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• W2981515841 abstract "In this paper, the decision-making problem for anti-jamming communications is studied. Most of the existing anti-jamming researches mainly focus on the single-domain anti-jamming such as power domain or frequency domain, which has limited performance facing strong jamming. Therefore, to effectively deal with some jamming attack, this paper proposes a multi-domain joint anti-jamming scheme, and considers the power domain and the frequency domain jointly. By modeling the anti-jamming process as a Markov decision process (MDP), reinforcement learning (RL) is adopted to solve the MDP. Then, the multi-domain joint anti-jamming algorithm is proposed to find the optimal decision-making strategy. Moreover, the proposed algorithm is verified to converge to an effective strategy. Simulation results show that the proposed algorithm has better throughput performance than the sensing-based random selection algorithm." @default.
• W2981515841 created "2019-11-01" @default.
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• W2981515841 date "2019-01-01" @default.
• W2981515841 modified "2023-10-11" @default.
• W2981515841 title "Joint Power and Channel Selection for Anti-jamming Communications: A Reinforcement Learning Approach" @default.
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• W2981515841 doi "https://doi.org/10.1007/978-3-030-32388-2_47" @default.
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