Model-based Bayesian reinforcement learning for enhancing primary user performance under jamming attack

AN Elbattrawy, AH Abd El-Malek, SI Rabia, WK Zahra - Ad Hoc Networks, 2023 - Elsevier
Due to the broadcast nature of wireless networks, jamming attacks are inevitable. Therefore,
this paper considers enhancing the throughput of a primary user (PU) suffering from a …

Anti-jamming transmissions with learning in heterogenous cognitive radio networks

T Chen, J Liu, L Xiao, L Huang - 2015 IEEE Wireless …, 2015 - ieeexplore.ieee.org
This paper investigates the interactions between a secondary user (SU) with frequency
hopping and a jammer with spectrum sensing in heterogenous cognitive radio networks …

Performance analysis of wireless energy harvesting cognitive radio networks under smart jamming attacks

DT Hoang, D Niyato, P Wang… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
In cognitive radio networks with wireless energy harvesting, secondary users are able to
harvest energy from a wireless power source and then use the harvested energy to transmit …

Anti-jamming game to combat intelligent jamming for cognitive radio networks

K Ibrahim, SX Ng, IM Qureshi, AN Malik… - IEEE Access, 2021 - ieeexplore.ieee.org
Cognitive Radio (CR) provides a promising solution to the spectrum scarcity problem in
dense wireless networks, where the sensing ability of cognitive users helps acquire …

Power control with reinforcement learning in cooperative cognitive radio networks against jamming

L Xiao, Y Li, J Liu, Y Zhao - The Journal of Supercomputing, 2015 - Springer
In this paper, we study the anti-jamming power control problem of secondary users (SUs) in
a large-scale cooperative cognitive radio network attacked by a smart jammer with the …

Primary-user-friendly dynamic spectrum anti-jamming access: A GAN-enhanced deep reinforcement learning approach

H Han, Y Xu, Z Jin, W Li, X Chen… - IEEE Wireless …, 2021 - ieeexplore.ieee.org
This letter studies the problem of deep reinforcement learning (DRL)-based dynamic
spectrum anti-jamming access in overlay cognitive radio networks. To prevent secondary …

Know Thy Enemy: An Opponent Modeling-Based Anti-Intelligent Jamming Strategy Beyond Equilibrium Solutions

W Li, Y Xu, J Chen, H Yuan, H Han… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
We investigate the problem of dynamic spectrum anti-jamming access against intelligent
jammer using game theory and opponent modeling. Previous work has formulated the …

A transfer games actor–critic learning framework for anti-jamming in multi-channel cognitive radio networks

HT Thien, VH Vu, I Koo - IEEE Access, 2021 - ieeexplore.ieee.org
A cognitive radio network (CRN) is a novel solution that promises to solve the spectrum
scarcity problem and enhance spectrum utilization. However, unsecured CRN can easily be …

Reinforcement learning based sensing policy optimization for energy efficient cognitive radio networks

J Oksanen, J Lundén, V Koivunen - Neurocomputing, 2012 - Elsevier
This paper introduces a machine learning based collaborative multi-band spectrum sensing
policy for cognitive radios. The proposed sensing policy guides secondary users to focus the …

An intelligent anti-jamming scheme for cognitive radio based on deep reinforcement learning

J Xu, H Lou, W Zhang, G Sang - IEEE Access, 2020 - ieeexplore.ieee.org
Cognitive radio network is an intelligent wireless communication system which can adjust its
transmission parameters according to the environment thanks to its learning ability. It is a …