ICASSP 2016accepted0 citations
Channel learning in indoor localization
Abstract
This work addresses the fundamental issue of online channel learning in indoor localization systems. We describe a novel algorithm for unsupervised channel learning where the path loss exponent in the Non-Line-Of-Sight (NLOS) region is adapted online while positioning. The algorithm has scalable complexity and is shown to provide significant improvement over non-adaptive systems.
BibTeX
@inproceedings{icassp2016_channellearningi,
title = {Channel learning in indoor localization},
author = {Mohamed F. Mansour},
booktitle = {ICASSP 2016},
year = {2016}
}