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A Fully Distributed Learning Algorithm for Power Allocation in Heterogeneous Networks

  • Hajar ElhammoutiEmail author
  • Loubna Echabbi
  • Rachid Elazouzi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9466)

Abstract

In this work, we present a Fully distributed Learning Algorithm for Power allocation in HetNetS, referred to as FLAPH algorithm, that reaches to the global optimum given by the total social welfare. Using a mix of macro and femto base stations, we discuss opportunities to maximize users global throughput. We prove the convergence of our algorithm and compare its performances with the well-established Gibbs algorithm which ensures convergence to the global optimum.

Keywords

Distributed algorithms HetNets Nash equilibrium Global optimum 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hajar Elhammouti
    • 1
    Email author
  • Loubna Echabbi
    • 1
  • Rachid Elazouzi
    • 2
  1. 1.Department of Telecommunications Systems, Networks and Services, STRSNational Institute of Posts and TelecommunicationsRabatMorocco
  2. 2.Department Laboratory of Informatique of Avignon, LIAUniversity of AvignonAvignonFrance

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