Learning End-to-End Hybrid Precoding for Multi-User mmWave Mobile System With GNNs

Learning End-to-End Hybrid Precoding for Multi-User mmWave Mobile System With GNNs

Hybrid precoding is an efficient technique for achieving high rates at a low cost in millimeter wave (mmWave) multi-antenna systems. Many research efforts have explored the use of deep learning to optimize hybrid precoding, particularly in static channel scenarios. However, in mobile communication s...

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Bibliographic Details
Main Authors: Ruiming Wang, Chenyang Yang, Shengqian Han, Jiajun Wu, Shuangfeng Han, Xiaoyun Wang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Hybrid precoding
end-to-end learning
channel prediction
channel estimation
graph neural network
Online Access:https://ieeexplore.ieee.org/document/10577095/
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