{"title":"Reduction of the numerical range of the state metrics in a Viterbi decoder","authors":"A.P. Hekstra","doi":"10.1109/ISIT.1994.394804","DOIUrl":null,"url":null,"abstract":"Large state metric differences indicate a strong discrimination between the likelihood of survivor paths. A state metric is called \"large\" if the state metric of a node in the trellis exceeds the minimum state metric at the given depth in the trellis by more than some constant B that depends on the binary convolutional code. Theorem I formulates a stopping rule that deletes all nodes with a \"large\" metric, as for any path that runs through such a node and for any received sequence, a detour exists via the node that has minimal state metric such that the resulting path has a smaller metric than the original path. The proof use simultaneous application of tight bounds for maximum state metric differences for the forward and the time reversed convolutional code.<<ETX>>","PeriodicalId":331390,"journal":{"name":"Proceedings of 1994 IEEE International Symposium on Information Theory","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE International Symposium on Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.1994.394804","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
Large state metric differences indicate a strong discrimination between the likelihood of survivor paths. A state metric is called "large" if the state metric of a node in the trellis exceeds the minimum state metric at the given depth in the trellis by more than some constant B that depends on the binary convolutional code. Theorem I formulates a stopping rule that deletes all nodes with a "large" metric, as for any path that runs through such a node and for any received sequence, a detour exists via the node that has minimal state metric such that the resulting path has a smaller metric than the original path. The proof use simultaneous application of tight bounds for maximum state metric differences for the forward and the time reversed convolutional code.<>