Load Balancing in Heterogeneous Networks using an Evolutionary Algorithm

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Title: Load Balancing in Heterogeneous Networks using an Evolutionary Algorithm
Authors: Fenton, MichaelLynch, DavidKucera, StepanClaussen, HolgerO'Neill, Michael
Permanent link: http://hdl.handle.net/10197/7297
Date: 28-May-2015
Online since: 2015-12-14T12:54:10Z
Abstract: Grammatical Evolution (GE) is applied to the problem of load balancing in heterogeneous cellular network deployments (HetNets). HetNets are multi-tiered cellular networks for which load balancing is a scalable means to maximise network capacity, assuming similar traffic from all users. This paper describes a proof of concept study in which GE is used in a genetic algorithm-like way to evolve constants which represent cell power and selection bias in order to achieve load balancing in HetNets. A fitness metric is derived to achieve load balancing both locally in sectors and globally across tiers. Initial results show promise for GE as a heuristic for load balancing. This finding motivates a more sophisticated grammar to bring enhanced Inter-Cell Interference Coordination optimisation into an evolutionary framework.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Start page: 70
End page: 76
Copyright (published version): 2015 IEEE
Keywords: Grammatical evolutionLoad balancingCellular networks
DOI: 10.1109/CEC.2015.7256876
Other versions: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7256876
Language: en
Status of Item: Peer reviewed
Conference Details: 2015 IEEE Congress on Evolutionary Computation (IEEE CEC), Sendai, Japan, 25 - 28 May 2015
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Business Research Collection
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