The rayleigh fading channel prediction via deep learning
Author
Abstract
This paper presents a multi-time channel prediction system based on backpropagation (BP) neural network with multi-hidden layers, which can predict channel information effectively and benefit for massive MIMO performance, power control, and artificial noise physical layer security scheme design. Meanwhile, an early stopping strategy to avoid the overfitting of BP neural network is introduced. By comparing the predicted normalized mean square error (NMSE), the simulation results show that the performances of the proposed scheme are extremely improved. Moreover, a sparse channel sample construction method is proposed, which saves system resources effectively without weakening performances.
Patrocinador
NSFC
61572114
National Major RD Program
2018YFB0904905
Chile Conicyt Fondecyt Project
1181809
Indexation
Artículo de publicación ISI
Quote Item
Wireless Communications and Mobile Computing Volume 2018, Article ID 6497340, 11 pages
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