Game theory for wireless engineers

被引:80
作者
MacKenzie, Allen B. [1 ]
Dasilva, Luiz A. [1 ]
机构
[1] Virginia Polytechnic Institute, State University
来源
Synthesis Lectures on Communications | 2005年 / 1卷
关键词
Communications theory; Distributed protocols; Game theory; Optimization; Wireless communications; Wireless networks;
D O I
10.2200/S00014ED1V01Y200508COM001
中图分类号
学科分类号
摘要
The application of mathematical analysis to wireless networks has met with limited success, due to the complexity of mobility and traffic models, coupled with the dynamic topology and the unpredictability of link quality that characterize such networks. The ability to model individual, independent decision makers whose actions potentially affect all other decision makers makes game theory particularly attractive to analyze the performance of ad hoc networks. Game theory is a field of applied mathematics that describes and analyzes interactive decision situations. It consists of a set of analytical tools that predict the outcome of complex interactions among rational entities, where rationality demands a strict adherence to a strategy based on perceived or measured results. In the early to mid-1990's, game theory was applied to networking problems including flow control, congestion control, routing and pricing of Internet services. More recently, there has been growing interest in adopting game-theoretic methods to model today's leading communications and networking issues, including power control and resource sharing in wireless and peer-to-peer networks. This work presents fundamental results in game theory and their application to wireless communications and networking. We discuss normal-form, repeated, and Markov games with examples selected from the literature. We also describe ways in which learning can be modeled in game theory, with direct applications to the emerging field of cognitive radio. Finally, we discuss challenges and limitations in the application of game theory to the analysis of wireless systems. We do not assume familiarity with game theory. We introduce major game theoretic models and discuss applications of game theory including medium access, routing, energy-efficient protocols, and others. We seek to provide the reader with a foundational understanding of the current research on game theory applied to wireless communications and networking. © Copyright 2006 by Morgan & Claypool 2006.
引用
收藏
页码:1 / 86
页数:85
相关论文
共 58 条
  • [11] Saraydar C.U., Mandayam N.B., Goodman D.J., Efficient power control via pricing in wireless data networks, IEEE Trans. Communications, 50, 2, pp. 291-303, (2002)
  • [12] Heikkinen T., Distributed scheduling via pricing in a communication network, Proceedings of Networking, (2002)
  • [13] Alpcan T., Basar T., Srikant R., Altman E., CDMA uplink power control as a noncooperative game, Proc. IEEE Conference on Decision and Control, pp. 197-202, (2001)
  • [14] Xiao M., Schroff N., Chong E., Utility based power control in cellular radio systems, Proceedings of IEEE INFOCOM, (2001)
  • [15] Economides A., Silvester J., Multi-objective routing in integrated services networks: A game theory approach, IEEE INFOCOM Networking in the 90s/Proceedings of the 10th Annual Joint Conference of the IEEE and Communications Societies, 3, pp. 1220-1227, (1991)
  • [16] Korilis Y., Lazar A., Orda A., Achieving network optima using Stackelberg routing strategics, IEEE/ACM Trans. Networking, 5, 1, pp. 161-173, (1997)
  • [17] La R.J., Anantharam V., Optimal routing control: Game theoretic approach, Proceedings of the 36th IEEE Conference on Decision and Control, 3, pp. 2910-2915, (1997)
  • [18] Roughgarden T., Tardos E., How bad is selfish routing?, Journal of the ACM, 49, 2, pp. 236-259, (2002)
  • [19] Braess D., Uber ein paradoxen der verkehrsplanung, Unternehmenforschung, 12, pp. 258-268, (1968)
  • [20] Murchland J.D., Braess's paradox of traffic flow, Transport. Res., 4, pp. 391-394, (1970)