Advertisement

Wireless Networks

, Volume 25, Issue 1, pp 75–85 | Cite as

Joint precoding and scheduling algorithm for massive MIMO in FDD multi-cell network

  • Bin HanEmail author
  • Zheng Jiang
  • Lin Liang
  • Peng Chen
  • Fengyi Yang
  • Qi Bi
Article

Abstract

Massive multiple-input multiple-output (MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional antenna array, is one of the most promising technologies to improve the spectral efficiency of the fifth generation mobile communication systems (5G). Since there is no short-term channel reciprocity, the frequency-division duplexing (FDD) massive MIMO system has to obtain channel state information with the help of uplink feedback with acceptable overhead. To cope with this issue, we propose the design of joint precoding and scheduling algorithm in FDD multi-cell network. In the algorithm, all the users are firstly grouped by the statistics of channel correlation matrix, then the inter-group interference exiting among intra-cell and inter-cell is eliminated at the first precoding stage. Then users are adaptively scheduled and beamformed at the second precoding stage based on the low dimension effective channel. Finally, the effectiveness of the proposed algorithm is presented through simulations.

Keywords

5G Massive MIMO Resource allocation Power allocation Scheduling 

Notes

Acknowledgements

This work was supported by the State Major Science and Technology Special Projects (Grant No. 2016ZX03001001-005).

References

  1. 1.
    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(1), 40–60.CrossRefGoogle Scholar
  2. 2.
    Zhang, H., Dong, Y., Cheng, J., Hossain, Md J, & Leung, V. C. M. (2016). Fronthauling for 5G LTE-U ultra dense cloud small cell networks. IEEE Wireless Communications, 23, 48–53.CrossRefGoogle Scholar
  3. 3.
    Lu, L., Li, G. Y., Lee Swindlehurst, A., Ashikhmin, A., & Zhang, R. (2014). An overview of massive MIMO: Benefits and challenges. IEEE Journal of Selected Topics in Signal Processing, 8(5), 742–758.CrossRefGoogle Scholar
  4. 4.
    Guo, K., Guo, Y., & Ascheid, G. (2013). On the performance of EVD-based channel estimations in MU-massive-MIMO systems. In Proceedings of IEEE personal indoor and mobile radio communications (PIMRC 2013), London, UK, pp. 1376–1380.Google Scholar
  5. 5.
    Jose, J., Ashikhmin, A., Marzetta, T., & Vishwanath, S. (2011). Pilot contamination and precoding in multi-cell TDD systems. IEEE Transactions on Wireless Communications, 10(8), 2640–2651.CrossRefGoogle Scholar
  6. 6.
    Dahrouj, H., & Yu, W. (2010). Coordinated beamforming for the multicell multi-antenna wireless system. IEEE Transactions on Wireless Communications, 9(5), 1748–1759.CrossRefGoogle Scholar
  7. 7.
    Shi, Q., Razaviyayn, M., Luo, Z.-Q., & He, C. (2011). An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel. IEEE Transactions on Signal Processing, 59(9), 4331–4340.MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Adhikary, A., Nam, J., Ahn, J.-Y., & Caire, G. (2013). Joint spatial division and multiplexing—The large-scale array regime. IEEE Transactions on Information Theory, 59(10), 6441–6463.MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Nam, J., Adhikary, A., Ahn, J. Y., & Caire, G. (2014). Joint spatial division and multiplexing: Opportunistic beamforming and user grouping. IEEE Journal of Selected Topics in Signal Processing, 8, 876–890.CrossRefGoogle Scholar
  10. 10.
    Chalise, B. K., Haering, L., & Czylwik, A. (2004). Robust uplink to downlink spatial covariance matrix transformation for downlink beamforming. In International Zurich seminar on communications, pp. 204–207.Google Scholar
  11. 11.
    Hugl, K., Kalliola, K., & Laurila, J. (2002). Spatial reciprocity of uplink and downlink radio channels in FDD systems. European Cooperation in the field of scientific and technical research, May, 2002.Google Scholar
  12. 12.
    Spencer, Q. H., Swindlehurst, A. L., & Haardt, M. (2004). Zero-forcing methods for downlink spatial multiplexing in multi-user MIMO channel. IEEE Transaction on Signal Processing, 52, 461–471.CrossRefzbMATHGoogle Scholar
  13. 13.
    Kim, H., Yu, H., Sung, Y., & Lee, Y. H. (2012). An efficient algorithm for zero-forcing coordinated beamforming. IEEE Communications Letters, 16(7), 994–997.CrossRefGoogle Scholar
  14. 14.
    Xu, Y., Yue, G., Prasad, N., Rangarajan, S., & Mao, S. (June 2014). User grouping and scheduling for large scale MIMO systems with two-stage precoding, In Proceedings of IEEE ICC. Sydney, Australia (pp. 5208–5213).Google Scholar
  15. 15.
    Molisch, A. F. (2010). Wireless Communications. (Vol. 15). New York, NY, USA: Wiley.Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.China Telecom Technology Innovation CenterBeijingChina

Personalised recommendations