Advertisement

Wireless Personal Communications

, Volume 79, Issue 1, pp 487–507 | Cite as

User Selection Criteria for Uplink Spatial Multiplexing MIMO Systems

  • Samir N. Al-GhadhbanEmail author
Article
  • 121 Downloads

Abstract

We study in this paper multiuser uplink scheduling algorithms for Multiple-Input Multiple-Output (MIMO) systems, where the multiusers compete for the MIMO Channel and the scheduler selects one user at a time based on a certain criterion. Then the selected user spatially multiplexes his data over the transmit antennas. This spatial multiplexing (SM) scheme provides high data rates while the multiuser diversity obtained from scheduling improves the performance of the uplink system. At the receiver, the Vertical-Bell-Labs LAyered Space Time architecture (V-BLAST) is used to detect the information layers. The main contribution of this paper is proposing and comparing the performance of several scheduling criteria for MIMO uplink scheduling. In addition, novel V-BLAST capacity bounds based on random matrix theory is presented. Furthermore, we investigate suboptimal schedulers and compare their performance. The main results of this study show that the scheduler that maximizes the optimal MIMO capacity doesn’t work well for a V-BLAST system. Instead, the optimal scheduler that maximizes the V-BLAST capacity is derived and analyzed. In addition, we look into scheduling for SM with sphere decoding and we find that in this case, using MIMO capacity as the scheduling criterion performs the best.

Keywords

MIMO multiuser uplink scheduling VBLAST Capacity  Spatial multiplexing 

Notes

Acknowledgments

The author would like to acknowledge the support provided by King Fahd University of Petroleum and Minerals (KFUPM) and King Abdulaziz City for Science and Technology (KACST) for funding this work through project number AR-29-79.

References

  1. 1.
    Knopp, R., & Humblet, P. (1995). Information capacity and power control in single cell multiuser communications. In Proceedings of the IEEE international computer conference (ICC’95), Seattle, WA.Google Scholar
  2. 2.
    Tse, D. N. C. (1997). Optimal power allocation over parallel Gaussian channels. In Proceedings of international symposium on information theory. Ulm, Germany.Google Scholar
  3. 3.
    Heath, Jr., R. W., Airy, M., & Paulraj, A. J. (2001). Multiuser diversity for MIMO wireless systems with linear receivers. In Signal, systems and computers 2001, conference record of the thirty-fifth asilomar conference on, vol. 2, pp. 1194–1199.Google Scholar
  4. 4.
    Airy, M., Shakkattai, S., & Heath, Jr., R. W. (2003). Spatially greedy scheduling in multi-user MIMO wireless systems. In Signals, systems and computers, 2003. Conference record of the thirty-seventh asilomar conference on, vol. 1, pp. 982–986.Google Scholar
  5. 5.
    Wang, L.-C., & Yeh, C.-J. (2010). Scheduling for multiuser MIMO broadcast systems: Transmit or receive beamforming? IEEE Wireless Communications, 9(9), 2779–2791.CrossRefGoogle Scholar
  6. 6.
    Pan, C.-H., & Lee, T.-S. (2013). Efficient QR-based multi-mode precoding for limited feedback multi-user MIMO systems. Wireless Personal Communications, Published Online, pp. 1–19.Google Scholar
  7. 7.
    Gozali, R., Buehrer, R. M., & Woerner, B. D. (2003). The impact of multiuser diversity on space-time block coding. IEEE Communications Letters, 7(5), 213–215.CrossRefGoogle Scholar
  8. 8.
    Lau, V.K.N., Liu, Y., & Chen, T.A. (2002). Optimal multi-user space time scheduling for wireless communications. In IEEE 56th VTC 2002-Fall. (2002), vol. 4, pp. 1939–1942.Google Scholar
  9. 9.
    Al-Ghadhban, S., Buehrer, R. M., & Robert, M. (2007). Uplink scheduling criteria comparison for V-BLAST users. In 9th international symposium on signal processing and its applications, 2007, pp. 1–4.Google Scholar
  10. 10.
    Wolniansky, P. W., Foschini, G. J., Golden, G. D., & Valenzuela, R. A. (1998). V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. In Proceedings of ISSSE-98, Pisa, Italy, pp. 295–300.Google Scholar
  11. 11.
    Choi, J., & Adachi, F. (2010). User selection criteria for multiuser systems with optimal and suboptimal LR based detectors. IEEE Transactions on Signal Processing, 58(10), 5463–5468.MathSciNetCrossRefGoogle Scholar
  12. 12.
    Bai, L., Chen, C., Choi, J., & Ling, C. (2011). Greedy user selection using a lattice reduction updating method for multiuser MIMO systems. IEEE Transactions on Vehicular Technology, 60(1), 136–147.CrossRefGoogle Scholar
  13. 13.
    Mao, J. L., Gao, J. C., Liu, Y. A., Xie, G., & Zhang, J. (2012). Robust multiuser MIMO scheduling algorithms with imperfect CSI. Science China Information Sciences, 55(4), 815–826.CrossRefzbMATHGoogle Scholar
  14. 14.
    Foschini, G. J., & Gan, M. J. (1998). On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communications, 6, 311–335.CrossRefGoogle Scholar
  15. 15.
    Papadias, C. B., & Foschini, G. J. (2002). On the capacity of certain space-time coding schemes. EURASIP Journal on Applied Signal Processing, 2002(5), 447–458.CrossRefzbMATHGoogle Scholar
  16. 16.
    Loyka, S., & Gagnon, F. (2004). On BER analysis of the BLAST without optimal ordering over Rayleigh fading channel. In Vehicular technology conference, VTC2004-Fall, IEEE 60th, vol. 2, pp. 1473–1477.Google Scholar
  17. 17.
    Jiang, Y., Zheng, X., & Li, J. (2005). Asymptotic performance analysis of V-BLAST. In Global telecommunications conference, 2005. GLOBECOM ’05. IEEE, vol. 6, p. 3886.Google Scholar
  18. 18.
    Lee, H., & Lee, I. (2006). Channel capacity of BLAST based on the zero forcing criterion. In Vehicular technology conference, VTC 2006-Spring. IEEE 63rd, vol. 4, pp. 1615–1619.Google Scholar
  19. 19.
    Edelman, A. (1988). Eigenvalues and condition numbers of random matrices. SIAM Journal on Matrix Analysis and Applications, 9(4), 543–560.MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    David, H. A. (1970). Order statistics (1st ed.). New York: Wiley.zbMATHGoogle Scholar
  21. 21.
    Gordon, Y., Litvak, A. E., Schutt, C., & Werner, E. (2006). On the minimum of several random variables. Proceedings of American Mathematical Society, 134(12), 3669–3675.MathSciNetCrossRefGoogle Scholar
  22. 22.
    Bertsimas, D., Natarajan, K., & Teo, C.-P. (2006). Tight bounds on expected order statistics. Probability in the Engineering and Informational Sciences, 20(4), 667–686.MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Zhang, X., Lv, Z., & Wang, W. (2008). Performance analysis of multiuser diversity in MIMO systems with antenna selection. IEEE Transactions on Wireless Communications, 7(1), 15–21.CrossRefzbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Electrical EngineeringKing Fahd University of Petroleum and MineralsDhahranSaudi Arabia

Personalised recommendations