Massive MIMO Uplink Transmission for Multi-Satellite Communications

In this paper, we investigate massive multiple-input multiple-output (MIMO) uplink (UL) transmission for multiple low-earth-orbit (LEO) satellite communications. We establish the system model and reveal that the signals transmitted from the user terminals (UTs), which are intended for different satellites, are typically asynchronous at each satellite. Then, at each UT, we propose linear precoding with time and frequency precompensations for each satellite, so that the signals intended for a specific satellite can be synchronized. We formulate the ergodic sum rate maximization problem and propose a Riemannian conjugate gradient (RCG) based precoding vector design algorithm within the manifold optimization framework, which does not include any matrix inversion. Simulation results indicate the effectiveness of our proposed approaches.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icct62411.2024.10946652
Citations
1
Primary Topic
Satellite Communication Systems
Type
article
Field-Weighted Citation Impact
1.30

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Massive MIMO Uplink Transmission for Multi-Satellite Communications

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Massive MIMO Uplink Transmission for Multi-Satellite Communications

Xiqi Gao, Xinrui Gong, Xiang‐Gen Xia, Ziyu Xiang, Kexin Li, Wenjing Liu, Rui Sun
article en
1 citations

Abstract

In this paper, we investigate massive multiple-input multiple-output (MIMO) uplink (UL) transmission for multiple low-earth-orbit (LEO) satellite communications. We establish the system model and reveal that the signals transmitted from the user terminals (UTs), which are intended for different satellites, are typically asynchronous at each satellite. Then, at each UT, we propose linear precoding with time and frequency precompensations for each satellite, so that the signals intended for a specific satellite can be synchronized. We formulate the ergodic sum rate maximization problem and propose a Riemannian conjugate gradient (RCG) based precoding vector design algorithm within the manifold optimization framework, which does not include any matrix inversion. Simulation results indicate the effectiveness of our proposed approaches.

Huawei Technologies (China) (CN), Purple Mountain Laboratories (CN), Southeast University (CN), University of Delaware (US)
Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 10%
Satellite Communication Systems
1.30
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