ABSTRACT
The precise placement of antennas is essential to ensure effective coverage, service quality, and network capacity in wireless communications, particularly given the exponential growth of mobile connectivity. The antenna positioning problem (APP) has evolved from theoretical approaches to practical solutions employing advanced algorithms, such as evolutionary algorithms. This study focuses on developing innovative web tools harnessing genetic algorithms to optimize antenna positioning, starting from propagation loss calculations. To achieve this, seven empirical models were reviewed and integrated into an antenna positioning web tool. Results demonstrate that, with minimal configuration and careful model selection, a detailed analysis of antenna positioning in any area is feasible. The tool was developed using Java 17 and TypeScript 5.1.6, utilizing the JMetal framework to apply genetic algorithms, and features a React-based web interface facilitating application integration. For future research, consideration is given to implementing a server capable of analyzing the environment based on specific area selection, thereby enhancing the precision and objectivity of antenna positioning analysis.
ABSTRACT
The implementation of a fast and efficient computer tool for field coverage studies in urban mobile radio systems is presented in this work. An accelerated and tailored ray launching method takes advantage of a ray tracing programmable framework optimized for massively parallel processing on GPUs. The PlotOptiX API is used to customize the code before applying the electromagnetic equations. The proposed code is described, and results are shown to demonstrate its correct operation. A high number of diffractions and reflections can be tracked in each ray from the transmitter to the receiver. In addition to the typical point-to-point simulation, measurement planes can also be set as receivers to provide fast predictions in wide urban areas.
