Matrix Manifold Precoder Design for User-Centric Network Massive MIMO

In this paper, we investigate the precoder design for user-centric network (UCN) massive multiple-input multiple-output (mMIMO) downlink with matrix manifold optimization. In UCN mMIMO systems, each user terminal (UT) is served by a subset of the base stations (BSs) instead of all BSs, lowering the...

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Veröffentlicht in:IEEE Global Communications Conference (Online) S. 4046 - 4051
Hauptverfasser: Sun, Rui, You, Li, Lu, An-An, Sun, Chen, Xiang, Ziyu, Gao, Xiqi, Xia, Xiang-Gen
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 08.12.2024
Schlagworte:
Complexity theory
Global communication
Manifold optimization
Manifolds
Massive MIMO
Optimization
Performance gain
Precoding
Riemannian submanifold
Simulation
Transforms
user-centric network massive MIMO
Vectors
ISSN:2576-6813
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Abstract In this paper, we investigate the precoder design for user-centric network (UCN) massive multiple-input multiple-output (mMIMO) downlink with matrix manifold optimization. In UCN mMIMO systems, each user terminal (UT) is served by a subset of the base stations (BSs) instead of all BSs, lowering the dimension of the precoders to be designed. Each BS in the system has a power constraint. By proving that the precoder set satisfying the constraints forms a Riemannian submanifold, we transform the constrained precoder design problem in Euclidean space as an unconstrained one on the Riemannian submanifold. Riemannian ingredients, including orthogonal projection, Riemannian gradient, retraction and vector transport, of the problem on the Riemannian submanifold are further derived, with which the Riemannian conjugate gradient (RCG) design method is proposed for solving the unconstrained problem. The proposed method avoids the inverses of large dimensional matrices. The complexity analyses show the high efficiency of RCG precoder design. Simulation results demonstrate the superiority of the proposed precoder design and the high efficiency of the UCN mMIMO system.
AbstractList In this paper, we investigate the precoder design for user-centric network (UCN) massive multiple-input multiple-output (mMIMO) downlink with matrix manifold optimization. In UCN mMIMO systems, each user terminal (UT) is served by a subset of the base stations (BSs) instead of all BSs, lowering the dimension of the precoders to be designed. Each BS in the system has a power constraint. By proving that the precoder set satisfying the constraints forms a Riemannian submanifold, we transform the constrained precoder design problem in Euclidean space as an unconstrained one on the Riemannian submanifold. Riemannian ingredients, including orthogonal projection, Riemannian gradient, retraction and vector transport, of the problem on the Riemannian submanifold are further derived, with which the Riemannian conjugate gradient (RCG) design method is proposed for solving the unconstrained problem. The proposed method avoids the inverses of large dimensional matrices. The complexity analyses show the high efficiency of RCG precoder design. Simulation results demonstrate the superiority of the proposed precoder design and the high efficiency of the UCN mMIMO system.
Author Gao, Xiqi
Sun, Chen
Xia, Xiang-Gen
Xiang, Ziyu
You, Li
Sun, Rui
Lu, An-An
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  surname: Sun
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  organization: Southeast University,National Mobile Communications Research Laboratory,Nanjing,China,210096
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  givenname: Li
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  organization: Southeast University,National Mobile Communications Research Laboratory,Nanjing,China,210096
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  givenname: An-An
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  organization: Southeast University,National Mobile Communications Research Laboratory,Nanjing,China,210096
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  givenname: Xiang-Gen
  surname: Xia
  fullname: Xia, Xiang-Gen
  email: xxia@ee.udel.edu
  organization: University of Delaware,Department of Electrical and Computer Engineering,Newark,USA,DE 19716
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Snippet In this paper, we investigate the precoder design for user-centric network (UCN) massive multiple-input multiple-output (mMIMO) downlink with matrix manifold...
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SubjectTerms Complexity theory
Global communication
Manifold optimization
Manifolds
Massive MIMO
Optimization
Performance gain
Precoding
Riemannian submanifold
Simulation
Transforms
user-centric network massive MIMO
Vectors
Title Matrix Manifold Precoder Design for User-Centric Network Massive MIMO
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