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Distributed Optimization of Local Area Networks

  • Sofie Pollin
  • Michael Timmers
  • Liesbet Van der Perre
Part of the Signals and Communication Technology book series (SCT)

Abstract

An important task of a cognitive radio is to learn and calibrate its behavior in the environment. How to achieve this efficiently is illustrated in this chapter for IEEE 802.11 networks that aim at minimizing the co-channel interference in a distributed way.

A novel control algorithm, Spatial Learning, is proposed, which learns the optimal operating point in a 3D design space at run-time. The learner interprets how the environment reacts to the selected actions and adapts his actions accordingly. Simulation-based experiments illustrate the trade-offs which need to be made, and the gains that can eventually be achieved.

Keywords

Nash Equilibrium Transmission Power Transmission Rate Spatial Learn Spatial Reuse 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Sofie Pollin
    • 1
  • Michael Timmers
    • 2
  • Liesbet Van der Perre
    • 3
  1. 1.SSET/wirelessIMECLeuvenBelgium
  2. 2.Bell LabsAlcatel-LucentAntwerpenBelgium
  3. 3.IMEC VZWLeuvenBelgium

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