Skip to main content
Log in

New approach to wireless channel modeling based on representing fields in the scattering medium as the sum of resonance oscillation fields

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

A new approach to channel modeling is proposed, in which the electromagnetic field in the scattering medium is regarded as the sum of resonance oscillation fields. Modeling starts with obtaining the scattering channel matrix that links amplitudes of spherical waves in receive-transmit regions. The scattering channel matrix provides a convenient model for MIMO communication systems, as it allows taking into account space and polarization characteristics of the fields. A method of transiting from the physical (field) to analytical (antenna) channel model is proposed, which enables taking into account multiple bounces off the antenna and surrounding objects that occur during propagation of waves. The use of the singularity expansion method (SEM) yielded accurate analytical expressions for the frequency dependence of entries of the scattering-channel matrix. The entries of the scattering-channel matrix are represented as the sum of two summands: the non-resonance summand accounting for single-bounce scattering and the resonance summand accounting for wave multiple-bounce scattering in the scattering medium. The impact of multiple-bounce scattering has been neglected in all models described earlier. A technique for building a discrete channel model for a frequency range is proposed. A set of parameters allowing the description of space-frequency characteristics of a simple-geometry wireless channel is presented. Statistical characteristics of random channel parameters are obtained, and the results of modeling such a channel are presented.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Winters, J. H. (1978). On the capacity of radio communication systems with diversity in a Rayleigh fading environment. IEEE Journal on Selected Areas Communications, SAC-5, 871–878.

    Google Scholar 

  2. Foschini, G. J., & Gans, M. J. (1998). On limits of wireless communications in a fading environment when using multi-ple antennas. Wireless Personal Communications, 6(3), 311–335.

    Article  Google Scholar 

  3. Telatar, E. I. (1999). Capacity of multi-antenna Gaussian channel. European Transactions on Telecommunications, 10(6), 385–395.

    Article  Google Scholar 

  4. http://www.airgonetworks.com.

  5. http://www.beceem.com.

  6. Almers, P., Bonek, E., Burr, A., et al. (2007). Survey of channel and radio propagation models for wireless MIMO systems. EURASIP Journal on Wireless Communications and Networking, 7(1), 1–19.

  7. Azpilicueta, L., Rawat, M., Rawat, K., Ghannouchi, F. M., & Falcone, F. (2014). A ray launching-neural network approach for radio wave propagation analysis in complex indoor invironments. IEEE Transactions on Antennas and Propagation, 62(5), 2777–2786.

    Article  Google Scholar 

  8. Vinogradov, E., Joseph, W., & Destges, C. (2015). Measurement—Based modeling of time-variant fading statistics in indoor peer-to-peer scenarios. IEEE Transactions on Antennas Propagation, 63(5), 2252–2263.

    Article  Google Scholar 

  9. Jackson, J. D. (1998). Classical electrodynamics (3rd ed.). New York: Wiley.

    MATH  Google Scholar 

  10. Felsen, L. B. (1976). Transient electromagnetic Fields. Berlin: Springer.

    Book  Google Scholar 

  11. Miller, E. K. (1998). Model-based parameter estimation in electromagnetics, Part I. Background and theoretical development. IEEE Antennas and Propagation Magazine, 40(1), 42–52.

    Article  Google Scholar 

  12. Miller, E. K. (1998). Model-based parameter estimation in electromagnetics, Part II. Application to EM observables. IEEE Antennas and Propagation Magazine, 40(2), 51–65.

    Article  Google Scholar 

  13. Miller, E. K. (1998). Model-based parameter estimation in electromagnetics, Part III. Application to EM integral equations. IEEE Antennas and Propagation Magazine, 40(3), 49–66.

    Article  Google Scholar 

  14. Kovalyov, I. P., & Ponomarev, D. M. (2011). The resonance mode theory for exterior problems of electrodynamics and its application to discrete antenna modeling in a frequency range. IEEE Transactions on Antennas Propagations, 59, 4181–4200.

    Article  MathSciNet  Google Scholar 

  15. Poon, A. S. Y., Brodersen, R. W., & Tse, D. N. C. (2005). Degrees of freedom in multiple-antenna channels: A signal space approach. IEEE Transactions on Information Theory, 51(2), 523–536.

    Article  MathSciNet  MATH  Google Scholar 

  16. Mohajer, M., Safavi-Naeini, S., & Chaudhuri, S. K. (2010). Spherical vector wave method for analysis and design of MIMO antenna system. IEEE Antennas and Propagation Letters, 9, 1267–1270.

    Article  Google Scholar 

  17. Glazunov, A. A., Gustafsson, M., & Molisch, A. F. (2011). On the physical limitations of the interaction of a spherical aperture and a random field. IEEE Transactions on Antennas and Propagation, 59(1), 119–128.

    Article  Google Scholar 

  18. Molina-Garcia-Pardo, J.-M., Rogrigues, J.-V., & Juan-Llacer, L. (2007). Parametric spherical wave multiple-input and multiple-output model for ray-base simulations. Radio Sci. 42(2), 154–164.

  19. Jeng-Shiann and Mary Ann Ingram. (2005). Spherical-wave model for short-range MIMO. IEEE Transactions on Communications, 53(9), 1534–1541.

    Article  Google Scholar 

  20. Bohagen, F., Orten, P., & Oien, G. (2009). On spherical vs. plane wave modeling of line-of-sight MIMO channels. IEEE Transactions on Communications, 57, 841–849.

    Article  Google Scholar 

  21. Corcoles, J., Pontes, J., Gonzalez, M. A., & Zwick, T. (2009). Modeling line-of-sight coupled MIMO systems with generalised scattering matrices and spherical wave translations. Electronics Letters, 45, 598–599.

    Article  Google Scholar 

  22. Glazunov, A. A., Gustafsson, M., Molisch, A. F., and Tufvesson, F. (2009). Physical modeling of MIMO antennas and channel by means of the spherical vector wave expansion. Electromagnetic Theory Departament of Electrical and Information Technology Lund University, pp. 1–31.

  23. Glazunov, A. A., Gustafsson, M., Molisch, A. F., Tufvesson, F., & Kristensson, G. (2009). Spherical vector wave expansion of Gaussian electromagnetic fields for antenna-channel interaction analysis. IEEE Transactions on Antennas Propagation, 57(7), 2055–2067.

    Article  MathSciNet  Google Scholar 

  24. Gustafsson, M., & Nordebo, S. (2006). Characterization of MIMO antennas using spherical vector waves. IEEE Transactions on Antennas Propagation, 54(9), 2679–2682.

    Article  MathSciNet  Google Scholar 

  25. Hansen, J. E. (Ed.). (1998) Near-field antenna measurements. IEE Electromagnetic Waves Series 26, London: Peter Peregrinus Ltd.

  26. Stratton, J. A. (1941). Electromagnetic theory. New York: McGraw-Hill.

    MATH  Google Scholar 

  27. Angot, P. A. (1957). Complements de mathemaiques al’usare des ingenieurs de l’elektronique et des elecommunications. Paris: Editions de la Revue d’Optique.

    Google Scholar 

  28. Kovalyov, I. P. (2004). SDMA for multi-path wireless channels. Limiting characteristics and stochastic models. Berlin: Springer.

    Book  Google Scholar 

  29. Okhmatovski, V. I., & Cangellaris, A. C. (2003). Efficient calculation of the electromagnetic dyadic Green’s function in spherical layered media. IEEE Transactions on Antennas Propagation, 51, 3209–3220.

    Article  MathSciNet  Google Scholar 

  30. Korn, G. A., & Korn, T. M. (1968). Mathematical handbook. New York: McGraw-Hill.

    MATH  Google Scholar 

  31. Abramowitz, M. & Stegun, I. A. (Eds.). (1964). Handbook on mathematical functions. Washington, DC: National Bureau of Standards.

  32. Loyka, S., & Kouki, A. (2002). New compound upper bound on MIMO channel capacity. IEEE Communications Letters, 6, 96–98.

    Article  Google Scholar 

  33. Wallace, J. W., Jensen, M. A., Swindlehurst, A. L., & Jeffs, B. D. (2003). Experimental characterization of the MIMO wireless channel: Acquisition and analysis. IEEE Transactions on Wireless Communications, 2(2), 335–343.

    Article  Google Scholar 

  34. Kermoal, J. P., Schumscher, L., Mogensen, P. E., & Pedersen, K. L. (2000). Experimental investigation of correlation properties of MIMO radio channels for indoor picocell scenarios. In IEEE Vehicular Technology Conference (Fall VTC 2000) (vol. 2, pp. 14–21). Boston, MA.

Download references

Acknowledgments

The authors wish to thank Yuri B. Akimov, the technical writer of MFI Soft, for his valuable advice on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Igor P. Kovalyov.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kovalyov, I.P., Kuzikova, N.I. & Ponomarev, D.M. New approach to wireless channel modeling based on representing fields in the scattering medium as the sum of resonance oscillation fields. Wireless Netw 22, 1779–1795 (2016). https://doi.org/10.1007/s11276-015-1062-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-1062-5

Keywords

Navigation