Deep Reinforcement Learning based Distributed Resource Allocation for V2V Broadcasting

被引：0
|
作者：
Ye, Hao [1 ]
Li, Geoffrey Ye [1 ]
机构：
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
来源：
2018 14TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) | 2018年
基金：
美国国家科学基金会;
关键词：
Deep Reinforcement Learning; V2V Communication; Resource Allocation;
D O I：
暂无
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：
In this article, we exploit deep reinforcement learning for joint resource allocation and scheduling in vehicle-tovehicle (V2V) broadcast communications. Each vehicle, considered as an autonomous agent, makes its decisions to find the messages and spectrum for transmission based on its local observations without requiring or having to wait for global information. From the simulation results, each vehicle can effectively learn how to ensure the stringent latency constraints on V2V links while minimizing the interference to vehicle-to-infrastructure (V2I) links.
引用
收藏
页码：440 / 445
页数：6
相关论文
共 50 条
  • [1] Deep Reinforcement Learning Based Resource Allocation for V2V Communications
    Ye, Hao
    Li, Geoffrey Ye
    Juang, Biing-Hwang Fred
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (04) : 3163 - 3173
  • [2] Deep Reinforcement Learning for Resource Allocation in V2V Communications
    Ye, Hao
    Li, Geoffrey Ye
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2018,
  • [3] Cooperative Reinforcement Learning based Adaptive Resource Allocation in V2V Communication
    Sharma, Sandeepika
    Singh, Brahmjit
    [J]. 2019 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN), 2019, : 489 - 494
  • [4] Deep Reinforcement Learning Based Resource Allocation for 5G V2V Groupcast Communications
    Wu, Shang-Huan
    Hwang, Ren-Hung
    Wang, Chih-Yu
    Chou, Ching-Hsuan
    [J]. 2023 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS, ICNC, 2023, : 1 - 6
  • [5] Distributed V2V Computation Offloading Based on Dynamic Pricing Using Deep Reinforcement Learning
    Shi, Jinming
    Du, Jun
    Wang, Jian
    Yuan, Jian
    [J]. 2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2020,
  • [6] Beam management optimization for V2V communications based on deep reinforcement learning
    Junliang Ye
    Xiaohu Ge
    [J]. Scientific Reports, 13
  • [7] Beam management optimization for V2V communications based on deep reinforcement learning
    Ye, Junliang
    Ge, Xiaohu
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [8] QoS based Deep Reinforcement Learning for V2X Resource Allocation
    Bhadauria, Shubhangi
    Shabbir, Zohaib
    Roth-Mandutz, Elke
    Fischer, Georg
    [J]. 2020 IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING (BLACKSEACOM), 2020,
  • [9] Resource Allocation for NOMA-based V2V System
    Xu, Yiyi
    Gu, Xinyu
    [J]. PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON NETWORK INFRASTRUCTURE AND DIGITAL CONTENT (IEEE IC-NIDC), 2018, : 239 - 243
  • [10] A Joint Power and Bandwidth Allocation Method Based on Deep Reinforcement Learning for V2V Communications in 5G
    Hu, Xin
    Xu, Sujie
    Wang, Libing
    Wang, Yin
    Liu, Zhijun
    Xu, Lexi
    Li, You
    Wang, Weidong
    [J]. CHINA COMMUNICATIONS, 2021, 18 (07) : 25 - 35
12345