2,387 research outputs found

    Applications of Repeated Games in Wireless Networks: A Survey

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    A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

    A Comprehensive Survey of Potential Game Approaches to Wireless Networks

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    Potential games form a class of non-cooperative games where unilateral improvement dynamics are guaranteed to converge in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on Communications, vol. E98-B, no. 9, Sept. 201

    Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities

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    Designing cost-effective and scalable backhaul solutions is one of the main challenges for emerging wireless small cell networks (SCNs). In this regard, millimeter wave (mmW) communication technologies have recently emerged as an attractive solution to realize the vision of a high-speed and reliable wireless small cell backhaul network (SCBN). In this paper, a novel approach is proposed for managing the spectral resources of a heterogeneous SCBN that can exploit simultaneously mmW and conventional frequency bands via carrier aggregation. In particular, a new SCBN model is proposed in which small cell base stations (SCBSs) equipped with broadband fiber backhaul allocate their frequency resources to SCBSs with wireless backhaul, by using aggregated bands. One unique feature of the studied model is that it jointly accounts for both wireless channel characteristics and economic factors during resource allocation. The problem is then formulated as a one-to-many matching game and a distributed algorithm is proposed to find a stable outcome of the game. The convergence of the algorithm is proven and the properties of the resulting matching are studied. Simulation results show that under the constraints of wireless backhauling, the proposed approach achieves substantial performance gains, reaching up to 30%30 \% compared to a conventional best-effort approach.Comment: In Proc. of the IEEE International Conference on Communications (ICC), Mobile and Wireless Networks Symposium, London, UK, June 201

    Spectrum Trading: An Abstracted Bibliography

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    This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

    A distributed algorithm for wireless resource allocation using coalitions and the Nash bargaining solution

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