The aim of this thesis was studying and describing known methods for testing transmission parameters in data networks based on protocol stack TCP/IP. Firstly were individual transmission parameters specified and determined their impact on service quality. Another aim was to carry out a comparison of the different methodologies of measurement of transmission parameters, performed their qualifications on the basis of these findings and methodology for measuring service quality from the user's perspective was proposed. It was a web application where users measured basic transmission parameters, then the users judged videos according to the evaluation scale MOS (Mean Opinion Score) and with the help of these data was analysis, classification connection and impact of connection on MOS evaluation.

This thesis deals with methodology for measuring transmission parameters of internet connection. The aim of the thesis is to cover and compare known methods used for testing. Based on the research then design and realize an application that will provide those kind of measurements.

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The purpose of this thesis is to investigate how the LoRa modulation configuration affects precision and accuracy when using LoRa for indoor positioning in non-line-of-sight conditions. The aim is to research if an optimum combination of spreading factor, bandwidth, and code rate factor can be found to result in the best possible positioning accuracy and precision, under certain predefined conditions. An experiment was conducted, where quantitative data was collected from an experimental setup. The experiment consisted of two testbeds which also included an analysis between them. Two kinds of test units were used in the experiment. The LoRa 868 MHz transmitter, which represented the unknown position, and the receivers that were used to estimate the position of the transmitter. The experiment gathered the RSSI values between the transmitter and receivers at different configurations and locations. The data collected from the experiment were analyzed using mathematical theory to answer the research question. The most accurate and precise value for each individual transmission parameter was established in the first testbed and used as the base data rates in the second testbed, to evaluate the best performing parameters simultaneously. The mean accuracy in testbed 1 varied from 180 cm to 388 cm, and the mean precision ranged between 0.432 dBm to 1.298 dBm. The mean accuracy in testbed 2 varied from 341 cm to 455 cm, and the mean precision ranged between 0.275 dBm to 1.495 dBm.  The experimental results indicate no connections between the data rate and precision. No correlation is found between the accuracy and the data rate. The standard deviation and absolute error fluctuate independently of the data rate and the transmitter position. In regard to the given results, the authors conclude that no linear relationship is found between the LoRa modulation configuration and the precision and accuracy of a position, in the selected environment. The experimental results show that LoRa could be used for indoor positioning applications where a rough estimation of a position is adequate since the mean accuracy is quite low for almost all tested modulation configurations. There could be applications where other factors, such as the energy consumption or communication range, are of more importance than accuracy. For those applications, LoRa could still be an adequate choice of technology.

[pt] Com o rápido crescimento da Internet das Coisas (IoT), surgiram novas tecnologias de comunicação sem fio para atender aos requisitos de longo alcance, baixo custo e baixo consumo de energia exigidos pelos aplicativos de IoT. Nesse contexto, surgiram as redes de longa distância de baixa potência (LPWANs), as quais oferecem diferentes soluções que atendem aos requisitos dos aplicativos de IoT mencionados anteriormente. Entre as soluções LPWAN existentes, o LoRaWAN tem-se destacado por receber atenção significativa da indústria e da academia nos últimos anos. Embora o LoRaWAN ofereça uma combinação atraente de transmissões de dados de longo alcance e baixo consumo de energia, ele ainda enfrenta vários desafios em termos de confiabilidade e escalabilidade. No entanto, devido a sua natureza de código aberto e à flexibilidade do esquema de modulação no qual ele se baseia (Long Range (LoRa) permite o ajuste de fatores de espalhamento e a potência de transmissão), o LoRaWAN também oferece importantes possibilidades de melhorias. Esta dissertação aproveita a adequação dos algoritmos de Aprendizagem por Reforço (RL) para resolver tarefas de tomada de decisão e os utiliza para ajustar dinamicamente os parâmetros de transmissão dos dispositivos finais LoRaWAN. O sistema proposto, chamado RL-LoRa, mostra melhorias significativas em termos de confiabilidade e escalabilidade quando comparado ao LoRaWAN. Especificamente, diminui a taxa de erro de pacote (PER) média do LoRaWAN em 15 porcento, o que pode aumentar ainda mais a escalabilidade da rede. / [en] With the massive growth of the Internet of Things (IoT), novel wireless communication technologies have emerged to address the long-range, lowcost, and low-power consumption requirements of the IoT applications. In this context, the Low Power Wide Area Networks (LPWANs) have appeared, offering different solutions that meet the IoT applications requirements mentioned before. Among the existing LPWAN solutions, LoRaWAN has stood out for receiving significant attention from both industry and academia in recent years. Although LoRaWAN offers a compelling combination of long-range and low-power consumption data transmissions, it still faces several challenges in terms of reliability and scalability. However, due to its open-source nature and the flexibility of the modulation scheme it is based on (Long Range (LoRa) modulation allows the adjustment of spreading factors and transmit power), LoRaWAN also offers important possibilities for improvements. This thesis takes advantage of the appropriateness of the Reinforcement Learning (RL) algorithms for solving decision-making tasks, and use them to dynamically adjust the transmission parameters of LoRaWAN end devices. The proposed system, called RL-LoRa, shows significant improvements in terms of reliability and scalability when compared with LoRaWAN. Specifically, it decreases the average Packet Error Ratio (PER) of LoRaWAN by 15 percent, which can further increase the network scalability.