Skip to main content

Advertisement

Log in

An Approach for Data Rate Maximization and Interference Mitigation in Massive MIMO Communication Systems Using SRPWGC-PD Algorithm

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Increasing usage of wireless communication systems and demand for higher data speed is appealing newer generations of cellular communication systems to provide higher data rate along with a reliable system, i.e. system which is free from interference. 5G Communication systems are believed to provide at least ten times betterment in area throughput, i.e. data rate by increasing the spectral efficiency. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatial multiplexing of users and hence increases the spectral and energy efficiency. However, although Massive MIMO suppresses intra-cell interference and uncorrelated noise to a significant amount, it cannot mitigate the Pilot Contamination (PC) which is caused by reusing the same set of pilot signals in adjacent cells. In this paper, a new Pilot Decontamination (PD) technique, named as Softly Reused Pilot Weighted Graph Coloring-based Pilot Decontamination (SRPWGC-PD) has been introduced. In the proposed scheme, a scheme named soft pilot reusing is applied to separate the users in cells into two (inner and outer) zones, and then outer-zone users are allocated with orthogonal pilots; whereas a special pilot allocation scheme named weighted graph coloring algorithm is applied to the inner zone users to make generated PC as less as possible. Simulation and numerical analysis provide an insight that the proposed scheme outperforms in most of the performance indices, when compared to the existing schemes reported in the literature.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31

Similar content being viewed by others

References

  1. Younas, T., Li, J., & Arshad, J. (2017). Achieving bandwidth eiciency by improved zero-forcing combining algorithm in massive mimo. Wireless Personal Communications, 97(2), 2581–2596.

    Article  Google Scholar 

  2. Van Chien, T., & Björnson, E. (2017). Massive mimo communications. In 5G mobile communications. Springer (pp. 77–116).

  3. Marzetta, T. L., et al. (2010). Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Transactions on Wireless Communications, 9(11), 3590.

    Article  Google Scholar 

  4. Boroujerdi, M. N., Abbasfar, A., & Ghanbari, M. (2019). Cell free massive mimo with limited capacity fronthaul. Wireless Personal Communications, 104(2), 633–648.

    Article  Google Scholar 

  5. Wang, H., Huang, Y., Jin, S., Du, Y., & Yang, L. (2017). Pilot contamination reduction in multi-cell tdd systems with very large mimo arrays. Wireless Personal Communications, 96(4), 5785–5808.

    Article  Google Scholar 

  6. Rusek, F., Persson, D., Lau, B. K., Larsson, E. G., Marzetta, T. L., Edfors, O., & Tufvesson, F. (2012). Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE signal processing magazine, 30(1), 40–60.

  7. Fernandes, F., Ashikhmin, A., & Marzetta, T. L. (2013). Inter-cell interference in noncooperative tdd large scale antenna systems. IEEE Journal on Selected Areas in Communications, 31(2), 192–201.

    Article  Google Scholar 

  8. Yin, H., Gesbert, D., Filippou, M., & Liu, Y. (2013). A coordinated approach to channel estimation in large-scale multiple-antenna systems. IEEE Journal on Selected Areas in Communications, 31(2), 264–273.

    Article  Google Scholar 

  9. Wang, H., Pan, Z., Ni, J., & Chih-Lin, I. (2013) A spatial domain based method against pilot contamination for multi-cell massive mimo systems. In 2013 8th international conference on communications and networking in China (CHINACOM) (pp. 218–222). IEEE.

  10. Zhu, X., Wang, Z., Dai, L., & Qian, C. (2015). Smart pilot assignment for massive mimo. IEEE Communications Letters, 19(9), 1644–1647.

    Article  Google Scholar 

  11. Jose, J., Ashikhmin, A., Marzetta, T. L., & Vishwanath, S. (2011). Pilot contamination and precoding in multi-cell tdd systems. IEEE Transactions on Wireless Communications, 10(8), 2640–2651.

    Article  Google Scholar 

  12. Ngo, H. Q., & Larsson, E. G. (2012). EVD-based channel estimations for multicell multiuser mimo with very large antenna arrays. In IEEE international conference on acoustics, speed and signal processing (ICASSP, March 25-30, Kyoto, Japan (pp. 3249–3252). IEEE.

  13. Li, K., Song, X., Ahmad, M. O., & Swamy, M. (2014). An improved multicell MMSE channel estimation in a massive MIMO system. International Journal of Antennas and Propagation, 2014.

  14. Müller, R. R., Cottatellucci, L., & Vehkaperä, M. (2014). Blind pilot decontamination. IEEE Journal of Selected Topics in Signal Processing, 8(5), 773–786.

    Article  Google Scholar 

  15. Zhu, X., Dai, L., & Wang, Z. (2015). Graph coloring based pilot allocation to mitigate pilot contamination for multi-cell massive MIMO systems. IEEE Communications Letters, 19(10), 1842–1845.

    Article  Google Scholar 

  16. Zhu, X., Wang, Z., Qian, C., Dai, L., Chen, J., Chen, S., et al. (2016). Soft pilot reuse and multicell block diagonalization precoding for massive MIMO systems. IEEE Transactions on Vehicular Technology, 65(5), 3285–3298.

    Article  Google Scholar 

  17. Zhu, X., Dai, L., Wang, Z., & Wang, X. (2017). Weighted-graph-coloring-based pilot decontamination for multicell massive MIMO systems. IEEE Transactions on Vehicular Technology, 66(3), 2829–2834.

    Article  Google Scholar 

  18. Doshi, V., Shah, D., Médard, M., & Effros, M. (2010). Functional compression through graph coloring. IEEE Transactions on Information Theory, 56(8), 3901–3917.

    Article  MathSciNet  Google Scholar 

  19. Vieira, J., Malkowsky, S., Nieman, K., Miers, Z., Kundargi, N., Liu, L., et al. (2014). A flexible 100-antenna testbed for massive MIMO. In: IEEE globecom workshops (GC Wkshps), 2014 (pp. 287–293). IEEE.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jaitashri Poddar.

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

Poddar, J., Subhashini, K.R. An Approach for Data Rate Maximization and Interference Mitigation in Massive MIMO Communication Systems Using SRPWGC-PD Algorithm. Wireless Pers Commun 115, 499–525 (2020). https://doi.org/10.1007/s11277-020-07583-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-020-07583-w

Keywords

Navigation