CLC number: TN928
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-05-01
Cited: 0
Clicked: 5831
Citations: Bibtex RefMan EndNote GB/T7714
https://orcid.org/0000-0001-7131-4232
Zhao Yi, Weixia Zou, Xuebin Sun. Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(6): 777-789.
@article{title="Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond",
author="Zhao Yi, Weixia Zou, Xuebin Sun",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="6",
pages="777-789",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000515"
}
%0 Journal Article
%T Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond
%A Zhao Yi
%A Weixia Zou
%A Xuebin Sun
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 6
%P 777-789
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000515
TY - JOUR
T1 - Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond
A1 - Zhao Yi
A1 - Weixia Zou
A1 - Xuebin Sun
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 6
SP - 777
EP - 789
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000515
Abstract: millimeter wave (mmWave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5G and beyond. To realize applications in future vehicular communications, it is important to take a robust mmWave vehicular network into consideration. However, one challenge in such a network is that mmWave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure (V2I). Moreover, traditional real-time channel estimation strategies are unavailable because vehicle mobility leads to a fast variation mmWave channel. To overcome these issues, a channel estimation approach for mmWave V2I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast time-varying channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the time-varying channel prior information (PI). Finally, by exploiting the PI and the characteristics of the channel, the time-varying channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mmWave time-varying vehicular system.
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