Matrix Manifold Precoder Design for Massive MIMO Downlink

We investigate the weighted sum-rate (WSR) max-imization 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 i...

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Bibliographic Details
Published in:IEEE Wireless Communications and Networking Conference : [proceedings] : WCNC pp. 1 - 6
Main Authors: Sun, Rui, Wang, Chen, Lu, An-An, Fu, Xiao, Liu, Xiaofeng, Zhang, Yuxuan, Gao, Xiqi, Xia, Xiang-Gen
Format: Conference Proceeding
Language:English
Published: IEEE 21.04.2024
Subjects:
Computational modeling
Design methodology
Downlink
linear precoding
Manifolds
Massive MIMO
matrix manifold optimization
Simulation
total power constraint
Transforms
weighted sum rate
ISSN:1558-2612
Online Access:Get full text
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Summary:We investigate the weighted sum-rate (WSR) max-imization 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.
ISSN:1558-2612
DOI:10.1109/WCNC57260.2024.10570510