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New indoor positioning technique using spectral data compression based on VLC for performance improvement

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Abstract

Recent developments in the fields of Smart Phones and Wireless Communication Technologies such as Wi-Fi, cellular networks, Bluetooth and VLC have made possible to realize Indoor Positioning System with a suitable accuracy. Fingerprinting based on Received Signal Strength (RSS) measurements is commonly the most popular method of localization because of its high accuracy compared to other methods. It does not require line-of-sight measurements of transmitters TXs, RSS-based Fingerprinting localization usually consists of two main phases: offline (training) and online (estimation). The database sizes grow rapidly as the coverage areas and the number of LEDs increases. In this paper, an improvement over traditional RSS-based fingerprinting localization is proposed by reducing the database sizes in both training and estimation phases. The reduction is based on a concept of compressed RSS images, which allows through an astute 2-D frequency analysis, only a fraction of the transform-domain components need to be stored and transferred to the receivers. The proposed localization method reduces the total number of fingerprint reference points RPs over the localization space; thus, minimizing both the time required for reading visible light signals and the number of reference points needed during the fingerprinting training process, which eventually makes the process less time-consuming, hence less energy-consuming. Moreover, the proposed system is able to provide results close to that given by the traditional RSS-based fingerprinting approach, with a similar localization estimation error and an important reduction in the database sizes.

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Acknowledgements

This work is supported by the Ministry of Higher Education and Scientific Research of Algeria, as part of research project (PRFU N°, A10N01UN240120180001). We would like to thank Pr. Khettabi Riad and Dr. Boulsina Fayçal for helping in the correction of English language.

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Authors and Affiliations

  1. LABCAV Laboratory, Université 8 Mai 1945 Guelma, Guelma, Algeria

    Ameur Chaabna

  2. LGEG Laboratory, Université 8 Mai 1945 Guelma, B.P 401, 24000, Guelma, Algeria

    Abdesselam Babouri

  3. Institut Supérieur d’Electronique de Paris (ISEP), Paris, France

    Xun Zhang & Chuanxi Huang

  4. LT Laboratory, Université 8 Mai 1945 Guelma , Guelma, Algeria

    Halim Chouabia

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  1. Ameur Chaabna
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  2. Abdesselam Babouri
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  3. Xun Zhang
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  4. Chuanxi Huang
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  5. Halim Chouabia
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Correspondence to Abdesselam Babouri.

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Chaabna, A., Babouri, A., Zhang, X. et al. New indoor positioning technique using spectral data compression based on VLC for performance improvement. Opt Quant Electron 52, 343 (2020). https://doi.org/10.1007/s11082-020-02452-z

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