{"title":"GF(q)上非二进制LDPC码的改进最小和阈值滤波算法","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":"{\"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}","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}
Modified min-sum algorithm with threshold filtering for nonbinary LDPC codes over GF(q)
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.