摘要
未来的第6代(6G)无线通信系统需要支持超大规模的用户需求,且对频谱效率和能源效率的要求越来越高。在此背景下,全息多输入多输出(MIMO)技术由于其具有智能可重构、电磁可调控、高方向性增益、成本低廉和部署灵活等潜力而愈发受到关注。在全息MIMO系统中,大量微小而廉价的天线单元被紧密集成,使其在低硬件成本的情况下能够实现高方向性增益,同时其可以对电磁波进行灵活的调控,从而有效提升了无线通信性能。该文从全息MIMO技术出发,首先简要介绍了全息MIMO的发展过程、技术现状、分类和特点,然后对全息MIMO在视距场景和空间平稳散射的非视距场景的信道模型进行了介绍,最后阐述了全息MIMO面对的挑战和未来趋势,并进行了总结。
The future Sixth-Generation(6G)wireless communication systems are required to support ultralarge-scale user demands,with increasing demands for spectrum efficiency and energy efficiency.In this context,Holographic Multiple-Input Multiple-Output(HMIMO)technology has gained increasing attention due to its potential for intelligent reconfigurability,electromagnetic tunability,high directional gain,cost-effectiveness,and flexible deployment.In holographic MIMO system,large amount small and cheap antenna units are integrated tightly,thus realize high directional gain at a low hardware cost and flexible adjustment of electromagnetic wave at the same time,thereby effectively enhancing the performance of wireless communication.A brief introduction to holographic MIMO technology is provided at the start of this paper,covering its current status,development process,classification,and key characteristics.Subsequently,the channel model for holographic MIMO in line-of-sight scenarios and non-line-of-sight scenarios with spatially smooth scattering is presented.Finally,the challenges and future trends faced by holographic MIMO technology are described,and the article is concluded.
作者
陈晓明
魏建川
黄崇文
CHEN Xiaoming;WEI Jianchuan;HUANG Chongwen(School of Information and Communications Engineering,Xi’an Jiaotong University,Xi’an 710049,China;College of Information Science and Electronic Engineering,Zhejiang University,Hangzhou 310027,China)
出处
《电子与信息学报》
EI
CAS
CSCD
北大核心
2024年第5期1703-1715,共13页
Journal of Electronics & Information Technology
基金
智能产品质量评价与可靠性保障技术工业和信息化部重点实验室基金(CEPREI2023-03)。
关键词
第6代通信
全息多输入多输出
可重构智能表面
信道模型
Sixth-Generation(6G)communications
Holographic Multiple-Input Multiple-Output(nMIMO)
Reconfigurable Intelligent Surface(RIS)
Channel model
