Game theory and reinforcement learning for anti-jamming defense in wireless communications: Current research, challenges, and solutions
L Jia, N Qi, Z Su, F Chu, S Fang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Due to the inherently open and shared nature of the wireless channels, wireless
communication networks are vulnerable to jamming attacks, and effective anti-jamming …
communication networks are vulnerable to jamming attacks, and effective anti-jamming …
A collaborative multi-agent reinforcement learning anti-jamming algorithm in wireless networks
F Yao, L Jia - IEEE wireless communications letters, 2019 - ieeexplore.ieee.org
In this letter, we investigate the anti-jamming defense problem in multi-user scenarios,
where the coordination among users is taken into consideration. The Markov game …
where the coordination among users is taken into consideration. The Markov game …
Mitigating jamming attack in 5G heterogeneous networks: A federated deep reinforcement learning approach
Jamming attack is one of the serious security breaches in the upcoming fifth-generation
heterogeneous networks (5G HetNets). Most of the existing anti-jamming techniques, such …
heterogeneous networks (5G HetNets). Most of the existing anti-jamming techniques, such …
Survey on cognitive anti‐jamming communications
In this study, the authors review various jamming and anti‐jamming strategies in the context
of cognitive radios (CRs). The study explores different jamming models and classifies them …
of cognitive radios (CRs). The study explores different jamming models and classifies them …
Cognitive risk control for anti-jamming V2V communications in autonomous vehicle networks
S Feng, S Haykin - IEEE Transactions on Vehicular Technology, 2019 - ieeexplore.ieee.org
The future of intelligent transportation system (ITS) is expected to be composed of connected
and autonomous vehicles (CAVs), the development of which will have great impact on …
and autonomous vehicles (CAVs), the development of which will have great impact on …
Detection and blind channel estimation for UAV-aided wireless sensor networks in smart cities under mobile jamming attack
Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs)
for smart city applications in several ways. Among them, a UAV can be employed as a relay …
for smart city applications in several ways. Among them, a UAV can be employed as a relay …
Pattern-aware intelligent anti-jamming communication: A sequential deep reinforcement learning approach
This paper investigates the problem of anti-jamming communication in dynamic and
intelligent jamming environment. A sequential deep reinforcement learning algorithm …
intelligent jamming environment. A sequential deep reinforcement learning algorithm …
Reinforcement learning for deceiving reactive jammers in wireless networks
Conventional anti-jamming methods mostly rely on frequency hop** to hide or escape
from jammers. These approaches are not efficient in terms of bandwidth usage and can also …
from jammers. These approaches are not efficient in terms of bandwidth usage and can also …
JaDe: Low power jamming detection using machine learning in vehicular networks
Vehicular networks, like any other wireless networks, are prone to jamming due to the
inherent nature of the wireless environment. In this letter, we consider an attacker who jams …
inherent nature of the wireless environment. In this letter, we consider an attacker who jams …
An improved anti-jamming method based on deep reinforcement learning and feature engineering
X Chang, Y Li, Y Zhao, Y Du, D Liu - IEEE Access, 2022 - ieeexplore.ieee.org
To improve the performance of anti-jamming communication in dynamic and adversarial
jamming environment, an improved anti-jamming method is proposed based on deep …
jamming environment, an improved anti-jamming method is proposed based on deep …