Novel genetic algorithm for computer-aided optimization of multi-femtocell deployments

In enterprise scenarios, multi-femtocell deployments can be carried out to improve indoor services performance. In this environment, a detailed cell planning can be made in order to optimize network performance. To solve optimization problems in wireless networks, many techniques have been proposed, typically taking the number of base stations to be deployed as an input to the automatic planning process or including them as a fixed cost to assess fitness value. In this paper, a novel genetic algorithm for computer aided optimization of multi-femtocell deployments is presented, assuming that the optimal number of femtocells to fulfill design constraints is unknown. This novel genetic approach is demonstrated using a multi-objective multi-femtocell deployment in a typical enterprise scenario.