{"title":"基于统一空时符号的Turbo码多路软输出Viterbi译码算法","authors":"Dapeng Zhang, Ju Liu, Qiangjun Niu, Hui Ji","doi":"10.1109/ICCSN.2009.85","DOIUrl":null,"url":null,"abstract":"UST symbol-based turbo code has recently been proposed which can reduce the system complexity and calculation amount compared with bit-wise concatenation scheme. However, the corresponding MAP decoding algorithm still makes hardware unbearable and later its simplified versions, Max-Log-MAP and Log-MAP algorithms, appeared. In this paper, we propose a multiary SOVA decoding algorithm for UST symbol-based turbo code. Using our UST symbol-based SOVA, soft output information from the prior iteration can be accepted as the a priori information for current iteration. Notably, the experimental results show that our algorithm can achieve close performance to Max-Log-MAP and Log-MAP algorithms with lower complexity. The performance of the SOVA and that of MAP algorithm are almost the same at a BER of 10-5, and is even better for a higher BER.","PeriodicalId":177679,"journal":{"name":"2009 International Conference on Communication Software and Networks","volume":"129 Suppl 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-ary Soft Output Viterbi decoding Algorithm for Unitary Space-Time Symbol-Based Turbo Code\",\"authors\":\"Dapeng Zhang, Ju Liu, Qiangjun Niu, Hui Ji\",\"doi\":\"10.1109/ICCSN.2009.85\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"UST symbol-based turbo code has recently been proposed which can reduce the system complexity and calculation amount compared with bit-wise concatenation scheme. However, the corresponding MAP decoding algorithm still makes hardware unbearable and later its simplified versions, Max-Log-MAP and Log-MAP algorithms, appeared. In this paper, we propose a multiary SOVA decoding algorithm for UST symbol-based turbo code. Using our UST symbol-based SOVA, soft output information from the prior iteration can be accepted as the a priori information for current iteration. Notably, the experimental results show that our algorithm can achieve close performance to Max-Log-MAP and Log-MAP algorithms with lower complexity. The performance of the SOVA and that of MAP algorithm are almost the same at a BER of 10-5, and is even better for a higher BER.\",\"PeriodicalId\":177679,\"journal\":{\"name\":\"2009 International Conference on Communication Software and Networks\",\"volume\":\"129 Suppl 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Communication Software and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSN.2009.85\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Communication Software and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2009.85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UST symbol-based turbo code has recently been proposed which can reduce the system complexity and calculation amount compared with bit-wise concatenation scheme. However, the corresponding MAP decoding algorithm still makes hardware unbearable and later its simplified versions, Max-Log-MAP and Log-MAP algorithms, appeared. In this paper, we propose a multiary SOVA decoding algorithm for UST symbol-based turbo code. Using our UST symbol-based SOVA, soft output information from the prior iteration can be accepted as the a priori information for current iteration. Notably, the experimental results show that our algorithm can achieve close performance to Max-Log-MAP and Log-MAP algorithms with lower complexity. The performance of the SOVA and that of MAP algorithm are almost the same at a BER of 10-5, and is even better for a higher BER.