TY - GEN
T1 - Multipath-based CSI fingerprinting localization with a machine learning approach
AU - Chen, Susu
AU - Fan, Jiancun
AU - Luo, Xinmin
AU - Zhang, Ying
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/24
Y1 - 2018/12/24
N2 - In this paper, we propose a multipath-based channel state information (CSI) fingerprinting positioning scheme in outdoor environment with a machine learning approach. In this scheme, multiple distinguishable paths are exploited to extract discriminative features of one location automatically. Meanwhile, we design a hierarchical architecture to train and position in two stages which improves the accuracy of localization effectively. Experimental results show that the location can be estimated with an accuracy about one meter.
AB - In this paper, we propose a multipath-based channel state information (CSI) fingerprinting positioning scheme in outdoor environment with a machine learning approach. In this scheme, multiple distinguishable paths are exploited to extract discriminative features of one location automatically. Meanwhile, we design a hierarchical architecture to train and position in two stages which improves the accuracy of localization effectively. Experimental results show that the location can be estimated with an accuracy about one meter.
UR - https://www.scopus.com/pages/publications/85061112206
U2 - 10.1109/WIAD.2018.8588448
DO - 10.1109/WIAD.2018.8588448
M3 - 会议稿件
AN - SCOPUS:85061112206
T3 - 2018 Wireless Advanced, WiAd 2018
BT - 2018 Wireless Advanced, WiAd 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Wireless Advanced, WiAd 2018
Y2 - 26 June 2018 through 28 June 2018
ER -