Francesco Xia
Artificial Neural Networks applied to Quality Prediction of a Wi-Fi link.
Rel. Stefano Scanzio, Gianluca Cena. Politecnico di Torino, Master of science program in Computer Engineering, 2021
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Abstract
Artificial intelligence, and in particular machine learning, is one of the enabling technologies of Industry 4.0. It is successfully used in many application contexts and with different scopes, including, for example, in preventive maintenance, automated inspections, and optimization of communication processes. This thesis aims to evaluate whether and to what extent artificial neural networks (ANN), a particular application of machine learning, can be profitably used to predict the quality of a Wi-Fi channel in terms of frame delivery ratio. Specifically, we defined two approaches for this purpose: one based on ANNs and the other based on a more traditional approach that mimics current adaptive solutions.
Then we tested the ability of each solution to predict the values of a target, which represents the state of a channel over time
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