Resource Allocation in V2X Communications Based on Multi-Agent Reinforcement Learning with Attention Mechanism

Resource Allocation in V2X Communications Based on Multi-Agent Reinforcement Learning with Attention Mechanism

In this paper, we study the joint optimization problem of the spectrum and power allocation for multiple vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) users in cellular vehicle-to-everything (C-V2X) communication, aiming to maximize the sum rate of V2I links while satisfying the low l...

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Bibliographic Details
Main Authors: Yuanfeng Ding, Yan Huang, Li Tang, Xizhong Qin, Zhenhong Jia
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Mathematics
Subjects:
vehicle-to-everything
resource allocation
attention mechanism
multi-agent reinforcement learning
low latency
Online Access:https://www.mdpi.com/2227-7390/10/19/3415

Internet

https://www.mdpi.com/2227-7390/10/19/3415

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