{"title":"基于训练和半盲信道估计的LS算法在MIMO系统中的性能评价","authors":"S. Moghaddam, H. Saremi","doi":"10.1109/WD.2008.4812848","DOIUrl":null,"url":null,"abstract":"There are many algorithms that can be used in a channel estimator. In this investigation, performance of LS algorithm in a training-based as well as a semi-blind channel estimation evaluated and their results has been compared. Simulation results show that performance of a semi-blind estimator is better than a training-based estimator. It is interesting for us due to transmitting less required training bits than a training-based algorithm and hence lower redundancy. Therefore we will achieve more bandwidth efficiency with better performance. Training-based method needs 100 times more additional bits than semi-blind method whereas semi-blind method needs only 25% more computational time to convergence.","PeriodicalId":247938,"journal":{"name":"2008 1st IFIP Wireless Days","volume":"200 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Performance evaluation of LS algorithm in both Training-Based and Semi-Blind channel estimations for MIMO Systems\",\"authors\":\"S. Moghaddam, H. Saremi\",\"doi\":\"10.1109/WD.2008.4812848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are many algorithms that can be used in a channel estimator. In this investigation, performance of LS algorithm in a training-based as well as a semi-blind channel estimation evaluated and their results has been compared. Simulation results show that performance of a semi-blind estimator is better than a training-based estimator. It is interesting for us due to transmitting less required training bits than a training-based algorithm and hence lower redundancy. Therefore we will achieve more bandwidth efficiency with better performance. Training-based method needs 100 times more additional bits than semi-blind method whereas semi-blind method needs only 25% more computational time to convergence.\",\"PeriodicalId\":247938,\"journal\":{\"name\":\"2008 1st IFIP Wireless Days\",\"volume\":\"200 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 1st IFIP Wireless Days\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WD.2008.4812848\",\"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 1st IFIP Wireless Days","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WD.2008.4812848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance evaluation of LS algorithm in both Training-Based and Semi-Blind channel estimations for MIMO Systems
There are many algorithms that can be used in a channel estimator. In this investigation, performance of LS algorithm in a training-based as well as a semi-blind channel estimation evaluated and their results has been compared. Simulation results show that performance of a semi-blind estimator is better than a training-based estimator. It is interesting for us due to transmitting less required training bits than a training-based algorithm and hence lower redundancy. Therefore we will achieve more bandwidth efficiency with better performance. Training-based method needs 100 times more additional bits than semi-blind method whereas semi-blind method needs only 25% more computational time to convergence.