• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A hidden anti-jamming method based on deep reinforcement learning

Vol. 15, No. 9, September 30, 2021
10.3837/tiis.2021.09.019, Download Paper (Free):

Abstract

In the field of anti-jamming based on dynamic spectrum, most methods try to improve the ability to avoid jamming and seldom consider whether the jammer would perceive the user's signal. Although these existing methods work in some anti-jamming scenarios, their long-term performance may be depressed when intelligent jammers can learn user's waveform or decision information from user's historical activities. Hence, we proposed a hidden anti-jamming method to address this problem by reducing the jammer's sense probability. In the proposed method, the action correlation between the user and the jammer is used to evaluate the hiding effect of the user's actions. And a deep reinforcement learning framework, including specific action correlation calculation and iteration learning algorithm, is designed to maximize the hiding and communication performance of the user synchronously. The simulation result shows that the algorithm proposed reduces the jammer's sense probability significantly and improves the user's anti-jamming performance slightly compared to the existing algorithms based on jamming avoidance.


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Cite this article

[IEEE Style]
Y. Wang, X. Liu, M. Wang and Y. Yu, "A hidden anti-jamming method based on deep reinforcement learning," KSII Transactions on Internet and Information Systems, vol. 15, no. 9, pp. 3444-3457, 2021. DOI: 10.3837/tiis.2021.09.019.

[ACM Style]
Yifan Wang, Xin Liu, Mei Wang, and Yu Yu. 2021. A hidden anti-jamming method based on deep reinforcement learning. KSII Transactions on Internet and Information Systems, 15, 9, (2021), 3444-3457. DOI: 10.3837/tiis.2021.09.019.

[BibTeX Style]
@article{tiis:24942, title="A hidden anti-jamming method based on deep reinforcement learning", author="Yifan Wang and Xin Liu and Mei Wang and Yu Yu and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2021.09.019}, volume={15}, number={9}, year="2021", month={September}, pages={3444-3457}}