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Volume 42 Issue 2
Feb.  2020
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Lun TANG, Jiao XIAO, Guofan ZHAO, Youchao YANG, Qianbin CHEN. Energy Efficiency Based Dynamic Resource Allocation Algorithm for Cellular Vehicular Based on Non-Orthogonal Multiple Access[J]. Journal of Electronics & Information Technology, 2020, 42(2): 526-533. doi: 10.11999/JEIT190006
Citation: Lun TANG, Jiao XIAO, Guofan ZHAO, Youchao YANG, Qianbin CHEN. Energy Efficiency Based Dynamic Resource Allocation Algorithm for Cellular Vehicular Based on Non-Orthogonal Multiple Access[J]. Journal of Electronics & Information Technology, 2020, 42(2): 526-533. doi: 10.11999/JEIT190006

Energy Efficiency Based Dynamic Resource Allocation Algorithm for Cellular Vehicular Based on Non-Orthogonal Multiple Access

doi: 10.11999/JEIT190006
Funds:  The National Natural Science Foundation of China (61571073), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-M201800601)
  • Received Date: 2019-01-03
  • Rev Recd Date: 2019-05-28
  • Available Online: 2019-11-25
  • Publish Date: 2020-02-19
  • In the Non-Orthogonal Multiple Access (NOMA) based cellular network with Vehicle-to-Vehicle (V2V) communication, to mitigate the co-channel interference between V2V users and cellular users as well as the power allocation problem based on the NOMA principle, an energy efficiency dynamic resource allocation algorithm is proposed. Firstly, a stochastic optimization model is established to maximize the energy efficiency by considering subchannel scheduling, power allocation and congestion control, in order to guarantee the delay and reliability of V2V users while satisfying the rate of cellular users. Then, leveraging on the Lyapunov stochastic optimization method, the traffic queues can be stabilized by admitting as much traffic data as possible to avoid network congestion, and the radio resource can be allocated dynamically according to the real-time network traffic and thus a suboptimal subchannel matching algorithm is designed to obtain the user scheduling scheme. Furthermore, the power allocation policy is obtained by utilizing successive convex optimization theory and Lagrange dual decomposition method. Finally, the simulation results show that the proposed algorithm can improve the system energy efficiency and ensure the Quality of Service (QoS) requirements of different users and network stability.

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