Analysis of Received Signal Strength Quantization in Fingerprinting Localization
Abstract
:1. Introduction and Motivation
- We thoroughly investigated the usefulness of reduction bit quantization considering why it can perform the same positioning accuracy as that of traditional RSS.
- Reduction bit quantization also reduces the data size. We investigated how much disk space and network traffic can be saved if reduced-bit quantization were used.
- We analyzed the RSS quantization effect on five different publicly open fingerprinting databases. Our findings are coherent and reflect all the real-life scenarios.
2. Related Work
3. Materials and Methods
3.1. Database Description
3.1.1. UJIIndoorLoc Database
3.1.2. TUT Database
3.1.3. Minho Database
3.1.4. Mannheim Database
3.1.5. Library Database
3.2. Facts in the Databases
3.3. Method
3.3.1. Quantization
3.3.2. Quantizer
3.3.3. Reason for the Same Positioning Performance by the Traditional and Quantized RSS Fingerprint
4. Experiment and Results
4.1. Experiment Setup
4.2. Positioning Performance
4.3. Floor Detection Performance
5. Discussion
5.1. Simplification
5.2. Enhancing Security
5.3. Less Storage
5.4. Less Traffic
Observation
- The effective range of RSS is from −30 to −103 dBm for fingerprinting localization. Any value beyond this range can be considered as noise.
- In Wi-Fi fingerprinting localization, 4-bit quantization is enough.
- To have good quality fingerprints, a well planned, organized Wi-Fi network is desirable.
- Sometimes, the number of APs per fingerprint in the crowd-sourced database is very high. RSS from the reliable or known AP should be used.
- Hot-spot or mobile AP can contribute a significant amount of noise. Data from those should be ignored.
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Database | Coverage () | Number of Training Sample | Number of Testing Sample | Number of AP | Positioning (m) Accuracy | Floor Detection (%) |
---|---|---|---|---|---|---|
UJIIndoorLoc | 108,703 | 19,936 | 1111 | 520 | 7.74 | 90.28 |
TUT | 22,570 | 697 | 3951 | 991 | 9.39 | 91.75 |
Minho | 1000 | 4973 | 810 | 11 | 4.7 | NA |
Mannheim | 312 | 14,300 | 5060 | 28 | 3.01 | NA |
Library | 308 | 576 | 3120 | 620 | 2.34 | 100 |
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Khandker, S.; Torres-Sospedra, J.; Ristaniemi, T. Analysis of Received Signal Strength Quantization in Fingerprinting Localization. Sensors 2020, 20, 3203. https://doi.org/10.3390/s20113203
Khandker S, Torres-Sospedra J, Ristaniemi T. Analysis of Received Signal Strength Quantization in Fingerprinting Localization. Sensors. 2020; 20(11):3203. https://doi.org/10.3390/s20113203
Chicago/Turabian StyleKhandker, Syed, Joaquín Torres-Sospedra, and Tapani Ristaniemi. 2020. "Analysis of Received Signal Strength Quantization in Fingerprinting Localization" Sensors 20, no. 11: 3203. https://doi.org/10.3390/s20113203