{"title":"时不变LDPC卷积码的循环分析","authors":"Hua Zhou, N. Goertz","doi":"10.1109/ICTEL.2010.5478744","DOIUrl":null,"url":null,"abstract":"Time-invariant low-density parity-check convolutional codes (LDPCccs) can be constructed from a polynomial form of a parity-check matrix that defines quasi-cyclic LDPC block codes based on circulant matrices. Based on this polynomial matrix, we discuss the relationships between the polynomial domain and the time domain parity-check and syndrome former matrices with respect to cycle properties. We present a novel, simple way to describe cycles in the polynomial version of the syndrome former matrix and we exploit this concept in a new cycle counting algorithm.","PeriodicalId":208094,"journal":{"name":"2010 17th International Conference on Telecommunications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Cycle analysis of time-invariant LDPC convolutional codes\",\"authors\":\"Hua Zhou, N. Goertz\",\"doi\":\"10.1109/ICTEL.2010.5478744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Time-invariant low-density parity-check convolutional codes (LDPCccs) can be constructed from a polynomial form of a parity-check matrix that defines quasi-cyclic LDPC block codes based on circulant matrices. Based on this polynomial matrix, we discuss the relationships between the polynomial domain and the time domain parity-check and syndrome former matrices with respect to cycle properties. We present a novel, simple way to describe cycles in the polynomial version of the syndrome former matrix and we exploit this concept in a new cycle counting algorithm.\",\"PeriodicalId\":208094,\"journal\":{\"name\":\"2010 17th International Conference on Telecommunications\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 17th International Conference on Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTEL.2010.5478744\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 17th International Conference on Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTEL.2010.5478744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cycle analysis of time-invariant LDPC convolutional codes
Time-invariant low-density parity-check convolutional codes (LDPCccs) can be constructed from a polynomial form of a parity-check matrix that defines quasi-cyclic LDPC block codes based on circulant matrices. Based on this polynomial matrix, we discuss the relationships between the polynomial domain and the time domain parity-check and syndrome former matrices with respect to cycle properties. We present a novel, simple way to describe cycles in the polynomial version of the syndrome former matrix and we exploit this concept in a new cycle counting algorithm.