Performance evaluation of heuristic techniques for coverage optimization in femtocells

Self-optimization of coverage is an essential element for successful deployment of enterprise femtocells. This paper evaluates the performance of genetic algorithm, particle swarm and simulated annealing heuristic techniques to solve a multi-objective coverage optimization problem when a number of femtocells are deployed to jointly provide indoor coverage. This paper demonstrates the different behaviors of the proposed algorithms. The results show that genetic algorithm and particle swarm have a higher potential of solving the problem compared to simulated annealing. This is due to their faster convergence time which is an important parameter for dynamic update of femtocells.