Deep reinforcement learning for time scheduling in RF-powered backscatter cognitive radio networks

TT Anh, NC Luong, D Niyato… - 2019 IEEE wireless …, 2019 - ieeexplore.ieee.org
In an RF-powered backscatter cognitive radio network, multiple secondary users
communicate with a secondary gateway by backscattering or harvesting energy and actively …

Reinforcement learning approach for RF-powered cognitive radio network with ambient backscatter

N Van Huynh, DT Hoang, DN Nguyen… - 2018 IEEE Global …, 2018 - ieeexplore.ieee.org
For an RF-powered cognitive radio network with ambient backscattering capability, while the
primary channel is busy, the RF-powered secondary user (RSU) can either backscatter the …

DDPG-based joint time and energy management in ambient backscatter-assisted hybrid underlay CRNs

K Zheng, X Jia, K Chi, X Liu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Ambient backscatter (AB) communications and radio frequency (RF)-powered cognitive
radio networks (CRNs) address the concerns of energy and spectrum scarcities from …

A hybrid communication scheme for throughput maximization in backscatter-aided energy harvesting cognitive radio networks

K Zheng, J Wang, X Liu, XW Yao… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Motivated by the benefits of cognitive radio (CR), energy harvesting (EH), and backscatter
communication (BC) technologies to support Internet of Things (IoT) systems, we investigate …

Optimal time sharing in RF-powered backscatter cognitive radio networks

DT Hoang, D Niyato, P Wang… - 2017 IEEE international …, 2017 - ieeexplore.ieee.org
In this paper, we propose a novel network model for RF-powered cognitive radio networks
and ambient backscatter communications. In the network under consideration, each …

A graph convolutional network-based deep reinforcement learning approach for resource allocation in a cognitive radio network

D Zhao, H Qin, B Song, B Han, X Du, M Guizani - Sensors, 2020 - mdpi.com
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 …

Deep reinforcement learning optimal transmission algorithm for cognitive Internet of Things with RF energy harvesting

S Guo, X Zhao - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
Spectrum scarcity and energy limitation are becoming two critical issues in designing
Internet of Things (IoT). As two promising technologies, cognitive radio (CR) and radio …

Deep learning-aided distributed transmit power control for underlay cognitive radio network

W Lee, K Lee - IEEE Transactions on Vehicular Technology, 2021 - ieeexplore.ieee.org
In this paper, we investigate deep learning-aided distributed transmit power control in the
context of an underlay cognitive radio network (CRN). In the proposed scheme, the fully …

Auction-based time scheduling for backscatter-aided RF-powered cognitive radio networks

X Gao, P Wang, D Niyato, K Yang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper investigates the time scheduling for a backscatter-aided radio-frequency-
powered cognitive radio network, where multiple secondary transmitters transmit data to the …

Stackelberg game for distributed time scheduling in RF-powered backscatter cognitive radio networks

W Wang, DT Hoang, D Niyato… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
In this paper, we study the transmission strategy adaptation problem in an RF-powered
cognitive radio network, in which hybrid secondary users are able to switch between the …