{"title":"Locally optimum detection performance analysis for narrowband interference rejection in spread spectrum communications","authors":"A. Roy, J. Doherty","doi":"10.1109/GLOCOM.2005.1577462","DOIUrl":null,"url":null,"abstract":"Locally Optimum (LO) detection offers a means of reliable signal detection under high noise conditions. This technique is applied to remove first order autoregressive narrowband interference from a spread spectrum system. A new expression for output signal-to-interference ratio (SIR) is derived and compared with simulation results. A comparison of the LO detector performance and adaptive Wiener filtering based on the output SIR is presented to highlight the strengths of this technique. Further, it is shown that LOD technique is not overly sensitive to model parameter estimation error.","PeriodicalId":319736,"journal":{"name":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2005.1577462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Locally Optimum (LO) detection offers a means of reliable signal detection under high noise conditions. This technique is applied to remove first order autoregressive narrowband interference from a spread spectrum system. A new expression for output signal-to-interference ratio (SIR) is derived and compared with simulation results. A comparison of the LO detector performance and adaptive Wiener filtering based on the output SIR is presented to highlight the strengths of this technique. Further, it is shown that LOD technique is not overly sensitive to model parameter estimation error.