Particle Swarm Optimization for Mobility Load Balancing SON in LTE Networks

摘要

This paper presents a self-optimizing solution for Mobility Load Balancing(MLB). The MLB-SON is performed in two phases. In the first, a MLB controlleris designed using Multi-Objective Particle Swarm Optimization (MO-PSO) whichincorporates a priori expert knowledge to considerably reduce the search spaceand optimization time. The dynamicity of the optimization phase is addressed.In the second phase, the controller is pushed into the base stations toimplement the MLB SON. The method is applied to dynamically adapt HandoverMargin parameters of a large scale LTE network in order to balance traffic ofthe network eNodeBs. Numerical results illustrate the benefits of the proposedsolution.