Towards V2I Age-Aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method-Reference-Cited by-同舟云学术

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Towards V2I Age-Aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method

Published:2023-11 Issue:6 Volume:32 Page:1230-1244
ISSN:2075-5597
Container-title:Chinese Journal of Electronics
language:
Short-container-title:Chinese J. Elect.

Author:

Qiong Wu¹,Shuai Shi¹,Ziyang Wan¹,Qiang Fan²,Pingyi Fan³,Cui Zhang⁴

Affiliation:

1. School of Internet of Things Engineering, Jiangnan University,Wuxi,China,214122

2. Qualcomm,San Jose,CA,USA,95110

3. Tsinghua University,Beijing National Research Center for Information Science and Technology,Beijing,China,100084

4. Banma Network Technology Co., Ltd.,Shanghai,China,200000

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/9970761/10292727/10292743.pdf?arnumber=10292743

Reference37 articles.

1. Age of Information Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective

2. Age of Information: An Introduction and Survey

3. Rainbow: Combining Improvements in Deep Reinforcement Learning

4. Velocity-adaptive Access Scheme for MEC-assisted Platooning Networks: Access Fairness Via Data Freshness

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3. A Cascaded Multi-Agent Reinforcement Learning-Based Resource Allocation for Cellular-V2X Vehicular Platooning Networks;Sensors;2024-08-30

4. Bit Error Rate Performance Improvement for Orthogonal Time Frequency Space Modulation with a Selective Decode-and-Forward Cooperative Communication Scenario in an Internet of Vehicles System;Sensors;2024-08-17

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