{"title":"EM Algorithm Based MAP Channel Estimation for Multi-Cell Massive MIMO Systems","authors":"Senol Sancar, B. Karakaya","doi":"10.1109/BlackSeaCom.2018.8433697","DOIUrl":null,"url":null,"abstract":"This paper represents an efficient expectation-maximization (EM) algorithm based maximum a posteriori (MAP) channel estimation method for multi-cell massive multiple input multiple output (MIMO) systems. MAP channel estimation method requires conjugate transpose of a τ x K pilot matrix where is the number of pilot symbols per user and K is the number of single antenna users. Conjugate transpose of large-size matrix increases computational complexity. The proposed method estimates the channel iteratively and converges to the same mean square error (MSE) performance of the MAP estimator with the increasing number of iterations. Consequently, the proposed method with low-rank approximation avoids conjugate transpose of large-size matrix and hence reduces the computational complexity significantly,","PeriodicalId":351647,"journal":{"name":"2018 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BlackSeaCom.2018.8433697","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
This paper represents an efficient expectation-maximization (EM) algorithm based maximum a posteriori (MAP) channel estimation method for multi-cell massive multiple input multiple output (MIMO) systems. MAP channel estimation method requires conjugate transpose of a τ x K pilot matrix where is the number of pilot symbols per user and K is the number of single antenna users. Conjugate transpose of large-size matrix increases computational complexity. The proposed method estimates the channel iteratively and converges to the same mean square error (MSE) performance of the MAP estimator with the increasing number of iterations. Consequently, the proposed method with low-rank approximation avoids conjugate transpose of large-size matrix and hence reduces the computational complexity significantly,
提出了一种基于最大后验(MAP)的高效期望最大化(EM)算法的多小区海量多输入多输出(MIMO)系统信道估计方法。MAP信道估计方法需要τ x K导频矩阵的共轭转置,其中为每个用户的导频符号数,K为单天线用户数。大尺寸矩阵的共轭转置增加了计算复杂度。该方法迭代估计信道,并随着迭代次数的增加收敛到与MAP估计器相同的均方误差(MSE)性能。因此,本文提出的低秩近似方法避免了大尺寸矩阵的共轭转置,从而大大降低了计算复杂度。