M. Niroomand, M. Derakhtian, Assieh Shahimaeen, S. Gazor
{"title":"Adaptive blind equalization for QAM modulated signals in the presence of frequency offset","authors":"M. Niroomand, M. Derakhtian, Assieh Shahimaeen, S. Gazor","doi":"10.1109/WOSSPA.2011.5931457","DOIUrl":null,"url":null,"abstract":"In this paper, we present an adaptive blind equalization for the frequency selective channel in the presence of the frequency offset. The adaptive recursions is based on the pseudo Newton method with stochastic gradient algorithm initialization (PNSI). We employ a the second order phase lock loop (PLL) to recover the frequency offset. We introduce a pseudo maximum likelihood (ML) method to estimate the frequency offset. The recovered symbols from these methods are compared by simulations which reveal the superiority of the proposed pseudo ML algorithm.","PeriodicalId":343415,"journal":{"name":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2011.5931457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we present an adaptive blind equalization for the frequency selective channel in the presence of the frequency offset. The adaptive recursions is based on the pseudo Newton method with stochastic gradient algorithm initialization (PNSI). We employ a the second order phase lock loop (PLL) to recover the frequency offset. We introduce a pseudo maximum likelihood (ML) method to estimate the frequency offset. The recovered symbols from these methods are compared by simulations which reveal the superiority of the proposed pseudo ML algorithm.