaoxia, XU Yun, LIU Wentao. Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics[J]. Journal of Electronics & Information Technology, 2016, 38(4): 863-869. doi: 10.11999/JEIT150703

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Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics

doi: 10.11999/JEIT150703

1.
(PLA Electronic Engineering Institute, Hefei 230037, China)
2.
(Unit 95915 of PLA, Tianjin 301612, China)

Funds:

The National Natural Science Foundation of China (61571446), The Natural Science Foundation of Anhui Province (KY13C152)

Received Date: 2015-06-08
Rev Recd Date: 2015-12-11
Publish Date: 2016-04-19

Abstract

Abstract

A new modulation recognition algorithm of digital communication signals based on the multi-fractal dimension characteristics is proposed. Employing preprocessing the received signal, the generalized dimension and the multi-fractal spectrum can be calculated by 2D data array. The effect of multi-fractal spectrum due to the weighted factorsq is discussed in detail, the 13 multi-fractal characteristic parameters are extracted. The Support Vector Machine (SVM) classifier based on the multi-fractal dimension characteristics is designed for recognition of different modulation signals. Simulation results show that the proposed method has a good recognition performance under low SNR.
- Modulation recognition,
- Multi-fractal dimension characteristics,
- Generalized dimension,
- Support Vector Machine (SVM)

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References(32)

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