Channel State Information Based Indoor Fingerprinting Localization

Rongjie Che; Honglong Chen

doi:10.3390/s23135830

Channel State Information Based Indoor Fingerprinting Localization

Sensors (Basel). 2023 Jun 22;23(13):5830. doi: 10.3390/s23135830.

Authors

Rongjie Che¹, Honglong Chen²

Affiliations

¹ Sinopec Petroleum Engineering Corporation, Dongying 257026, China.
² College of Control Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.

Abstract

Indoor localization is one of the key techniques for location-based services (LBSs), which play a significant role in applications in confined spaces, such as tunnels and mines. To achieve indoor localization in confined spaces, the channel state information (CSI) of WiFi can be selected as a feature to distinguish locations due to its fine-grained characteristics compared with the received signal strength (RSS). In this paper, two indoor localization approaches based on CSI fingerprinting were designed: amplitude-of-CSI-based indoor fingerprinting localization (AmpFi) and full-dimensional CSI-based indoor fingerprinting localization (FuFi). AmpFi adopts the amplitude of the CSI as the localization fingerprint in the offline phase, and in the online phase, the improved weighted K-nearest neighbor (IWKNN) is proposed to estimate the unknown locations. Based on AmpFi, FuFi is proposed, which considers all of the subcarriers in the MIMO system as the independent features and adopts the normalized amplitudes of the full-dimensional subcarriers as the fingerprint. AmpFi and FuFi were implemented on a commercial network interface card (NIC), where FuFi outperformed several other typical fingerprinting-based indoor localization approaches.

Keywords: IWKNN; channel state information; fingerprinting-based; full-dimensional subcarriers; indoor localization.

Grants and funding

This work was funded in part by the Shandong Provincial Natural Science Foundation, China, under Grant ZR2022YQ61, NSFC under Grants 61772551, 62111530052, the Fundamental Research Funds for the Central Universities, China, under Grant 22CX01003A-9.