Spectrum for V2X: Allocation and Sharing

被引:9
|
作者
Ligo, Alexandre K. [1 ]
Peha, Jon M. [1 ]
机构
[1] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA
基金
美国安德鲁·梅隆基金会; 美国国家科学基金会;
关键词
Spectrum sharing; unlicensed spectrum; ITS; connected vehicles; DSRC; V2X; policy; COEXISTENCE; INTERNET;
D O I
10.1109/TCCN.2019.2916026
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper investigates how much spectrum should be available for intelligent transportation systems (ITS), and whether part of that spectrum should be shared with unlicensed devices, as has been considered by the U.S. Federal Communications Commission (FCC), and if so, what sharing scheme should be adopted. We found that the ITS bandwidth that maximizes social welfare could be either much more or much less than what has already been allocated, because optimal bandwidth is sensitive to uncertain factors, such as device penetration, future data rates, and spectrum opportunity cost. That uncertainty is offset if ITS spectrum is shared under a scheme of coexistence among equals. We also found that the bandwidth required to obtain given throughputs on shared spectrum can be considerably less than the bandwidth to obtain the same throughputs in separate bands. We conclude that the spectrum available for ITS should be maintained or increased, but much of ITS spectrum should be shared with non-ITS devices.
引用
收藏
页码:768 / 779
页数:12
相关论文
共 50 条
  • [21] Cross-Layer Resource Allocation for Multihop V2X Communications
    He, Yanhua
    Tang, Liangrui
    Ren, Yun
    Rodriguez, Jonathan
    Mumtaz, Shahid
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2019, 2019
  • [22] Federated Learning-Based Resource Allocation for V2X Communications
    Bhardwaj, Sanjay
    Kim, Da-Hye
    Kim, Dong-Seong
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2025, 26 (01) : 382 - 396
  • [23] QoS based Deep Reinforcement Learning for V2X Resource Allocation
    Bhadauria, Shubhangi
    Shabbir, Zohaib
    Roth-Mandutz, Elke
    Fischer, Georg
    2020 IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING (BLACKSEACOM), 2020,
  • [24] V2X offloading and resource allocation under SDN and MEC architecture
    Zhang H.
    Wang Z.
    He X.
    Wang, Zixin (377698527@qq.com), 1600, Editorial Board of Journal on Communications (41): : 114 - 124
  • [25] Centralized Resource Allocation Latency of SideLink Communication in NR V2X
    Sabeeh, Saif
    2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL), 2022,
  • [26] Deep Neural Network Based Resource Allocation for V2X Communications
    Gao, Jin
    Khandaker, Muhammad R. A.
    Tariq, Faisal
    Wong, Kai-Kit
    Khan, Risala T.
    2019 IEEE 90TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2019-FALL), 2019,
  • [27] Experimental evaluation of V2X connectivity technologies with V2X channel models
    Molla, Dereje-Mechal
    Hadji, Chadli
    Maaloul, Sassi
    Berbineau, Marion
    Narouwa, Massamaesso
    Mendiboure, Leo
    Badis, Hakim
    2024 18TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION, EUCAP, 2024,
  • [28] Secure Resource Allocation for LTE-Based V2X Service
    Ahmed, Kazi J.
    Lee, Myung J.
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (12) : 11324 - 11331
  • [29] Stackelberg Game-Based Power Allocation for V2X Communications
    Zhang, Erqing
    Yin, Sixing
    Ma, Huisheng
    SENSORS, 2020, 20 (01)
  • [30] Optimizing V2X Communication: Spectrum Resource Allocation and Power Control Strategies for Next-Generation Wireless Technologies
    Ibrahim, Ali. M. A.
    Chen, Zhigang
    Wang, Yijie
    Eljailany, Hala A.
    Ipaye, Aridegbe A.
    APPLIED SCIENCES-BASEL, 2024, 14 (02):