LOS/NLOS Classification Using Scenario-Dependent Unsupervised Machine Learning

Anil Kirmaz,Diomidis S. Michalopoulos,Irina Balan,Wolfgang Gerstacker

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)（2021）

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摘要

Location information is essential for a wide range of applications requiring, for example, highly accurate positioning information such as industrial automation, autonomous driving, inbound logistics and augmented reality. One of the major error sources in positioning is non-line-of-sight (NLOS) propagation while a line-of-sight (LOS) propagation is anticipated. Therefore, classifying positioning ...

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关键词

Performance evaluation,Machine learning,Position measurement,Feature extraction,Distance measurement,Reliability,Channel models

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