Abstract
K-nearest neighbor (kNN) is one of the most popular methods used in indoor positioning systems. The estimated position is, nevertheless, the center of the area formed by some fingerprints which have the smallest Euclidean distance, regardless of the difference between these distances. This leads to an error in the prediction process. In this paper, to improve the positioning accuracy, some variants of kNN, namely Weighted kNN (WkNN), are suggested. In addition to evaluating the quality of each method, we provide a detailed comparison of all methods together to figure out the optimal solution for the visible LED light positioning system. The obtained results show that all the proposed WkNN methods can significantly improve the positioning accuracy. However, the level of improvement is not exactly the same. In the best case, our proposed solution achieves an improvement by 100-fold compared to traditional kNN method.
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References
Chowdhury, M.Z., Hossan, M.T., Islam, A., Jang, Y.M.: A comparative survey of optical wireless technologies: architectures and applications. IEEE Access 6, 9819–9840 (2018)
Căilean, A.M., Dimian, M.: Current challenges for visible light communications usage in vehicle applications: a survey. IEEE Commun. Surv. Tutorials 19(4), 2681–2703 (2017). https://doi.org/10.1109/COMST.2017.2706940
Steendam, H.: A 3-D positioning algorithm for AOA-based VLP with an aperture-based receiver. IEEE J. Sel. Areas Commun. 36(1), 23–33 (2018). https://doi.org/10.1109/JSAC.2017.2774478
Eroglu, Y.S., Guvenc, I., Pala, N., et al.: AOA-based localization and tracking in multi-element VLC systems. In: 2015 IEEE 16th Annual Wireless and Microwave Technology Conference (WAMICON), Cocoa Beach, FL, pp. 1–5 (2015). http://10.0.4.85/WAMICON.2015.7120424
Amini, C., Taherpour, A., Khattab, T., Gazor, S.: Theoretical accuracy analysis of indoor visible light communication positioning system based on time-of-arrival. In: 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Vancouver, BC, pp. 1–5 (2016). http://10.0.4.85/CCECE.2016.7726718
Wang, T.Q., Sekercioglu, Y.A., Neild, A., Armstrong, J.: Position accuracy of time-of-arrival based ranging using visible light with application in indoor localization systems. J. Lightwave Technol. 31(20), 3302–3308 (2013). https://doi.org/10.1109/JLT.2013.2281592
Do, T.-H., Yoo, M.: TDOA-based indoor positioning using visible light. Photon Netw. Commun. 27(2), 80–88 (2014)
Wang, C., Wang, L., Chi, X., Liu, S., Shi, W., Deng, J.: The research of indoor positioning based on visible light communication. China Commun. 12(8), 85–92 (2015). https://doi.org/10.1109/CC.2015.7224709
Vongkulbhisal, J., Chantaramolee, B., Zhao, Y., Mohammed, W.S.: A fingerprinting-based indoor localization system using intensity modulation of light emitting diodes. Microw. Opt. Technol. Lett. 54(5), 1218–1227 (2012)
Van, M.T., Van Tuan, N., Son, T.T., Le-Minh, H., Burton, A.: Weighted k-nearest neighbour model for indoor VLC positioning. IET Commun. 11, 864–871 (2017). https://doi.org/10.1049/iet-com.2016.0961
Xu, M., Xia, W., Jia, Z., Zhu, Y., Shen, L.: A VLC-based 3-D indoor positioning system using fingerprinting and K-nearest neighbor. In: 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), Sydney, NSW, pp. 1–5 (2017). http://10.0.4.85/VTCSpring.2017.8108345
Komine, T., Nakagawa, M.: Fundamental analysis for visible-light communication system using LED lights. IEEE Trans. Consum. Electron. 50(1), 100–107 (2004). https://doi.org/10.1109/TCE.2004.1277847
Zhuang, Y., Hua, L., Qi, L., Yang, J., Cao, P., et al.: A survey of positioning systems using visible LED lights. IEEE Commun. Surv. Tutor. 20, 1963–1988 (2018). https://doi.org/10.1109/COMST.2018.2806558
Do, T.H., Yoo, M.: An in-depth survey of visible light communication based positioning systems. Sensors 16, 678 (2016). https://doi.org/10.3390/s16050678
Kail, G., Maechler, P., Preyss, N., Burg, A.: Robust asynchronous indoor localization using LED lighting. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, pp. 1866–1870 (2014)
Zhao, Y., et al.: Proximity report triggering threshold optimization for network-based indoor positioning. In: Proceedings of 18th International Conference on Information Fusion (Fusion), Washington, DC, USA, pp. 1061–1069 (2015)
Li, Z., Braun, T., Zhao, X., Zhao, Z., Hu, F., Liang, H.: A narrow-band indoor positioning system by fusing time and received signal strength via ensemble learning. IEEE Access 6, 9936–9950 (2018). https://doi.org/10.1109/ACCESS.2018.2794337
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This work was supported by Korea Hydro & Nuclear Power company through the project “Nuclear Innovation Center for Haeoleum Alliance”.
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Tran, H.Q., Ha, C. (2019). Comparison of Various Weighted K-Nearest Neighbor Methods for Positioning Systems Using Visible LED Lights. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science(), vol 11643. Springer, Cham. https://doi.org/10.1007/978-3-030-26763-6_57
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DOI: https://doi.org/10.1007/978-3-030-26763-6_57
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