| Abstract: | Femtocells are designed to cover small indoor areas. In commercial buildings, femtocell placement and number is one of the most important network issues. In such buildings, another problem is uneven traffic distribution in different spaces, which causes high traffic and low traffic areas. Due to the small coverage areas of femtocells and these high traffic and low traffic areas, some femtocells are overloaded and some femtocells are underloaded. Also, increase in the distance of high-traffic areas from the femtocells, increases the number of resource blocks used. These issues reduce network efficiency. In this article, femtocell placement has been managed in such a way that the traffic load on the femtocells is balanced and is reduced the number of resource blocks used in the building and efficiency is increased. A mathematical model for femtocell placement has been introduced which balancing the femtocell load and reducing the average number of resource blocks used, the conditions of maximum coverage area and minimum femtocell number should also be fulfilled. This challenge has been addressed by using non-dominated sorting genetic algorithm (NSGA-II). An initial population generation algorithm and a selection function are also presented. The assessment results indicate that compared to the latest studies, this newly proposed method reduces the average load on the whole building by 79% and decreases the load variance between the femtocells by 86%. |
