基于深度Q学习的蜂窝车联网边路资源分配算法

doi:10.11959/j.issn.2096-6652.202309

Abstract

Abstract:

For the sidelink resource autonomous selection scheme of different priority services in celluar-vehicle to everything (C-V2X) system, the procedure of autonomous selection algorithm based on reference signal energy was analyzed, and the energy threshold equation was designed.For the energy equation parameter estimation problem, energy-based autonomous selection algorithm was combined with deep Q learning algorithm, and the optimal parameter value of the energy threshold equation was obtained by iteration of the finite-degree algorithm.Simulation results showed that the side resource allocation algorithm based on deep Q learning could ensure the side resource requirements of V2X services with different priorities, and improve the packet reception ratio performance of the system.

Key words: C-V2X, sidelink, autonomous resource selection, machine learning, PRR

CLC Number:

TN929.5

Hui XU. Sidelink resource allocation algorithm of C-V2X based on deep Q learning[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(1): 83-91.

Figures/Tables 11

References 19

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参数	优先级p1,p2	动作集合a_t	b	折扣γ	学习因子α	资源分配信息SA	子信道	数据包
值	{1,2,3,4,5,6,7,8}	{0,1,2,3,…,10}	-87	0.5	0.9	30 bit（发两次）	10 PRB	190/300 B

Sidelink resource allocation algorithm of C-V2X based on deep Q learning

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