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 …
Deep learning-based selective spectrum sensing and allocation in cognitive vehicular radio networks
The main challenge with Vehicular Ad-Hoc Networks (VANETs) for assisting Intelligent
Transportation Services (ITSs) is ensuring effective data delivery under various network …
Transportation Services (ITSs) is ensuring effective data delivery under various network …
Federated Deep Reinforcement Learning-Based Spectrum Access Algorithm With Warranty Contract in Intelligent Transportation Systems
Cognitive radio (CR) provides an effective solution to meet the huge bandwidth
requirements in intelligent transportation systems (ITS), which enables secondary users …
requirements in intelligent transportation systems (ITS), which enables secondary users …
Multiple channel access using deep reinforcement learning for congested vehicular networks
Vehicular Ad-hoc Network (VANET) is a standard protocol for wireless vehicular
communication that enables Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) …
communication that enables Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) …
A robust channel access using cooperative reinforcement learning for congested vehicular networks
Vehicular Ad-hoc Network (VANET) is an emerging technique dedicated to wireless
vehicular communication to improve transportation safety by exchanging driving information …
vehicular communication to improve transportation safety by exchanging driving information …
A multi-channel and multi-user dynamic spectrum access algorithm based on deep reinforcement learning in Cognitive Vehicular Networks with sensing error
L Chen, K Fu, Q Zhao, X Zhao - Physical Communication, 2022 - Elsevier
In this paper, a spectrum access problem is proposed to improve the spectrum access rates
of secondary vehicles in Cognitive Vehicular Networks, where the channel capacity …
of secondary vehicles in Cognitive Vehicular Networks, where the channel capacity …
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 …
Historical spectrum sensing data mining for cognitive radio enabled vehicular ad-hoc networks
XL Huang, J Wu, W Li, Z Zhang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
In vehicular ad-hoc network (VANET), the reliability of communication is associated with
driving safety. However, research shows that the safety-message transmission in VANET …
driving safety. However, research shows that the safety-message transmission in VANET …
From channel selection to strategy selection: Enhancing VANETs using socially-inspired foraging and deference strategies
MA Shattal, A Wisniewska, B Khan… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Dynamic spectrum access (DSA) has been hailed as a possible panacea for the “spectrum
crunch,” drawing significant attention from researchers and industry alike. Here, we describe …
crunch,” drawing significant attention from researchers and industry alike. Here, we describe …
Multi-agent deep reinforcement learning-empowered channel allocation in vehicular networks
AS Kumar, L Zhao, X Fernando - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Channel allocation has a direct and profound impact on the performance of vehicle-to-
everything (V2X) networks. Considering the dynamic nature of vehicular environments, it is …
everything (V2X) networks. Considering the dynamic nature of vehicular environments, it is …