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 …
A usage aware dynamic spectrum access scheme for interweave cognitive radio network by exploiting deep reinforcement learning
Future-generation wireless networks should accommodate surging growth in mobile data
traffic and support an increasingly high density of wireless devices. Consequently, as the …
traffic and support an increasingly high density of wireless devices. Consequently, as the …
Deep learning-inspired message passing algorithm for efficient resource allocation in cognitive radio networks
M Liu, T Song, J Hu, J Yang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Energy efficiency (EE) and spectrum efficiency (SE) have received significant attentions on
optimizing the network performance in cognitive radio networks. In this paper, an EE+ SE …
optimizing the network performance in cognitive radio networks. In this paper, an EE+ SE …
Resource allocation based on deep neural networks for cognitive radio networks
Resource allocation is of great importance in the next generation wireless communication
systems, especially for cognitive radio networks (CRNs). Many resource allocation strategies …
systems, especially for cognitive radio networks (CRNs). Many resource allocation strategies …
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 …
Deep reinforcement learning for resource allocation with network slicing in cognitive radio network
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 …
Resource allocation for multi-channel underlay cognitive radio network based on deep neural network
W Lee - IEEE Communications Letters, 2018 - ieeexplore.ieee.org
In this letter, a resource allocation strategy based on a deep neural network (DNN) is
proposed for multi-channel cognitive radio networks, where the secondary user (SU) …
proposed for multi-channel cognitive radio networks, where the secondary user (SU) …
Energy-efficient resource allocation in cognitive radio networks under cooperative multi-agent model-free reinforcement learning schemes
The most prominent challenge to the wireless community is to meet the demand for radio
resources. Cognitive Radio (CR) is envisioned as a potential solution that utilizes its …
resources. Cognitive Radio (CR) is envisioned as a potential solution that utilizes its …
Imperfect CSI based intelligent dynamic spectrum management using cooperative reinforcement learning framework in cognitive radio networks
The rapid development of wireless traffic pushed the wireless community to research
different solutions towards the efficient utilization of the available radio spectrum. However, a …
different solutions towards the efficient utilization of the available radio spectrum. However, a …
Energy-efficient resource allocation for heterogeneous cognitive radio network based on two-tier crossover genetic algorithm
Y Jiao, I Joe - Journal of communications and networks, 2016 - ieeexplore.ieee.org
Cognitive radio (CR) is considered an attractive technology to deal with the spectrum
scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity …
scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity …
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