Analysis of Received Signal Strength Quantization in Fingerprinting Localization

Abstract
In recent times, Received Signal Strength (RSS)-based Wi-Fi fingerprinting localization has become one of the most promising techniques for indoor localization. The primary aim of RSS is to check the quality of the signal to determine the coverage and the quality of service. Therefore, fine-resolution RSS is needed, which is generally expressed by 1-dBm granularity. However, we found that, for fingerprinting localization, fine-granular RSS is unnecessary. A coarse-granular RSS can yield the same positioning accuracy. In this paper, we propose quantization for only the effective portion of the signal strength for fingerprinting localization. We found that, if a quantized RSS fingerprint can carry the major characteristics of a radio environment, it is sufficient for localization. Five publicly open fingerprinting databases with four different quantization strategies were used to evaluate the study. The proposed method can help to simplify the hardware configuration, enhance security, and save approximately 40–60% storage space and data traffic.
Main Authors
Format
Articles Research article
Published
2020
Series
Subjects
Publication in research information system
Publisher
MDPI
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202006255099Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
1424-8220
DOI
https://doi.org/10.3390/s20113203
Language
English
Published in
Sensors
Citation
  • Khandker, S., Torres-Sospedra, J., & Ristaniemi, T. (2020). Analysis of Received Signal Strength Quantization in Fingerprinting Localization. Sensors, 20(11), Article 3203. https://doi.org/10.3390/s20113203
License
CC BY 4.0Open Access
Additional information about funding
Syed Khandker expresses his warm thanks to the Riitta and Jorma J. Takanen foundation for its financial support. Joaquín Torres-Sospedra is funded by the Torres-Quevedo Programme of the Spanish government, Grant No. PTQ2018-009981 (Project INSIGNIA).
Copyright© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

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