Load balancing in heterogeneous networks using an evolutionary algorithm

• Published in: 2015 IEEE Congress on Evolutionary Computation (CEC) pp. 70 - 76
• Main Authors: Fenton, Michael, Lynch, David, Kucera, Stepan, Claussen, Holger, O'Neill, Michael
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2015
• Subjects: Bandwidth; Grammar; Heating; Noise; Optimization; Sociology; Statistics
• ISSN: 1089-778X; 1941-0026
• DOI: 10.1109/CEC.2015.7256876

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.