IRS-assisted anti-jamming communication based on action space smooth Q-learning
Authors: 
Yang Liu, Kui Xu, Nan Ma, Mi Zhang, Chengqian Ma, Yueyue ZhangAuthors Info & Claims
Yang Liu, Kui Xu, Nan Ma, Mi Zhang, Chengqian Ma, Yueyue ZhangAuthors Info & ClaimsPages 14 - 21
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.
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Index Terms
- IRS-assisted anti-jamming communication based on action space smooth Q-learning
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Published In
July 2023
100 pages
ISBN:9798400708855
DOI:10.1145/3616480
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Published: 13 October 2023
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IECC 2023
IECC 2023: 2023 5th International Electronics Communication Conference ?IECC)
July 21 - 23, 2023
Osaka City, Japan
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