{"title":"Estimation of Gilbert's model parameters using the simulated annealing method","authors":"Tan-Hsu Tan, Wen-Whei Chang","doi":"10.1109/PIMRC.1996.568479","DOIUrl":null,"url":null,"abstract":"Errors encountered in digital mobile radio channels are not independent but exhibit varying degrees of statistical dependencies. In many mobile applications, Gilbert's (1960) finite-state Markov chain model has been shown to adequately characterize the bursty-noise binary channels. An estimation method based on the simulated annealing algorithm is proposed for computing the model. Parameters from the sample error sequences. Experimental results indicate that the simulated annealing method yields more accurate identification at a faster convergence rate for comparison with the gradient iterative method.","PeriodicalId":206655,"journal":{"name":"Proceedings of PIMRC '96 - 7th International Symposium on Personal, Indoor, and Mobile Communications","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of PIMRC '96 - 7th International Symposium on Personal, Indoor, and Mobile Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.1996.568479","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
Errors encountered in digital mobile radio channels are not independent but exhibit varying degrees of statistical dependencies. In many mobile applications, Gilbert's (1960) finite-state Markov chain model has been shown to adequately characterize the bursty-noise binary channels. An estimation method based on the simulated annealing algorithm is proposed for computing the model. Parameters from the sample error sequences. Experimental results indicate that the simulated annealing method yields more accurate identification at a faster convergence rate for comparison with the gradient iterative method.