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Energy-Efficient Resource Allocation for D2D-V2V Communication with Load Balancing

Author

Listed:
  • Jie Bi

    (College of Information Science and Engineering, Xinjiang University, Urumqi 830000, China)

  • Xizhong Qin

    (College of Information Science and Engineering, Xinjiang University, Urumqi 830000, China)

  • Zhenhong Jia

    (College of Information Science and Engineering, Xinjiang University, Urumqi 830000, China)

Abstract

The significance of vehicle-to everything (V2X) communication in ensuring road safety is undeniable. In addition, real-time vehicle communication requires an ample amount of spectrum resources. However, the existing spectrum resources are seriously scarce, and the utilization rate is not high, leading to high delays in V2X communication and other unfavorable factors in the case of fast-moving vehicles, bringing great safety risks to driving. Load balancing is one of the most effective methods to improve spectrum utilization. However, the existing load balancing schemes merely focus on static conditions, with a lack of joint scheduling schemes, which cannot support the communication framework of dynamic V2X. To address both of these issues, in this paper, a new communication method is proposed. In addition, this paper studies a joint load balancing scheme of mobility vehicle-to-vehicle (V2V) and user association under incomplete channel state information (CSI) and realizes the load balancing management of a cross-cell V2X network. An algorithm combining power control and resource allocation mode selection is proposed. In particular, according to different coverage areas, different allocation algorithms are adopted to maximize the overall system efficiency. The simulation results show that this strategy can maintain low latency and effectively improve the system energy efficiency of vehicle users.

Suggested Citation

  • Jie Bi & Xizhong Qin & Zhenhong Jia, 2023. "Energy-Efficient Resource Allocation for D2D-V2V Communication with Load Balancing," Mathematics, MDPI, vol. 11(13), pages 1-20, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2848-:d:1179042
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    References listed on IDEAS

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    1. Yuanfeng Ding & Yan Huang & Li Tang & Xizhong Qin & Zhenhong Jia, 2022. "Resource Allocation in V2X Communications Based on Multi-Agent Reinforcement Learning with Attention Mechanism," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    2. Werner Dinkelbach, 1967. "On Nonlinear Fractional Programming," Management Science, INFORMS, vol. 13(7), pages 492-498, March.
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    Cited by:

    1. Young-Hwan You & Yong-An Jung, 2023. "Complexity-Efficient Sidelink Synchronization Signal Detection Scheme for Cellular Vehicle-to-Everything Communication Systems," Mathematics, MDPI, vol. 11(18), pages 1-15, September.

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