{"title":"Efficient QR decomposition algorithm for LTE standard","authors":"K. Kalyani, D. Sellathambi, S. Rajaram","doi":"10.1109/ICCCNT.2013.6726492","DOIUrl":null,"url":null,"abstract":"LTE has become a hotspot of research and application in high speed broadband wireless access. MIMO signal detecting algorithms are necessary process in LTE receiver design. One of the main baseband function in MIMO receivers is QR decomposition of the channel matrix. This paper presents a new QR decomposition algorithm with several advantages to the previous method. The execution time of the QRD algorithm reduced by designing a new algorithm based on Householder transformation (HT) instead of existing algorithm. For QRD of large size matrices, this algorithm can achieve computational efficiency with robust numerical stability. The proposed scheme reduces the computation by half the amount to previous method.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"43 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
LTE has become a hotspot of research and application in high speed broadband wireless access. MIMO signal detecting algorithms are necessary process in LTE receiver design. One of the main baseband function in MIMO receivers is QR decomposition of the channel matrix. This paper presents a new QR decomposition algorithm with several advantages to the previous method. The execution time of the QRD algorithm reduced by designing a new algorithm based on Householder transformation (HT) instead of existing algorithm. For QRD of large size matrices, this algorithm can achieve computational efficiency with robust numerical stability. The proposed scheme reduces the computation by half the amount to previous method.