Advertisement

MMSE algorithm based two stages hybrid precoding for millimeter wave massive MIMO systems

  • Sahar SaidEmail author
  • Waleed Saad
  • Mona Shokair
Article

Abstract

Millimeter wave (mm-wave) communications has been sighted as solution becoming strong technology for the fifth generation networks. That is because, it brings orders of degree higher spectrum than current cellular bands and helps applications that require weak latency. Massive MIMO is used to minimize the severe constraints enjoined by the excessive propagation loss for millimeter wave frequencies. Where, normal implementation of antenna arrays is transmitted to multiple users simultaneously. Due to hardware constraints in mm-wave systems, classical lower frequency precoding techniques are difficult to be applied at mm-wave. A proposed modified hybrid precoding is suggested for downlink massive MIMO mm-wave systems in this paper. The hybrid precoding consists of mixed of analog and digital processing which is based on minimum mean square error (MMSE) algorithm. Where, quantized beamstearing codebooks are used to produce the analog and digital beamforming vectors with small training and feedback overhead. Extensive simulation programs are executed to compare the performance of the proposed precoding scheme with analog beamforming performance at different digital baseband precoders such as zero forcing precoder. Moreover, studies on the impact of modified hybrid beamforming parameters on the system performance are done. These parameters such as; the number of BS antennas, the number of mobile station antennas, number of effective channel quantization bits and number of RF beamforming quantization bits. Besides, the impact of rate threshold on the coverage probability is studied under different values of NBS antennas. It is shown that the performance of the modified hybrid precoding using MMSE is very close to the single user performance with only 0.5 b/s/Hz performance degradation at SNR = − 5 dB.

Keywords

Massive MIMO ZF MMSE Millimeter wave 

References

  1. 1.
    Xiao, M., Mumtaz, S., Huang, Y., & Dai, L. (2017). Millimeter wave communications for future mobile networks. IEEE Journal on Selected Areas in Communications, 35(9), 1909–1935.CrossRefGoogle Scholar
  2. 2.
    Roh, W., Seol, J.-Y., Park, J., Lee, B., Lee, J., Kim, Y., et al. (2014). Millimeter-wave beamforming as an enabling technology for 5 g cellular communications: Theoretical feasibility and prototype results. IEEE Communications Magazine, 52(2), 106–113.CrossRefGoogle Scholar
  3. 3.
    Mumtaz, S., Rodriquez, J., & Dai, L. (2016). Mm-wave massive MIMO: A paradigm for 5G. Amsterdam: Elsevier.Google Scholar
  4. 4.
    Li, C., Zhang, J., & Letaief, K. B. (2014). Throughput and energy efficiency analysis of small cell networks with multi-antenna base stations. IEEE Transactions on Wireless Communications, 13(5), 2505–2517.CrossRefGoogle Scholar
  5. 5.
    Bartoli, G., Fantacci, R., Letaief, K., Marabissi, D., Privitera, N., Pucci, M., et al. (2014). Beamforming for small cell deployment in LTE-advanced and beyond. IEEE Wireless Communications, 21(2), 50–56.CrossRefGoogle Scholar
  6. 6.
    Venugpal, K., Valenti, M. C., & Health Jr., R. W. (2015). Device to device millimeter wave communications: Interference, coverage, rate and finite topologies. IEEE Transactions on Wireless Communications. arxiv preprint arxiv:1506.07158.Google Scholar
  7. 7.
    Kutty, S., Member, S., & Sen, D. (2016). Beamforming for millimeter wave communications: An inclusive survey. IEEE Communication Survey Tutorials, 18(2), 949–973.CrossRefGoogle Scholar
  8. 8.
    Ahmed, I., Khammari, H., & Shahid, A. (2018). A survey on hybrid beamforming techniques in 5G: Architecture and system model perspectives. IEEE Communications Surveys and Tutorials.  https://doi.org/10.1109/COMST.2018.2843719.Google Scholar
  9. 9.
    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(3), 501–513.CrossRefGoogle Scholar
  10. 10.
    Xue, Q., Fang, X., & Wang, C. X. (2017). Beamspace SU-MIMO for future millimeter wave wireless communications. IEEE Journal on Selected Areas in Communications, 35(7), 1564–1575.CrossRefGoogle Scholar
  11. 11.
    Sayeed, A., & Brady, J. (2016). Beamspace MIMO channel modeling and measurement: Methodology and results at 28 GHz. In IEEE Globecom workshops (pp. 1–6).Google Scholar
  12. 12.
    Xue, Q., Fang, X., & Xiao, M. (2018). Beam management for millimeter wave beamspace MU-MIMO systems. IEEE Transactions on Communications, 99, 1.CrossRefGoogle Scholar
  13. 13.
    Liu, C., Li, M., Hanly, S. V., Collings, I. B., & Whiting, P. (2017). Millimeter wave beam alignment: Large deviations analysis and design insights. IEEE Journal on Selected Areas in Communications, 35(7), 1619–1631.Google Scholar
  14. 14.
    Gao, X., Dai, L., Chen, Z., Wang, Z., & Zhang, Z. (2016). Near-optimal beam selection for beamspace mm-wave massive MIMO systems. IEEE Communications Letters, 20(5), 1054–1057.CrossRefGoogle Scholar
  15. 15.
    Xie, T., Dai, L., Gao, X., Yao, H., & Wang, X. (2017). On the power leakage problem in beamspace MIMO systems with lens antenna array. In Proceedings of IEEE 86th vehicular technology conference (IEEE VTC’17 Fall), Toronto, Canada.Google Scholar
  16. 16.
    Gao, X., Dai, L., Han, Sh, & Wang, X. (2017). Reliable beamspace channel estimation for millimeter-wave massive MIMO systems with lens antenna array. IEEE Transaction on Wireless Communications, 16(6010–6021), 2017.Google Scholar
  17. 17.
    Zhang, Y., & Zhang, R. (2016). Millimeter wave MIMO with lens antenna array: A new path division multiplexing paradigm. IEEE Transactions Communication, 64(4), 1557–1571.CrossRefGoogle Scholar
  18. 18.
    Molisch, A. F., Ratnam, V. V., Han, S., Li, Z., Nguyen, S. L. H., Li, L., et al. (2017). Hybrid beamforming for massive MIMO: A survey. IEEE Communications Magazine, 55(9), 134–141.CrossRefGoogle Scholar
  19. 19.
    Ni, W., & Dong, X. (2016). Hybrid block diagonalization for massive multiuser MIMO systems. IEEE Transactions on Communications, 64(1), 201–211.MathSciNetCrossRefGoogle Scholar
  20. 20.
    Alkhateeb, A., Leus, G., & Heath, R. W. (2015). Limited feedback hybrid precoding for multi-user millimeter wave systems. IEEE Transactions on Wireless Communications, 14(11), 6481–6494.CrossRefGoogle Scholar
  21. 21.
    Alkhateeb, A., El Ayach, O., Leus, G., & Heath, R. W. (2014). Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE Journal of Selected Topics in Signal Processing, 8(5), 831–846.CrossRefGoogle Scholar
  22. 22.
    Xu, G., Hsiang, C., & Ma, W. (2017). Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks. IEEE International Conference on Communications, 5, 13601–13616.Google Scholar
  23. 23.
    Shen, J.-C., Yu, X., Zhang, J., & Letaief, K. (2016). Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems. IEEE Journal of Selected Topics in Signal Processing, 10(3), 485–500.CrossRefGoogle Scholar
  24. 24.
    Liu, W., Li, M., Tian, X., Wang, Z., & Liu, Q. (2017). Iterative hybrid precoder and combiner design for mm-wave MIMO OFDM systems. IEEE Communications Letters, 21(7), 1581–1584.CrossRefGoogle Scholar
  25. 25.
    Rajashekar, R., & Hanzo, L. (2017). Iterative matrix decomposition aided block diagonalization for mm-wave multiuser MIMO systems. IEEE Transactions on Wireless Communications, 16(3), 1372–1384.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Nuclear Research CenterAtomic Energy AuthorityCairoEgypt
  2. 2.Electronic and Electrical Communications Department, Faculty of Electronic EngineeringMenoufia UniversityMenoufEgypt
  3. 3.Electrical Engineering Department, College of EngineeringShaqra UniversityDawadmiSaudi Arabia

Personalised recommendations