The fifth generation (5G) wireless communication network uses multiple input multiple output (MIMO) technology, which requires a lot of air interface resource estimation and feedback MIMO channel. Besides optimizing pilot, estimation and feedback design, channel fading prediction is also an effective way to save air interface resources. In this paper, phase space reconstruction method is used to study the phase space reconstruction parameters related to three-dimensional channel model, and a small sample online learning method based on empirical knowledge is proposed to predict MIMO channel coefficients and channel capacity. It is found that the wireless channel data is chaotic, and the phase space delay time and embedding dimension obey a certain distribution, so it can be set as the prior parameters of real-time prediction. Experimental results show that the prediction efficiency of the proposed method is about six times higher than that of the traditional ARMA method, and the minimum average error of channel capacity is 5.91%. Finally, the effectiveness of the phase space reconstruction method is verified by the measured data of an urban area, and the minimum average error of channel capacity prediction is 0.91%.
FENG Xinyu
,
LI Kai
,
REN Tianfeng
,
LI Hanhui
,
YANG Yang
,
ZHOU Mingtuo
. Three dimensional MIMO wireless channel prediction based on phase space reconstruction[J]. Journal of University of Chinese Academy of Sciences, 2023
, 40(1)
: 135
-143
.
DOI: 10.7523/j.ucas.2021.0032
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