Advertisement

Signal Dragging: Effects of Terminal Movement on War-Driving in CDMA/WCDMA Networks

  • Daehyung Jo
  • Jeongkeun Lee
  • Semun Lee
  • Taejoon Ha
  • Taekyoung Kwon
  • Yanghee Choi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4718)

Abstract

In cellular networks, the signal pattern reported by a mobile terminal has been the major source for localization. In this paper we show how the signal pattern is affected by the terminal movement such as the speed and the moving direction in CDMA/WCDMA networks. When the mobile terminal is moving, its signal pattern tends to contain more signals from base stations positioned opposite of the terminal’s moving direction than signals from base stations positioned in the forward. We call this phenomenon “signal dragging”. If the signal dragging prevails, it naturally provides a useful hint for figuring out the movement of a terminal, e.g., direction. We also show that the accuracy of the localization algorithm based on pattern matching varies greatly depending on the terminal movement. Based on these experimental results in commercial networks we suggest the practical data collection procedure, e.g., the war-driving, should consider the terminal movement. Otherwise the use of war-driving data can be harmful.

Keywords

Pattern Match Signal Pattern Code Division Multiple Access Mobile Terminal Pilot Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chen, M.Y., et al.: Practical Metropolitan-Scale Positioning for GSM Phones. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Sohn, T., et al.: Mobility Detection Using Everyday GSM Trace. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Anderson, I., Muller, H.: Context Awareness via GSM Signal Strength Fluctuation. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 27–31. Springer, Heidelberg (2006)Google Scholar
  4. 4.
    Krumm, J., Horvitz, E.: LOCADIO: Inferring Motion and Location from Wi-Fi Signal Strengths. In: Proceedings of Mobiquitous (2004)Google Scholar
  5. 5.
    Kim, M., et al.: Risks of using AP locations discovered through war driving. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    LaMarca, A., et al.: Place Lab: Device Positioning Using Radio Beacons in the Wild. In: Hutter, D., Ullmann, M. (eds.) SPC 2005. LNCS, vol. 3450, Springer, Heidelberg (2005)Google Scholar
  7. 7.
    Zhu, J., et al.: Indoor/outdoor location of cellular handsets based on received signal strength. Electronics Letters,  41(1) (2005)Google Scholar
  8. 8.
    Lee, J., et al.: Distributed and energy-efficient target localization and tracking in wireless sensor networks. Elsevier Computer Communications 29(13-14), 2494–2505 (2006)Google Scholar
  9. 9.
    Lee, S., et al.: Use of AGPS call data records for non-GPS terminal positioning in cellular networks. In: Proceedings of WINSYS (2006)Google Scholar
  10. 10.
    Bahl, P., Padmanabhan, V.N.: RADAR: An In-Building RF-Based User Location and Tracking System. In: Proceedings of IEEE INFOCOM, vol. 2, pp. 775–784 (2000)Google Scholar
  11. 11.
    Tanner, R., Woodard, J.: WCDMA Requirements and Practical Design. Wiley, Chichester (2004)Google Scholar
  12. 12.
    3GPP TS 25.221 V7.2.0. Physical channels and mapping of transport channels onto physical channels (TDD) (2007)Google Scholar
  13. 13.
    3GPP TS 25.304 V7.1.0. User Equipment (UE) procedures in idle mode and procedures for cell reselection in connected mode (2006)Google Scholar
  14. 14.
    Vijay, K.: IS-95 CDMA and cdma2000 Cellular/PCS Systems Implementation. Prentice Hall, Englewood Cliffs (2000)Google Scholar
  15. 15.
    3GPP2 C.S0002-D v2.0. Physical Layer Standard for cdma2000 Spread Spectrum Systems (2005)Google Scholar
  16. 16.
    3GPP2 C.S0005-D v2.0. Upper Layer (Layer 3) Signaling Standard for cdma2000 Spread Spectrum Systems (2005)Google Scholar
  17. 17.
    Arulampalam, S., Maskell, S., Gordon, N., Clapp, T.: A Tutorial on Particle Filters for Online Non-Linear/Non-Gaussian Bayesian Tracking. IEEE Transactions on Signal Processing 50(2), 174–188 (2002)CrossRefGoogle Scholar
  18. 18.
    Hightower, J., Borriello, G.: Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study. In: Davies, N., Mynatt, E.D., Siio, I. (eds.) UbiComp 2004. LNCS, vol. 3205, Springer, Heidelberg (2004)Google Scholar
  19. 19.
    Gustafsson, F., et al.: Particle Filters for Positioning, Navigation and Tracking. IEEE Transactions on Signal Processing 50(2), 425–437 (2002)CrossRefGoogle Scholar
  20. 20.
    Priyantha, N.B., et al.: The cricket location-support system. In: Proceedings of Mobicom, pp. 32–43 (2000)Google Scholar
  21. 21.
    Cheng, Y.C., et al.: Accuracy characterization for metropolitan-scale Wi-Fi localization. In: Proceedings of MobiSys (2005)Google Scholar
  22. 22.
    Stage 2 functional specification of User Equipment (UE) positioning in UTRAN (Release 4). 3GPPGoogle Scholar
  23. 23.
    Zhao, Y.: Standardization of Mobile Phone Positioning for 3G Systems. In: IEEE Communications Magazine (July 2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Daehyung Jo
    • 1
  • Jeongkeun Lee
    • 1
  • Semun Lee
    • 1
  • Taejoon Ha
    • 2
  • Taekyoung Kwon
    • 1
  • Yanghee Choi
    • 1
  1. 1.School of Computer Science and Engineering, Seoul National University 
  2. 2.Radiant Technologies, Inc. 

Personalised recommendations