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- W4387621365 abstract "Due to the characteristics of wireless network vulnerable to malicious jamming, this paper explores an Intelligent reflecting surface (IRS)-assisted anti-jamming communication system. Specifically, the IRS reflects the transmitted signal of the base station and the jamming signal at the same time. We model the joint optimization problem of transmitter power control and IRS reflection phase shift coefficient as a model-free reinforcement learning problem. Furthermore, we propose an action space smooth Q-learning (ASSQ) algorithm, which can promptly attain the optimal strategy by speeding up the convergence of learning. Simulation results demonstrate that the proposed ASSQ algorithm can effectively accelerate the convergence of learning and improve anti-jamming performance." @default.
- W4387621365 created "2023-10-14" @default.
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- W4387621365 date "2023-07-21" @default.
- W4387621365 modified "2023-10-15" @default.
- W4387621365 title "IRS-assisted anti-jamming communication based on action space smooth Q-learning" @default.
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- W4387621365 doi "https://doi.org/10.1145/3616480.3616483" @default.
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