A One-Leader Multi-Follower Bayesian-Stackelberg Game for Anti-Jamming Transmission in UAV Communication Networks

Xu, Yifan; Ren, Guochun; Chen, Jin; Luo, Yunpeng; Jia, Luliang; Liu, Xin; Yang, Yang; Xu, Yuhua

doi:10.1109/access.2018.2828033

Cited by 92 publications

(65 citation statements)

References 42 publications

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“…Compare this paper to our previous works [27,28], which studied anti-jamming channel selection in wireless communication networks, and to our previous works [29], the main differences are: i) Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 13 September 2018 doi:10.20944/preprints201809.0227.v1 Work [27] investigated the multi-agent learning method for anti-jamming problem, and work [28] considered the single reinforcement learning in fading environment. However, both these two works did not take the mobility of UAVs into consideration.…”

Section: Introductionmentioning

confidence: 61%

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: 61%

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

Xu¹,

Ren²,

Jin³

et al. 2018

Preprint

Self Cite

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“…It is well known that game theory is efficient for solving the challenge of resource competition for example the anti-jamming transmission problem [25,26], the opportunistic spectrum access problem [27], the distributed channel-slot selection optimizing problem [28], even the challenging UAV relay selection problem [29], and the ultra-dense small cell network problem [30]. Similarly, we propose a UAV-assisted caching game in this paper from a game-theoretic perspective.…”

Section: Game Modelmentioning

confidence: 99%

Context-Aware Caching Distribution and UAV Deployment: A Game-Theoretic Approach

et al. 2018

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This paper investigates the problem of the optimal arrangement for both unmanned aerial vehicles’ (UAVs’) caching contents and service locations in UAV-assisted networks based on the context awareness, which considers the influence between users and environment. In the existing work, users within the coverage of UAVs are considered to be served perfectly, which ignores the communication probability caused by line-of-sight (LOS) and non-line-of-sight (NLOS) links. However, the links are related to the deployment of UAVs. Moreover, the transmission overhead should be taken into account. To balance the tradeoff between these two factors, we design the ratio of users’ probability and transmission overhead as the performance measure mechanism to evaluate the performance of UAV-assisted networks. Then, we formulate the objective for maximizing the performance of UAV-assisted networks as a UAV-assisted caching game. It is proved that the game is an exact potential game with the performance of UAV-assisted networks serving as the potential function. Next, we propose a log-linear caching algorithm (LCA) to achieve the Nash equilibrium (NE). Finally, related simulation results reflect the great performance of the proposed algorithm.

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“…It is well known that game theory is efficient for solving the challenge of resource competition like the anti-jamming transmission problem [24,25], the opportunistic spectrum access problem [26], the distributed channel-slot selection optimizing problem [27], even the challenging UAV relay selection problem [28] and ultra-dense small cell network problem [29]. Similarly, we propose a UAV-assisted caching game in this paper from a game-theoretic perspective.…”

Section: Game Modelmentioning

confidence: 99%

Context-aware Caching Distribution and UAV Deployment: A Game-theoretic Approach

Fang¹,

Tian²,

Zhang³

et al. 2018

Preprint

View full text Add to dashboard Cite

This paper investigates the problem of the optimal arrangement for both UAVs’ caching contents and service locations in UAV-assisted networks based on the context awareness, which considers the influence between users and environment. In the existing work, users within the coverage of UAVs are considered to be served perfectly, which ignores the communication probability caused by line-of-sight (LOS) and non- line-of-sight (NLOS) links. However, the links are related to UAV deployment. Moreover, the transmission overhead should be taken into account. To balance the tradeoff between these two factors, we design the ratio of users’ probability and transmission overhead as the performance measure mechanism to evaluate the performance of UAV-assisted networks. Then, we formulate the objective for maximizing the performance of UAV-assisted networks as a UAV-assisted caching game. It is proved that the game is an exact potential game with the performance of UAV-assisted networks serving as the potential function. Next, we propose the log-linear caching algorithm (LCA) to achieve the Nash equilibrium (NE). Finally, related simulation results reflect the great performance of the proposed algorithm.

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A One-Leader Multi-Follower Bayesian-Stackelberg Game for Anti-Jamming Transmission in UAV Communication Networks

Cited by 92 publications

References 42 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

Context-Aware Caching Distribution and UAV Deployment: A Game-Theoretic Approach

Context-aware Caching Distribution and UAV Deployment: A Game-theoretic Approach

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