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

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 In the extremely high band, the channel state information (CSI) from channel estimation will be outdated quickly, and herein,...

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Main Authors: Changwei Lv, Jia-Chin Lin, Zhaocheng Yang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8615988/
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spelling doaj-05f5deed5d254111a698f4f2ab30ae2a2021-03-29T22:24:57ZengIEEEIEEE Access2169-35362019-01-017151831519510.1109/ACCESS.2019.28936198615988Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading ChannelsChangwei Lv0https://orcid.org/0000-0003-3585-2003Jia-Chin Lin1Zhaocheng Yang2Shenzhen Institute of Information Technology, Shenzhen, ChinaDepartment of Communication Engineering, National Central University, Taoyuan, TaiwanCollege of Information Engineering, Shenzhen University, Shenzhen, ChinaThe 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 In the extremely high band, the channel state information (CSI) from channel estimation will be outdated quickly, and herein, seriously degrading the system performance.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.https://ieeexplore.ieee.org/document/8615988/Channel predictionchannel representationsmillimeter wavesparse channelMIMO-OFDM systems
collection DOAJ
language English
format Article
sources DOAJ
author Changwei Lv
Jia-Chin Lin
Zhaocheng Yang
spellingShingle Changwei Lv
Jia-Chin Lin
Zhaocheng Yang
Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
IEEE Access
Channel prediction
channel representations
millimeter wave
sparse channel
MIMO-OFDM systems
author_facet Changwei Lv
Jia-Chin Lin
Zhaocheng Yang
author_sort Changwei Lv
title Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
title_short Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
title_full Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
title_fullStr Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
title_full_unstemmed Channel Prediction for Millimeter Wave MIMO-OFDM Communications in Rapidly Time-Varying Frequency-Selective Fading Channels
title_sort channel prediction for millimeter wave mimo-ofdm communications in rapidly time-varying frequency-selective fading channels
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description 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.
topic Channel prediction
channel representations
millimeter wave
sparse channel
MIMO-OFDM systems
url https://ieeexplore.ieee.org/document/8615988/
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AT jiachinlin channelpredictionformillimeterwavemimoofdmcommunicationsinrapidlytimevaryingfrequencyselectivefadingchannels
AT zhaochengyang channelpredictionformillimeterwavemimoofdmcommunicationsinrapidlytimevaryingfrequencyselectivefadingchannels
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