Skip to main content
Springer Nature Link
Log in

Angle Domain Massive MIMO-OFDMA Using a Scalar Channel Estimate

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Massive Multiple-Input Multiple-Output (MIMO) technology has the potential to deliver high spectral efficiencies by leveraging the ability to form narrow beams that can be resolve users based on location. Complexity is a significant barrier, particularly for massive MIMO systems employing orthogonal frequency division multiplexing (OFDM). This paper presents a simple technique for employing multiple-beamforming on the downlink of massive MIMO-OFDM systems. With a focus on practicability, the channel state information (CSI) is specified with only two scalar parameters, namely, beam angle and average channel signal to noise ratio. A novel channel estimation procedure is described, wherein, all mobile users will acquire CSI simultaneously using circularly-shifted pseudo-noise training sequences. The base station then performs an optimization task to identify suitable spectrum (or subcarriers) for each user. We have shown an iterative algorithm for orthogonal multiple access in this paper. Extension to non-orthogonal multiple access is straightforward. Simulation results are presented to show the behavior of our multiple-beam OFDM technique. We have considered only the cellular downlink in this paper.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014). Massive mimo for next generation wireless systems. IEEE Communications Magazine, 52, 186–195.

    Article  Google Scholar 

  2. Chen, S., & Zhao, J. (2014). The requirements, challenges, and technologies for 5g of terrestrial mobile telecommunication. IEEE Communications Magazine, 52, 36–43.

    Article  Google Scholar 

  3. Rusek, F. (2013). Scaling up mimo: Opportunities and challenges with very large arrays. IEEE Signal Processing Magazine, 30, 40–60.

    Article  Google Scholar 

  4. Krishna, S., Mishra, G., & Sharma, S. (2018). A series fed planar micro strip patch antenna array with 1-d beam steering for 5g spectrum massive mimo applications. In: Proceedings Radio and Wireless Symposium, pp. 1–5.

  5. Krishna, S., & Sharma, S. (2017). A dual polarization massive mimo panel array antenna at ka-band with beam forming capability. In Proceedings of URSI National Radio Science Meeting, pp. 1–5.

  6. Chen, S., Sun, S., Rao, Q., & Su, X. (2016). Adaptive beamforming in tdd-based mobile communication systems: State of the art and 5g research directions. IEEE Wireless Communications, 23, 81–87.

    Article  Google Scholar 

  7. Xia, M., Wu, Y.-C., & Aissa, S. (2012). Non-orthogonal opportunistic beamforming: Performance analysis and implementation. IEEE Transactions on Wireless Communications, 11, 1424–1433.

    Article  Google Scholar 

  8. Heath, R. W. Jr, González-Prelcic, N., Rangan, S., Roh, W., & Sayeed, A. M. (2016). An overview of signal processing techniques for millimeter wave mimo systems. IEEE Journal of Selected Topics in Signal Processing, 10, 436–453.

    Article  Google Scholar 

  9. Brady, J., Behdad, N., & Sayeed, A. (2013). Beamspace mimo for millimeter-wave communications: System architecture, modeling, analysis, and measurements. IEEE Transactions on Antennas and Propagation, 61, 3814–3827.

    Article  Google Scholar 

  10. Rao, X., Dai, L., Chen, Z., Wang, Z., & Zhang, Z. (2016). Near-optimal beam selection for beamspace mmwave massive mimo systems. IEEE Communications Letters, 20, 1054–1057.

    Article  Google Scholar 

  11. Sohrabi, F., & Yu, W. (2016). Hybrid digital and analog beamforming design for large-scale antenna arrays. IEEE Journal of Selected Topics in Signal Processing, 10, 501–513.

    Article  Google Scholar 

  12. Alkhateeb, A., El Ayach, O., Leus, G., & Heath, R. W. Jr. (2014). Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE Journal of Selected Topics in Signal Processing, 8, 831–846.

    Article  Google Scholar 

  13. Nguyen, D., Le, L., Le-Ngoc, T., & Heath, R. W. (2017). Hybrid mmse precoding and combining designs for mmwave multiuser systems. IEEE Access, 5, 19167–19181.

    Article  Google Scholar 

  14. You, L., Rao, X., Li, G., Xia, X., & Ma, N. (2017). Bdma for millimeter-wave/terahertz massive mimo transmission with per-beam synchronization. IEEE Journal on Selected Areas in Communications, 35, 1550–1553.

    Article  Google Scholar 

  15. Zhu, F., Rao, F., Jin, S., Lin, H., & Yao, M. (2018). Robust downlink beam forming for bdma massive mimo system. IEEE Transactions on Communications, 66, 1496–1507.

    Article  Google Scholar 

  16. Sun, C., Rao, X., & Ding, Z. (2017). Bdma in multicell massive mimo communications: Power allocation algorithms. IEEE Transactions on Signal Processing, 65, 2962–2974.

    Article  MathSciNet  Google Scholar 

  17. You, L., Rao, X., Li, G., Gia, X., & Mia, N. (2017). Bdma for millimeter-wave/terahertz massive mimo transmission for per-beam synchronization. IEEE Journal on Selected Areas in Communications, 35, 1550–1563.

    Article  Google Scholar 

  18. Nee, R., & Prasad, R. (2000). OFDM for wireless multimedia communications (1st ed.). Norwood: Artech House.

    Google Scholar 

  19. Caire, G., Taricco, G., & Biglieri, E. (1998). Bit-interleaved coded modulation. IEEE Transactions on Information Theory, 44, 927–946.

    Article  MathSciNet  Google Scholar 

  20. Wicker, S. B. (1995). Error control systems for digital communication and storage (1st ed.). Upper Saddle River: Prentice Hall.

    MATH  Google Scholar 

  21. Lathi, B. P., & Ding, Z. (2009). Principles of digital and analog communication (4th ed.). Oxford: Oxford University Press.

    Google Scholar 

  22. Proakis, J. G. (2001). Digital communications (4th ed.). New York: McGraw-Hill.

    MATH  Google Scholar 

  23. Benedetto, S., & Biglieri, E. (1999). Principles of digital transmission: With wireless applications. New York: Kluwer Academic/Plenum Publishers.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA, USA

    Santosh Nagaraj

Authors
  1. Santosh Nagaraj
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Santosh Nagaraj.

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

Nagaraj, S. Angle Domain Massive MIMO-OFDMA Using a Scalar Channel Estimate. Wireless Pers Commun 119, 617–627 (2021). https://doi.org/10.1007/s11277-021-08226-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08226-4

Keywords