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 …

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 …

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 …

Opportunistic ambient backscatter communication in RF-powered cognitive radio networks

R Kishore, S Gurugopinath… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
In the present contribution, we propose a novel opportunistic ambient backscatter
communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) …

Optimal resource allocation for RF-powered underlay cognitive radio networks with ambient backscatter communication

Y Zhuang, X Li, H Ji, H Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we study radio frequency (RF)-powered underlay cognitive radio networks
(CRNs) with power-domain non-orthogonal multiple access (NOMA). In these networks, by …

Deep reinforcement learning-based optimization for irs-assisted cognitive radio systems

C Zhong, M Cui, G Zhang, Q Wu, X Guan… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In this paper, we consider an intelligent reflecting surface (IRS)-assisted cognitive radio
system and maximize the secondary user (SU) rate by jointly optimizing the transmit power …

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 …

Ambient backscatter: A new approach to improve network performance for RF-powered cognitive radio networks

DT Hoang, D Niyato, P Wang, DI Kim… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper introduces a new solution to improve the performance for secondary systems in
radio frequency (RF) powered cognitive radio networks (CRNs). In a conventional RF …

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 …

[HTML][HTML] 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 …