Performance Evaluation of C-V2X Mode 4 Communications

被引:6
作者
Chen, Miling [1 ]
Chai, Rong [1 ]
Hu, Hang [1 ]
Jiang, Wenhang [1 ]
He, Lin [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Key Lab Mobile Commun Technol, Chongqing 400065, Peoples R China
来源
2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2021年
基金
中国国家自然科学基金;
关键词
C-V2X; Mode; 4; sensing-based semi-persistent scheduling; packet reception ratio;
D O I
10.1109/WCNC49053.2021.9417517
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cellular vehicular-to-everything (C-V2X), as a key technology of Internet of Vehicles (IoVs), is expected to improve road traffic safety and achieve intelligent transportation. C-V2X mainly supports two communication modes, Mode 3 and Mode 4. Mode 3 supports centralized control and management of network resources whereas Mode 4 allows vehicles to select radio resources independently for data transmission without the aid of network infrastructures. In this paper, we present an overview of C-V2X Mode 4 communication and stress several major enhancements compared to long term evolution (LTE), including subframe structure design, synchronization mechanism, resource pool configuration, and resource scheduling mechanism, i.e., sensing-based semi-persistent scheduling (S-SPS), etc. To evaluate the transmission performance of C-V2X, we set up a system-level simulation platform based on the integration of traffic simulator CarMaker and network simulator (NS)-3, where CarMaker is utilized to simulate real vehicle trajectories and NS-3 is applied to implement the communication protocols of C-V2X. Under various simulation scenarios, the transmission performance in terms of packet reception ratio (PRR) is examined and the impacts of resource scheduling parameters, including resource reselection probability, resource reservation interval and channel bandwidth on PRR are evaluated.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Multiagent Reinforcement Learning-Based Semi-Persistent Scheduling Scheme in C-V2X Mode 4
    Gu, Bo
    Chen, Weixiang
    Alazab, Mamoun
    Tan, Xiaojun
    Guizani, Mohsen
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (11) : 12044 - 12056
  • [32] Performance Analysis of Sensing-Based Semi-Persistent Scheduling in C-V2X Networks
    Nabil, Amr
    Kaur, Komalbir
    Dietrich, Carl
    Marojevic, Vuk
    2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2018,
  • [33] 携手推进C-V2X产业发展
    吕晓峰
    智能网联汽车, 2019, (01) : 49 - 49
  • [34] 蜂窝车联网(C-V2X)综述
    陈山枝
    时岩
    胡金玲
    中国科学基金, 2020, 34 (02) : 179 - 185
  • [35] On Wireless Blind Spots in the C-V2X Sidelink
    Bazzi, Alessandro
    Campolo, Claudia
    Molinaro, Antonella
    Berthet, Antoine O.
    Masini, Barbara M.
    Zanella, Alberto
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (08) : 9239 - 9243
  • [36] C-V2X切片随机接入技术
    杨保峰
    宋健
    沈庆国
    移动通信, 2021, 45 (06) : 27 - 36
  • [37] C-V2X无线技术演进研究
    牟晋宏
    山东通信技术, 2021, 41 (03) : 18 - 22
  • [38] Latency Analysis of Drone-Assisted C-V2X Communications for Basic Safety and Co-Operative Perception Messages
    Gupta, Abhishek
    Fernando, Xavier N.
    DRONES, 2024, 8 (10)
  • [39] GPS Accuracy of the Latest C-V2X Units for V2X Applications
    Choffin, Zachary
    Riley, William
    Hainen, Alexander
    Balasubramanian, Bharat
    Bittle, Joshua
    Jo, Han-Shin
    Jeong, Nathan
    2023 IEEE VEHICLE POWER AND PROPULSION CONFERENCE, VPPC, 2023,
  • [40] Building mmWave on the evolving C-V2X: MmWave NR-V2X
    Chen, Shanzhi
    He, Xinxin
    Zhao, Rui
    Hu, Jinling
    Zhang, Xin
    CHINA COMMUNICATIONS, 2024, 21 (01) : 88 - 101