Skip to main content
SpringerLink
Log in

Performance Evaluation of Virtual MIMO Multi-User System in a Measured Indoor Environment at 5 GHz

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Wideband indoor MIMO channel measurements were performed in office building with carrier frequency at 5.25 GHz with 100 MHz radio frequency bandwidth. In this paper nineteen measured indoor propagation data sets are used to study the behavior of virtual MIMO system formed by two users compared to its classical user. A classical user having 4 antenna elements, two spaced antennas from two classical users are brought together to form 4 \(\times \) 8 virtual MIMO with base station having 8 antennas. Nineteen measured datasets are available from which 171 possible virtual MIMO pairs are formed. The capacity, \(K\)-factor, rms delay spread and spatial correlation are evaluated for 171 possible pairs of users whose channels were measured while standing. The results show that virtual MIMO in many cases is desirable for capacity improvement. The capacity improvement of virtual MIMO system is found to be 60.2 % over both two constituent users and 31 % over only one constituent user. The result show also that capacity improvement is mostly due to the rms delay spread and special correlation reduction than the \(K\)-factor reduction.

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
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Andrews, J. G., Ghosh, A., & Muhamed, R. (2008). Fundamentals of WiMAX: Understanding broadband wireless networking. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  2. Balan, H. V., Rogalin, R., Michaloliakos, A., Psounis, K., & Caire, G. (2013). AirSync: Enabling distributed multiuser MIMO with full spatial multiplexing. IEEE/ACM Transactions on Networking, 21, 1681–1695.

    Article  Google Scholar 

  3. Cho, Y. S., Kim, J., Yang, W. Y., & Kang, C. G. (2010). MIMO-OFDM wireless communications with Matlab. Singapore: Wiley.

    Book  Google Scholar 

  4. Sanayei, S., & Nosratinia, A. (2004). Antenna selection in MIMO systems. IEEE Communications Magazine, 42, 68–73.

    Article  Google Scholar 

  5. Yang, Y., Blum, R. S., & Sfar, S. (2009). Antenna selection for MIMO systems with closely spaced antennas. Eurasip Journal on Wireless Commun. and Networking, 2009, 1–11.

  6. Xie, Z. B., Wang, J. K., Wang, Y., & Gao, J. (2008). Effective antenna selection in MIMO systems under spatial correlated fading. In Proceedings of the 7th World congress intelligent control and automation (pp. 25–27). Chongqing, China.

  7. Jayaweera, S. K. (2007). V-BLAST-based virtual MIMO for distributed wireless sensor networks. IEEE Transactions on Communications, 55, 1867–1872.

    Article  MathSciNet  Google Scholar 

  8. Xu, K., & Chizuni, D. (2007). A V-BLAST based virtual MIMO transmission scheme for sensor network lifetime maximization. In IEEE vehicular technology conference, Fall (pp. 377–381). Baltimore, MD.

  9. Webb, M., Yu, M., & Beach, M. (2011). Propagation characteristics, metrics, and statistics for virtual MIMO performance in a measured outdoor cell. IEEE Transactions on Antennas and Propagation, 59, 236–244.

    Article  Google Scholar 

  10. Dai, J. X., Chen, M., & Chung, P. J. (2013). The downlink capacity of single-user SA-MIMO system. Wireless Personal Communications, 69, 1333–1345.

    Article  Google Scholar 

  11. Paulraj, A., Nabar, R., & Gore, D. (2003). Introduction to space–time wireless communications. Cambridge: Cambridge University Press.

    Google Scholar 

  12. Foschini, G. J. (1996). Layered space–time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal, 1, 41–59.

    Article  Google Scholar 

  13. Cattoni, A. F., Moullec, Y., Le, Sacchi C., & Ieee. (2013). Zero-forcing pre-coding for MIMO WiMAX transceivers: Performance analysis and implementation issues. In 2013 IEEE Aerospace conference (pp. 1–7). Big Sky, Montana, USA.

  14. Cho, Y. S., Kim, J., Yang, W. Y., & Kang, C. G. (2010). MIMO channel capacity. In MIMO-OFDM wireless communications with Matlab (pp. 263–280). Singapore: Wiley.

  15. Ilic-Delibasic, M., & Pejanovic-Djurisic, M. (2012). Impact of random K factor on Ricean fading wireless system performance. In Electrotechnical conference New York (pp. 233–236).

  16. Greenstein, L. J., Ghassemzadeh, S. S., Erceg, V., & Michelson, D. G. (2009). Ricean K-factors in narrow-band fixed wireless channels: Theory, experiments, and statistical models. IEEE Transactions on Vehicular Technology, 58, 4000–4012.

    Article  Google Scholar 

  17. Rappaport, T. S. (2002). Wireless communications: Principle and practice (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  18. Zhao, X., Kivinen, J., Skog, K., & Vainikainen, P. (2003). Characterization of Doppler spectra for mobile communication at 5.3 GHz. IEEE Transactions on Vehicular Technology, 52, 14–23.

    Article  Google Scholar 

  19. Lee, J. H., & Cheng, C. C. (2012). Spatial correlation of multiple antenna arrays in wireless communication systems. Progress in Electromagnetics Research, 132, 347–368.

    Article  Google Scholar 

  20. Zhang, Y., Xiao, L. M., Zhou, S. D., & Wang, J. (2013). Measurement-based spatial correlation and capacity of indoor distributed MIMO system. International Journal of Antennas and Propagation, 2013, 1–7.

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

    Article  Google Scholar 

  22. Chuah, C. N., Tse, D. N. C., Kahn, J. M., & Valenzuela, R. A. (2002). Capacity scaling in MIMO wireless systems under correlated fading. IEEE Transactions on Information Theory, 48, 637–650.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 61372051, and the 863 Project No. 2014AA01A701.

Author information

Authors and Affiliations

  1. School of Electrical and Electronic Engineering, China Electric Power University, Beijing, 102206, China

    Balla Moussa Coulibaly, Xiongwen Zhao, Suiyan Geng & Yiwei Li

  2. State Radio Monitoring Center, Beijing, 100037, China

    Jingchun Li

Authors
  1. Balla Moussa Coulibaly
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiongwen Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suiyan Geng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yiwei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jingchun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Balla Moussa Coulibaly.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coulibaly, B.M., Zhao, X., Geng, S. et al. Performance Evaluation of Virtual MIMO Multi-User System in a Measured Indoor Environment at 5 GHz. Wireless Pers Commun 82, 1249–1262 (2015). https://doi.org/10.1007/s11277-015-2279-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2279-4

Keywords

Search

Navigation