Deep Reinforcement Learning-Based Resource Allocation for Cellular Vehicular Network Mode 3 with Underlay Approach

Deep Reinforcement Learning-Based Resource Allocation for Cellular Vehicular Network Mode 3 with Underlay Approach

Vehicle-to-vehicle (V2V) communication has attracted increasing attention since it can improve road safety and traffic efficiency. In the underlay approach of mode 3, the V2V links need to reuse the spectrum resources preoccupied with vehicle-to-infrastructure (V2I) links, which will interfere with...

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Bibliographic Details
Main Authors: Jinjuan Fu, Xizhong Qin, Yan Huang, Li Tang, Yan Liu
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
vehicular network
deep reinforcement learning
resource management
low latency
Online Access:https://www.mdpi.com/1424-8220/22/5/1874

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