• DocumentCode
    742628
  • Title

    Multi-Objective Energy-Efficient Resource Allocation for Multi-RAT Heterogeneous Networks

  • Author

    Yu, Guanding ; Jiang, Yuhuan ; Xu, Lukai ; Li, Geoffrey Ye

  • Volume
    33
  • Issue
    10
  • fYear
    2015
  • Firstpage
    2118
  • Lastpage
    2127
  • Abstract
    Heterogeneous network (HetNet) integrated with multiple radio access technologies (RATs) is a promising technique for satisfying the exponentially increasing traffic demand of future cellular systems. In this paper, we investigate energy-efficient resource allocation in a multi-RAT HetNet, aimed at maximizing the energy efficiency (EE) for each individual user while guaranteeing the quality-of-service (QoS) requirement. Since the EE cannot be simultaneously maximized for every user, a multiple-objective optimization problem (MOOP) is formulated. To find its Pareto optimal solution, we first introduce the concept of Utopia EE, defined as the maximum achievable EE, for each user. Then, using the weighted Tchebycheff method, a single-objective optimization problem (SOOP) is formulated, which can achieve Pareto optimal solution of the original MOOP. The SOOP is a generalized fractional programming problem that aims to minimize the maximum of several quasiconvex fractional functions. We further transform the problem into an equivalent but better tractable one, and develop an iterative algorithm to effectively solve it. Numerical results demonstrate that the proposed algorithm yields fast convergence, high system EE, and flexible EE tradeoff.
  • Keywords
    Bandwidth; Pareto optimization; Programming; Rats; Resource management; Uplink; Energy efficiency; Pareto optimal; generalized fractional programming; multi-RAT heterogeneous networks; multiple objective optimization; pareto optimal; resource allocation;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2015.2435374
  • Filename
    7110541