Game-Theoretic Learning Anti-Jamming Approaches in Wireless Networks

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 appro...

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Bibliographic Details
Published in:IEEE communications magazine 2022-05, Vol.60 (5), p.60-66
Main Authors: Jia, Luliang, Qi, Nan, Chu, Feihuang, Fang, Shengliang, Wang, Ximing, Ma, Shuli, Feng, Shuo
Format: Magazinearticle
Language:English
Subjects:
Decision making
Decision theory
Game theory
Jamming
Learning
Markov processes
Wireless networks
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Summary: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.
ISSN:0163-6804
1558-1896
DOI:10.1109/MCOM.001.00496