Advertisement

Wireless Networks

, Volume 23, Issue 7, pp 2281–2288 | Cite as

How significant is the assumption of the uniform channel phase distribution on the performance of spatial multiplexing MIMO system?

  • Raed MeslehEmail author
  • Osamah S. Badarneh
  • Abdelhamid Younis
  • Fares S. Almehmadi
Article

Abstract

Spatial multiplexing (SMX) multiple-input multiple-output (MIMO) systems are promising candidates to enhance the achievable throughput and the overall spectral efficiency in future wireless systems. Performance studies of these systems over different channel conditions assume simplified models for the channel phase distribution. This paper highlights the impact of the channel phase distribution assumption on the performance of SMX MIMO systems. The Nakagami-m and the \(\eta -\mu\) fading channels are considered in this study. In existing literature, performance studies of SMX MIMO systems over Nakagami-m fading channel assume uniform phase distribution. Though, it has been reported recently that the Nakagami-m channel phase distribution is not uniform. In this article, we show that the assumption of the channel phase distribution has a major impact on the performance of SMX MIMO systems. The obtained results demonstrate that the performance of SMX MIMO systems significantly varies with different channel phase distributions. Furthermore, it is shown that uniform assumption of channel phase distribution is incorrect and leads to erroneous conclusions. Detailed performance analysis for more accurate channel models are provided and results are sustained through Monte-Carlo simulations.

Keywords

Channel phase distribution Spatial multiplexing (SMX) Nakagami-m channel \(\eta -\mu\) channel Performance analysis 

References

  1. 1.
    Wang, P., Li, Y., Song, L., & Vucetic, B. (2015). Multi-gigabit millimeter wave wireless communications for 5G: From fixed access to cellular networks. IEEE Communications Magazine, 53(1), 168–178.CrossRefGoogle Scholar
  2. 2.
    Al-Dulaimi, A., Al-Rubaye, S., Ni, Q., & Sousa, E. (2015). 5G communications race: Pursuit of more capacity triggers lte in unlicensed band. IEEE Vehicular Technology Magazine, 10(1), 43–51.CrossRefGoogle Scholar
  3. 3.
    Mallik, R., Singh, S., Murch, R., & Mehra, S. (2015). Signal design for multiple antenna systems with spatial multiplexing and noncoherent reception. IEEE Transactions on Communications, 63(4), 1245–1258.CrossRefGoogle Scholar
  4. 4.
    Larsson, E., Edfors, O., Tufvesson, F., & Marzetta, T. (2014). Massive mimo for next generation wireless systems. IEEE Communications Magazine, 52(2), 186–195.CrossRefGoogle Scholar
  5. 5.
    Ordoez, L., Palomar, D., Pages-Zamora, A., & Fonollosa, J. (2007). High-snr analytical performance of spatial multiplexing mimo systems with csi. IEEE Transactions on Signal Processing, 55(11), 5447–5463.MathSciNetCrossRefGoogle Scholar
  6. 6.
    Lu, L., Li, G., Swindlehurst, A., Ashikhmin, A., & Zhang, R. (2014). An overview of massive mimo: Benefits and challenges. IEEE Journal of Selected Topics in Signal Processing, 8(5), 742–758.CrossRefGoogle Scholar
  7. 7.
    Gao, X., Edfors, O., Rusek, F., & Tufvesson, F. (2015). Massive mimo performance evaluation based on measured propagation data. IEEE Transactions on Wireless Communications, 14(7), 3899–3911.CrossRefGoogle Scholar
  8. 8.
    Hashem, T., & Islam, M. (2014). Performance analysis of mimo link under fading channels. In 2014 17th International conference on computer and information technology (ICCIT) (pp. 498–503).Google Scholar
  9. 9.
    Jiang, Y., & Varanasi, M. (2009). The rf-chain limited mimo system-part I: Optimum diversity-multiplexing tradeoff. IEEE Transactions on Wireless Communications, 8(10), 5238–5247.CrossRefGoogle Scholar
  10. 10.
    Di Renzo, M., & Lu, W. (2015). Stochastic geometry modeling and performance evaluation of mimo cellular networks using the equivalent-in-distribution (eid)-based approach. IEEE Transactions on Communications, 63(3), 977–996.CrossRefGoogle Scholar
  11. 11.
    Simon, M. K., & Alouini, M. (2005). Digital Communication over Fading Channels (2nd ed.). ser. Wiley series in telecommunications and signal processing. John Wiley & Sons, Inc., ISBN: 978-0-471-64953-3.Google Scholar
  12. 12.
    Di Renzo, M., & Haas, H. (2012). Bit error probability of spatial modulation (SM) MIMO over generalized fading channels. IEEE Transactions on Vehicular Technology, 61(3), 1124–1144.CrossRefGoogle Scholar
  13. 13.
    Yacoub, M. (2010). Nakagami-m phase-envelope joint distribution: a new model. IEEE Transactions on Vehicular Technology, 59(3), 1552–1557.MathSciNetCrossRefGoogle Scholar
  14. 14.
    Yacoub, M. D. (2007). The \(\eta -\mu\) distribution and the \(\kappa -\mu\) distribution. IEEE Antennas Propagation Magazine, 49(1), 68–81.CrossRefGoogle Scholar
  15. 15.
    Proakis, J. G., & Salehi, M. (2008). Digital communications (5th ed.). ser. McGraw-Hill Series in Electrical and Computer Engineering, Director, S. W. (Ed.), McGraw-Hill Higher Education.Google Scholar
  16. 16.
    Mesleh, R., Ikki, S. S., & Aggoune, H. M. (2014). Quadrature spatial modulation-performance analysis and impact of imperfect channel knowledge. Transactions on Emerging Telecommunications Technologies, (2905), 1–9. doi: 10.1002/ett.2905.
  17. 17.
    Nakagami, M. (1960). The m-distribution–A general formula of intensity distribution of rapid fading. In W. C. Hoffmann (Ed.), Statistical methods in radio wave propagation. New York: Elmsford.Google Scholar
  18. 18.
    Yacoub, M., Fraidenraich, G., & Santos Filho, J. (2005). Nakagami-m phase-envelope joint distribution. Electronics Letters, 41(5), 259–261.CrossRefGoogle Scholar
  19. 19.
    da Costa, D. B., & Yacoub, M. D. (2007). The \(\eta -\mu\) joint phase-envelope distribution. IEEE Antennas Wireless Propagation Letters, 6, 195–198.CrossRefGoogle Scholar
  20. 20.
    Turin, G. L. (1960). The characteristic function of hermitian quadratic forms in complex normal variables. Biometrika, 47(1/2), 199–201.MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Abramowitz, M., & Stegun, I. A. (1972). Handbook of mathematical functions with fomulas, graphs, and mathematical tables (9th ed.). New York: Dover Publications.zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Raed Mesleh
    • 1
    Email author
  • Osamah S. Badarneh
    • 2
  • Abdelhamid Younis
    • 3
  • Fares S. Almehmadi
    • 2
  1. 1.Communications Engineering Department, School of Computer Engineering and Information TechnologyGerman Jordanian UniversityAmmanJordan
  2. 2.Electrical Engineering Department, Faculty of EngineeringUniversity of TabukTabukSaudi Arabia
  3. 3.Electrical and Electronics Engineering Department, Faculty of EngineeringUniversity of BenghaziBenghaziLibya

Personalised recommendations