Clustering based self-optimization of pilot power in dense femtocell deployments using genetic algorithms

Femtocells are small base stations used to enhance cellular coverage in an indoor environment. However, dense femtocell deployments can lead to severe performance degradation. This paper adopts a new strategy to self-optimize the pilot power of femtocells by creating disjoint femtocell clusters which are managed by the chosen cluster heads (CHs). Each CH optimizes the coverage of its connected members by applying a multi-objective heuristic based on genetic algorithm. The simulation results show that the proposed approach can significantly reduce both the computational time and the data overhead compared with the centralized power optimization.