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
Link To Document :
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