Skip to main content
SpringerLink
Log in

Frame Structures for Massive MIMO Communications Under Channel Aging

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

We study the problem of optimizing the frame structure of a massive MIMO system under channel aging. We argue that the conventional TDD frame structure with lumped training is suboptimal under rapidly aging channels. We, therefore discuss a generalized frame structure allowing for the training of a fraction of the total number of users, with the conventional lumped and interspersed training frames as its special cases. We then derive the achievable uplink and downlink rates for this system, incorporating the cost for switching from uplink to downlink and vice versa. The analysis, and the subsequent numerical results clearly bring out the dependence of the rates achievable in a massive MIMO system on the choice of the frame structure.

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

References

  1. Narasimhan, T., & Chockalingam, A. (2014). Channel hardening-exploiting message passing (CHEMP) receiver in large-scale MIMO systems. IEEE Journal of Selected Topics in Signal Processing, 8, 847–860.

    Article  Google Scholar 

  2. Marzetta, T. L., Larsson, E. G., Yang, H., & Ngo, H. Q. (2016). Fundamentals of massive MIMO. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  3. Hoydis, J., ten Brink, S., & Debbah, M. (2013). Massive MIMO in the UL/DL of cellular networks: How many antennas do we need? IEEE Journal on Selected Areas in Communications, 31, 160–171.

    Article  Google Scholar 

  4. Blandino, S., Mangraviti, G., Desset, C., Bourdoux, A., Wambacq, P., & Pollin, S. (2019). Multi-user hybrid MIMO at 60 GHz using 16-antenna transmitters. IEEE Transactions on Circuits and Systems I: Regular Papers, 66, 848–858.

    Article  Google Scholar 

  5. Rahman, M., & Park, J.-D. (2018). The smallest form factor UWB antenna with quintuple rejection bands for iot applications utilizing RSRR and RCSRR. Sensors, 18, 911.

    Article  Google Scholar 

  6. Yin, H., Gesbert, D., Filippou, M., & Liu, Y. (2013). A coordinated approach to channel estimation in large-scale multiple-antenna systems. IEEE Journal on Selected Areas in Communications, 31, 264–273.

    Article  Google Scholar 

  7. Jose, J., Ashikhmin, A., Marzetta, T. L., & Vishwanath, S. (2011). Pilot contamination and precoding in multi-cell TDD systems. IEEE Transactions on Wireless Communications, 10, 2640–2651.

    Article  Google Scholar 

  8. Truong, K. T., & Heath, R. W. (2013). Effects of channel aging in massive MIMO systems. Journal of Communications and Networks, 15, 338–351.

    Article  Google Scholar 

  9. Papazafeiropoulos, A. K., & Ratnarajah, T. (2015). Deterministic equivalent performance analysis of time-varying massive MIMO systems. IEEE Transactions on Wireless Communications, 14, 5795–5809.

    Article  Google Scholar 

  10. Amarasuriya, G., & Poor, H. V. (2015). Impact of channel aging in multi-way relay networks with massive MIMO. In Proceedings of IEEE international conference on communications (ICC 2015), London, UK (pp. 1951–1957). June.

  11. Papazafeiropoulos, A. K. (2016). Impact of general channel aging conditions on the downlink performance of massive MIMO. IEEE Transactions on Vehicular Technology, 66, 1428–1444.

    Article  Google Scholar 

  12. Chopra, R., Murthy, C. R., & Suraweera, H. A. (2016). On the throughput of large MIMO beamforming systems with channel aging. IEEE Signal Processing Letters, 23, 1523–1527.

    Article  Google Scholar 

  13. Chopra, R., Murthy, C., Suraweera, H., & Larsson, E. (2018). Performance analysis of FDD massive MIMO systems under channel aging. IEEE Transactions on Wireless Communications, 17, 1094–1108.

    Article  Google Scholar 

  14. Kashyap, S., Mollén, C., Björnson, E., & Larsson, E. G. (2017). Performance analysis of TDD massive MIMO with Kalman channel predication. In Proceedings of international conference on acoustics, speech and signal processing (ICASSP 2017), New Orleans, LA (pp. 3554–3558). March.

  15. Arya, V., & Appaiah, K. (2018). Kalman filter based tracking for channel aging in massive MIMO systems. In 2018 International conference on signal processing and communications (SPCOM) (SPCOM 2018). Bangalore: Indian Institute of Science.

  16. Chopra, R. (2018). Uplink training for massive MIMO systems under channel aging. In 2018 International conference on signal processing and communications (SPCOM) (SPCOM 2018). Bangalore: Indian Institute of Science.

  17. Chen, L., Iellamo, S., & Coupechoux, M. (2011). Opportunistic spectrum access with channel switching cost for cognitive radio networks. In 2011 IEEE International conference on communications (ICC) (pp. 1–5). June.

  18. 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, 40–60.

    Article  Google Scholar 

  19. Jakes, W. C., & Cox, D. C. (Eds.). (1994). Microwave mobile communications. New York: Wiley.

    Google Scholar 

  20. Abramowitz, M., & Stegun, I. A. (1964). Handbook of mathematical functions with formulas, graphs, and mathematical tables (9th ed.). New York: Dover.

    MATH  Google Scholar 

  21. Hassibi, B., & Hochwald, B. M. (2003). How much training is needed in multiple-antenna wireless links? IEEE Transactions on Information Theory, 49, 951–963.

    Article  Google Scholar 

  22. Couillet, R., & Debbah, M. (2011). Random matrix methods for wireless communications (1st ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

Download references

Acknowledgements

Funding was provided by Indian Institute of Technology Guwahati (Grant No. xEEESUGIITG01212RBHU001).

Author information

Authors and Affiliations

  1. Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Anubhab Chowdhury & Ribhu Chopra

Authors
  1. Anubhab Chowdhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ribhu Chopra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ribhu Chopra.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chowdhury, A., Chopra, R. Frame Structures for Massive MIMO Communications Under Channel Aging. Wireless Pers Commun 111, 2659–2669 (2020). https://doi.org/10.1007/s11277-019-07008-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-07008-3

Keywords

Search

Navigation