Modelos de pérdidas de propagación en redes de internet de las cosas: una mirada desde el aprendizaje de máquina
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2020-09-24Autor
González-Palacio, Mauricio
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A common task when planning a wireless network is the analysis of propagation losses between two transceivers. Different models, from theoretical and empirical natures are proposed in the literature; however, some of them are difficult to be parametrized, and others are thought for very specific scenarios. In this work, we perform a comparison between the simplified path loss lognormal shadow fading model versus a Support Vector Machine (SVM) regressor in a WLAN network. Results show that SVMs are more accurate predicting shadow fading effects
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