Cellular network bandwidth management scheme by using Nash bargaining solution

Kim, Sung-Wook

doi:10.1049/iet-com.2010.0309

Cited by 19 publications

(11 citation statements)

References 14 publications

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“…Generally, the formal game model consists of players, the possible strategies of the players, and utility functions of the strategies [4,5]. Therefore, to represent a traditional game G, the game model components are given by G ¼ < N; S; U 1 ; ::; U n f g> , where N is the number of players, S is a non-empty set of the strategies, U i ∈ {U 1 ,.., U n } is the utility function of player i, and optimize S i : U i S i ð Þ→ℜ; S i ∈S .…”

Section: Wireless Link Estimationmentioning

confidence: 99%

“…It can describe the possibility of reacting to the actions of the other decision makers and analyze the situations of conflict and cooperation. In recent times, game theory has emerged as an effective method for designing routing algorithms and has introduced well-fitted models to describe the interaction among network vehicles [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…In 1950, John Nash introduced the fundamental notion of the Nash bargaining solution (NBS) to allocate a resource fairly and optimally [4]. The NBS is a field of cooperative game theory and an effective tool to achieve a mutually desirable solution with a good balance between efficiency and fairness [4].…”

Section: Introductionmentioning

confidence: 99%

“…The NBS is a field of cooperative game theory and an effective tool to achieve a mutually desirable solution with a good balance between efficiency and fairness [4]. Owing to its numerous desirable properties, the basic concept of NBS has become an interesting research topic in a wider range of real-life situations, such as economics, political science, sociology, psychology, and biology.…”

Section: Introductionmentioning

confidence: 99%

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Timed bargaining-based opportunistic routing model for dynamic vehicular ad hoc network

Kim

2016

J Wireless Com Network

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Vehicular ad hoc network (VANET) is a mobile ad hoc network with a dynamic property; the vehicles possess high mobility and undergo fast topology changes. This special type of mobile ad hoc network is a popular topic of research. Owing to the specific features of VANETs, unique routing protocols are required for short-range, high-speed communication among nearby vehicles. In this study, we propose a new opportunistic routing scheme based on the timed bargaining game. In order to dynamically adapt to the current VANET situation, the proposed scheme effectively formulates the opportunistic routing mechanism as an iterative bargaining model with a timed learning approach. Based on a simulation study, it is confirmed that the proposed scheme can achieve better performance than other existing schemes in diverse VANET environments.

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Section: Wireless Link Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Timed bargaining-based opportunistic routing model for dynamic vehicular ad hoc network

Kim

2016

J Wireless Com Network

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“…Therefore, efficient bandwidth management plays an important role in determining network performance. Adaptive bandwidth reservation and borrowing algorithms are proposed for multimedia cellular networks in [29]. Based on the well-known game-theoretic concept of bargaining, wireless bandwidth is controlled as efficiently as possible while ensuring quality-of-service (QoS) guarantees for higher-priority traffic services.…”

Section: State-of-the Artmentioning

confidence: 99%

Strategic bargaining in wireless networks: basics, opportunities and challenges

Yang

Anpalagan³

2014

IET Communications

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Strategic bargaining cooperative games have found extensive applications to resource management in wireless networks. In this survey, basics of a strategic bargaining game and solution concepts are firstly presented. Geometrical interpretations are introduced to better understand real meanings of them. Then, the authors survey the applications of various strategic bargaining games for the emerging wireless networks, where the authors concentrate on several interesting problems based on their previous systematic studies: (i) distributed resource management design for cognitive radio networks based on geometrical interpretation of the cooperative solution; (ii) asymmetric bargaining modelling for green communications; (iii) a unified utility tradeoff design between spectral and energy efficiency in heterogeneous cellular networks; (iv) the cooperative rate splitting game for Long Term Evolution-coordinated multi-point system; and (v) a general bargaining formulation with different tradeoffs between efficiency and fairness. In addition, the authors survey the applications of strategic bargaining games to cooperation incentive mechanism, bargaining game on capacity region of interference channel and multiuser and multimedia applications. Finally, challenges and potential research direction are summarised in this work.

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