Fenton, MichaelMichaelFentonLynch, DavidDavidLynchKucera, StepanStepanKuceraClaussen, HolgerHolgerClaussenO'Neill, MichaelMichaelO'Neill2015-12-142015-12-142015 IEEE2015-05-28http://hdl.handle.net/10197/72972015 IEEE Congress on Evolutionary Computation (IEEE CEC), Sendai, Japan, 25 - 28 May 2015Grammatical 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.en© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Grammatical evolutionLoad balancingCellular networksConference Publication707610.1109/CEC.2015.72568762015-11-30https://creativecommons.org/licenses/by-nc-nd/3.0/ie/