The Journal of China Universities of Posts and Telecommunications ›› 2023, Vol. 30 ›› Issue (6): 68-81.doi: 10.19682/j.cnki.1005-8885.2023.1020

Special Issue: 复杂网络传播与网络控制

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Fairness optimization and power allocation in cognitive NOMA / OMA V2V network with imperfect SIC

Liang Xiaolin, Liu Qianlong, Cao Wangbin, Liu Shuaiqi, Zhao Shuhuan, Zhao Xiongwen   

  1. 1. College of Electronic and Information Engineering, Hebei University, Baoding 071002, China
    2. Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, China
    3. School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
    4. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2023-09-18 Revised:2023-10-03 Online:2023-12-28 Published:2023-12-28
  • Contact: Cao Wangbin
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (62001166, 62172139), the Open Subject
    of Hebei Key Laboratory of Power Internet of Things Technology (2023KFKT002), and the Natural Science Foundation of Hebei Province of China (F2022201055).


In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle (V2V) communication system, in this paper, the fairness optimization and power allocation for the cognitive V2V network that takes into account the realistic three-dimensional (3D) channel are investigated. Large-scale and small-scale fading are considered in the proposed channel model. An adaptive non-orthogonal multiple access ( NOMA) / orthogonal multiple access (OMA) scheme is proposed to reduce the complexity of successive-interference-cancellation (SIC) in decoding and improve spectrum utilization. Also, a fairness index that takes into account each user’s requirements is proposed to indicate the optimal point clearly. In the imperfect SIC, the optimization problem of maximizing user fairness is formulated. Then, a subgradient descent method is proposed to solve the optimization problem with customizable precision. And the computational complexity of the proposed method is analyzed. The achievable rate, outage probability and user fairness are analyzed. The results show that the proposed adaptive NOMA / OMA (A-NOMA / OMA) outperforms both NOMA and OMA. The simulation results are compared with validated analysis to confirm the theoretical analysis.

Key words: adaptive non-orthogonal multiple access ( NOMA ) / orthogonal multiple access ( OMA ), user fairness, power allocation, imperfect successive-interference-cancellation (SIC), vehicle-to-vehicle (V2V) communication