Dynamic Spectrum Access in Time-Varying Environment: Distributed Learning Beyond Expectation Optimization

Xu, Yuhua; Wang, Jinlong; Wu, Qihui; Zheng, Jianchao; Shen, Liang; Anpalagan, Alagan

doi:10.1109/tcomm.2017.2734768

Cited by 70 publications

(39 citation statements)

References 49 publications

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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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Section: Game Modelmentioning

confidence: 99%

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

et al. 2018

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“…Therefore, motivated by learning algorithm design in [31,32], we construct a coalition selection algorithm based on coalition order and a coalition selection algorithm based on Pareto order, which can be abbreviated as CO-CSA and PO-CSA, respectively (Algorithm 2). The core of the algorithm is to follow the coalition selection mechanism; according to Theorem 3, it can converge P in the solution of the problem.…”

Section: Algorithm Designmentioning

confidence: 99%

Group Buying-Based Data Transmission in Flying Ad-Hoc Networks: A Coalition Game Approach

et al. 2018

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In scenarios such as natural disasters and military strikes, it is common for unmanned aerial vehicles (UAVs) to form groups to execute reconnaissance and surveillance. To ensure the effectiveness of UAV communications, repeated resource acquisition issues and transmission mechanism designs need to be addressed urgently. Since large-scale UAVs will generate high transmission overhead due to the overlapping resource requirements, in this paper, we propose a resource allocation optimization method based on distributed data content in a Flying Ad-hoc network (FANET). The resource allocation problem with the goal of throughput maximization is constructed as a coalition game framework. Firstly, a data transmission mechanism is designed for UAVs to execute information interaction within the coalitions. Secondly, a novel mechanism of coalition selection based on group-buying is investigated for UAV coalitions to acquire data from the central UAV. The data transmission and coalition selection problem are modeled as coalition graph game and coalition formation game, respectively. Through the design of the utility function, we prove that both games have stable solutions. We also prove the convergence of the proposed approach with coalition order and Pareto order. Based on simulation results, coalition order based coalition selection algorithm (CO-CSA) and Pareto order based coalition selection algorithm (PO-CSA) are proposed to explore the stable coalition partition of system model. CO-CSA and PO-CSA can achieve higher data throughput than the contrast onetime coalition selection algorithm (Onetime-CSA) (at least increased by 34.5% and 16.9%, respectively). Besides, although PO-CSA has relatively lower throughput gain, its convergence times is on average 50.9% less than that of CO-CSA, which means that the algorithm choice is scenario-dependent.

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“…Considering the cooperative behaviours among UAVs should be well depicted, potential game is adopted, which applies to distributed multi-agent system and can associate with the local utility and global utility of each participant [25] [26]. Hence, combining with the distributed self-organizing characteristics of UAVs, the whole system can make decisions to achieve more efficient performance.…”

Section: Analysis Of the Mission Reward Maximizationmentioning

confidence: 99%

A Coalition Formation Game Approach for Efficient Cooperative Multi-UAV Deployment

Ruan¹,

Chen²,

Guo³

et al. 2018

Preprint

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UAV cooperative control has been an important issue in UAV-assisted sensor network, thanks to the considerable benefit obtained from the cooperative mechanism of UAVs being applied as a flying base station. In coverage scenario, the tradeoff between coverage performance and transmission performance often makes deployment of UAVs fall into a dilemma, since both indexes are related to the distance between UAVs. To address this issue, UAV coverage and data transmission mechanism is analyzed in this paper, then an efficient multi-UAV cooperative deployment model is proposed. The problem is also modeled as a coalition formation game (CFG). The CFG with Pareto order is proved to have a stable partition. Then, an effective approach consisting of coverage deployment and coalition selection is designed, wherein UAVs can decide strategies cooperatively to achieve better coverage performance. Combining analysis of game approach, coalition selection and position deployment algorithm based on Pareto order (CSPDA-PO) is designed to execute coverage deployment and coalition selection. Finally, simulation results are shown to validate the proposed approach based on efficient multi-UAV cooperative deployment model.

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Dynamic Spectrum Access in Time-Varying Environment: Distributed Learning Beyond Expectation Optimization

Cited by 70 publications

References 49 publications

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

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

Group Buying-Based Data Transmission in Flying Ad-Hoc Networks: A Coalition Game Approach

A Coalition Formation Game Approach for Efficient Cooperative Multi-UAV Deployment

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