{"title":"递归系统卷积码的权值分布","authors":"H. Yoshikawa","doi":"10.1109/ISITA.2008.4895622","DOIUrl":null,"url":null,"abstract":"An analytical bound to bit error probability of turbo codes can be derived by weight distribution of recursive systematic convolutional codes. In this paper, the conditional weight enumerating function of terminated recursive systematic convolutional codes is computed. This form can be expressed as a function of number of information bits, and can reduce the computational complexity of calculation of error bounds. Applying these results, it is shown that improved error bound can be obtained by the conditional weight enumerating function of parallel concatenated convolutional codes.","PeriodicalId":338675,"journal":{"name":"2008 International Symposium on Information Theory and Its Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the weight distribution of recursive systematic convolutional codes\",\"authors\":\"H. Yoshikawa\",\"doi\":\"10.1109/ISITA.2008.4895622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An analytical bound to bit error probability of turbo codes can be derived by weight distribution of recursive systematic convolutional codes. In this paper, the conditional weight enumerating function of terminated recursive systematic convolutional codes is computed. This form can be expressed as a function of number of information bits, and can reduce the computational complexity of calculation of error bounds. Applying these results, it is shown that improved error bound can be obtained by the conditional weight enumerating function of parallel concatenated convolutional codes.\",\"PeriodicalId\":338675,\"journal\":{\"name\":\"2008 International Symposium on Information Theory and Its Applications\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Symposium on Information Theory and Its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISITA.2008.4895622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Symposium on Information Theory and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITA.2008.4895622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the weight distribution of recursive systematic convolutional codes
An analytical bound to bit error probability of turbo codes can be derived by weight distribution of recursive systematic convolutional codes. In this paper, the conditional weight enumerating function of terminated recursive systematic convolutional codes is computed. This form can be expressed as a function of number of information bits, and can reduce the computational complexity of calculation of error bounds. Applying these results, it is shown that improved error bound can be obtained by the conditional weight enumerating function of parallel concatenated convolutional codes.