A Comparative Study of Machine-Learning Indoor Localization Using FM and DVB-T Signals in Real Testbed Environments
Published: Jun 1, 2017
Abstract
Wireless indoor localization is a key technology for the future Internet of things (IoT) paradigm. In this paper, we perform an experimental comparative study of machine learning-based localization schemes, such as k-nearest neighbor (k-NN) and variants of support vector machine (SVM), based on the received signal strength (RSS) measurements of the ambient frequency modulation (FM) and digital video broadcasting- terrestrial (DVB-T) signals in...
Paper Details
Title
A Comparative Study of Machine-Learning Indoor Localization Using FM and DVB-T Signals in Real Testbed Environments
Published Date
Jun 1, 2017
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