Semantic-Aware Spectrum Sharing in Internet of Vehicles Based on Deep Reinforcement Learning
This work aims to investigate semantic communication in high-speed mobile Internet of
vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to …
vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to …
An IOV Spectrum Sharing Approach based on Multi-Agent Deep Reinforcement Learning
H Qian, L Cai - International Journal of Uncertainty, Fuzziness and …, 2024 - World Scientific
Highly dynamic Internet of Vehicles spectrum sharing can share spectrum owned by vehicle-
to-infrastructure links through multiple workshop links to achieve efficient resource …
to-infrastructure links through multiple workshop links to achieve efficient resource …
Multi-agent reinforcement learning for spectrum sharing in vehicular networks
This paper investigates the spectrum sharing problem in vehicular networks, where multiple
vehicle-to-vehicle (V2V) links reuse the frequency spectrum preoccupied by vehicle-to …
vehicle-to-vehicle (V2V) links reuse the frequency spectrum preoccupied by vehicle-to …
[HTML][HTML] A Hybrid Multi-Agent Reinforcement Learning Approach for Spectrum Sharing in Vehicular Networks
Efficient spectrum sharing is essential for maximizing data communication performance in
Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that …
Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that …
Video semantics based resource allocation algorithm for spectrum multiplexing scenarios in vehicular networks
Due to the time-varying scenarios and multiple requirements in vehicular networks, it is
difficult to guarantee the accuracy of video semantic understanding within the scarce …
difficult to guarantee the accuracy of video semantic understanding within the scarce …
A dynamic spectrum access algorithm based on deep reinforcement learning with novel multi-vehicle reward functions in cognitive vehicular networks
L Chen, Z Wang, X Zhao, X Shen, W He - Telecommunication Systems, 2024 - Springer
As a revolution in the field of transportation, the demand for communication of vehicles is
increasing. Therefore, how to improve the success rate of vehicle spectrum access has …
increasing. Therefore, how to improve the success rate of vehicle spectrum access has …
[HTML][HTML] Deep reinforcement learning-based spectrum allocation algorithm in Internet of vehicles discriminating services
Z Guan, Y Wang, M He - Applied Sciences, 2022 - mdpi.com
With the rapid development of global automotive industry intelligence and networking, the
Internet of Vehicles (IoV) service, as a key communication technology, has been faced with …
Internet of Vehicles (IoV) service, as a key communication technology, has been faced with …
Dynamic spectrum access for C-V2X via imitating indian buffet process
P Li, XW Tang, XL Huang, F Hu - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
In dense traffic cases, the channels among vehicles and infrastructures in cellular vehicle-to-
everything (C-V2X) network are likely to be congested. Vehicles can select spectrum …
everything (C-V2X) network are likely to be congested. Vehicles can select spectrum …
Spectrum Sharing for vehicular communications in a multi-operator scenario
At 5.9 GHz intelligent transportation system (ITS) band, there are two competing standards
supporting vehicular networking, namely dedicated short-range communication (DSRC) and …
supporting vehicular networking, namely dedicated short-range communication (DSRC) and …
Intelligent dynamic spectrum access using deep reinforcement learning for VANETs
Y Wang, X Li, P Wan, R Shao - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In vehicular ad hoc networks (VANETs), vehicles can communicate with other vehicles or
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …