{"title":"A New Digital Modulation Recognition Technique Using the Phase Detector Reliability","authors":"Adel Metref, Daniel Le Guennec, J. Palicot","doi":"10.1109/AICT.2010.82","DOIUrl":null,"url":null,"abstract":"A new feature based digital modulation identification algorithm has been developed and presented in this paper. The algorithm developed uses the reliability of a decision-directed (DD) phase detector as a modulation scheme classification feature. Unlike feature based methods found in literature, the classification decision of the proposed algorithm does not rely on decision thresholds. Simulation results covering 64-QAM, 16-QAM, 16-APSK and 8-PSK modulation schemes show promising identification statistics with high probability of correct classification in the presence of noise even with high order modulation schemes.","PeriodicalId":339151,"journal":{"name":"2010 Sixth Advanced International Conference on Telecommunications","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Sixth Advanced International Conference on Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICT.2010.82","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
A new feature based digital modulation identification algorithm has been developed and presented in this paper. The algorithm developed uses the reliability of a decision-directed (DD) phase detector as a modulation scheme classification feature. Unlike feature based methods found in literature, the classification decision of the proposed algorithm does not rely on decision thresholds. Simulation results covering 64-QAM, 16-QAM, 16-APSK and 8-PSK modulation schemes show promising identification statistics with high probability of correct classification in the presence of noise even with high order modulation schemes.