Attention Enhanced Multi-Agent Reinforcement Learning for Cooperative Spectrum Sensing in Cognitive Radio Networks
A Gao, Q Wang, Y Wang, C Du, Y Hu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Cooperative spectrum sensing (CSS) technology has been widely studied to enhance the
spectrum sharing efficiency spatially and temporally in cognitive radio networks (CRNs) …
spectrum sharing efficiency spatially and temporally in cognitive radio networks (CRNs) …
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) …
Enhanced multiband multiuser cooperative spectrum sensing for distributed CRNs
Multi-band cooperative spectrum sensing (CSS) can provide opportunistic spectrum access
to secondary users (SUs) in cognitive radio networks (CRNs). In multi-band CSS, the …
to secondary users (SUs) in cognitive radio networks (CRNs). In multi-band CSS, the …
Coordination graph-based deep reinforcement learning for cooperative spectrum sensing under correlated fading
P Cai, Y Zhang, C Pan - IEEE Wireless Communications …, 2020 - ieeexplore.ieee.org
In this letter, cooperative spectrum sensing (CSS) under correlated fading in cognitive radio
networks is modeled, and the distributed deep reinforcement learning method is adopted to …
networks is modeled, and the distributed deep reinforcement learning method is adopted to …
Distributed learning-based multi-band multi-user cooperative sensing in cognitive radio networks
Multi-band cooperative spectrum sensing can provide access to a wide range of spectrum in
cognitive radio networks (CRNs). The design of multi-band spectrum sensing is very …
cognitive radio networks (CRNs). The design of multi-band spectrum sensing is very …
Cooperative Spectrum Sensing using DQN in CRN
M Moneesh, T Tejaswi, T Yeshwanth… - … Transactions on Mobile …, 2021 - eudl.eu
It is imperative to address the problem of spectrum under usage and inefficiency because of
the increasing spectrum demand and slender spectrum resources. One of the salient …
the increasing spectrum demand and slender spectrum resources. One of the salient …
Federated learning-based cooperative spectrum sensing in cognitive radio
Z Chen, YQ Xu, H Wang, D Guo - IEEE Communications …, 2021 - ieeexplore.ieee.org
Deep cooperative sensing is a cooperative spectrum sensing (CSS) algorithm based on a
deep neural network (DNN). Since training DNN requires a large amount of sample data …
deep neural network (DNN). Since training DNN requires a large amount of sample data …
DeepSense: An unsupervised deep clustering approach for cooperative spectrum sensing
NA Khalek, W Hamouda - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
Cognitive radio (CR) users can transmit data as vacant licensed bands become available.
By using machine learning, CR users can intelligently sense channel activity and determine …
By using machine learning, CR users can intelligently sense channel activity and determine …
Deep transfer cooperative sensing in cognitive radio
In this letter, we propose a deep transfer cooperative sensing (DTCS) approach in cognitive
radio networks, where multiple secondary users (SUs) cooperate to detect the presence of …
radio networks, where multiple secondary users (SUs) cooperate to detect the presence of …
Reinforcement learning enabled cooperative spectrum sensing in cognitive radio networks
W Ning, X Huang, K Yang, F Wu… - … of Communications and …, 2020 - ieeexplore.ieee.org
In cognitive radio (CR) networks, fast and accurate spectrum sensing plays a fundamental
role in achieving high spectral efficiency. In this paper, a reinforcement learning (RL) …
role in achieving high spectral efficiency. In this paper, a reinforcement learning (RL) …