Métodos meta-heurísticos de localização pela potência do sinal óptico recebido

Abstract

This academic work presents the structures of visible light positioning (VLP) systems, which utilize the classical Newton-Raphson algorithm and metaheuristic algorithms such as particle swarm optimization, ant colony optimization, and k-nearest neighbors. The aim is to compare the impacts of the metaheuristic algorithms on the widely established classical method within the scientific community. All evaluated positioning methods leverage the received signal strength (RSS) information to eliminate the need for synchronization between the receiver and transmitter clocks. This enables to design a VLP system based on visible light communication (VLC) using orthogonal frequency-division multiplexing modulation (OFDM). This approach offers the advantage of distinguishing the received powers from the receiver, providing valuable information about RSS. Furthermore, this work implements the proposed three metaheuristic algorithms to optimize the VLP system. The parameters of these algorithms are tuned to obtain the most accurate estimates. The main results are analyzed in precision, accuracy, convergence rate, and execution time, comparing the metaheuristic algorithms with the classical method. These results validate the proposals presented in this thesis, demonstrating the effectiveness of the metaheuristic algorithms in the context of visible light positioning systems.