{"title":"Vector quantization techniques for multiple-antenna channel information feedback","authors":"J. Roh, B. Rao","doi":"10.1109/SPCOM.2004.1458490","DOIUrl":null,"url":null,"abstract":"This paper presents vector quantization (VQ) techniques in the context of multiple-antenna systems with finite-rate feedback. For MISO systems, we introduce a new design criterion and develop the corresponding iterative design algorithm for quantization of the beamforming vector. For complexity-limited systems, tree-structured VQ is also examined and compared with the full-search VQ method. The method is extended to MIMO channels by employing a parameterization method that exploits the orthonormality in the spatial information matrix and using the MISO approach in a sequential manner. The parameterization method can also be used to develop an effective low-complexity scheme to deal with quantization of time-varying channels. Also briefly discussed is a matrix quantization method for feeding back the beamforming matrix in MIMO spatial multiplexing systems.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPCOM.2004.1458490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
This paper presents vector quantization (VQ) techniques in the context of multiple-antenna systems with finite-rate feedback. For MISO systems, we introduce a new design criterion and develop the corresponding iterative design algorithm for quantization of the beamforming vector. For complexity-limited systems, tree-structured VQ is also examined and compared with the full-search VQ method. The method is extended to MIMO channels by employing a parameterization method that exploits the orthonormality in the spatial information matrix and using the MISO approach in a sequential manner. The parameterization method can also be used to develop an effective low-complexity scheme to deal with quantization of time-varying channels. Also briefly discussed is a matrix quantization method for feeding back the beamforming matrix in MIMO spatial multiplexing systems.