The main objective of this Master Thesis is the development of an optimization algorithm from a theoretical point of view for UMTS. The objective of the optimization is to ensure the coverage at maximum number of users through the adjustment of the base stations main pointing parameters. Initially, a rectangular scenario is considered. This rectangular region must be covered by specific number of base stations distributed uniformly. Each base station has installed trisectorial antennas and each antenna will be treated independently. The chosen scenario represents a flat terrain where the propagation loss is modeled as a function of the distance, including shadowing lognormal. For each of the points of the scenario the level of received power of the pilot signal from each base station is determined, in order to be able of determining the coverage levels in the scenario. Furthermore, the best server sector is determined for the evaluated points. This scenario will be used to validate the simulation tool. The next step is the introduction of a rectangular region in the scenario which simulates a building where the losses are higher, causing a reduction of the received power levels. With the introduction of this element, it is possible to model the levels of coverage within a building. For the optimization of the points located in this region an algorithm was developed. The optimization algorithm reconfigures settings of the antenna pointing parameters (azimuth and downtilt) in order to optimize the levels of the coverage inside the building. In this Master Thesis the scenario will be analyzed with the developed tool and reconfiguration settings will be proposed to improve the coverage of the region, in general for the scenario and particular in the building, with the available scenario resources. In chapter 1, an introduction to the mobile communication systems is done, by means of the developed tool that simulates the air interface of mobile communication system. At the end of the chapter the goals of the thesis are presented. In chapter 2, a description of the developed tool is done. The propagation and antenna models used for the simulation are detailed. In addition the input parameters that define the scenario characteristics and the output parameters obtained after the simulation are described. This chapter also details the simulation process. In chapter 3, a description of the optimization algorithm is shown: in which is specified the involved parameters in the optimization, the decision function that the algorithm applies for determining the best solution and the detailed process of the algorithm. Chapter 4 contains the obtained results both simulation tool and optimization results once the algorithm has been applied. Finally, the chapter 5 shows the conclusions extracted after the development of the tool, the algorithm implementation and the obtained results. In this section also several future lines for the development of new capacities of the tool and the algorithm are proposed.