Power control Stackelberg game in cooperative anti-jamming communications

Li, Yan; Xiao, Liang; Liu, Jinliang; Tang, Yuliang

doi:10.1109/gamenets.2014.7043719

Cited by 40 publications

(24 citation statements)

References 19 publications

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“…Moreover, a outlook of the application of anti-jamming Stackelberg game was also made. In [12][13][14], Stackelberg game approaches were adopted for the anti-jamming power control problem, where the user acted as the leader, and the jammer acted as the follower of the game. Utility functions were designed, and Stackelberg Equilibriums (SE) were also obtained via game approaches.…”

Section: Introductionmentioning

confidence: 99%

Location-aware Cooperative Anti-jamming Distributed Channel Selection Approach in UAV Communication Networks

Xu¹,

Ren²,

Jin³

et al. 2018

Preprint

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This paper investigates the cooperative anti-jamming distributed channel selection problem in UAV communication networks. Considering the existence of malicious jamming and co-channel interference, a location-aware cooperative anti-jamming scheme is designed for the purpose of maximizing the users' utilities. Users in the UAV group cooperate with each other via location information sharing. When the received interference energy is lower than mutual interference threshold, users conduct channel selection strategies independently. Otherwise, users take joint actions with a cooperative anti-jamming pattern under the impact of mutual interference. Aimed at the independent anti-jamming channel selection problem under no mutual interference, a Markov Decision Process framework is introduced, whereas for the cooperative anti-jamming channel selection case under the influence of co-channel mutual interference, a Markov game framework is employed. Furthermore, motivated by reinforcement learning with a ``Cooperation-Decision-Feedback-Adjustment" idea, we design a location-aware cooperative anti-jamming distributed channel selection algorithm (LCADCSA) to obtain the optimal anti-jamming channel strategies for the users with a distributed way. In addition, the channel switching cost and cooperation cost, which have great impact on the users' utilities, are introduced. Finally, simulation results show that the proposed algorithm converges to a stable solution with which the UAV group can avoid the malicious jamming as well as co-channel interference effectively.

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Section: Introductionmentioning

confidence: 99%

Location-aware Cooperative Anti-jamming Distributed Channel Selection Approach in UAV Communication Networks

Xu¹,

Ren²,

Jin³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Multiple types of jammers, such as constant jammers, random jammers, reactive jammers and smart jammers, have been found to attack wireless networks and have received extensive research attention [1]- [4]. Most existing anti-jamming techniques assume accurate jamming detection [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

Jamming Detection of Smartphones for WiFi Signals

Liu

et al. 2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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In this paper, we investigate the impact of jamming attacks on the performance of smartphones regarding their WiFi access and propose a real-time jamming detection method based on the received signal strength indicator and the packet loss rate of WiFi signals, which can be easily implemented on Android smartphones. Experiments are performed to evaluate the proposed jamming detection method, in which universal software radio peripherals are used as jammers to block the WiFi signals between smartphone phones and wireless routers. Experimental results show that the proposed application can detect jamming attacks with small false alarm rate and miss detection rate.Index Terms-Packet loss rate, Received signal strength indicator, Denial of service, Jamming detection

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“…Then, they analyzed the asymptotic convergence by proposing a hierarchical power control algorithm (HPCA). In [27], a smart jammer can quickly learn the transmission strategies of the legitimate transmitters, and then he would adjust his strategy to damage the legitimate transmission. Meanwhile, the transmitters are aware of the existence of the smart jammer.…”

Section: Related Workmentioning

confidence: 99%

Smart Jamming Attacks in Wireless Networks During a Transmission Cycle: Stackelberg Game with Hierarchical Learning Solution

Lmater¹,

Haddad²,

Karouit³

et al. 2018

ijacsa

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Abstract-Due to the broadcast nature of the shared medium, wireless communications become more vulnerable to malicious attacks. In this paper, we tackle the problem of jamming in wireless network when the transmission of the jammer and the transmitter occur with a non-zero cost. We focus on a jammer who keeps track of the re-transmission attempts of the packet until it is dropped. Firstly, we consider a power control problem following a Nash Game model, where all players take action simultaneously. Secondly, we consider a Stackelberg Game model, in which the transmitter is the leader and the jammer is the follower. As the jammer has the ability to sense the transmission power, the transmitter adjusts its transmission power accordingly, knowing that the jammer will do so. We provide the closed-form expressions of the equilibrium strategies where both the transmitter and the jammer have a complete information. Thereafter, we consider a worst case scenario where the transmitter has an incomplete information while the jammer has a complete information. We introduce a Reinforcement Learning method, thus, the transmitter can act autonomously in a dynamic environment without knowing the above Game model. It turns out that despite the jammer ability of sensing the active channel, the transmitter can enhance its efficiency by predicting the jammer reaction according to its own strategy.

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Power control Stackelberg game in cooperative anti-jamming communications

Cited by 40 publications

References 19 publications

Location-aware Cooperative Anti-jamming Distributed Channel Selection Approach in UAV Communication Networks

Location-aware Cooperative Anti-jamming Distributed Channel Selection Approach in UAV Communication Networks

Jamming Detection of Smartphones for WiFi Signals

Smart Jamming Attacks in Wireless Networks During a Transmission Cycle: Stackelberg Game with Hierarchical Learning Solution

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