Advertisement

Wireless Personal Communications

, Volume 102, Issue 1, pp 583–597 | Cite as

Novel Multi-room Multi-obstacle Indoor Propagation Model for Wireless Networks

  • Marija Malnar
  • Nenad Jevtic
Article
  • 47 Downloads

Abstract

In this paper a new propagation model is proposed for use in complex indoor environments. The model was tested in the frequency range of 2.4 GHz in the environment with long hallways where the effect of guided waves may occur. The comparison with measurements confirmed that proposed model can be effectively used in such environments.

Keywords

Indoor Radio propagation model Parameter estimation WLAN Guided waves 

Notes

Acknowledgements

This research is supported by the Serbian Ministry of Science and Technological Development Projects Numbers TR320025 and TR36047. The authors would like to thank professors Natasa Neskovic and Aleksandar Neskovic from School of Electrical Engineering, University of Belgrade for all the help and advices.

References

  1. 1.
    Neskovic, A., Neskovic, N., & Paunovic, G. (2000). Modern approaches in modeling of mobile radio systems propagation environment. IEEE Communications Surveys & Tutorials, 3(3), 2–12.CrossRefGoogle Scholar
  2. 2.
    Zhang, J., & De la Roche, G. (2010). Femtocells: Technologies and deployment (p. 328). New York: Wiley.CrossRefGoogle Scholar
  3. 3.
    Legendre, J. F., Marsault, T., & Ollivier, T. (2014). Fast 3D raytracing used for predicting TEMPEST classification. Microwave and Optical Technology Letters, 56, 519–523.CrossRefGoogle Scholar
  4. 4.
    Mohammed, Y. E., Abdallah, A. S., & Liu, Y. A. (2003). Characterization of indoor penetration loss at ISM band. In Proceedings of Asia-Pacific conference on environmental electromagnetic CEEM’ 2003, Hangzhou, China, 7993387.Google Scholar
  5. 5.
    Cherukuri, J. (2004). Comparative study of stochastic indoor propagation models. Technical report, The University of North Carolina at Charlotte, 2004.Google Scholar
  6. 6.
    Katulski, R. J., & Lipka, A. (2007). Methodology of radio signal power distribution modeling for WLAN networks. In Proceedings of EUROCON 2007 the international conference on computer as a tool, Warsaw, Poland, 9810560.Google Scholar
  7. 7.
    Žarković, J., Stojković, P., & Nešković, N. (2011). 3D statistički propagacioni model za indoor radio pokrivanje u WLAN mrežama. In Proceedings of telecommunications forum TELFOR 2011, Belgrade, Serbia (pp. 461–464).Google Scholar
  8. 8.
    Seidel, S., & Rappaport, T. (1992). 914 MHz path loss prediction models for indoor wireless communications in multifloored buildings. IEEE Transactions on Antennas and Propagation, 40(2), 207–217.CrossRefGoogle Scholar
  9. 9.
    Further advancements for E-UTRA (physical layer aspects). 3GPP TR 36.814 v9.0.0 2010 Tech. Rep. 4.Google Scholar
  10. 10.
    Kyösti, P. et al. (2008). IST-4-027756 WINNER II D1.1.2 V1.2 WINNER II Channel Models.Google Scholar
  11. 11.
    Erceg, V. et al. (2004). TGn channel Models IEEE P802.11WLANs, Technical Reports.Google Scholar
  12. 12.
    Zhao, X., Suiyan, G., & Coulibaly, B. M. (2013). Path-loss model including los-nlos transition regions for indoor corridors at 5 GHz. IEEE Antennas and Propagation Magazine, 55, 217–223.CrossRefGoogle Scholar
  13. 13.
    Valcarce, A., & Zhang, J. (2010). Empirical indoor-to-outdoor propagation model for residential areas at 0.9–3.5 GHz. IEEE Antennas Wireless Propag Lett, 9, 682–685.CrossRefGoogle Scholar
  14. 14.
    Degli-Esposti, V., Falciasecca, G., Fuschini, F., & Vitucci, E. M. (2013). A meaningful indoor path-loss formula. IEEE Antennas and Wireless Propagation Letters, 12, 872–875.CrossRefGoogle Scholar
  15. 15.
    Zyoud, A., Habaebi, M., & Islam, R. (2016). Parameterized indoor propagation model for mobile communication links. Microwave and Optical Technology Letters, 58(4), 823–826.CrossRefGoogle Scholar
  16. 16.
    Lee, D. J. Y., & Lee, W. C. Y. (2000). Propagation prediction in and through buildings. IEEE Transactions on Vehicular Technology, 49(5), 1529–1533.CrossRefGoogle Scholar
  17. 17.
    Han, S., Gong, Z., Meng, W., & Li, C. (2015). An indoor radio propagation model considering angles for WLAN infrastructures. Wireless Communications and Mobile Computing, 15, 2038–2048.CrossRefGoogle Scholar
  18. 18.
    Borenovic, M., & Neskovic, A. Indoor georeferenced RSSI database. Resource documents. Avaiable online at http://telekomunikacije.etf.rs/research/wlanpositioning/rssiDatabase.zip. Accessed July 2017.
  19. 19.
    Cisco Aironet 802.11a/b/g Cardbus AIR-CB21AG-E-K9. Avaiable online at https://www.cisco.com. Accessed November 2017.
  20. 20.
    Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wassermann, W. (1996). Applied linear statistical model (4th ed.). Chicago: McGraw-Hill/Irwin.Google Scholar
  21. 21.
    Zhang, Y. P., & Hwang, Y. (1998). Theory of the radio-wave propagation in railway tunnels. IEEE Transactions on Vehicular Technology, 47(3), 1027–1036.CrossRefGoogle Scholar
  22. 22.
    Forooshani, A., Bashir, S., Michelson, D., & Noghanian, S. (2013). A survey of wireless communications and propagation modelin in underground mines. IEEE Communications Surveys & Tutorials, 15(4), 1524–1545.CrossRefGoogle Scholar
  23. 23.
    Molina-Garcia-Pardo, J., Lienard, M., & Deguaque, P. (2009). Propagation in tunnels: Experimental investigations and channel modeling in a wide frequency band for MIMO applications. EURASIP Journal on Wireless Communiactions and Networking, 2009, 7.Google Scholar
  24. 24.
    MATLAB. Resource document. www.mathworks.com.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Transport and Traffic EngineeringUniversity of BelgradeBelgradeSerbia

Personalised recommendations