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Managing Policies for Dynamic Spectrum Access

  • David Lewis
  • Kevin Feeney
  • Kevin Foley
  • Linda Doyle
  • Tim Forde
  • Patroklos Argyroudis
  • John Keeney
  • Declan O’Sullivan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4195)

Abstract

The advent of software radio technology and the resulting potential for dynamic access to the radio spectrum presents major new challenges in managing that access. These challenges arise from the likely spread of spectrum access decision-making authority well beyond existing regulatory authorities to a wide variety of co-existing market-based or open-access schemes. Policy-based management mechanisms are proposed as a flexible means for defining the rules that determine spectrum allocation dynamically. However, many existing policy based mechanisms rely on a fixed organisation structure and so are insufficiently flexible to support combinations of central allocation, market mechanisms and commons usage. In this paper we present the application of a novel policy-based management mechanism based on self-managing communities to the management of policy authoring authority. We show how an existing implementation could be used to manage a software-based radio system and how this approach provides self-organisation of multiple groupings with differing goals and policies in the allocation of spectrum. This is illustrated by taking real world policy authoring scenario from the world first software radio test license.

Keywords

Supply Chain Cognitive Radio Policy Language Policy Rule Spectrum Allocation 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Lewis
    • 1
  • Kevin Feeney
    • 1
  • Kevin Foley
    • 1
  • Linda Doyle
    • 1
  • Tim Forde
    • 1
  • Patroklos Argyroudis
    • 1
  • John Keeney
    • 1
  • Declan O’Sullivan
    • 1
  1. 1.Knowledge & Data Engineering Group & Centre for Telecommunication Value-chain Research, School of Computer Science and StatisticsTrinity College DublinIreland

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