Reconfigurable Intelligent Surface (RIS)-Aided Vehicular Networks Their Protocols, Resource Allocation, and Performance

被引:46
|
作者
Chen, Yuanbin [1 ]
Wang, Ying [2 ]
Zhang, Jiayi [3 ]
Zhang, Ping [4 ]
Hanzo, Lajos [5 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[2] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[3] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[4] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switch Technol, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[5] Univ Southampton, Dept Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
来源
IEEE VEHICULAR TECHNOLOGY MAGAZINE | 2022年 / 17卷 / 02期
基金
国家重点研发计划; 英国工程与自然科学研究理事会; 中国国家自然科学基金; 北京市自然科学基金; 欧洲研究理事会;
关键词
SYSTEMS;
D O I
10.1109/MVT.2022.3158046
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving. Having said that, the 3rd Generation Partnership Project (3GPP) faces numerous open challenges concerning the RIS-aided vehicle-to-everything (V2X) solutions of the near future. To tackle these challenges and to stimulate future research, this article focuses on the prospective transmission design of RIS-aided V2X communications. In particular, two V2X sidelink modes are enhanced by exploiting RISs and their variants, followed by a customized transmission frame structure that partitions the transmission efforts into different phases. Next, effective channel-tracking and resource allocation techniques are developed for attaining a high beamforming gain at low overhead and complexity. Finally, promising research topics are highlighted, and future 3GPP standardization items are proposed for RIS-aided V2X systems. © 2005-2012 IEEE.
引用
收藏
页码:26 / 36
页数:11
相关论文
共 50 条
  • [41] Performance Analysis of Cascaded Reconfigurable Intelligent Surface Networks
    Tyrovolas, Dimitrios
    Tegos, Sotiris A.
    Dimitriadou-Panidou, Emmanouela C.
    Diamantoulakis, Panagiotis D.
    Liaskos, Christos K.
    Karagiannidis, George K.
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2022, 11 (09) : 1855 - 1859
  • [42] Robust Transmission for Reconfigurable Intelligent Surface Aided Millimeter Wave Vehicular Communications With Statistical CSI
    Chen, Yuanbin
    Wang, Ying
    Jiao, Lei
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2022, 21 (02) : 928 - 944
  • [43] Reconfigurable Intelligent Surface-Aided Cognitive NOMA Networks: Performance Analysis and Deep Learning Evaluation
    Vu, Thai-Hoc
    Nguyen, Toan-Van
    da Costa, Daniel Benevides
    Kim, Sunghwan
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2022, 21 (12) : 10662 - 10677
  • [44] Secrecy Performance Analysis for Reconfigurable Intelligent Surface aided NOMA Network
    Tang, Zhiqing
    Hou, Tianwei
    Liu, Yuanwei
    Zhang, Jiankang
    2021 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2021,
  • [45] Performance Analysis of Distributed Reconfigurable Intelligent Surface Aided NOMA Systems
    Caihong Gong
    Xiaoming Dai
    Jianuo Cui
    Keping Long
    Wireless Personal Communications, 2023, 131 : 217 - 231
  • [46] Performance Analysis of Distributed Reconfigurable Intelligent Surface Aided NOMA Systems
    Gong, Caihong
    Dai, Xiaoming
    Cui, Jianuo
    Long, Keping
    WIRELESS PERSONAL COMMUNICATIONS, 2023, 131 (01) : 217 - 231
  • [47] Intelligent Reflecting Surface Aided Vehicular Communications
    Dampahalage, Dilin
    Manosha, K. B. Shashika
    Rajatheva, Nandana
    Latva-aho, Matti
    2020 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2020,
  • [48] Self-Sustainable Intelligent Omni-Surface Aided Wireless Networks: Protocol Design and Resource Allocation
    Lv, Lu
    Luo, Hao
    Li, Zan
    Wu, Qingqing
    Ding, Zhiguo
    Al-Dhahir, Naofal
    Chen, Jian
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (07) : 7503 - 7519
  • [49] Performance Analysis for Large Intelligent Surface Assisted Vehicular Networks
    Yiyang Ni
    Yaxuan Liu
    Jin Zhou
    Qin Wang
    Haitao Zhao
    Hongbo Zhu
    中国通信, 2021, 18 (03) : 1 - 17
  • [50] ARTNet: Ai-Based Resource Allocation and Task Offloading in a Reconfigurable Internet of Vehicular Networks
    Ibrar, Muhammad
    Akbar, Aamir
    Jan, Syed Rooh Ullah
    Jan, Mian Ahmad
    Wang, Lei
    Song, Houbing
    Shah, Nadir
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2022, 9 (01): : 67 - 77