Study On Optical Communications, Volume. 49, Issue 3, 71(2023)

Spectrum Resourse Management Method of V2X based on Deep Reinforcement Learning

Ming-hu WU... Bo JIN, Nan ZHAO* and Ru WANG |Show fewer author(s)
Author Affiliations
  • School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
  • show less

    Aiming at the problem of spectrum scarcity faced by Vehicle to Everything (V2X) communication, a deep reinforcement learning method is proposed to manage V2X spectrum resources. Firstly, the V2X communication model of a single vehicle to infrastructure link is established. Combined with the constraints such as frequency spectrum subband and transmission power, the optimization problem is constructed to maximize the comprehensive efficiency of V2X communication network. Secondly, considering the non-convexity of the optimization problem, the communication model can be regarded as a Markov decision process. Then, the Dueling-Deep Q Network (Dueling-DQN) algorithm is introduced to obtain the optimal spectrum subband selection and transmission power allocation strategy to maximize the comprehensive efficiency of V2X communication network. Finally, the simulation is carried out on tensorflow software platform to verify the performance of the proposed method. The simulation results show that Dueling-DQN algorithm can obtain higher link performance and V2X communication network efficiency compared with other algorithm.

    Tools

    Get Citation

    Copy Citation Text

    Ming-hu WU, Bo JIN, Nan ZHAO, Ru WANG. Spectrum Resourse Management Method of V2X based on Deep Reinforcement Learning[J]. Study On Optical Communications, 2023, 49(3): 71

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Research Articles

    Received: Jun. 21, 2022

    Accepted: --

    Published Online: Jun. 12, 2023

    The Author Email: ZHAO Nan (nzhao@mail.hbut.edu.cn)

    DOI:10.13756/j.gtxyj.2023.03.012

    Topics