TY - GEN
T1 - RSSI-Based Indoor Localization Using Leaky Coaxial Cable with a PNN Approach
AU - Zhu, Junjie
AU - Hou, Pengcheng
AU - Nagayama, Kenta
AU - Hou, Yafei
AU - Denno, Satoshi
N1 - Funding Information:
ACKNOWLEDGEMENT This work was supported by the JSPS KAKENHI Grand Number 20K04484 and the Telecommunications Advancement Foundation (TAF).
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper proposes a probabilistic neural network-based (PNN-based) localization method using multiple leaky coaxial cables (LCX) for indoor multipath-rich environment. LCX which can be used as antennas has been applied to wireless communication widely in recent years. Different from conventional localization methods based on time of arrival (ToA) or time difference of arrival (TDoA), we present a probabilistic neural network (PNN) approach by utilizing received signal strength indicator (RSSI) in LCX system. The proposal is aimed at the two-dimensional localization in a trajectory. We evaluate the localization performance of the PNN-based method using RSSI data from LCX. In addition, we also compare the performance of the PNN-based method over the same environment but using conventional monopole antennas. The results show the PNN-based localization method using LCX is promising and is better than that using monopole antennas.
AB - This paper proposes a probabilistic neural network-based (PNN-based) localization method using multiple leaky coaxial cables (LCX) for indoor multipath-rich environment. LCX which can be used as antennas has been applied to wireless communication widely in recent years. Different from conventional localization methods based on time of arrival (ToA) or time difference of arrival (TDoA), we present a probabilistic neural network (PNN) approach by utilizing received signal strength indicator (RSSI) in LCX system. The proposal is aimed at the two-dimensional localization in a trajectory. We evaluate the localization performance of the PNN-based method using RSSI data from LCX. In addition, we also compare the performance of the PNN-based method over the same environment but using conventional monopole antennas. The results show the PNN-based localization method using LCX is promising and is better than that using monopole antennas.
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U2 - 10.1109/GCCE53005.2021.9622078
DO - 10.1109/GCCE53005.2021.9622078
M3 - Conference contribution
AN - SCOPUS:85123504062
T3 - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
SP - 220
EP - 221
BT - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Y2 - 12 October 2021 through 15 October 2021
ER -