{"title":"一种改进的低复杂度LMMSE信道估计算法","authors":"Xuchen Wang, Feng Guo","doi":"10.1109/ICCECT.2012.120","DOIUrl":null,"url":null,"abstract":"This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on hardware platform, which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Finally, comparisons are made between the simulation performances of improved LMMSE algorithm with those of other estimation methods for further analysis.","PeriodicalId":153613,"journal":{"name":"2012 International Conference on Control Engineering and Communication Technology","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Low-Complexity LMMSE Channel Estimation Algorithm\",\"authors\":\"Xuchen Wang, Feng Guo\",\"doi\":\"10.1109/ICCECT.2012.120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on hardware platform, which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Finally, comparisons are made between the simulation performances of improved LMMSE algorithm with those of other estimation methods for further analysis.\",\"PeriodicalId\":153613,\"journal\":{\"name\":\"2012 International Conference on Control Engineering and Communication Technology\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Control Engineering and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECT.2012.120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Control Engineering and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECT.2012.120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Low-Complexity LMMSE Channel Estimation Algorithm
This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on hardware platform, which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Finally, comparisons are made between the simulation performances of improved LMMSE algorithm with those of other estimation methods for further analysis.