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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 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.

Ketersediaan

Informasi Detail

Judul Seri

IEEE COMMUNICATIONS MAGAZINE; Vol.60 No.5 May 2022

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 60-67

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

GAME THEORY
MARKOV PROCESSES
WIRELESS NETWORKS
JAMMING

Info Detail Spesifik

DOI: 10.1109/MCOM.001.00496

Pernyataan Tanggungjawab

Luliang Jia, Nan Qi, Feihuang Chu, Shengliang Fang, Ximing Wang, Shuli Ma, Shuo Feng

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