{"title":"Novel polyphase training sequence based synchronization estimator for OFDM","authors":"G. Potnis, D. Jalihal","doi":"10.1109/NCC.2011.5734711","DOIUrl":null,"url":null,"abstract":"Orthogonal Frequency Division Multiplexing (OFDM) systems are sensitive to timing and frequency estimation errors. A DFT spread modified polyphase training sequence is proposed which has better merit factor and peak to average power ratio. By using the proposed training sequence two estimators are presented for timing and frequency synchronization. The CRLB expressions in closed form for these two estimators are also presented under the assumption of strict decoupling of timing and frequency offsets. Simulation results show that the MSE of the proposed estimators follow their respective CRLB","PeriodicalId":158295,"journal":{"name":"2011 National Conference on Communications (NCC)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2011.5734711","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
Orthogonal Frequency Division Multiplexing (OFDM) systems are sensitive to timing and frequency estimation errors. A DFT spread modified polyphase training sequence is proposed which has better merit factor and peak to average power ratio. By using the proposed training sequence two estimators are presented for timing and frequency synchronization. The CRLB expressions in closed form for these two estimators are also presented under the assumption of strict decoupling of timing and frequency offsets. Simulation results show that the MSE of the proposed estimators follow their respective CRLB
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