An Intelligent MIMO Hybrid Beamforming to Increase the Number of Users

  • M. PreethikaEmail author
  • S. Deepa
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)


The rate of the data demand is highly growing and number of user becomes high for utilizing the spectrum systematically, which can be made possible by using Multiuser MIMO. It allows the transmitter’s base station (BS) to contact at a time with more receivers of the mobile stations (MS) through similar resources of time and frequency. In enormous MIMO base station antennas will be in the order of tens or hundreds to increase streams of data confined inside the cell. In this paper MIMO system is designed using OFDM scattering model and simulated to analyse various parameters with different number of users and RF chains. MIMO system increases the data rate with increased number of users and minimizes loss in the system.


MIMO Hybrid beamforming MATLAB RF chains Number of users Error magnitude 


  1. 1.
    Molisch, A.F., et al.: Hybrid beamforming for massive MIMO: a survey. IEEE Commun. Mag. 55(9), 134–141 (2017)CrossRefGoogle Scholar
  2. 2.
    Ayach, O.E., Rajagopal, S., Abu-Surra, S., Pi, Z., Heath, R.: Spatially sparse precoding in millimeter wave MIMO systems. IEEE Trans. Wireless Commun. 13(3), 1499–1513 (2014)CrossRefGoogle Scholar
  3. 3.
    Alkhateeb, A., El Ayach, O., Leus, G., Heath Jr., R.W.: Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE J. Sel. Topics Signal Process. 8(5), 831–846 (2014)CrossRefGoogle Scholar
  4. 4.
    Ni, W., Dong, X., Lu, W.S.: Near-optimal hybrid processing for massive MIMO systems via matrix decomposition (2015).
  5. 5.
    Payami, S., Ghoraishi, M., Dianati, M.: Hybrid beamforming for large antenna arrays with phase shifter selection. IEEE Trans. Wireless Commun. 15(11), 7258–7271 (2016)CrossRefGoogle Scholar
  6. 6.
    Bogale, T.E., Le, L.B.: Beamforming for multiuser massive MIMO systems: Digital versus hybrid analog-digital. In: Proceedings IEEE Global Communication Conference (GLOBECOM 2014), pp. 4066–4071, December 2014Google Scholar
  7. 7.
    Liang, L., Xu, W., Dong, X.: Low-complexity hybrid precoding in massive multiuser MIMO systems. IEEE Wireless Commun. Lett. 3(6), 653–656 (2014)CrossRefGoogle Scholar
  8. 8.
    Alkhateeb, A., Leus, G., Heath Jr., R.W.: Limited feedback hybrid precoding for multi-user millimeter wave systems. IEEE Trans. Wireless Commun. 14(11), 6481–6494 (2015)CrossRefGoogle Scholar
  9. 9.
    Ni, W., Dong, X.: Hybrid block diagonalization for massive multiuser MIMO systems. IEEE Trans. Commun. 64(1), 201–211 (2016)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Song, N., Sun, H., Yang, T.: Coordinated hybrid beamforming for millimeter wave multi-user massive MIMO systems. In: Proceedings IEEE Global Communication Conference (GLOBECOM 2016), pp. 1–6, December 2016Google Scholar
  11. 11.
    Rajashekar, R., Hanzo, L.: Iterative matrix decomposition aided block diagonalization for mm-wave multiuser MIMO systems. IEEE Trans. Wireless Commun. 16(3), 1372–1384 (2017)CrossRefGoogle Scholar
  12. 12.
    Sohrabi, F., Yu, W.: Hybrid digital and analog beamforming design for large-scale MIMO systems. In: Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2929–2933, April 2015Google Scholar
  13. 13.
    Singh, J., Ramakrishna, S.: On the feasibility of codebook-based beamforming in millimeter wave systems with multiple antenna arrays. IEEE Trans. Wireless Commun. 14(5), 2670–2683 (2015)CrossRefGoogle Scholar
  14. 14.
    Wu, X., Liu, D., Yin, F.: Hybrid beamforming for multi-user massive MIMO systems. IEEE Trans. Commun. 66(9), 3878–3891 (2018)CrossRefGoogle Scholar
  15. 15.
    Li Z., Han, S., Molisch, A.F.: Hybrid beamforming design for millimeter-wave multi-user massive MIMO downlink. In: 2016 IEEE ICC Signal Processing for Communications Symposium (2016)Google Scholar
  16. 16.
    Adhikary, A., Nam, J., Ahn, J.-Y., Caire, G.: Joint spatial division and multiplexing - the large-scale array regime. IEEE Trans. Inf. Theory 59(10), 6441–6463 (2013)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Spencer, Q., Swindlehurst, A., Haardt, M.: Zero-Forcing methods for downlink spatial multiplexing in multiuser MIMO channels. IEEE Trans. Signal Process. 52(2), 461–471 (2004)MathSciNetCrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringPanimalar Engineering CollegeChennaiIndia

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