Game-Theoretic Learning Anti-Jamming Approaches in Wireless Networks | IEEE Journals & Magazine | IEEE Xplore

Game-Theoretic Learning Anti-Jamming Approaches in Wireless Networks


Abstract:

In this article, the anti-jamming communication problem is investigated from a game-theoretic learning perspective. By exploring and analyzing intelligent anti-jamming co...Show More

Abstract:

In this article, the anti-jamming communication problem is investigated from a game-theoretic learning perspective. By exploring and analyzing intelligent anti-jamming communication, we present the characteristics of jammers and the requirements of an intelligent anti-jamming approach. Such an approach is required of self-sensing, self-decision making, self-coordination, self-evaluation, and learning ability. Then a game-theoretic learning anti-jamming (GTLAJ) paradigm is proposed, and its framework and challenges are introduced. Moreover, through three cases (i.e., Stackelberg anti-jamming game, Markov anti-jamming game, and hypergraph-based anti-jamming game), different anti-jamming game models and applications are discussed, and some future directions are presented.
Published in: IEEE Communications Magazine ( Volume: 60, Issue: 5, May 2022)
Page(s): 60 - 66
Date of Publication: 17 May 2022

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