The Rayleigh Fading Channel Prediction via Deep Learning. (25th July 2018)

• Record Type: Journal Article
• Authors: Liao, Run-Fa; Wen, Hong; Wu, Jinsong; Song, Huanhuan; Pan, Fei; Dong, Lian
• Other Names: Cassioli Dajana Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2018(2018)
• Publication Date: 2018-07-25
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2018/6497340
• Languages: English
• ISSNs: 1530-8669

Abstract

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.