Graph convolution network deep reinforcement learning approach based on manifold regularization in cognitive radio network
Z Yanyan, L Zeyu, W Baocong - 2021 International Wireless …, 2021 - ieeexplore.ieee.org
In this paper, we propose GCNMR-ELM policy model for deep reinforcement learning
approach in cognitive radio network and applications this policy model in cognitive radio on …
approach in cognitive radio network and applications this policy model in cognitive radio on …
Spectrum management in high-speed railway cooperative cognitive radio network based on multi-agent reinforcement learning
C Wang, Q Wu, Z Tang, J Sheng… - … and Mobile Computing …, 2020 - ieeexplore.ieee.org
As the high-speed railway industry matures, higher requirements are put forward for the
railway wireless communication, and the demand for spectrum resources is also increasing …
railway wireless communication, and the demand for spectrum resources is also increasing …
A graph convolutional network-based deep reinforcement learning approach for resource allocation in a cognitive radio network
Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth
of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can …
of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can …
Reinforcement learning based 5G enabled cognitive radio networks
Cognitive radio (CR) is a spectrum sharing technology that facilitates a hierarchal
coexistence between licensed and license-exempt users over licensed bands. One of the …
coexistence between licensed and license-exempt users over licensed bands. One of the …
Cognitive radio network throughput maximization with deep reinforcement learning
Radio Frequency powered Cognitive Radio Networks (RF-CRN) are likely to be the eyes
and ears of upcoming modern networks such as Internet of Things (IoT), requiring increased …
and ears of upcoming modern networks such as Internet of Things (IoT), requiring increased …
Graph convolutional reinforcement learning for resource allocation in hybrid overlay–underlay cognitive radio network with network slicing
Nowadays, wireless communication system is facing the problems of spectrum resource
shortage. Cognitive radio technology allows cognitive users to use the spectrums authorized …
shortage. Cognitive radio technology allows cognitive users to use the spectrums authorized …
Defend Against Jamming Attacks Using Deep Reinforcement Learning
W Shen, W Wang, H Jin… - 2021 13th International …, 2021 - ieeexplore.ieee.org
Cognitive radio network has the learning ability to adjust transmission behavior to adapt to
dynamic electromagnetic environment, and it has become a research hotspot in the field of …
dynamic electromagnetic environment, and it has become a research hotspot in the field of …
Fast learning cognitive radios in underlay dynamic spectrum access: Integration of transfer learning into deep reinforcement learning
F Shah-Mohammadi… - 2020 Wireless …, 2020 - ieeexplore.ieee.org
Cognitive radio (CR) as a leading technology in realizing dynamic spectrum access (DSA)
offers a large efficiency and flexibility in the use of radio spectrum. The cognition feature …
offers a large efficiency and flexibility in the use of radio spectrum. The cognition feature …
A survey of deep learning for tactical wireless networks
W Pawgasame - 2018 5th Asian Conference on Defense …, 2018 - ieeexplore.ieee.org
A tactical wireless network is a military radio communication network supporting mission-
critical applications. Hence, a tactical wireless network demands more reliability, availability …
critical applications. Hence, a tactical wireless network demands more reliability, availability …
Deep reinforcement learning for resource allocation with network slicing in cognitive radio network
S Yuan, Y Zhang, W Qie, T Ma, S Li - Computer Science and …, 2021 - doiserbia.nb.rs
With the development of wireless communication technology, the requirement for data rate is
growing rapidly. Mobile communication system faces the problem of shortage of spectrum …
growing rapidly. Mobile communication system faces the problem of shortage of spectrum …
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