Matrix Manifold Precoder Design for Massive MIMO Downlink

被引:0
作者
Sun, Rui [1 ,2 ]
Wang, Chen [1 ,2 ]
Lu, An-An [1 ,2 ]
Fu, Xiao [1 ,2 ]
Liu, Xiaofeng
Zhang, Yuxuan
Gao, Xiqi [1 ,2 ]
Xia, Xiang-Gen [3 ]
机构
[1] Southeast Univ, Natl Mobile Communicat Res Lab, Nanjing 210096, Peoples R China
[2] Purple Mt Labs, Nanjing 211111, Peoples R China
[3] Univ Delaware, Dept Elect & Comp Engn, Newark, DE 19716 USA
来源
2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024 | 2024年
基金
国家重点研发计划;
关键词
linear precoding; matrix manifold optimization; total power constraint; weighted sum rate; ALLOCATION; OPTIMIZATION; MMSE;
D O I
10.1109/WCNC57260.2024.10570510
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We investigate the weighted sum-rate (WSR) maximization linear precoder design under total power constraint (TPC) for massive MIMO downlink with matrix manifold optimization. Particularly, we prove that the precoders under TPC are on a Riemannian submanifold, and transform the constrained problem in Euclidean space to the unconstrained one on manifold. In accordance with this, Riemannian design methods using Riemannian steepest descent and Riemannian conjugate gradient are provided to design the WSR-maximization precoders under TPC. Riemannian methods are free of the inverse of large dimensional matrix, posing significant computational savings and potentially allowing to avoid ill numerical behavior in algorithms. Complexity analysis and performance simulations demonstrate the advantages of the proposed precoder design.
引用
收藏
页数:6
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