{"title":"Largest Generalized Eigenvector Precoder for CoMP-JT Massive MIMO Systems","authors":"Xianglong Yu, Hanqing Wang, Yiling Yuan, Xiaohan Wang, Hao Chen","doi":"10.1109/EuCNC/6GSummit58263.2023.10188356","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the downlink (DL) precoder design in coordinated multi-point joint transmission massive multiple-input multiple-output systems. The DL precoder design problem is formulate to maximize the sum-rate under the per base station transmit power constraint. Utilizing the first-order condition, the structure of the optimal precoder is derived, involving the generalized eigenvectors of a pair of matrices. In accordance with this, the largest generalized eigenvector (LGEV) precoder is proposed to solve the first-order condition in an iterative manner, which involves solving the complicated generalized eigenvalue problem in each iteration. Specifically, we propose to solve the eigenvalue problem numerically for low-complexity implementation based on the inverse free Krylov subspace method. Simulation results demonstrate that the proposed LGEV precoder achieves satisfactory performances with fast convergences within a couple of iterations.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"78 1","pages":"114-119"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"公共管理高层论坛","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we investigate the downlink (DL) precoder design in coordinated multi-point joint transmission massive multiple-input multiple-output systems. The DL precoder design problem is formulate to maximize the sum-rate under the per base station transmit power constraint. Utilizing the first-order condition, the structure of the optimal precoder is derived, involving the generalized eigenvectors of a pair of matrices. In accordance with this, the largest generalized eigenvector (LGEV) precoder is proposed to solve the first-order condition in an iterative manner, which involves solving the complicated generalized eigenvalue problem in each iteration. Specifically, we propose to solve the eigenvalue problem numerically for low-complexity implementation based on the inverse free Krylov subspace method. Simulation results demonstrate that the proposed LGEV precoder achieves satisfactory performances with fast convergences within a couple of iterations.