Channel Prediction for Millimeter Wave MIMO-OFDM Communication in Rapidly Time-Varying Frequency-Selective Fading Channels

被引:18
|
作者
Lv, Changwei [1 ]
Lin, Jia-Chin [2 ]
Yang, Zhaocheng [3 ,4 ]
机构
[1] Shenzhen Inst Informat Technol, Shenzhen 518172, Peoples R China
[2] Natl Cent Univ, Dept Commun Engn, Taoyuan 32001, Taiwan
[3] Shenzhen Univ, Coll Informat Engn, Shenzhen 518067, Peoples R China
[4] Shenzhen Univ, Coll Informat Engn, Guangdong Key Lab Intelligent Informat Proc, Shenzhen 518060, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
基金
中国国家自然科学基金;
关键词
Channel prediction; channel representations; millimeter wave; sparse channel; MIMO-OFDM systems; LONG-RANGE PREDICTION; ADAPTIVE TRANSMISSION; LOW-COMPLEXITY; CHALLENGES; TRACKING; SIGNALS; SYSTEM;
D O I
10.1109/ACCESS.2019.2893619
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems communicate at the extremely high-frequency band. In the extremely high band, the channel state information (CSI) from channel estimation will be outdated quickly, and herein, seriously degrading the system performance. In this paper, we focus on the channel prediction to obtain prior CSI in mmWave MIMO-OFDM systems. First, the mmWave MIMO-OFDM channel is categorized and represented in four domains: the array-frequency, array-time, angle-frequency, as well as angle-time. Then, for the above four domains, we investigate the effects of the channel representations on channel prediction, and analyze the mean-squared error performance as well as the computational complexity of the investigated prediction methods. We derive that the angle-time-domain prediction method achieves higher accuracy than the other three prediction techniques. In addition, we propose an enhanced angle-time-domain channel predictor by exploiting the spatial-time sparsity of the MIMO-OFDM channel to further improve the prediction accuracy. Finally, the simulation results confirm the statistical analysis and verify the superiority of the proposed predictors.
引用
收藏
页码:15183 / 15195
页数:13
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