Type of modulation identification using Wavelet Transform and Neural Network

• Autorzy: Walenczykowska M. , Kawalec A.

Identyfikatory

DOI

10.1515/bpasts-2016-0028

• Języki publikacji: EN

Abstrakty

EN

Automatic recognition of the signal modulation type turned out to be useful in many areas, including electronic warfare or surveillance. The wavelet transform is an effective way to extract signal features for identification purposes. In this paper there are M-ary ASK, M-ary PSK, M-ary FSK, M-ary QAM, OOK and MSK signals analysed. The mean value, variance and central moments up to five of continuous wavelet transform (CWT) are used as signal features. The principal component analysis (PCA) is applied to reduce a number of features. A multi-layer neural network trained with backpropagation learning algorithm is considered as a classifier. There are two research variants: interclass and intraclass recognition with a wide range of signal-to-noise ratio (SNR).

Słowa kluczowe

EN

modulation identification; artificial neural networks; continuous wavelet transform (CWT)

PL

identyfikacja modulacji; sztuczne sieci neuronowe (SSN); transformacja falkowa (CWT)

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2016
• Tom: Vol. 64, nr 1
• Strony: 257--261
• Opis fizyczny: Bibliogr. 19 poz., wykr., tab.

Twórcy

autor

Walenczykowska M.

• Institute of Radioelectronics, Military University of Technology, 2 Gen. Sylwestra Kaliskiego St., 00-980 Warsaw, Poland

autor

Kawalec A.

• Institute of Radioelectronics, Military University of Technology, 2 Gen. Sylwestra Kaliskiego St., 00-980 Warsaw, Poland

Bibliografia

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• [16] M. Walenczykowska and A. Kawalec, “Modulation type recognition based on wavelet transform and neural network”, Electronics - Constructions, Technologies, Behaviours 53, 120-123 (2012), (in Polish).
• [17] M. Walenczykowska and A. Kawalec, “Analysis of automatic modulation recognition algorithm for Cognitive Radio (CR) and radio intelligence (SIGINT)”, Electronics - Constructions, Technologies, Behaviours 56, 36-39 (2015), DOI:10.15199/13.2015.4.7.
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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.