线性分组码的最优阈值顺序译码算法

Chen Jun, Sun Rong, W. Xinmei
{"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}
引用次数: 2

摘要

提出了将序列译码与阈值译码相结合的二进制线性分组码的最优阈值顺序译码算法。他们使用堆栈算法在块代码的网格中搜索具有最优Fano度量函数值的路径。当找到一个新的候选码字时,使用Fano-optimal阈值对其执行最优性检查。如果检查成功,则候选码字是最可能的(ML)码字,并且搜索停止。否则,搜索过程将继续,直到找到最优路径,这也表示ML码字,或者解码器的内存缓冲区溢出,在这种情况下,输出硬决策字。仿真结果表明,与现有的译码算法相比,本文提出的译码算法在不影响译码性能的前提下显著降低了译码复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信