• DocumentCode
    681680
  • Title

    On Pareto-Koopmans efficiency for performance-driven optimisation in Self-Organising Networks

  • Author

    Peyvandi, Hossein ; Imran, Ali ; Imran, Muhammad Ali ; Tafazolli, Rahim

  • Author_Institution
    Centre for Commun. Syst. Res. (CCSR), Univ. of Surrey, Guildford, UK
  • fYear
    2013
  • fDate
    2-3 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, a novel Multi-Objective Optimisation (MOO) method has been introduced for Self-Organising Networks (SONs). Meta-heuristic algorithms based on Simulated Annealing (SA) are used to evaluate the Pareto Frontier (PF) of UE throughput vs. fairness index in a simulation of Coverage & Capacity Optimisation (CCO) use-case in SON-LTE. We have evaluated the performance optimisation methods through the final optimal set of solutions. The boundaries of the optimal sets are evaluated as PF and compared with the results of the conventional method of Multi-Objective Simulated Annealing (MOSA). We have detected a Pareto improvement for the estimated PF of the proposed method, which outperforms that of MOSA.
  • Keywords
    Long Term Evolution; Pareto optimisation; simulated annealing; CCO; MOO method; Pareto frontier; Pareto-Koopmans efficiency; SON-LTE; UE throughput; coverage & capacity optimisation; fairness index; meta-heuristic algorithms; multiobjective optimisation method; performance-driven optimisation; self-organising networks; simulated annealing; Coverage and Capacity Optimisation; EASA; Multi-Objective Optimisation; Pareto Frontier; Self-Organising;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Intelligent Signal Processing Conference 2013 (ISP 2013), IET
  • Conference_Location
    London
  • Electronic_ISBN
    978-1-84919-774-8
  • Type

    conf

  • DOI
    10.1049/cp.2013.2053
  • Filename
    6740502