{"title":"Wireless device identification in MIMO channels","authors":"Ming-Wei Liu, J. Doherty","doi":"10.1109/CISS.2009.5054783","DOIUrl":null,"url":null,"abstract":"A data-aided iterative algorithm to estimate the nonlinearities of wireless emitters for Specific emitter Identification (SEI) is presented. To achieve robust estimation, Inter Symbol Interference (ISI) is removed by iteratively estimating the channel coefficients and nonlinear transmit symbols to achieve asymptotically unbiased estimation. The complexity of the iteration procedure is further reduced by increasing the step size of the iteration result. The algorithm is applicable to various communication systems where multiple amplitude level schemes are used such as QAM, OFDM, and PAM in Multiple-Input Multiple-Output (MIMO) channels. Numerical results are shown which achieve nonlinearity estimation and radio emitter identification over empirical channel models using an Orthogonal Frequency Division Multiplexing (OFDM) MIMO system.","PeriodicalId":433796,"journal":{"name":"2009 43rd Annual Conference on Information Sciences and Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 43rd Annual Conference on Information Sciences and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS.2009.5054783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
A data-aided iterative algorithm to estimate the nonlinearities of wireless emitters for Specific emitter Identification (SEI) is presented. To achieve robust estimation, Inter Symbol Interference (ISI) is removed by iteratively estimating the channel coefficients and nonlinear transmit symbols to achieve asymptotically unbiased estimation. The complexity of the iteration procedure is further reduced by increasing the step size of the iteration result. The algorithm is applicable to various communication systems where multiple amplitude level schemes are used such as QAM, OFDM, and PAM in Multiple-Input Multiple-Output (MIMO) channels. Numerical results are shown which achieve nonlinearity estimation and radio emitter identification over empirical channel models using an Orthogonal Frequency Division Multiplexing (OFDM) MIMO system.