Muloc: Multi-scale combination mask indoor localization network for WiFi based on channel state information

With the popularization of sensor technology, researchers extract Channel State Information (CSI) from WiFi, which reflects the movement of family members by observing changes in signal transmission in residences. However, WiFi signals are still affected by multipath effects in residences. Therefore, we construct a multi-scale CSI combination mask matrix between adjacent scales based on the ternary closure. Next, we propose a competitive localization network based on aggregated affinity propagation algorithm. Experiments have been conducted to demonstrate that the proposed algorithm achieves significant improvement compared to other classical algorithms in the indoor environment.

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Publication Details

Journal
ICT Express
Published
2025-04-25
DOI
https://doi.org/10.1016/j.icte.2025.04.005
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Muloc: Multi-scale combination mask indoor localization network for WiFi based on channel state information

Zhiao Cao, Haoyang Qi, Lanfeng Li, Xin Song et al.
ICT Express
Indoor and Outdoor Localization Technologies
article

Muloc: Multi-scale combination mask indoor localization network for WiFi based on channel state information

Zhiao Cao, Haoyang Qi, Lanfeng Li, Xin Song, Yuqi Zhang
article en

Abstract

With the popularization of sensor technology, researchers extract Channel State Information (CSI) from WiFi, which reflects the movement of family members by observing changes in signal transmission in residences. However, WiFi signals are still affected by multipath effects in residences. Therefore, we construct a multi-scale CSI combination mask matrix between adjacent scales based on the ternary closure. Next, we propose a competitive localization network based on aggregated affinity propagation algorithm. Experiments have been conducted to demonstrate that the proposed algorithm achieves significant improvement compared to other classical algorithms in the indoor environment.

ICT ExpressVol. 11(3)
Northeastern University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hebei Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 93%
Indoor and Outdoor Localization Technologies
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