{"title":"Modulation identification of digital M-ary QAM signals by Hilbert-Huang Transform","authors":"Yesim Hekim Tanc, A. Akan","doi":"10.1109/ICECS.2013.6815505","DOIUrl":null,"url":null,"abstract":"The problem of identifying the modulation types of the signals at the receiver is an intermediate step between signal detection and demodulation. In this paper, Hilbert-Huang Transform is proposed for identifying the modulation level of M-ary Quadrature Amplitude Modulation (QAM) signals in the presence of the Additive White Gaussian Noise. Hilbert-Huang Transform decomposes the non-stationary signal into sum of oscillatory signals with different frequency and obtains the instantaneous features of the signals, like time-frequency and time-amplitude information. The statistical properties of instantaneous data sets are used to determine the modulation levels of M-ary QAM signals. The most important feature of the proposed method is that, the algorithm does not utilize any a priori knowledge about the signal. Computer simulations demonstrate the accuracy of the proposed algorithm.","PeriodicalId":117453,"journal":{"name":"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS.2013.6815505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The problem of identifying the modulation types of the signals at the receiver is an intermediate step between signal detection and demodulation. In this paper, Hilbert-Huang Transform is proposed for identifying the modulation level of M-ary Quadrature Amplitude Modulation (QAM) signals in the presence of the Additive White Gaussian Noise. Hilbert-Huang Transform decomposes the non-stationary signal into sum of oscillatory signals with different frequency and obtains the instantaneous features of the signals, like time-frequency and time-amplitude information. The statistical properties of instantaneous data sets are used to determine the modulation levels of M-ary QAM signals. The most important feature of the proposed method is that, the algorithm does not utilize any a priori knowledge about the signal. Computer simulations demonstrate the accuracy of the proposed algorithm.