Dynamic spectrum access in cognitive radio networks using deep reinforcement learning and evolutionary game

P Yang, L Li, J Yin, H Zhang, W Liang… - 2018 IEEE/CIC …, 2018 - ieeexplore.ieee.org
With the rapid development of wireless communication technology, the low utilization of
spectrum resources and the high demand for spectrum have always been an urgent and …

Cognitive radio‐enabled Internet of Vehicles: a cooperative spectrum sensing and allocation for vehicular communication

J Eze, S Zhang, E Liu, E Eze - IET Networks, 2018 - Wiley Online Library
Internet of Things (IoTs) era is expected to empower all aspects of Intelligent Transportation
System (ITS) to improve transport safety and reduce road accidents. US Federal …

Multichannel spectrum access based on reinforcement learning in cognitive internet of things

C Sun, H Ding, X Liu - Ad Hoc Networks, 2020 - Elsevier
With the development of Internet of Things (IoT), the demands for communication spectrum
have increased rapidly, resulting in the shortage of limited spectrum resources. Cognitive …

Cooperative multi-agent reinforcement-learning-based distributed dynamic spectrum access in cognitive radio networks

X Tan, L Zhou, H Wang, Y Sun, H Zhao… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
With the development of wireless communication and Internet of Things (IoT), there are
massive wireless devices that need to share the limited spectrum resources. Dynamic …

A usage aware dynamic spectrum access scheme for interweave cognitive radio network by exploiting deep reinforcement learning

X Wang, Y Teraki, M Umehira, H Zhou, Y Ji - Sensors, 2022 - mdpi.com
Future-generation wireless networks should accommodate surging growth in mobile data
traffic and support an increasingly high density of wireless devices. Consequently, as the …

An Improved Dynamic Spectrum Access Algorithm Based on Reinforcement Learning

C Zhong, C Ye, C Wu, A Zhan - International Conference on Machine …, 2022 - Springer
This paper proposes an improved dynamic spectrum access algorithm based on
reinforcement Learning in cognitive radio networks. Q-learning algorithm is used as the core …

Deep learning-based selective spectrum sensing and allocation in cognitive vehicular radio networks

A Paul, K Choi - Vehicular Communications, 2023 - Elsevier
The main challenge with Vehicular Ad-Hoc Networks (VANETs) for assisting Intelligent
Transportation Services (ITSs) is ensuring effective data delivery under various network …

Dynamic multichannel sensing in cognitive radio: Hierarchical reinforcement learning

S Liu, J Wu, J He - IEEE Access, 2021 - ieeexplore.ieee.org
Efficient use of spectral resources is critical in wireless networks and has been extensively
studied in recent years. Dynamic spectrum access (DSA) is one of the key techniques on …

Spectrum Sharing with Dynamic Cournot Game in Vehicle‐Enabled Cognitive Small‐Cell Networks

G Wu, H Jiang - Journal of Computer Networks and …, 2019 - Wiley Online Library
Cognitive radio technology can effectively improve spectrum efficiency in wireless networks
and is also applicable to vehicle small‐cell networks. In this paper, we consider the problem …

Distributed dynamic spectrum access through multi-agent deep recurrent Q-learning in cognitive radio network

MK Giri, S Majumder - Physical Communication, 2023 - Elsevier
This paper addresses the problem of distributed dynamic spectrum access in a cognitive
radio (CR) environment utilizing deep recurrent reinforcement learning. Specifically, the …