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On pareto-koopmans efficiency for performance-driven optimisation in self-organising networks

  • H. Peyvandi
  • , A. Imran
  • , M. A. Imran
  • , R. Tafazolli
  • University of Surrey
  • Qatar University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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 SONLTE. 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.

Original languageEnglish
Title of host publicationIET Intelligent Signal Processing Conference 2013, ISP 2013
Edition619 CP
DOIs
StatePublished - 2013
Externally publishedYes
EventIET Intelligent Signal Processing Conference 2013, ISP 2013 - London, United Kingdom
Duration: 2 Dec 20133 Dec 2013

Publication series

NameIET Conference Publications
Number619 CP
Volume2013

Conference

ConferenceIET Intelligent Signal Processing Conference 2013, ISP 2013
Country/TerritoryUnited Kingdom
CityLondon
Period2/12/133/12/13

Keywords

  • Coverage and capacity optimisation
  • EASA
  • Multi-objective optimisation
  • Pareto frontier
  • Self-organising

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