Geometry-Based Statistical Modeling of Non-Stationary MIMO Vehicle-to-Vehicle Channels

ABSTRACT

A novel geometry-based statistical model (GBSM) for non-stationary multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) fading channels is presented in this paper. In contrast to the existing geometrical models for non-stationary channels, which are based on a spherical wave propagation (SWP) approach, our proposal builds on the principles of plane wave propagation (PWP). This modeling approach simplifies the mathematical analysis of the relevant statistics of non-stationary channels, such as the space-time-frequency cross-correlation function (STF-CCF). To demonstrate the mathematical tractability of the model, we derive a novel closed-form expression for the STF-CCF. For that purpose, we consider a geometrical one-ring scattering model, and assume that the angle of arrival (AOA) of the received multipath signal follows the von Mises distribution. The obtained results provide valuable theoretical insights into the cross-correlation properties of non-stationary MIMO V2V fading channels.

References

1. A. Abdi and M. Kaveh. A space-time correlation model for multielement antenna systems in mobile fading channels. IEEE J. Sel. Areas in Commun., 20(3):550--560, Apr. 2002.
2. L. Bernado, T. Zemen, F. Tufvesson, A. Molisch, and C. F. Mecklenbrauker. The (in)validity of the WSSUS assumption in vehicular radio channels. In Proc. 23rd IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC'12), pages 1757--1762, Sidney, Australia, Sept. 2012.
3. R. Bishop. Intelligent vehicle applications worldwide. IEEE Intelligent Systems and their Applications, 15(1):78--81, Jan. 2000.
4. A. Chelli and M. Patzold. A non-stationary mimo vehicle-to-vehicle channel model based on the geometrical t-junction model. In International Conference on Wireless Communications & Signal Processing (WCSP), pages 1--5, Nanjing, China, Nov. 2009.
5. A. Chelli and M. Patzold. A non-stationary mimo vehicle-to-vehicle channel model derived from the geometrical street model. In Proc. IEEE 74th Vehicular Technology Conference (VTC2011-Fall), pages 1--6, San Francisco CA, USA, Sept. 2011.
6. C. A. Gutiérrez, J. T. Gutiérrez-Mena, J. M. Luna-Rivera, D. U. Campos-Delgado, R. Velázquez, and M. Patzold. Geometry-based statistical modeling of nonstationary time and frequency dispersive mobile-to-mobile channels. IEEE Trans. Veh. Technol. Under review.
7. IEEE 802.11 p. Amendment to standard for information technology-telecommunications and information exchange between systems-local and metropolitan area networks-specific requirements - part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications-amendment 7: Wireless access in vehicular environment.
8. G. Karagiannis, O. Altintas, E. Ekici, G. Heijenk, B. Jarupan, K. Lin, and T. Weil. Vehicular networking: A survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Communications Surveys & Tutorials, 13(4):584--616, 2011.
9. J. Karedal, F. Tufvesson, N. Czink, A. Paier, C. Dumard, T. Zemen, C. Mecklenbrauker, and A. F. Molisch. A geometry-based stochastic MIMO model for vehicle-to-vehicle communications. IEEE Trans. Wireless Commun., 8(7):3646--3657, 2009.
10. J. B. Kenney. Dedicated short-range communications (DSRC) standards in the United States. Proc. IEEE, 99(7):1162--1182, July 2011.
11. G. Matz. On non-wssus wireless fading channels. IEEE Trans. Wireless Commun., 4(5):2465--2478, Sept. 2005.
12. C. Mecklenbrauker, A. Molisch, J. Karedal, F. Tufvesson, A. Paier, L. Bernardo, T. Zemen, O. Klemp, and N. Czink. Vehicular channel characterization and its implications for wireless system design and performance. Proc. IEEE, 99(7):1189--1212, July 2011.
13. A. Molisch. Wireless Communications. John Wiley and Sons, Chichester, UK, 2005.
14. A. Molisch, F. Tufvesson, J. Karedal, and C. Mecklenbrauker. A survey on vehicle-to-vehicle propagation channels. IEEE Wireless Commun., 16(6):12--22, December 2009.
15. P. Papadimitratos, A. L. Fortelle, K. Evenssen, R. Brignolo, and S. Cosenza. Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Commun. Mag., 47(11):84--95, Nov. 2009.
16. A. Papoulis and S. U. Pillai. Probability, Random Variables and Stochastic Processes. McGraw-Hill, New York, fourth edition, 2002.
17. K. I. Pedersen, P. E. Mongensen, and B. H. Fleury. Power azimuth spectrum in outdoor environments. IEEE Electron. Lett., 33(18):1583--1584, Aug. 1997.
18. F. M. Schubert, M. L. Jakobsen, and B. H. Fleury. Non-stationary propagation model for scattering volumes with application to the rural lms channel. IEEE Trans. Antennas Propag., 61(5):2817--2828, 2013.
19. A. Sheng-hai, L. Byung-Hyug, and S. Dong-Ryeol. A survey of intelligent transportation systems. In 2011 Third International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), pages 332--337, Bali, Indonesia, July 2011.
20. B. Sklar. Digital Communications: Fundamentals and Applications. Prentice Hall, New Jersey, second edition, 2001.
21. M. Walter, D. Shutin, and U.-C. Fiebig. Delay-dependent doppler probability density functions for vehicle-to-vehicle scatter channels. IEEE Trans. Antennas Propag., 62(4):2238--2249, Apr. 2014.
22. C.-X. Wang, X. Cheng, and D. I. Laurenson. Vehicle-to-vehicle channel modeling and measurements: Recent advances and future challenges. IEEE Commun. Mag., 47(11):96--103, Nov. 2009.
23. World-Health-Organization. Global Status Report on Road Safety. WHO Press, Geneva, Switzerland, 2009.
24. A. G. Zajić and G. L. Stüber. Space-time correlated mobile-to-mobile channels: Modelling and simulation. IEEE Trans. Veh. Technol., 57(2):715--726, Mar. 2008.

Index Terms

• Computing methodologies

  • Modeling and simulation

    • Model development and analysis

      • Modeling methodologies

• Mathematics of computing

  • Probability and statistics

    • Statistical paradigms

      • Statistical graphics