An Eigen-based Approach for Enhancing Matrix Inversion Approximation in Massive MIMO Systems
學年 105
學期 2
出版(發表)日期 2017-06-01
作品名稱 An Eigen-based Approach for Enhancing Matrix Inversion Approximation in Massive MIMO Systems
作品名稱(其他語言)
著者 Kelvin Kuang-Chi Lee; Chiao-En Chen
單位
出版者
著錄名稱、卷期、頁數 IEEE Transactions on Vehicular Technology 66(6), p.5480-5484
摘要 This correspondence presents a new matrix inversion approximation (MIA) method for massive multiple-inputmultiple- output (MIMO) systems. In contrast to the existing methods which are mostly derived from the Neumann series expansion framework, additional coefficients have been introduced in our proposed method to enhance the precision of approximation. We propose an efficient algorithm for the coefficient design which consists of an eigenvalue estimation procedure derived from random matrix theory, and a least-squares fitting procedure that solves a low-dimension over-determined system of linear equations. Complexity analysis and simulation results show that our eigen-based MIA method exhibits practically comparable computational complexity while achieving substantial performance enhancement compared to other benchmark methods.
關鍵字 Marcenko-Pastur law;Neumann series;matrix inversion;massive MIMO;zero-forcing;random matrix
語言 en_US
ISSN 0018-9545
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者
審稿制度
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/109079 )