Advertisement

Theoretical and Experimental Analysis of WiFi Location Fingerprint Sampling Period

  • Qin Wu
  • Hao Lin
  • Jiuzhen LiangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 501)

Abstract

Indoor positioning with smartphones is of great importance for a lot of applications and has attracted many researchers’ interests these years. Received Signal Strength (RSS) fingerprinting has been considered as an efficient method for indoor positioning. Numerous systems have been developed based on it. Location fingerprint sampling is the first step of the RSS fingerprinting method. Slow sampling speed will delay the positioning speed and will reduce the accuracy if the tracking object is moving. Theoretically, the sampling period is about one fingerprint per second. However, our experiments on some Android phones/pads show that it may even take more than 10 s to sample a fingerprint occasionally. By analyzing the Android WiFi scanning framework, it is easy to find which part of the fingerprint sampling process costs more time. After theoretically analysis and experimental measurement, we provide some suggestions on how to improve sampling speed on some practical WiFi positioning system architectures. To contribute to the research community of WiFi positioning, we make all our measurement codes and our data sets available as open source.

Keywords

Indoor positioning WiFi Location fingerprint Sampling period Android 

Notes

Acknowledgement

This work is partially supported by Blue Project of Universities in Jiangsu Province Training Young Academic Leaders Object, the six talent peaks project of Jiangsu Province (No. DZXX-028) and National Natural Science Foundation of China (No.61170121, 61202312).

References

  1. 1.
    Lam, K.Y., Ng, J.K., Wang, J.T.: A business model for personalized promotion systems on using WLAN localization and NFC techniques. In: 27th Advanced International Conference on Information Networking and Applications Workshops (WAINA), pp. 1129–1134 (2013)Google Scholar
  2. 2.
    Qi, Y., Soh, C.B., Gunawan, E., et al.: An accurate 3D UWB hyperbolic localization in indoor multipath environment using iterative taylor-series estimation. In: IEEE 77th Vehicular Technology Conference (VTC Spring), pp. 1–5 (2013)Google Scholar
  3. 3.
    Bahl, P., Padmanabhan, V.N.: RADAR: an in-building rf-based user location and tracking system. In: Proceedings of IEEE INFOCOM, pp. 775–784 (2000)Google Scholar
  4. 4.
    Youssef, M., Agrawala, A.K.: The horus wlan location determination system. In: Proceedings of ACM MobiSys, pp. 205–218 (2005)Google Scholar
  5. 5.
    Wang, H., Sen, S., Elgohary, A., et al.: No need to war-drive: unsupervised indoor localization. In: Proceedings of ACM MobiSys, pp. 197–210 (2012)Google Scholar
  6. 6.
    Laoudias, C., Constantinou, G., Constantinides, M., et al.: The airplace indoor positioning platform for android smartphones. In: IEEE 13th International Conference on Mobile Data Management (MDM), pp. 312–315 (2012)Google Scholar
  7. 7.
    Yang, Z., Wu, C., Liu, Y.: Locating in fingerprint space: wireless indoor localization with little human intervention. In: Proceedings of ACM MOBICOM, pp. 269–280 (2012)Google Scholar
  8. 8.
    Fang, S.-H., Lin, T.-N.: A dynamic system approach for radio location fingerprinting in wireless local area networks. IEEE Trans. Commun. 58(4), 1020–1025 (2010)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Laoudias, C., Constantinou, G., Constantinides, M., Nicolaou, S., Zeinalipour-Yazti, D., Panayiotou, C.G.: An online sequential extreme learning machine approach to wifi based indoor positioning. In: IEEE World Forum on Internet of Things (2014)Google Scholar
  10. 10.
    IEEE Computer Society LAN/MAN Standards Committee. Ieee standard for information technology: Part 11: Wireless lan medium access control (MAC) and physical layer (PHY) specifications (2012)Google Scholar
  11. 11.
    Ramani, I., Savage, S.: Syncscan: practical fast handoff for 802.11 infrastructure networks. In: Proceedings of IEEE INFOCOM, pp. 675–684 (2005)Google Scholar
  12. 12.
    Almulla, M., Wang, Y., Boukerche, A., et al.: A fast location-based handoff scheme for vehicular networks. In: IEEE International Conference on Communications (ICC), pp. 1464–1468 (2013)Google Scholar
  13. 13.
    Mishra, A., Shin, M., Arbaugh, W.A.: An empirical analysis of the ieee 802.11 MAC layer handoff process. ACM SIGCOMM Comput. Commun. Rev. 33(2), 93–102 (2003)CrossRefGoogle Scholar
  14. 14.
    Montavont, N., Arcia-Moret, A., Castignani, G.: On the selection of scanning parameters in IEEE 802.11 networks. In: IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), pp. 2137–2141 (2013)Google Scholar
  15. 15.
    Chen, X., Qiao, D.: Hand: Fast handoff with null dwell time for ieee 802.11 networks. In: Proceedings of IEEE INFOCOM, pp. 1–9 (2010)Google Scholar
  16. 16.
    Liu, H., Darabi, H., Banerjee, P.P., et al.: Survey of wireless indoor positioning techniques and systems. IEEE Trans. Syst. Man Cybern. 37(6), 1067–1080 (2007)CrossRefGoogle Scholar
  17. 17.
    Drane, C., Macnaughtan, M., Scott, C.: Positioning GSM telephones. IEEE Commun. Mag. 36(4), 46–54 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceJiangnan UniversityWuxiChina

Personalised recommendations