BiLoc: Bi-Modal Deep Learning for Indoor Localization With Commodity 5GHz WiFi

BiLoc: Bi-Modal Deep Learning for Indoor Localization With Commodity 5GHz WiFi

In this paper, we study fingerprinting-based indoor localization in commodity 5-GHz WiFi networks. We first theoretically and experimentally validate three hypotheses on the channel state information (CSI) data of 5-GHz OFDM channels. We then propose a system termed BiLoc, which uses bi-modality dee...

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Bibliographic Details
Main Authors: Xuyu Wang, Lingjun Gao, Shiwen Mao
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Indoor localization
fingerprinting
deep learning
5GHz commodity WiFi
channel state information
bi-modality fingerprinting
Online Access:https://ieeexplore.ieee.org/document/7888438/

Internet

https://ieeexplore.ieee.org/document/7888438/

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