Skip to main content
SpringerLink
Log in

A probabilistic approach to determine mobile station location with application in cellular networks

  • Published:
annals of telecommunications - annales des télécommunications Aims and scope Submit manuscript

Abstract

A probabilistic approach to the mobile station location problem is analyzed, and an algorithm that implements such an approach is presented. Information about the mobile station location is collected in the form of two-dimensional probability density functions provided from various sources. Combining the probability density functions into a joined probability density function is addressed. To provide computational efficiency, a method to limit the space of a possible location of the mobile station to a rectangular region of the minimal size is presented. Discretization of space is performed next, reducing the probability density functions to matrices of probabilities. The algorithm for combining the probability density functions is adjusted for an application with the matrices of probabilities. To reduce the computational burden further, probability density functions of the exclusion type, taking only two values, zero and nonzero, are introduced, providing savings in storage space and computational time. Information about the timing advance parameter value and the received signal level are interpreted by probability density functions of the exclusion type. Application of the algorithm is illustrated by two sets of measurements performed in an urban and a suburban region.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Drane C, Macnaughtan M, Scott G (1998) Positioning GSM telephones. IEEE Commun Mag 36(4):46–54, 59

    Article  Google Scholar 

  2. FCC (2001) Fact Sheet—FCC Wireless 911 Requirements. FCC, Washington, D.C.

    Google Scholar 

  3. Sun G, Chen J, Guo W, Liu KJR (2005) Signal processing techniques in network-aided positioning—a survey of state-of-the-art positioning designs. IEEE Signal Process Mag 22(4):12–23

    Article  Google Scholar 

  4. Reed JH, Krizman KJ, Woerner BD, Rappaport TS (1998) An overview of the challenges and progress in meeting the E 911 requirement for location service. IEEE Commun Mag 36(4):30–37, 59

    Article  Google Scholar 

  5. Simić M, Pejović P (2009) A comparison of three methods to determine mobile station location in cellular communication systems. Eur Trans Telecommun. doi:10.1002/ett.1333

    Google Scholar 

  6. Borkowski JM (2008) On applicable cellular positioning for UMTS. Doctor of technology dissertation, institute of communication engineering, Tampere Technology University

  7. BIPM, IEC, IFCC, ISO, IUPAC, IUPAP, and OIML (1993) Guide to the expression of uncertainty in measurement. International Organization for Standardization, Geneva

    Google Scholar 

  8. Küpper A (2005) Location-based services: fundamentals and operation. Wiley, Chichester

    Book  Google Scholar 

  9. Gwon Y, Jain R, Kawahara T (2004) Robust indoor location estimation of stationary and mobile users. In: Proceedings of twenty–third annual joint conference of the IEEE computer and communications societies. (Infocom 2004), vol 2. IEEE, Hong Kong, pp 1032–1043

    Google Scholar 

  10. Manolakis DE (1996) Efficient solution and performance analysis of 3-D position estimation by trilateration. IEEE Trans Aerosp Electron Syst 32(4):1239–1248

    Article  Google Scholar 

  11. Nishida Y, Kitamura K, Hori T, Nishitani A, Kanade T, Mizoguchi H (2004) Quick realization of function for detecting human activity events by ultrasonic 3D tag and stereo vision. In: Proceedings of the second IEEE annual conference on pervasive computing and communications, (PERCOM’04), pp 43–54

  12. Savvides A, Han CC, Strivastava MB (2001) Dynamic fine-grained localization in ad-hoc networks of sensors. In: Proceedings of 7th international conference on mobile computing and networking, pp 166–179

  13. Sugano M, Kawazoe T, Ohta Y, Murata M (2006) Indoor localization system using RSSI measurement of wireless sensor network based on ZigBee standard. In: Proceedings of IASTED international conference on wireless sensor networks, (WSN 2006), Banff

  14. Rice A, Harle R (2005) Evaluating lateration-based positioning algorithms for fine-grained tracking. In: Proceedings of the 2005 joint workshop on foundations of mobile computing, DIALM-POMC ’05

  15. Wendlandt K, Ouhmich A, Angermann M, Robertson P (2002) Implementation of soft location on mobile devices. In: International symposium on indoor localisation and position finding, DGON

  16. Fox D, Hightower J, Kauz H, Liao L, Patterson D (2003) Bayesian techniques for location estimation. In: Proceedings UBIComp Workshop, pp 16–18

  17. Roos T, Myllymäki P, Tirri H (2002) A statistical modeling approach to location estimation. IEEE Trans Mobile Comput 1(1):59–69

    Article  Google Scholar 

  18. Kontkanen P, Myllymäki P, Roos T, Tirri H, Valtonen K, Wettig H (2004) Topics in probabilistic location estimation in wireless networks. In: 15th IEEE International symposium on personal, indoor and mobile radio communications, (PIMRC 2004), vol 2, pp 1052–1056, 5–8 September 2004

  19. Chu KMK, Leung KRPH, Ng JKY, Li CH (2004) Locating mobile stations with statistical directional propagation model. In: Proceedings of 18th international conference on advanced information networking and applications, (AINA 2004), Fukuoka, pp 230–235, 29–31 March 2004

  20. Chu KMK, Ng JKY, Leung KRPH (2006) A new approach for locating mobile stations under the statistical directional propagation model. In: Proceedings of the 20th international conference on advanced information networking and applications, (AINA 2006), vol 1, pp 932–940

  21. Papoulis A (1991) Probability, random variables and stochastic processes. McGraw Hill, New York

    Google Scholar 

  22. 3GPP (2005) 3GPP TS 05.08, release 1999 (v8.23.0), Radio subsystem link control. http://www.3gpp.org/ftp/Specs/archive/05 series/05.08

  23. Buchanan W, Munoz J, Manson R, Raja K (2004) Analysis and migration of location-finding methods for GSM and 3G networks. In: Proceedings of 5th IEE international conference on 3G mobile communication technologies, pp 352–358

  24. Seidel SY, Rappaport TS, Jain S, Lord ML, Singh R (1991) Path loss, scattering, and multipath delay statistics in four European cities for digital cellular and microcellular radiotelephone. IEEE Trans Veh Technol 40(4):721–730

    Article  Google Scholar 

  25. Rappaport TS (2001) Wireless communications principles and practice, 2nd edn. Prentice Hall, Englewood Cliffs

    Google Scholar 

  26. Sklar B (1997) Rayleigh fading channels in mobile digital communication systems, part I: characterization. IEEE Commun Mag 35(7):90–100

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Professor Miroslav L. Dukić of the School of Electrical Engineering, University of Belgrade, for suggesting the research topic and for his valuable comments on the manuscript.

Author information

Authors and Affiliations

  1. School of Electrical Engineering, University of Belgrade, Belgrade, Serbia

    Mirjana I. Simić & Predrag V. Pejović

Authors
  1. Mirjana I. Simić
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Predrag V. Pejović
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Predrag V. Pejović.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Simić, M.I., Pejović, P.V. A probabilistic approach to determine mobile station location with application in cellular networks. Ann. Telecommun. 64, 639 (2009). https://doi.org/10.1007/s12243-009-0113-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12243-009-0113-2

Keywords

Search

Navigation