# Game-theoretic Learning Anti-jamming Approaches in Wireless Networks

arXiv: https://arxiv.org/abs/2207.00159 · HTML: https://mlsanity.com/paper/2207.00159/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jun 2022.

## Built on by (most cited first, 1 of 1)

- [Achieving Hiding and Smart Anti-Jamming Communication: A Parallel DRL Approach against Moving Reactive Jammer](https://mlsanity.com/paper/2502.02385/) (2025)

## Abstract (arXiv)

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 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 of GTLAJ 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.