V. B. Wijekoon, Shuiyin Liu, E. Viterbo, Y. Hong, R. Micheloni, A. Marelli
{"title":"基于协集概率的非二进制LDPC码多数逻辑译码","authors":"V. B. Wijekoon, Shuiyin Liu, E. Viterbo, Y. Hong, R. Micheloni, A. Marelli","doi":"10.1109/ITW44776.2019.8989103","DOIUrl":null,"url":null,"abstract":"This paper presents a majority-logic decoding (MLgD) algorithm for non-binary LDPC codes based on a novel expansion of the Tanner graph. The expansion introduced converts the Q-ary graph into a binary one, which makes the new MLgD algorithm more attractive for hardware implementations. Proposed algorithm performs significantly better than the existing MLgD algorithms in the waterfall region, and it shows a much lower error-floor as well. Algorithm only requires integer additions, comparisons, finite field operations and some binary operations. Thus, it offers an effective trade-off between performance and complexity in decoding non-binary LDPC codes.","PeriodicalId":214379,"journal":{"name":"2019 IEEE Information Theory Workshop (ITW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coset Probability Based Majority-logic Decoding for Non-binary LDPC Codes\",\"authors\":\"V. B. Wijekoon, Shuiyin Liu, E. Viterbo, Y. Hong, R. Micheloni, A. Marelli\",\"doi\":\"10.1109/ITW44776.2019.8989103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a majority-logic decoding (MLgD) algorithm for non-binary LDPC codes based on a novel expansion of the Tanner graph. The expansion introduced converts the Q-ary graph into a binary one, which makes the new MLgD algorithm more attractive for hardware implementations. Proposed algorithm performs significantly better than the existing MLgD algorithms in the waterfall region, and it shows a much lower error-floor as well. Algorithm only requires integer additions, comparisons, finite field operations and some binary operations. Thus, it offers an effective trade-off between performance and complexity in decoding non-binary LDPC codes.\",\"PeriodicalId\":214379,\"journal\":{\"name\":\"2019 IEEE Information Theory Workshop (ITW)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Information Theory Workshop (ITW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITW44776.2019.8989103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Information Theory Workshop (ITW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW44776.2019.8989103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coset Probability Based Majority-logic Decoding for Non-binary LDPC Codes
This paper presents a majority-logic decoding (MLgD) algorithm for non-binary LDPC codes based on a novel expansion of the Tanner graph. The expansion introduced converts the Q-ary graph into a binary one, which makes the new MLgD algorithm more attractive for hardware implementations. Proposed algorithm performs significantly better than the existing MLgD algorithms in the waterfall region, and it shows a much lower error-floor as well. Algorithm only requires integer additions, comparisons, finite field operations and some binary operations. Thus, it offers an effective trade-off between performance and complexity in decoding non-binary LDPC codes.