Jens Steinwandt, R. D. Lamare, Lei Wang, Nuan Song, M. Haardt
{"title":"Widely linear adaptive beamforming algorithm based on the conjugate gradient method","authors":"Jens Steinwandt, R. D. Lamare, Lei Wang, Nuan Song, M. Haardt","doi":"10.1109/WSA.2011.5741912","DOIUrl":null,"url":null,"abstract":"A new widely linear (WL) adaptive beamforming algorithm for non-circular sources based on the conjugate gradient (CG) method is proposed, which we refer to as the widely linear conjugate gradient (WL-CG) algorithm. It is designed according to the widely linearly constrained minimum variance (WL-CMV) criterion and takes full advantage of the second-order statistics of the non-circular data. Since only the knowledge of the steering vector of the desired user is necessary, the proposed method is non-data-aided. The CG method is a powerful algorithm used to design an adaptive beamformer and has an attractive trade-off between performance and complexity. Simulation results show that the proposed WL-CG algorithm provides an excellent performance, while requiring a low complexity compared to existing widely linear beamforming techniques.","PeriodicalId":307097,"journal":{"name":"2011 International ITG Workshop on Smart Antennas","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International ITG Workshop on Smart Antennas","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSA.2011.5741912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
A new widely linear (WL) adaptive beamforming algorithm for non-circular sources based on the conjugate gradient (CG) method is proposed, which we refer to as the widely linear conjugate gradient (WL-CG) algorithm. It is designed according to the widely linearly constrained minimum variance (WL-CMV) criterion and takes full advantage of the second-order statistics of the non-circular data. Since only the knowledge of the steering vector of the desired user is necessary, the proposed method is non-data-aided. The CG method is a powerful algorithm used to design an adaptive beamformer and has an attractive trade-off between performance and complexity. Simulation results show that the proposed WL-CG algorithm provides an excellent performance, while requiring a low complexity compared to existing widely linear beamforming techniques.