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Research on power allocation in V2X network based on Reinforcement Learning
Wang Yanlong 1 *,Liu Jun 2,Yang Jie 2
1.Beijing University of Posts and Telecommunications (School of Artificial Intelligence);Beijing University of Posts and Telecommunications (School of Artificial Intelligence);Beijing University of Posts and Telecommunications (School of Artificial Intelligence)
2.
*Correspondence author
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Funding: none
Opened online:30 March 2021
Accepted by: none
Citation: Wang Yanlong,Liu Jun,Yang Jie.Research on power allocation in V2X network based on Reinforcement Learning[OL]. [30 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754266
 
 
With the rapid development of IoT (Internet of Things), the application scenarios of wireless devices accessing the network has been greatly enriched. Vehicle-to-Everything (V2X) is one of the most typical scenarios. This paper proposes a model of the V2X power distribution problem in a multi-base station scenario for the power allocation problem, and designs three types of reinforcement learning algorithms. The specific optimization problems are publicized and deduced and the elements of the reinforcement learning algorithm are sorted out. The results show that the performance of the DDPG algorithm is the best, which verifies the feasibility of the reinforcement learning algorithm in the V2X scenarios.
Keywords: V2X; power allocation; reinforcement learning; DDPG
 
 
 

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