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 …
Reinforcement learning-based NOMA power allocation in the presence of smart jamming
Nonorthogonal multiple access (NOMA) systems are vulnerable to jamming attacks,
especially smart jammers who apply programmable and smart radio devices such as …
especially smart jammers who apply programmable and smart radio devices such as …
Two-dimensional anti-jamming communication based on deep reinforcement learning
In this paper, a two-dimensional anti-jamming communication scheme for cognitive radio
networks is developed, in which a secondary user (SU) exploits both spread spectrum and …
networks is developed, in which a secondary user (SU) exploits both spread spectrum and …
Two-dimensional antijamming mobile communication based on reinforcement learning
By using smart radio devices, a jammer can dynamically change its jamming policy based
on opposing security mechanisms; it can even induce the mobile device to enter a specific …
on opposing security mechanisms; it can even induce the mobile device to enter a specific …
Jamming resilient communication using MIMO interference cancellation
Jamming attack is a serious threat to the wireless communications. Reactive jamming
maximizes the attack efficiency by jamming only when the targets are communicating, which …
maximizes the attack efficiency by jamming only when the targets are communicating, which …
Federated Deep Reinforcement Learning for Efficient Jamming Attack Mitigation in O-RAN
Z Abou El Houda, H Moudoud… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Open RAN (ORAN or O-RAN) revolutionizes Radio Access Networks (RAN) by offering
flexibility and cost-efficiency through inter-vendor equipment interoperability. More …
flexibility and cost-efficiency through inter-vendor equipment interoperability. More …
UAV networks against multiple maneuvering smart jamming with knowledge-based reinforcement learning
The unmanned aerial vehicles (UAVs) networks are very vulnerable to smart jammers that
can choose their jamming strategy based on the ongoing channel state accordingly …
can choose their jamming strategy based on the ongoing channel state accordingly …
A proactive eavesdropping game in MIMO systems based on multiagent deep reinforcement learning
D Guo, H Ding, L Tang, X Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper considers an adversarial scenario between a legitimate eavesdropper and a
suspicious communication pair. All three nodes are equipped with multiple antennas. The …
suspicious communication pair. All three nodes are equipped with multiple antennas. The …
Secure mobile edge computing in IoT via collaborative online learning
To accommodate heterogeneous tasks for the Internet of Things (IoT), the emerging mobile
edge paradigm extends computing services from the cloud to the edge, but at the same time …
edge paradigm extends computing services from the cloud to the edge, but at the same time …
Maintaining information freshness under jamming
In UAV communication with a ground control station, mission success requires maintaining
the freshness of the received information, especially when the communication faces hostile …
the freshness of the received information, especially when the communication faces hostile …