Full Text:   <372>

Summary:  <326>

CLC number: TN928

On-line Access: 2021-07-12

Received: 2020-09-30

Revision Accepted: 2021-01-21

Crosschecked: 2021-05-01

Cited: 0

Clicked: 904

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Zhao Yi

https://orcid.org/0000-0001-7131-4232

Weixia Zou

https://orcid.org/0000-0002-1452-9787

Xuebin Sun

https://orcid.org/0000-0002-7508-4945

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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.6 P.777-789

http://doi.org/10.1631/FITEE.2000515


Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond


Author(s):  Zhao Yi, Weixia Zou, Xuebin Sun

Affiliation(s):  MOE Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China; more

Corresponding email(s):   yz17tx@bupt.edu.cn, zwx0218@bupt.edu.cn

Key Words:  Massive multiple-input multiple-output, Millimeter wave, Channel estimation, Vehicular communication, Time-varying


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.

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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.

基于先验信息的5G及后5G毫米波大规模多入多出车载通信信道估计

易钊1,邹卫霞1,2,孙学斌1
1北京邮电大学泛网无线通信教育部重点实验室,中国北京市,100876
2东南大学毫米波国家重点实验室,中国南京市,210096
摘要:毫米波(mmWave)被认为是5G及后5G高带宽车载通信的可行解决方案。为实现在未来车辆通信中的应用,鲁棒的毫米波车载网络非常重要。然而,一个挑战是,毫米波应在车辆或车辆到基础设施(V2I)之间提供高速和超高速数据交换。此外,由于车辆的高速移动引起毫米波信道快速变化,传统的实时信道估计方案难以实现。针对这些问题,提出一种毫米波V2I车辆通信信道估计方法。首先考虑快速运动的车辆场景,建立相应的快速时变信道数学模型。然后,利用基站与每个移动用户之间的时间变化规律和确定的到达方向,预测时变信道先验信息(PI)。最后,利用PI和信道特性对时变信道进行估计。仿真结果表明,在毫米波时变车载通信系统中,该方案在归一化均方误差和和率性能上均优于传统方案。

关键词:大规模多入多出;毫米波;信道估计;车辆通信;时变

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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