Against Jamming Attack in Wireless Communication Networks: A Reinforcement Learning Approach
Ding Ma,
Yang Wang,
Sai Wu
Abstract:When wireless communication networks encounter jamming attacks, they experience spectrum resource occupation and data communication failures. In order to address this issue, an anti-jamming algorithm based on distributed multi-agent reinforcement learning is proposed. Each terminal observes the spectrum state of the environment and takes it as an input. The algorithm then employs Q-learning, along with the primary and backup channel allocation rules, to finalize the selection of the communication channel. The … Show more
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