An intelligent antijamming decision-making method based on deep reinforcement learning for multi-user communication is proposed in this paper.

In this paper, an anti-jamming intelligent decision-making method for multi-user communication based on deep reinforcement learning was proposed. It adopted ...

An intelligent antijamming decision-making method based on deep reinforcement learning for multi-user communication that effectively overcome the ...

In order to solve the problem of intelligent anti-jamming decision-making in battlefield communication, this paper designs an intelligent decision-making method ...

Anti-jamming communication based on reinforcement learning is difficult to converge quickly, which affects the quality of communication. A sequential deep ...

Aiming at the problem of intelligent cooperative jamming decision-making against frequency agility and frequency diversity in cognitive electronic warfare, an ...

This paper addresses the emerging threat issues posed by high-dynamic intelligent jamming and proposes an intelligent anti-jamming communication algorithm ...

Finally, a hidden anti-jamming algorithm is proposed, which links the instantaneous return with the communication quality of users and the correlation between ...

This paper designs a new Meta-PPO deep reinforcement learning algorithm that combines Proximal Policy Optimization (PPO) and MAML meta-learning ideas.

This article designs Double Deep Q Network (Double DQN) to model the confrontation between the cognitive radio network and the jammer and proposes an ...