{"title":"基于格约简的误差检测方案的MIMO系统近极大似然检测","authors":"Dong-jin Lee, Mea-Hwa Park, Y. Byun","doi":"10.1109/APCC.2006.255908","DOIUrl":null,"url":null,"abstract":"MLD (maximum likelihood detection) has shown optimum performance in MIMO systems. However, its complexity generally makes it impractical. To solve this problem, various techniques were proposed. LRAD (lattice-reduction-aided detection) was also proposed to improve the performance of MIMO systems. In this paper, we suggest error symbol detection and correction in symbols estimated by LRAD. In other words, the proposed system detects the first symbols by LRAD and searches error terms in the first detection symbols. And correct the error symbols by optimal or sub-optimal systems. As a result, its performance approaches more nearly to that of MLD which shows optimum performance, but it has much less complexity than MLD","PeriodicalId":205758,"journal":{"name":"2006 Asia-Pacific Conference on Communications","volume":"379 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Near-Maximum Likelihood Detection of MIMO Systems Using Error Detection Scheme Based Lattice Reduction\",\"authors\":\"Dong-jin Lee, Mea-Hwa Park, Y. Byun\",\"doi\":\"10.1109/APCC.2006.255908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MLD (maximum likelihood detection) has shown optimum performance in MIMO systems. However, its complexity generally makes it impractical. To solve this problem, various techniques were proposed. LRAD (lattice-reduction-aided detection) was also proposed to improve the performance of MIMO systems. In this paper, we suggest error symbol detection and correction in symbols estimated by LRAD. In other words, the proposed system detects the first symbols by LRAD and searches error terms in the first detection symbols. And correct the error symbols by optimal or sub-optimal systems. As a result, its performance approaches more nearly to that of MLD which shows optimum performance, but it has much less complexity than MLD\",\"PeriodicalId\":205758,\"journal\":{\"name\":\"2006 Asia-Pacific Conference on Communications\",\"volume\":\"379 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Asia-Pacific Conference on Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCC.2006.255908\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Asia-Pacific Conference on Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCC.2006.255908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Near-Maximum Likelihood Detection of MIMO Systems Using Error Detection Scheme Based Lattice Reduction
MLD (maximum likelihood detection) has shown optimum performance in MIMO systems. However, its complexity generally makes it impractical. To solve this problem, various techniques were proposed. LRAD (lattice-reduction-aided detection) was also proposed to improve the performance of MIMO systems. In this paper, we suggest error symbol detection and correction in symbols estimated by LRAD. In other words, the proposed system detects the first symbols by LRAD and searches error terms in the first detection symbols. And correct the error symbols by optimal or sub-optimal systems. As a result, its performance approaches more nearly to that of MLD which shows optimum performance, but it has much less complexity than MLD