Title: Modulation Classification of MFSK Modulated Signals Using Wavelet Decomposition

Abstract: In this study,a wavelet decomposition based method is proposed for determining the modulation type of the incoming signal to the receiver which is one of the important problems in intelligent communication systems. In this method, it is aimed to design the transmitted signal for determining the type of Mary FSK modulated signal and to detect the energy in each frequency band by using Discrete Wavelet Transform (DWT). For this, standard deviations in the lower bands are as features. In order to evaluate the performance of the classifier, simulation studies have been performed at different signal-to-noise ratio (SNR) levels. When the results for different frequency settings, i.e. carrier frequency and frequency range, it is seen that the classifier using the K-means clustering algorithm has a higher correct classification performance than the results reported in the literature when the suitable carrier frequency and frequency range are selected.

Keywords: M-ary frequency shift keying (MFSK); discrete wavelet transform; wavelet decomposition; k-means clustering algorithm

Başlık: MFSK Kiplenimli İşaretlerde Dalgacık Ayrıştırması Kullanarak Kiplenim Sınıflandırılması

Özet: Bu çalışmada, akıllı haberleşme sistemlerindeki önemli problemlerden birisi olan alıcıya gelen işarete ait kiplenim türünün belirlenmesi için dalgacık ayrıştırması tabanlı bir yöntem önerilmiştir. Bu yöntemde amaç, M-seviyeli frekans kaydırmalı anahtarlamaya sahip (M-ary FSK) işaretlerde kiplenim türünün tespit edilmesi için gönderici işaretin tasarlanması ve Ayrık Dalgacık Dönüşümü (ADD) ile her bir frekans bandına düşen enerjilerin tespit edilmesidir. Bunun için alt bandlardaki işaretlerin standart sapmaları öznitelik olarak kullanılmıştır. Sınıflandırıcının performansını değerlendirmek için farklı işaret gürültü oranı (SNR) seviyelerinde benzetim çalışmaları yapılmıştır. Frekans aralığı değiştirilerek elde edilen sonuçlar karşılaştırıldığında, uygun taşıyıcı frekansı ve frekans aralığı seçildiğinde K-ortalama kümeleme algoritması kullanan sınıflandırıcının literatürde raporlanan sonuçlara göre daha yüksek doğru sınıflandırma başarımına sahip olduğu görülmektedir.

Anahtar kelimeler: M-seviyeli frekans kaydırmalı anahtarlama (MFSK); ayrık dalgacık dönüşümü; dalgacık ayrıştırması; k-ortalama kümeleme algoritması

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