{"title":"线性分组码的最优阈值顺序译码算法","authors":"Chen Jun, Sun Rong, W. Xinmei","doi":"10.1109/VETECS.2000.851529","DOIUrl":null,"url":null,"abstract":"Optimal threshold sequential decoding algorithms for binary linear block codes which combine the sequential decoding with the threshold decoding are presented. They use the stack algorithm to search through the trellis of the block codes for a path which has the optimal value of the Fano metric function. When a new candidate codeword is found, an optimality check is performed on it by using the Fano-optimal threshold. If checked successfully, the candidate codeword is the most likely (ML) codeword and the search stops. Otherwise the search process continues until either an optimal path is found, which also represents the ML codeword, or the memory buffer of the decoder overflows, in which case the hard decision word is output. Simulation results show that compared with the decoding algorithms available, the proposed decoding algorithms significantly reduce the decoding complexity without losing the decoding performance.","PeriodicalId":318880,"journal":{"name":"VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal threshold sequential decoding algorithms for linear block codes\",\"authors\":\"Chen Jun, Sun Rong, W. Xinmei\",\"doi\":\"10.1109/VETECS.2000.851529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimal threshold sequential decoding algorithms for binary linear block codes which combine the sequential decoding with the threshold decoding are presented. They use the stack algorithm to search through the trellis of the block codes for a path which has the optimal value of the Fano metric function. When a new candidate codeword is found, an optimality check is performed on it by using the Fano-optimal threshold. If checked successfully, the candidate codeword is the most likely (ML) codeword and the search stops. Otherwise the search process continues until either an optimal path is found, which also represents the ML codeword, or the memory buffer of the decoder overflows, in which case the hard decision word is output. Simulation results show that compared with the decoding algorithms available, the proposed decoding algorithms significantly reduce the decoding complexity without losing the decoding performance.\",\"PeriodicalId\":318880,\"journal\":{\"name\":\"VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026)\",\"volume\":\"140 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VETECS.2000.851529\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VETECS.2000.851529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal threshold sequential decoding algorithms for linear block codes
Optimal threshold sequential decoding algorithms for binary linear block codes which combine the sequential decoding with the threshold decoding are presented. They use the stack algorithm to search through the trellis of the block codes for a path which has the optimal value of the Fano metric function. When a new candidate codeword is found, an optimality check is performed on it by using the Fano-optimal threshold. If checked successfully, the candidate codeword is the most likely (ML) codeword and the search stops. Otherwise the search process continues until either an optimal path is found, which also represents the ML codeword, or the memory buffer of the decoder overflows, in which case the hard decision word is output. Simulation results show that compared with the decoding algorithms available, the proposed decoding algorithms significantly reduce the decoding complexity without losing the decoding performance.