Group layer MU-MIMO for 5G wireless systems


Multiple-input multiple-output (MIMO) and nonorthogonal multiple access technologies are considered as fundamental components to meet the high spectral efficiency requirements of the forthcoming 5G wireless systems and beyond. In this context, group layer multiuser MIMO (GL-MU-MIMO) scheme has been proposed by the authors with linear group multiuser detection and receive antenna selection (RAS) to increase the number of simultaneously and reliably connected users more than the utilized number of radio frequency chains at the base station. In this paper, we derive the sum rate and capacity region expressions for GL-MU-MIMO uplink Rayleigh fading channels to demonstrate the impact of power allocation on the system performance and user-fairness. In addition, two low complexity RAS algorithms are proposed to maximize the sum rate of designed users’ groups and overall channel capacity. These techniques are utilized for new dynamic user grouping, RAS, and power allocation strategy to optimize the system performance under total received power and minimum user rate constrains. Compared with the generic MU-MIMO, numerical simulations demonstrate valuable tradeoffs between user overloading, complexity, and achieved performance through efficient utilization of groups’ power allocation. The new outcomes of GL-MU-MIMO extends the state-of-the-art towards diverse multi-antenna applications for future communications.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11


  1. 1.

    Ji, H., Kim, Y., Lee, J., Onggosanusi, E., Nam, Y., Zhang, J., et al. (2017). Overview of full-dimension MIMO in LTE-Advanced Pro. IEEE Communications Magazine, 55(2), 176–184.

    Article  Google Scholar 

  2. 2.

    Lien, S.-Y., Shieh, S.-L., Huang, Y., Su, B., Hsu, Y.-L., & Wei, H.-Y. (2017). 5G new radio: Waveform, frame structure, multiple access, and initial access. IEEE Communications Magazine, 55(6), 64–71.

    Article  Google Scholar 

  3. 3.

    Al-Hussaibi, W., & Ali, F. (2018). A closed-form approximation of correlated multiuser MIMO ergodic capacity with antenna selection and imperfect channel estimation. IEEE Transactions on Vehicular Technology, 67(6), 5515–5519.

    Article  Google Scholar 

  4. 4.

    Pätzold, M. (2018). Countdown to the full-scale development of 5G new radio. IEEE Vehicular Technology Magazine, 13(2), 7–13.

    Article  Google Scholar 

  5. 5.

    Al-Hussaibi, W., & Ali, F. (2018). Extending the user capacity of MU-MIMO with low detection complexity and receive diversity. Wireless Networks, 24(6), 2237–2249.

    Article  Google Scholar 

  6. 6.

    Bjornson, E., Larsson, E., & Debbah, M. (2016). Massive MIMO for maximal spectral efficiency: How many users and pilots should be allocated. IEEE Transactions on Wireless Communications, 15(2), 1293–1308.

    Article  Google Scholar 

  7. 7.

    Miao, G. (2013). Energy-efficient uplink multi-user MIMO. IEEE Transactions on Wireless Communications, 12(5), 2302–2313.

    Article  Google Scholar 

  8. 8.

    Al-Hussaibi, W., & Ali, F. (2016). Constellation constrained MU-MIMO system for higher sum rate capacity and error performance over correlated channels. Wireless Communications and Mobile Computing, 16(6), 717–732.

    Article  Google Scholar 

  9. 9.

    Dai, L., Wang, B., Ding, Z., Wang, Z., Chen, S., & Hanzo, L. (2018). A survey of non-orthogonal multiple access for 5G. IEEE Communications Surveys & Tutorials, 20(3), 2294–2323.

    Article  Google Scholar 

  10. 10.

    Lei, L., Yuan, D., & Varbrand, P. (2016). On power minimization for non-orthogonal multiple access (NOMA). IEEE Communications Letters, 20(12), 2458–2461.

    Article  Google Scholar 

  11. 11.

    Ding, Z., Liu, Y., Choi, J., Sun, Q., Elkashlan, M., Chih-Lin, I., et al. (2017). Application of non-orthogonal multiple access in LTE and 5G networks. IEEE Communications Magazine, 55(2), 185–191.

    Article  Google Scholar 

  12. 12.

    Gao, X., Edfors, O., Rusek, F., & Tufvesson, F. (2015). Massive MIMO performance evaluation based on measured propagation data. IEEE Transactions on Wireless Communications, 14(7), 3899–3911.

    Article  Google Scholar 

  13. 13.

    Mehta, N. B., Kashyap, S., & Molisch, A. F. (2012). Antenna selection in LTE: From motivation to specification. IEEE Communications Magazine, 50(10), 144–150.

    Article  Google Scholar 

  14. 14.

    Chih-Lin, I., Rowell, C., Han, S., Xu, Z., Li, G., & Pan, Z. (2014). Toward green and soft: A 5G perspective. IEEE Communications Magazine, 52(2), 66–73.

    Article  Google Scholar 

  15. 15.

    Zhang, P., Chen, S., & Hanzo, L. (2015). Two-tier channel estimation aided near-capacity MIMO transceivers relying on norm-based joint transmit and receive antenna selection. IEEE Transactions on Wireless Communications, 14(1), 122–137.

    Article  Google Scholar 

  16. 16.

    Al-Hussaibi, W., & Ali, F. (2013). Fast receive antenna selection for spatial multiplexing MIMO over correlated Rayleigh fading channels. Wireless Personal Communications, 70(4), 1243–1259.

    Article  Google Scholar 

  17. 17.

    Xu, Z., Sfar, S., & Blum, R. (2009). Analysis of MIMO systems with receive antenna selection in spatially correlated Rayleigh fading channels. IEEE Transactions on Vehicular Technology, 58(1), 251–262.

    Article  Google Scholar 

  18. 18.

    Zhang, Y., Ji, C., Malik, W., O’Brien, D., & Edwards, D. (2009). Receive antenna selection for MIMO systems over correlated fading channels. IEEE Transactions on Wireless Communications, 8(9), 4393–4399.

    Article  Google Scholar 

  19. 19.

    Lim, B., Krzymien, W., & Schlegel, C. (2009). Efficient sum rate maximization and resource allocation in block-diagonalized space-division multiplexing. IEEE Transactions on Vehicular Technology, 58(1), 478–484.

    Article  Google Scholar 

  20. 20.

    Dai, L., Sfar, S., & Letaief, K. (2006). Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels. IEEE Transactions on Communications, 54(3), 563–573.

    Article  Google Scholar 

  21. 21.

    Al-Hussaibi, W., & Ali, F. (2011). Receive antenna selection for uplink multiuser MIMO systems over correlated Rayleigh fading channels. In Proceedings of 14th WPMC’11, Brest, France, October 3–7, 2011.

  22. 22.

    Gao, X., Edfors, O., Tufvesson, F., & Larsson, E. (2015). Massive MIMO in real propagation environments: Do all antennas contribute equally? IEEE Transactions on Communications, 63(11), 3917–3928.

    Article  Google Scholar 

  23. 23.

    Gao, X., Edfors, O., Tufvesson, F., & Larsson, E. (2015). Multi-switch for antenna selection in massive MIMO. In Proceedings of IEEE GLOBCOM conference, San Diego, USA, December 2015.

  24. 24.

    Amadori, P., & Masouros, C. (2016). Interference-driven antenna selection for massive multiuser MIMO. IEEE Transactions on Vehicular Technology, 65(8), 5944–5958.

    Article  Google Scholar 

  25. 25.

    Mi, D., Dianati, M., Muhaidat, S., & Chen, Y. (2015). A novel antenna selection scheme for spatially correlated massive MIMO uplinks with imperfect channel estimation. In Proceedings of 81st IEEE VTC Spring, Glasgow, May 2015.

  26. 26.

    Yang, Z., Ding, Z., Fan, P., & Al-Dhahir, N. (2016). A general power allocation scheme to guarantee quality of service in downlink and uplink NOMA systems. IEEE Transactions on Wireless Communications, 15(11), 7244–7257.

    Article  Google Scholar 

  27. 27.

    Ding, Z., Adachi, F., & Poor, H. (2016). The application of MIMO to non-orthogonal multiple access. IEEE Transactions on Wireless Communications, 15(1), 537–552.

    Article  Google Scholar 

  28. 28.

    Xie, H., Wang, B., Gao, F., & Jin, S. (2016). A full-space spectrum-sharing strategy for massive MIMO cognitive radio systems. IEEE Journal on Selected Areas in Communications, 34(10), 2537–2549.

    Article  Google Scholar 

  29. 29.

    Clarke, P., & de Lamare, R. (2012). Transmit diversity and relay selection algorithms for multirelay cooperative MIMO systems. IEEE Transactions on Vehicular Technology, 61(3), 1084–1098.

    Article  Google Scholar 

  30. 30.

    Liu, Y., Ding, Z., Elkashlan, M., & Poor, H. V. (2016). Cooperative non-orthogonal multiple access with simultaneous wireless information and power transfer. IEEE Journal on Selected Areas in Communications, 34(4), 938–953.

    Article  Google Scholar 

  31. 31.

    Liu, Y., Pan, G., Zhang, H., & Song, M. (2016). On the capacity comparison between MIMO-NOMA and MIMO-OMA. IEEE Access, 4, 2123–2129.

    Article  Google Scholar 

  32. 32.

    Sun, Q., Han, S., Chih-Lin, I., & Pan, Z. (2015). On the ergodic capacity of MIMO NOMA systems. IEEE Wireless Communications Letters, 4(4), 405–408.

    Article  Google Scholar 

  33. 33.

    Choi, J. (2016). On the power allocation for MIMO-NOMA systems with layered transmissions. IEEE Transactions on Wireless Communications, 15(5), 3226–3237.

    Article  Google Scholar 

  34. 34.

    Ali, M. S., Hossain, E., & Kim, D. (2017). Non-orthogonal multiple access (NOMA) for downlink multiuser MIMO systems: User clustering, beamforming, and power allocation. IEEE Access, 5, 565–577.

    Article  Google Scholar 

  35. 35.

    Liu, Y., Elkashlan, M., Ding, Z., & Karagiannidis, G. (2016). Fairness of user clustering in MIMO non-orthogonal multiple access systems. IEEE Communications Letters, 20(7), 1465–1468.

    Google Scholar 

  36. 36.

    Soysal, A., & Ulukus, S. (2010). Joint channel estimation and resource allocation for MIMO systems—Part II: Multi-user and numerical analysis. IEEE Transactions on Wireless Communications, 9(2), 632–640.

    Article  Google Scholar 

  37. 37.

    Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communication. Cambridge: Cambridge University Press.

    Google Scholar 

  38. 38.

    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 

  39. 39.

    Al-Hussaibi, W., & Ali, F. (2012). Generation of correlated Rayleigh fading channels for accurate simulation of promising wireless communication systems. Simulation Modelling Practice and Theory, 25(4), 56–72.

    Article  Google Scholar 

  40. 40.

    Ding, Z., Dai, L., & Poor, V. H. (2016). MIMO-NOMA design for small packet transmission in the internet of things. IEEE Access, 4, 1393–1405.

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Walid A. Al-Hussaibi.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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

Verify currency and authenticity via CrossMark

Cite this article

Al-Hussaibi, W.A., Ali, F.H. Group layer MU-MIMO for 5G wireless systems. Telecommun Syst 70, 525–540 (2019).

Download citation


  • Nonorthogonal multiple access (NOMA)
  • User overloading
  • Channel capacity
  • Antenna selection
  • 5G systems