Empirical Study and Signal Intensity Prediction for Cellular Vehicle-to-Everything (C-V2X)-Reference-Cited by-同舟云学术

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Empirical Study and Signal Intensity Prediction for Cellular Vehicle-to-Everything (C-V2X)

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
language:
Short-container-title:

Author:

Lu Yang¹,Zhang Yifan²,Shi Tuo²,Wang Jianping²,Wu Jen-Ming³,Liu Bingyi¹

Affiliation:

1. Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China

2. City University of Hong Kong,Department of Computer Science,Hong Kong SAR,China

3. Hon Hai Research Institute,Next-Gen. Communication Research Center,Taiwan

Funder

National Natural Science Foundation of China

Research and Development

Wuhan University of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10333258/10333344/10333693.pdf?arnumber=10333693

Reference18 articles.

1. A Comprehensive Survey on Vehicular Ad Hoc Networks (VANETs)

2. A Novel V2V-Based Temporary Warning Network for Safety Message Dissemination in Urban Environments

3. CPA-MAC: A Collision Prediction and Avoidance MAC for Safety Message Dissemination in MEC-Assisted VANETs

4. Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution

5. Deep Reinforcement Learning for Vehicular Edge Computing

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