Skip to main content
SpringerLink
Log in

Sub-optimal Antenna Selection in the High SNR MIMO Correlated Downlink Channel

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this paper, we present a sub-optimal antenna selection technique to enhance the channel capacity in the case of High SNR MIMO correlated downlink channel. Most related work has thus far considered uncorrelated MIMO channel with antenna selection technique and used a larger radio frequency (RF) module. Thus, we propose the MIMO correlated downlink MIMO channel with sub-optimal antenna selection method to employ a smaller number of RF module. In this paper, we first design and develop the Toeplitz channel correlation matrices which reflect the correlations between the transmitter antennas, then apply a sub-optimal transmit antenna selection technique to improve the channel capacity. Mote Carlo simulation results show that the channel capacity significantly enhance considering equal power transmission.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Gesbert, D., Shafi, M., Shiu, D. S., Smith, P. J., & Naguib, A. (2003). From theory to practice: An overview of MIMO coded wireless systems. IEEE Journal on selected areas in Communications, 21(3), 281–302.

    Article  Google Scholar 

  2. Bölcskei, H., Borgmann, M., & Paulraj, A. J. (2003). Impact of the propagation environment on the performance of space-frequency coded MIMO OFDM. IEEE Journal on Selected Areas in Communications, 21(3), 427–439.

    Article  Google Scholar 

  3. Tulino, A., Lozano, M., & Verdu, S. (2005). Impact of antenna correlation on the capacity of multi-antenna channels. IEEE Transaction on Information Theory, 51(7), 2491–2509.

    Article  MATH  Google Scholar 

  4. Shiu, D., Foschini, G. J., Gans, M. J., & Kahn, J. M. (2000). Fading correlation and its effect on the capacity of multielement antenna systems. IEEE Transactions on Communications, 48(3), 502–513.

    Article  Google Scholar 

  5. Smith, P. J., Roy, S., & Shafi, M. (2003). Capacity of MIMO systems with semi-correlated flat fading. IEEE Transactions on Information Theory, 49(10), 2781–2788.

    Article  MathSciNet  MATH  Google Scholar 

  6. Kermoal, J. P., Schumacher, L., Pedersen, K. I., Mogensen, P. E., & Frederik-Sen, F. (2002). A stochastic MIMO radio channel model with experimental validation. IEEE Journal on Selected Area in Communications, 20(6), 1211–1226.

    Article  Google Scholar 

  7. Heath, R. W., & Paulraj, A. J. (2000). Switching between multiplexing and diversity based on constellation distance. In Proceedings of Allerton conference on communication, control and computing (pp. 212–221).

  8. Antonio, F., et al. (2007). Adaptive MIMO transmission for exploiting the capacity of spatially correlated channels. IEEE Transaction on Vehicular Technology, 56(2), 619–630.

    Article  Google Scholar 

  9. Mestre, X., Fonollosa, J. R., & Zamora, A. P. (2003). Capacity of MIMO channels: Asymptotic evaluation under correlated fading. IEEE Journal on Selected Areas in Communications, 21(5), 829–838.

    Article  Google Scholar 

  10. Gore, D., Heath, R. W., & Paulraj, A. (2002). Transmit selection in spatial multiplexing systems. IEEE Communications Letters, 6(11), 491–493.

    Article  Google Scholar 

  11. Telatar, E. (1999). Capacity of multi-antenna Gaussian channels. European Transaction on Telecommunications, 10, 585–595.

    Article  MathSciNet  Google Scholar 

  12. Young, S. C., Kim, J., Yang, W. Y., & Kang, C. G. (2010). MIMO-OFDM wireless communications with MatLab. London: Wiley.

    Google Scholar 

  13. Michael, K. N. (2003). Circulant and skew-circulant splitting methods for Toeplitz systems. Journal of Computational and Applied Mathematics, 159, 101–108.

    Article  MathSciNet  MATH  Google Scholar 

  14. Haykin, S. (1991). Adaptive filter theory. Upper Saddle River, NJ: Prentice-Hall.

    MATH  Google Scholar 

  15. Pang, H., Wang, X., Huang, K., & Jiang, J. (2012). The eigenvalue decomposition method for wireless physical layer security. In: 14th IEEE international conference on communication technology (ICCT), Chengdu, China (pp 594–598).

  16. Mohammed, A. H., & Jawad A. K. H. (2002). Block eigenvalue decomposition using n-th roots of the identity matrix. In: Proceedings of the 41st IEEE, conference in decision and control, Las Vegas, USA (pp 2119–2124).

Download references

Acknowledgements

This work was supported by MEST 2015R1A2A1A05000977, NRF, Republic of Korea.

Author information

Authors and Affiliations

  1. Department of Electronic and Information Engineering, Chonbuk National University, Jeonju, 561-756, Korea

    Md. Abdul Latif Sarker, Moon Ho Lee & Sunil Chinnadurai

Authors
  1. Md. Abdul Latif Sarker
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Moon Ho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sunil Chinnadurai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Moon Ho Lee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarker, M.A.L., Lee, M.H. & Chinnadurai, S. Sub-optimal Antenna Selection in the High SNR MIMO Correlated Downlink Channel. Wireless Pers Commun 99, 1713–1724 (2018). https://doi.org/10.1007/s11277-018-5339-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5339-8

Keywords

Search

Navigation