Skip to main content
Log in

Average Transmit Power of Adaptive ZF Very Large Multi-user and Multi-antenna Systems

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this paper, we investigate adaptive zero-forcing uplink transmission for very large multi-user multi-antenna systems in Rayleigh fading environments. We assume that the number of antennas at the base station (denoted as \(M\)) is not less than the number of users (denoted as \(K\)) with each having single antenna, and power control can be done at the transmitter(s) as channel condition changes. Under constraints of individual rates and maximum transmit powers, we adopt the optimal transmit strategy of minimizing the total average transmit power (ATP). We derive and give individual ATP expressions for each link with short- and long-term rate constraints, respectively. Numerical results show that the individual ATP for each link with short term rate constraint is quite close to its long term counterpart when \(M-K\) is large, and its corresponding outage probability can be designed to be nearly zero at the same time. Finally, we present two simple adaptive transmission schemes with constant transmit power satisfying short- and long-term rate constraints, respectively. Both of them are easy to implement, and asymptotically optimal when \(M-K\) grows without bound.

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

Similar content being viewed by others

References

  1. Goldsmith, A., Jafar, S. A., Jindal, N., & Vishwanath, S. (2003). Capacity limits of MIMO channels. IEEE Journal on Selected Areas in Communications, 21(5), 684–702.

    Article  Google Scholar 

  2. Gesbert, D., Kountouris, M., Heath, R. W, Jr, Chae, C.-B., & Sälzer, T. (2007). Shifting the MIMO paradigm. IEEE Signal Processing Magazine, 24(5), 36–46.

    Article  Google Scholar 

  3. Peel, C. B., Hochwald, B. M., & Swindlehurst, A. L. (2005). A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization. IEEE Transactions on Communicatios, 53(1), 195–202.

    Article  Google Scholar 

  4. Yoo, T., & Goldsmith, A. (2006). On the optimality of multiantenna broadcast scheduling using zero-forcing beamming. IEEE Journal on Selected Areas in Communications, 24(3), 528–541.

    Article  Google Scholar 

  5. Wiesel, A., Eldar, Y. C., & Shamai, S. (2008). Zero-forcing precoding and generalized inverses. IEEE Transactions on Signal Processing, 56(9), 4409–4418.

    Article  MathSciNet  Google Scholar 

  6. Marzetta, T. L. (2010). Noncooperative cellular wireless with unlimited numbers of BS antennas. IEEE Transactions on Wireless Communications, 9(11), 3590–3600.

    Article  Google Scholar 

  7. Rusek, F., Persson, D., Lau, B. K., Larsson, E. G., Marzetta, T. L., Edfors, O., et al. (2013). Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE Signal Processing Magazine, 30(1), 40–60.

    Article  Google Scholar 

  8. Gao, X., Edfors, O., Rusek, F., & Tufvesson, F. (2011). Linear pre-coding performance in measured very-large MIMO channels. In Proceedings of the IEEE vehicular technology conference (VTC) (pp. 1–5). San Francisco, CA, US, Sept. 2011.

  9. Ngo, H. Q., Larsson, E. G., & Marzetta, T. L. (2013). Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Transactions on Communications, 61(4), 1436–1449.

    Article  Google Scholar 

  10. Matthaiou, M., Zhong, C., Mckay, M. R., & Ratnarajah, T. (2013). Sum rate analysis of ZF receivers in distributed MIMO systems. IEEE Journal on Selected Areas in Communications, 31(2), 180–191.

    Article  Google Scholar 

  11. Ngo, H. Q., Matthaiou, M., Duong, T. Q., & Larsson, E. G. (2013). Uplink performance analysis of multicell MU-SIMO systems with ZF receivers. IEEE Transactions on Vehicular Technology, 62(9), 4471–4483.

    Article  Google Scholar 

  12. Caire, G., & Kumar, K. R. (2007). Information theoretic foundations of adaptive code and modulation. Proceedings of the IEEE, 95(12), 2274–2298.

    Article  Google Scholar 

  13. Li, G. Y., Xu, Z., Xiong, C., Yang, C., Zhang, S., Chen, Y., et al. (2011). Energy-efficient wireless communications: Tutorial, survey, and open issues. IEEE Wireless Communications, 18(6), 28–35.

    Article  Google Scholar 

  14. Joung, J., Ho, C. K., & Sun, S. (2014). Spectral efficiency and energy efficiency of OFDM systems: Impact of power amplifiers and countermeasures. IEEE Journal on Selected Areas in Communications, 32(2), 208–220.

    Article  Google Scholar 

  15. Schbert, M., & Boche, H. (2004). Solution of the multiuser downlink beamforming problem with individual SINR constraints. IEEE Transactions on Vehicular Technology, 53(1), 18–28.

    Article  Google Scholar 

  16. Wang, P., & Li, P. (2011). On maximum eigenmode beamforming and multi-user gain. IEEE Transactions on Information Theory, 57(7), 4170–4186.

    Article  Google Scholar 

  17. Yue, D.-W., & Yuan, J. (2011). On the power of MIMO broadcast systems under SNR constraints with limited feedback. IEEE Transactions on Vehicular Technology, 60(1), 349–353.

    Article  Google Scholar 

  18. Matthaiou, M., Chatzidiamantis, N. D., Karagiannidis, G. K., & Nossek, J. A. (2011). ZF detectors over correlated K Fading MIMO channels. IEEE Trans. on Communicatios, 59(6), 1591–1603.

    Article  Google Scholar 

  19. Dohler, M., Heath, R. W, Jr, Lozano, A., Papadias, C. B., & Valenzuela, R. A. (2011). Is the PHY layer dead? IEEE Communications Magazine, 49(4), 159–165.

    Article  Google Scholar 

  20. Andrews, L. C. (1998). Speical functions of mathematics for engineering. Oxford: Oxford University Press.

    Google Scholar 

  21. Alouini, M.-S., & Goldsmith, A. J. (1999). Capacity of Rayleigh fading channels under different adaptive transmission and diversity-combining techniques. IEEE Transactions on Vehicular Technology, 48(4), 1165–1181.

    Article  Google Scholar 

  22. Mohammed, S. K., & Larsson, E. G. (2012). Single-user beamforming in large-scale MISO systems with per-antenna constant-envelope constraints: The doughnut channel. IEEE Transactions on Wireless Communicatios, 11(11), 3992–4005.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dian-Wu Yue.

Additional information

This work was presented in part at the 9th European Wireless Conference, Guildford, UK, April 16–18, 2013. This work was supported in part by the Scheme of Research Exchanges with China and India, the Royal Academy of Engineering, the Specialized Research Fund for the Doctoral Program of Higher Education under Grant 20132125110006, the National Natural Science Foundation of China under Grant 61371091 and 61301228, and the Fundamental Research Funds for the Central Universities under Grant 3132013334.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yue, DW., Sun, Y. Average Transmit Power of Adaptive ZF Very Large Multi-user and Multi-antenna Systems. Wireless Pers Commun 81, 1215–1232 (2015). https://doi.org/10.1007/s11277-014-2180-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-014-2180-6

Keywords

Navigation