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 …
massive wireless devices that need to share the limited spectrum resources. Dynamic …
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 …
A cooperative spectrum sensing with multi-agent reinforcement learning approach in cognitive radio networks
Cognitive radio networks (CRNs) can greatly improve the temporal and spatial spectrum
utilization by identifying and exploring spectrum holes of the licensed primary users (PUs) …
utilization by identifying and exploring spectrum holes of the licensed primary users (PUs) …
Dynamic spectrum access in cognitive radio networks using deep reinforcement learning and evolutionary game
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 …
spectrum resources and the high demand for spectrum have always been an urgent and …
Deep reinforcement learning for dynamic spectrum sensing and aggregation in multi-channel wireless networks
Y Li, W Zhang, CX Wang, J Sun… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, the problem of dynamic spectrum sensing and aggregation is investigated in a
wireless network containing N correlated channels, where these channels are occupied or …
wireless network containing N correlated channels, where these channels are occupied or …
Multi-agent reinforcement learning-based distributed dynamic spectrum access
Dynamic spectrum access (DSA) is an effective solution for efficiently utilizing the radio
spectrum by sharing it among various networks. Two primary tasks of a DSA controller are …
spectrum by sharing it among various networks. Two primary tasks of a DSA controller are …
Deep multi-user reinforcement learning for distributed dynamic spectrum access
O Naparstek, K Cohen - IEEE transactions on wireless …, 2018 - ieeexplore.ieee.org
We consider the problem of dynamic spectrum access for network utility maximization in
multichannel wireless networks. The shared bandwidth is divided into K orthogonal …
multichannel wireless networks. The shared bandwidth is divided into K orthogonal …
Deep reinforcement learning for dynamic spectrum access in wireless networks
Y Xu, J Yu, WC Headley… - MILCOM 2018-2018 IEEE …, 2018 - ieeexplore.ieee.org
This paper investigates the use of deep reinforcement learning (DRL) to solve the dynamic
spectrum access problem. Specifically, we examine the scenario where multiple discrete …
spectrum access problem. Specifically, we examine the scenario where multiple discrete …
Machine-learning-based opportunistic spectrum access in cognitive radio networks
The explosive growth of wireless devices and data rate demands makes spectrum scarcity a
serious problem. A promising solution is to employ OSA, which enables SUs to seek and …
serious problem. A promising solution is to employ OSA, which enables SUs to seek and …
Distributive dynamic spectrum access through deep reinforcement learning: A reservoir computing-based approach
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to
share radio spectrum among different networks. As a secondary user (SU), a DSA device …
share radio spectrum among different networks. As a secondary user (SU), a DSA device …
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