Improving macrocell-small cell coexistence through adaptive interference draining

Francesco Pantisano, Mehdi Bennis, Walid Saad, Merouane Debbah, Matti Latva-Aho

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to a macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBS tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs.

Original languageEnglish (US)
Article number6684542
Pages (from-to)942-955
Number of pages14
JournalIEEE Transactions on Wireless Communications
Issue number2
StatePublished - Feb 2014
Externally publishedYes


  • coalition games
  • draining
  • game theory
  • interference management
  • MIMO
  • Small cell networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics


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