Low-Complexity Beam Domain Precoding for XL-MIMO Downlink with User Grouping and Beam Extraction

This paper proposes a low-complexity beam domain precoder design for the three-dimensional (3D) extra-large-scale multi-input multi-output (XL-MIMO) downlink with multi-antenna user equipments (UEs). To reduce the complexity while maintaining the performance of the eigen zero forcing (EZF) precoder, we divide the UEs into different groups. Each group designs its precoding matrix using selected beam vectors, respectively. We call this precoder the beam domain group precoding (BDGP). We formulate a combinatorial optimization problem and derive a heuristic algorithm to solve the grouping problem based on statistical channel state information (CSI). Moreover, we introduce a novel beam extraction algorithm to maximize the inter-group signal to interference plus noise ratio (SINR). To further reduce the complexity of BDGP, we leverage the sparsity of the beam domain channel and inter-group interference and replace the matrix inversion with the approach that solves linear equations twice through Cholesky decomposition. Simulation results show that BDGP significantly reduces the complexity while achieving comparable sum-rate performance.

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Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/icccs65393.2025.11069680
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Complexity Beam Domain Precoding for XL-MIMO Downlink with User Grouping and Beam Extraction

Ping‐Rong Lin, An-An Lu, Nan Zheng, Xiqi Gao
Advanced MIMO Systems Optimization
article

Low-Complexity Beam Domain Precoding for XL-MIMO Downlink with User Grouping and Beam Extraction

Ping‐Rong Lin, An-An Lu, Nan Zheng, Xiqi Gao
article en

Abstract

This paper proposes a low-complexity beam domain precoder design for the three-dimensional (3D) extra-large-scale multi-input multi-output (XL-MIMO) downlink with multi-antenna user equipments (UEs). To reduce the complexity while maintaining the performance of the eigen zero forcing (EZF) precoder, we divide the UEs into different groups. Each group designs its precoding matrix using selected beam vectors, respectively. We call this precoder the beam domain group precoding (BDGP). We formulate a combinatorial optimization problem and derive a heuristic algorithm to solve the grouping problem based on statistical channel state information (CSI). Moreover, we introduce a novel beam extraction algorithm to maximize the inter-group signal to interference plus noise ratio (SINR). To further reduce the complexity of BDGP, we leverage the sparsity of the beam domain channel and inter-group interference and replace the matrix inversion with the approach that solves linear equations twice through Cholesky decomposition. Simulation results show that BDGP significantly reduces the complexity while achieving comparable sum-rate performance.

Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 85%
Advanced MIMO Systems Optimization
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