Game-Theoretic Learning Anti-Jamming Approaches in Wireless Networks

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

doi:10.1109/mcom.001.00496

Cited by 23 publications

(10 citation statements)

References 15 publications

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“…The sparse problems encountered in many domains of scientific research and engineering practice have attracted extensive attention in recent years, such as MmWave Massive MIMO channel estimation [1]- [3], machine learning [4], [5], jammer detection [6], [7], image processing [8]- [12]. The canonical form of this problems can be expressed as…”

Section: Introductionmentioning

confidence: 99%

An Iterative Threshold Algorithm of Log-Sum Regularization for Sparse Problem

Zhou

Liu

Zhang

et al. 2023

IEEE Trans. Circuits Syst. Video Technol.

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The log-sum regularization has been always drawing widespread attention in the field of sparse problem. However, it brings about a non-convex, non-smooth, and non-Lipschitz optimization problem that is difficult to tackle. To overcome the problem, an iterative threshold algorithm of log-sum regularization is proposed in this paper. Firstly, by deducing the derivative mathematical expression of log-sum function, a property theorem about solution for log-sum regularization is established. Secondly, based on the above theorem, the optimal setting rules of the compromising parameters are elaborated, and the iterative logsum threshold algorithm is proposed. Thirdly, under the situation that the compromising parameters of log-sum regularization are relatively small, it can be proven that the proposed algorithm converges to a local minimizer of log-sum regularization. Finally, a series of simulations are implemented to examine performance of the algorithm, and the results exhibit that the proposed algorithm outperforms the state-of-the-art algorithms in terms of iterations and precision.

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Section: Introductionmentioning

confidence: 99%

An Iterative Threshold Algorithm of Log-Sum Regularization for Sparse Problem

Zhou

Liu

Zhang

et al. 2023

IEEE Trans. Circuits Syst. Video Technol.

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“…However, Due to the sharing and open nature of wireless communications, interference has become a critical and major threat in the application of RIS. There are many interference sources with different forms, we focus on frequencydomain anti-interference techniques and can evade interference through frequency hopping [8]. Possible uncontrolled interference sources in these scenarios were likely to seriously damage the communication system performance while escaping from being predicted and avoided in advance.…”

Section: Introductionmentioning

confidence: 99%

Metasurface-Based Modulation With Enhanced Interference Resilience

Liu

Pang

et al. 2023

IEEE Commun. Lett.

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Reconfigurable Intelligent Surfaces (RISs) have great potential for Internet of Things (IoT) applications due to their cost-effectiveness and energy-efficiency. However, under the application of RIS, current RIS systems cannot actively predict and avoid interference, as evolving interference signals can dynamically change their frequency bands. To address this issue, we develop a learning-based dynamic RIS spectrum access scheme to avoid interference and enhance wireless transmission reliability. An intelligent metasurface-based modulation (MM) is designed for generating and reflecting anti-interference radiofrequency signals. Specifically, a Dyna-Q algorithm is employed at the RIS controller to learn the frequency of interference signals, which is used to determine the frequency of the carrier signals. Experiments are conducted on the proposed RIS demo system to evaluate its anti-interference capability, and the results show that our scheme leads to an increase of at least 50% in the system throughput. These numerical results demonstrate the effectiveness of proposed scheme.

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“…The communication anti-jamming process is actually a game process between the wireless communication system and the jammer; therefore, the game theory used in antijamming technologies has attracted wide research interest [2][3][4]. In the existing literature, methods such as Stackelberg game [5], stochastic learning theory [6], and reinforcement learning [7][8][9] have been studied, from the aspects of frequency and power By building a game model between communication and jamming, and by implementing a continuous trial-and-error method to avoid jamming, the optimal communication anti-jamming strategy was determined.…”

Section: Introductionmentioning

confidence: 99%

A Coalition Formation Game-Based Multi-User Grouping Approach in the Jamming Environment

2022

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Due to the broadcast nature of wireless communication, it is vulnerable to malicious jamming attacks. Meanwhile, multiple users need to share the limited spectrum resources to enhance the spectrum utilization efficiency because of the scarcity of wireless spectrum resources. Therefore, wireless communication systems need to deal with the malicious jamming attacks and mutual interference among different users. In this paper, a multi-user anti-jamming grouping approach based on a coalition formation game is studied. The proposed approach can maximize users’ transmission rate while avoiding channel jamming through optimization of the coalition formation strategy under the influence of malicious jamming. With the help of the exact potential energy game, we demonstrate that the proposed game model can obtain stable Nash equilibrium solutions. Lastly, the effectiveness of the proposed algorithm is demonstrated through numerical.

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Game-Theoretic Learning Anti-Jamming Approaches in Wireless Networks

Cited by 23 publications

References 15 publications

An Iterative Threshold Algorithm of Log-Sum Regularization for Sparse Problem

An Iterative Threshold Algorithm of Log-Sum Regularization for Sparse Problem

Metasurface-Based Modulation With Enhanced Interference Resilience

A Coalition Formation Game-Based Multi-User Grouping Approach in the Jamming Environment

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