期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Reinforcement learning based edge computing in B5G
1
作者 Jiachen Yang Yiwen Sun +4 位作者 Yutian Lei Zhuo Zhang Yang Li yongjun bao Zhihan Lv 《Digital Communications and Networks》 SCIE CSCD 2024年第1期1-6,共6页
The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports f... The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link. 展开更多
关键词 Reinforcement learning Edge computing Beyond 5G Vehicle-to-pedestrian
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部