{"title":"Modified min-sum algorithm with threshold filtering for nonbinary LDPC codes over GF(q)","authors":"Yue Liu, Jun Ning, Jinhong Yuan","doi":"10.1109/ISITA.2008.4895537","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a scheme to reduce the computation complexity of min-sum (MS) algorithm for decoding of nonbinary low-density parity-check (LDPC) codes over GF(q). Previously, MS algorithm reduced the decoding complexity by lowering the size of the configuration set for each variable node through a sorting. In the proposed scheme, we modify the MS algorithm by minimizing the size of the configuration set for each variable node through a filtering. In the filtering, the reduction of the set size can be controlled by a preset threshold. This way we can reduce the complexity more efficiently. Simulation results show, compared to the previous EMS algorithm, the complexity of proposed scheme is reduced with a negligible degradation in the code performance.","PeriodicalId":338675,"journal":{"name":"2008 International Symposium on Information Theory and Its Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","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.2008.4895537","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we propose a scheme to reduce the computation complexity of min-sum (MS) algorithm for decoding of nonbinary low-density parity-check (LDPC) codes over GF(q). Previously, MS algorithm reduced the decoding complexity by lowering the size of the configuration set for each variable node through a sorting. In the proposed scheme, we modify the MS algorithm by minimizing the size of the configuration set for each variable node through a filtering. In the filtering, the reduction of the set size can be controlled by a preset threshold. This way we can reduce the complexity more efficiently. Simulation results show, compared to the previous EMS algorithm, the complexity of proposed scheme is reduced with a negligible degradation in the code performance.