• DocumentCode
    1908357
  • Title

    Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory

  • Author

    Andrews, Matthew ; Dinitz, Michael

  • Author_Institution
    Bell Labs., Murray Hill, NJ
  • fYear
    2009
  • fDate
    19-25 April 2009
  • Firstpage
    1332
  • Lastpage
    1340
  • Abstract
    In this paper we consider the problem of maximizing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission powers for each connection so as to maximize the number of connections for which this threshold is met. We believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking. We study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms. We also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission powers) as well as discrete aspects (i.e. which connections should be supported). Our results are: ldr We show that maximizing the number of supported connections is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. ldr We present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. ldr We examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero power. We show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections. We also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and - has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008.
  • Keywords
    approximation theory; channel capacity; computational complexity; distributed algorithms; game theory; radio networks; radio receivers; NP-hard problem; arbitrary wireless network capacity maximization; channel condition; distributed algorithm complexity; game theory; polynomial time approximation algorithm; wireless receiver; Algorithm design and analysis; Approximation algorithms; Background noise; Distributed algorithms; Game theory; Linear programming; Nash equilibrium; Polynomials; Signal to noise ratio; Wireless networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM 2009, IEEE
  • Conference_Location
    Rio de Janeiro
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4244-3512-8
  • Electronic_ISBN
    0743-166X
  • Type

    conf

  • DOI
    10.1109/INFCOM.2009.5062048
  • Filename
    5062048