Skip to main content
Log in

Three-dimensional Positioning in 3GPP Wireless Networks with Small Cells with Barometric Pressure Sensor

  • Published:
Journal of Signal Processing Systems Aims and scope Submit manuscript

Abstract

The US federal communications commission announced new location accuracy requirements for emergency calls. To examine these requirements, we first establish a 3GPP system-level simulator and calibrate its performance for radio access technology-dependent techniques. After considering the 3D channel model, we test and conclude that existing technologies fail to satisfy the indoor vertical accuracy requirement. Therefore, we propose a two-step least-square estimator that adopts a barometric pressure sensor (BPS) to measure the altitude above sea level. The use of BPS improves accuracy for both vertical and horizontal aspects. The positioning performance of both outdoor and indoor user equipment (UE) is simulated, and the results demonstrate that 67% of UE can be localized within 18-m horizontal and 3-m vertical accuracy with 10 small cells. The improved vertical accuracy obtained by the proposed method can be beneficial to UAV communication.

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

Access this article

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

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13

References

  1. Commission, F.C., & et al. (2015). Report and order and second further notice of proposed rulemaking. Amendment of the Commission’s Rules with Regard to Commercial Operations in the, pp. 3550–3650.

  2. Baker, M., Sesia, S, & Toufik, I. (2011). LTE: The UMTS Long Term Evolution From Theory to Practice.

  3. 3GPP TR37.857 v1.0.1. (2015). Study on Indoor Positioning Enhancements for UTRA and LTE (Release 13), 3GPP.

  4. Kangas, A., Siomina, I., & Wigren, T. (2011). Positioning in LTE, Handbook of Position Location: Theory, Practice, and Advances, pp. 1081–1127.

  5. RP-193237. (2019). New SID on NR Positioning Enhancements, 3GPP.

  6. 3GPP TR 38.855 V2.1.0. (2019). Study on NR Positioning Support (Release 16), 3GPP.

  7. Haque, F., Dehghanian, V., Fapojuwo, A.O., & Nielsen, J. (2018). A sensor fusion-based framework for floor localization. IEEE Sensors Journal, 19(2), 623–631.

    Article  Google Scholar 

  8. Strozzi, N., Parisi, F., & Ferrari, G. (2016). A multifloor hybrid inertial/barometric navigation system. In IEEE International conference on indoor positioning and indoor navigation (IPIN) (pp. 1–5).

  9. Ehrlich, C.R., Blankenbach, J., & Sieprath, A. (2016). Towards a robust smartphone-based 2.5D pedestrian localization. In IEEE International conference on indoor positioning and indoor navigation (IPIN) (pp. 1–8).

  10. Bo, L., Xiaohui, L., & Wenli, W. (2017). Research on barometric altimeter aiding GPS arithmetic in challenge environment. In 2017 13th IEEE international conference on electronic measurement & instruments (ICEMI) (pp. 581–585).

  11. 3GPP TR36.873 v12.2.0. (2015). Study on 3D Channel Model for LTE (Release 12), 3GPP.

  12. Mondal, B., Thomas, T.A., Visotsky, E., Vook, F.W., Ghosh, A., Nam, Y.H., Li, Y., Zhang, J., Zhang, M., Luo, Q., Kakishima, Y., & Kitao, K. (2015). 3D Channel model in 3GPP. IEEE Communications Magazine, 53(3), 16–23.

    Article  Google Scholar 

  13. Foy, W.H. (1976). Position-location solutions by taylor-series estimation. IEEE Transactions on Aerospace and Electronic Systems, 2, 187–194.

    Article  Google Scholar 

  14. Chan, Y.T., & Ho, K.C. (1994). A simple and efficient estimator for hyperbolic location. IEEE Transactions on Signal Processing, 42(8), 1905–1915.

    Article  Google Scholar 

  15. Ademaj, F., Taranetz, M., & Rupp, M. (2016). 3GPP 3D MIMO channel model: a holistic implementation guideline for open source simulation tools. EURASIP Journal on Wireless Communications and Networking, 2016(1), 1–14.

    Article  Google Scholar 

  16. Kammoun, A., Khanfir, H., Altman, Z., Debbah, M., & Kamoun, M. (2014). Preliminary results on 3D channel modeling: from theory to standardization. IEEE Journal on Selected Areas in Communications, 32(6), 1219–1229.

    Article  Google Scholar 

  17. Zekavat, R., & Buehrer, R.M. (2012). Channel modeling and its impact on localization, (pp. 105–135). New York: Wiley-IEEE Press.

    Google Scholar 

  18. Fischer, S. (2014). Observed time difference of arrival (OTDOA) positioning in 3GPP LTE, Qualcomm White Pap.

  19. Shen, Y., Wymeersch, H., & Win, M.Z. (2010). Fundamental limits of wideband localization—part ii: cooperative networks. IEEE Transactions on Information Theory, 56(10), 4981–5000.

    Article  MathSciNet  Google Scholar 

  20. Van Trees, H.L. (2004). Detection, estimation, and modulation theory, part I: detection, estimation, and linear modulation theory. New York: Wiley.

    MATH  Google Scholar 

  21. Tseng, P.-H., & Feng, K.-T. (2012). Geometry-assisted localization algorithms for wireless networks. IEEE Transactions on Mobile Computing, 12(4), 774–789.

    Article  Google Scholar 

  22. Rydén, H., Razavi, S.M., Gunnarsson, F., Kim, S.M., Wang, M., Blankenship, Y., Grövlen, A., & Busin, A. (2015). Baseline performance of LTE positioning in 3GPP 3D MIMO indoor user scenarios. In 2015 international conference on location and GNSS (ICL-GNSS) (pp. 1–6).

  23. FOY, W.H. (1976). Position-Location Solutions by Taylor-Series estimation. IEEE Transactions on Aerospace and Electronic Systems, AES-12(2), 187–194.

    Article  Google Scholar 

  24. Shen, G., Zetik, R., & Thoma, R.S. (2008). Performance comparison of TOA and TDOA based location estimation algorithms in LOS environment. In 5th workshop on positioning, navigation and communication, 2008. WPNC 2008 (pp. 71–78).

  25. 3GPP TR 36.819 V11.2.0. (2013). Coordinated Multi-point Operation for LTE Physical Layer Aspects (Release 11), 3GPP.

  26. McDermott, K.P. (2015). On the improvement of positioning in lte with collaboration and pressure sensors. Master’s thesis, Virginia Tech.

Download references

Acknowledgments

This work was mainly supported by the University System of Taipei Joint Research Program under Grant USTP-NTUT-NTPU-104-01 and USTP-NTUT-NTPU-105-02. This work was supported in part by the Ministry of Science and Technology of Taiwan under Grant 107-2221-E- 027-040-MY2 and 109-2221-E-027-089-, and the Technological University Paradigms.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Po-Hsuan Tseng.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shieh, SL., Tang, CH. & Tseng, PH. Three-dimensional Positioning in 3GPP Wireless Networks with Small Cells with Barometric Pressure Sensor. J Sign Process Syst 92, 1407–1420 (2020). https://doi.org/10.1007/s11265-020-01566-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11265-020-01566-7

Keywords

Navigation