Firefly Algorithm-based Optimization of Base Transceiver Station Placement

Abstract

Long-Term Evolution (LTE), also known as the 4th generation (4G) is a system currently seen as a development system of UMTS/HSPA, which is one of the 3rd generation (3G) evolutions. One of the supporting components of the LTE network is ENodeB. An ENodeB can be analogous to a Base Transceiver Station (BTS). As customer needs are increasing, the need for BTS (ENodeB) is also increasing. It causes a large number of base stations. On the other hand, the construction of new base stations will certainly cost a lot and cause temper the city's landscape. Therefore, it is necessary to optimize the BTS placement. Hence, in this research, we design a simulation of BTS placement optimization using the firefly algorithm (FA) with the parameter to be optimized is the coverage area and traffic. The fitness value obtained from this study reached 97.73% and reduced existing BTS by 50%. This fitness is comparable with the hybrid evolutionary FA (HEFA)-based model, which produces an average fitness of 98.62%.