Applications of multi-agent reinforcement learning in future internet: A comprehensive survey
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
Secure transmission scheme based on joint radar and communication in mobile vehicular networks
Vehicle-to-vehicle (V2V) communication applications face significant challenges to security
and privacy since all types of possible breaches are common in connected and autonomous …
and privacy since all types of possible breaches are common in connected and autonomous …
Dynamic beam pattern and bandwidth allocation based on multi-agent deep reinforcement learning for beam hopping satellite systems
Due to the non-uniform geographic distribution and time-varying characteristics of the
ground traffic request, how to make full use of the limited beam resources to serve users …
ground traffic request, how to make full use of the limited beam resources to serve users …
GPDS: A multi-agent deep reinforcement learning game for anti-jamming secure computing in MEC network
Abstract The openness of Mobile Edge Computing (MEC) networks makes them vulnerable
to interference attacks by malicious jammers, which endangers the communication quality of …
to interference attacks by malicious jammers, which endangers the communication quality of …
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 …
Outage constrained robust beamforming optimization for multiuser IRS-assisted anti-jamming communications with incomplete information
Malicious jamming attacks have been regarded as a serious threat to Internet of Things (IoT)
networks, which can significantly degrade the Quality of Service (QoS) of users. This article …
networks, which can significantly degrade the Quality of Service (QoS) of users. This article …
Dynamic spectrum anti-jamming communications: Challenges and opportunities
Due to the openness of the transmission medium, it is necessary for radio systems to have
anti-jamming abilities. Traditional anti-jamming methods such as sequence-based …
anti-jamming abilities. Traditional anti-jamming methods such as sequence-based …
Beam-domain anti-jamming transmission for downlink massive MIMO systems: A Stackelberg game perspective
Z Shen, K Xu, X Xia - IEEE Transactions on Information …, 2021 - ieeexplore.ieee.org
In this paper, beam-domain (BD) anti-jamming transmission in a downlink massive multiple-
input multiple-output (MIMO) system is investigated. A smart jammer with multiple antennas …
input multiple-output (MIMO) system is investigated. A smart jammer with multiple antennas …
Safe exploration in wireless security: A safe reinforcement learning algorithm with hierarchical structure
Most safe reinforcement learning (RL) algorithms depend on the accurate reward that is
rarely available in wireless security applications and suffer from severe performance …
rarely available in wireless security applications and suffer from severe performance …