Skip to main content
Log in

Analysis of a New MIMO Broadcast Channel Limited Feedback Scheduling Algorithm with User Grouping

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this paper, we present and analyze a new multiuser multiple-input multiple-output (MU MIMO) broadcast channel scheduling algorithm with limited feedback and user grouping. Here signal-to-noise-plus-interference-ratio (SINR) feedback is used for the scheduling criteria. The algorithm deals with the following three scenarios: (a) All transmit antennas are active. (b) Receive antennas at the mobile station (MS) with maximum SINR values are assigned to the transmit antennas at the base station (BS). (c) A given receive antenna is not scheduled for more than one BS transmit antenna, which ensures user fairness. A detailed comparison of the proposed algorithm with the limited feedback antenna selection algorithms proposed by Zhang et al. and Sharif et al. is presented. Further, we have extended the proposed algorithm to heterogeneous environment, where users having similar signal-to-noise-ratio (SNR) are grouped together. Also, we evaluate the effects of sending the beamforming data (here indices of the receiving antennas) to the BS in terms of complexity of MS and feedback load ratio. A detailed analytical approach for throughput of the system is presented in this paper for the proposed algorithm. We also verify the simulation results with the analytical results.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Bayesteh, A., & Khandani, A., (2005). On the user selection for MIMO broadcast channels. In Proceedings of the IEEE international symposium on information theory (pp. 2325–2329), Adelaide, Australia, Sept. 4–9, 2005.

  2. Caire, G., & Shamai, S. (2003). On the achievable throughput of a multiantenna gaussian broadcast channel. IEEE Transactions on Information Theory, 43, 1691–1706.

    Article  MathSciNet  Google Scholar 

  3. Choi, L.-U., & Murch, R. D. (2004). A transmit pre-processing technique for multi-user MIMO systems using a decomposition approach. IEEE Transactions on Wireless Communication, 3, 20–24.

  4. David, H. A. (1981). Order statistics. New York: Wiley.

    MATH  Google Scholar 

  5. Dimic, G., & Sidiropoulos, N. D. (2005). On downlink beamforming with greedy user selection: Performance analysis and a simple new algorithm. IEEE Transactionas on Signal Processing, 53, 3857–3868.

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  7. Foschini, G. J., & Gans, M. J. (1998). On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communication, 6, 311–335.

    Article  Google Scholar 

  8. Jaewoo, S., & Cioffi, J. M. (2009). Multiuser diversity in a MIMO system with opportunistic feedback. IEEE Transactions on Vehicular Technology, 58, 4909–4918.

  9. Jindal, N., & Goldsmith, A. (2005). Dirty-paper coding versus TDMA for MIMO broadcast channels. IEEE Transactions on Information Theory, 51, 1783–1794.

  10. Knopp, R., & Humblet, P. A. (1995). Information capacity and power control in single cell multiuser communications. In Proceedings of the IEEE international conference on communication (pp. 331–335), June 1995.

  11. Letaief, K. B., & Zhang, Y. (2006). Dynamic multiuser resource allocation and adaptation for wireless systems. IEEE Wireless Communication, 13, 38–47.

    Article  Google Scholar 

  12. Love, D., Heath, R., Lau, V. N., Gesbert, D., Rao, B., & Andrews, M. (2008). An overview of limited feedback in wireless communication systems. IEEE Journal on Selected Areas in Communications, 26, 1341–1365.

    Article  Google Scholar 

  13. Min, M., Kim, D., Kim, H., & Im, G. (2013). Opportunistic two-stage feedback and scheduling for MIMO downlink systems. IEEE Transactions on Communications, 61, 312–324.

  14. Peel, C. B., Hochwald, B. M., & Swindlehurst, A. L. (2005). A vectorperturbation technique for near-capacity multiantenna multiuser communication part i: Channel inversion and regularization. IEEE Transactions on Communications, 53, 195–202.

    Article  Google Scholar 

  15. Sfar, S., Dai, L., & Letaief, K. B. (2005). Optimal diversity-multiplexing tradeoff with group detection for MIMO systems. IEEE Transactions on Communications, 53, 1178–1190.

  16. Sharif, M., & Hassibi, B. (2005). On the capacity of MIMO broadcast channels with partial side information. IEEE Transactions on Information Theory, 51, 506–522.

  17. Swannack, C., Uysal-Biyikoglu, E., & Wornell, G. W. (2005). MIMO broadcast scheduling with limited channel state information. In Proceedings of annual allerton conference on communication: Control and computing, Sept. 2005.

  18. Telatar, E. (1999). Capacity of multi-antenna gaussian channels. European Transactions on Telecommunication, 10, 585–596.

    Article  Google Scholar 

  19. Vishwanath, S., Jindal, N., & Goldsmith, A. (2003). Duality, achievable rates and sum-rate capacity of gaussian MIMO broadcast channel. IEEE Transactions on Information Theory, 49, 2658–2668.

  20. Viswanath, P., Tse, D. N. C., & Laroia, R. (2002). Opportunistic beamforming using dumb antennas. IEEE Transactions on Information Theory, 48, 1277–1294.

    Article  MATH  MathSciNet  Google Scholar 

  21. Weingarten, H., Steinberg, Y., & Shamai, S. (2004). The capacity region of the gaussian MIMO broadcast channel, In Proceedings of the IEEE international symposium on information theory (p. 174), Chicago, IL, USA, June 27-July 2, 2004.

  22. Wunder, G., Schreck, J., & Jung, P. (2012). Nearly doubling the throughput of multiuser MIMO systems using codebook tailored limited feedback protocol. IEEE Transactions on Wireless Communication, 11, 3921–3931.

  23. Yoo, T., & Goldsmith, A. (2006). On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE Journal on Selected Areas in Communications, 24, 528–541.

    Article  Google Scholar 

  24. Zhang, W., & Letaief, K. B. (2007). MIMO broadcast scheduling with limited feedback. IEEE Journal on Selected Areas in Communications, 25, 1457–1467.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prabina Pattanayak.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pattanayak, P., Roy, K.M. & Kumar, P. Analysis of a New MIMO Broadcast Channel Limited Feedback Scheduling Algorithm with User Grouping. Wireless Pers Commun 80, 1079–1094 (2015). https://doi.org/10.1007/s11277-014-2072-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-014-2072-9

Keywords

Navigation