{"title":"Error Probabilities Due to Additive Combinations of Gaussian and Impulsive Noise","authors":"R. Ziemer","doi":"10.1109/TCOM.1967.1089608","DOIUrl":null,"url":null,"abstract":"In this paper a Poisson impulse noise model is utilized to calculate error probability characteristics of a matched filter receiver operating in an additive combination of impulsive and Gaussian noise. Comparisons of the theoretical predictions are made with experimental data obtained from a simulated communication system. The results indicate that only a small amount of Gaussian noise power has a considerable effect on the probability of error for small signal-to-noise ratios (SNRs). Also, it is found that each noise component may be looked upon as acting separately, the Gaussian noise component dominating the error probability for low SNRs and the impulsive component dominating for high SNRs. Thus, approximate error probability curves may be calculated by using a result applicable for Gaussian interference at low SNRs, and an asymptotic formula corresponding to impulsive background noise at high SNRs.","PeriodicalId":134522,"journal":{"name":"IEEE Transactions on Communication Technology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1967-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TCOM.1967.1089608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
In this paper a Poisson impulse noise model is utilized to calculate error probability characteristics of a matched filter receiver operating in an additive combination of impulsive and Gaussian noise. Comparisons of the theoretical predictions are made with experimental data obtained from a simulated communication system. The results indicate that only a small amount of Gaussian noise power has a considerable effect on the probability of error for small signal-to-noise ratios (SNRs). Also, it is found that each noise component may be looked upon as acting separately, the Gaussian noise component dominating the error probability for low SNRs and the impulsive component dominating for high SNRs. Thus, approximate error probability curves may be calculated by using a result applicable for Gaussian interference at low SNRs, and an asymptotic formula corresponding to impulsive background noise at high SNRs.