Skip to main content
Log in

Impacts of practical channel impairments on the downlink spectral efficiency of large-scale distributed antenna systems

  • Research Paper
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

Channel impairments are major limiting factors in the performance of large-scale antenna systems. In this paper, we analyze the impacts of practical channel impairments caused by pilot contamination, Doppler shift, and phase noise on the downlink spectral efficiency of large-scale distributed antenna systems (L-DASs) with maximum ratio transmission (MRT) and zero-forcing (ZF) beamforming, in which per user power normalization is considered. Using a joint channel model that allows study of the simultaneous impacts of these channel impairments, we derive accurate and tractable closed-form approximations for the ergodic achievable downlink rate, thereby enabling spectral efficiency analysis of L-DASs and an efficient evaluation of the impacts of the channel impairments. It is shown that channel impairments reduce the downlink spectral efficiency and have a significant impact on ZF beamforming. The asymptotic user rate limit is also determined, from which we analyze the asymptotic performance of L-DASs with channel impairments. The analytical results show that MRT and ZF beamforming achieve the same asymptotic performance limit even with channel impairments. It is also found that the use of a large-scale antenna array at the base station sides can weaken the impacts of channel impairments.

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.

Similar content being viewed by others

References

  1. Marzetta T L. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans Wirel Commun, 2010, 9: 3590–3600

    Google Scholar 

  2. Wang D, Zhang Y, Wei H, et al. An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications. Sci China Inf Sci, 2016, 59: 081301

    Google Scholar 

  3. Lu L, Li G Y, Swindlehurst A L, et al. An overview of massive MIMO: benefits and challenges. IEEE J Sel Top Signal Process, 2014, 8: 742–758

    Google Scholar 

  4. Rusek F, Persson D, Lau B K, et al. Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Signal Process Mag, 2013, 30: 40–60

    Google Scholar 

  5. Zhang J, Wen C K, Jin S, et al. On capacity of large-scale MIMO multiple access channels with distributed sets of correlated antennas. IEEE J Sel Areas Commun, 2013, 31: 133–148

    Google Scholar 

  6. Fernandes F, Ashikhmin A, Marzetta T L. Inter-cell interference in noncooperative TDD large scale antenna systems. IEEE J Sel Areas Commun, 2013, 31: 192–201

    Google Scholar 

  7. Adhikary A, Ashikhmin A, Marzetta T L. Uplink interference reduction in large scale antenna systems. In: Proceedings of IEEE International Symposium on Information Theory, Honolulu, 2014. 2529–2533

    Google Scholar 

  8. Wen C K, Jin S, Wong K K, et al. Channel estimation for massive MIMO using gaussian-mixture Bayesian learning. IEEE Trans Wirel Commun, 2015, 14: 1356–1368

    Google Scholar 

  9. Truong K T, Heath R W. Effects of channel aging in massive MIMO systems. J Commun Netw, 2013, 15: 338–351

    Google Scholar 

  10. Papazafeiropoulos A K, Ngo H Q, Matthaiou M, et al. Uplink performance of conventional and massive MIMO cellular systems with delayed CSIT. In: Proceedings of IEEE International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), Washington, 2014. 601–606

    Google Scholar 

  11. Papazafeiropoulos A K, Ratnarajah T. Deterministic equivalent performance analysis of time-varying massive MIMO systems. IEEE Trans Wirel Commun, 2015, 14: 5795–5809

    Google Scholar 

  12. Papazafeiropoulos A K. Impact of user mobility on optimal linear receivers in cellular networks. In: Proceedings of IEEE International Conference on Communications (ICC), London, 2015. 2239–2244

    Google Scholar 

  13. Guo K, Khodapanah B, Ascheid G. Performance analysis of downlink MMSE beamforming training in TDD MUmassive-MIMO. In: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), Doha, 2016

    Google Scholar 

  14. Pitarokoilis A, Moammed S K, Larsson E G. Achievable rates of ZF receivers in massive MIMO with phase noise impairments. In: Proceedings of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2013. 1004–1008

    Google Scholar 

  15. Pitarokoilis A, Mohammed S K, Larsson E G. Uplink performance of time-reversal MRC in massive MIMO systems subject to phase noise. IEEE Trans Wirel Commun, 2015, 14: 711–723

    Google Scholar 

  16. Bjornson E, Matthaiou M, Debbah M. Massive MIMO with non-ideal arbitrary arrays: hardware scaling laws and circuit-aware design. IEEE Trans Wirel Commun, 2015, 14: 4353–4368

    Google Scholar 

  17. Corvaja R, Armada A G. Phase noise degradation in massive MIMO downlink with zero-forcing and maximum ratio transmission precoding. IEEE Trans Veh Technol, 2016, 65: 8052–8059

    Google Scholar 

  18. Zhu J, Schober R, Bhargava V K. Physical layer security for massive MIMO systems impaired by phase noise. In: Proceedings of the 17th International Workshop on Signal Processing Advances inWireless Communications (SPAWC), Edinburgh, 2016

    Google Scholar 

  19. Larsson E, Edfors O, Tufvesson F, et al. Massive MIMO for next generation wireless systems. IEEE Commun Mag, 2014, 52: 184–195

    Google Scholar 

  20. Lee S R, Moon S H, Kim J S, et al. Capacity analysis of distributed antenna systems in a composite fading channel. IEEE Trans Wirel Commun, 2012, 11: 1076–1086

    Google Scholar 

  21. Zhu P, You X, Li J, et al. Spectral efficiency analysis of large-scale distributed antenna system in a composite correlated Rayleigh fading channel. IET Commun, 2015, 9: 681–688

    Google Scholar 

  22. Wang D M, You X H, Wang J Z, et al. Spectral efficiency of distributed MIMO cellular systems in a composite fading channel. In: Proceedings of IEEE International Conference on Communications (ICC’08), Prague, 2008. 1259–1264

    Google Scholar 

  23. Wang J, Dai L. Asymptotic rate analysis of downlink multi-user systems with co-located and distributed antennas. IEEE Trans Wirel Commun, 2015, 14: 3046–3058

    Google Scholar 

  24. Wang J, Dai L. Downlink rate analysis for virtual-cell based large-scale distributed antenna systems. IEEE Trans Wirel Commun, 2016, 15: 1998–2011

    Google Scholar 

  25. Björnson E, Matthaiou M, Pitarokoilis A, et al. Distributed massive MIMO in cellular networks: impact of imperfect hardware and number of oscillators. In: Proceedings of European Signal Processing Conference (EUSIPCO), Nice, 2015. 2436–2440

    Google Scholar 

  26. Papazafeiropoulos A K. Impact of general channel aging conditions on the downlink performance of massive MIMO. IEEE Trans Veh Technol, 2017, 66: 1428–1442

    Google Scholar 

  27. Li J M, Wang D M, Zhu P C, et al. Uplink spectral efficiency analysis of distributed massive MIMO with channel impairments. IEEE Access, 2017, 5: 5020–5030

    Google Scholar 

  28. Interdonato G, Ngo H Q, Larsson E G, et al. How much do downlink pilots improve cell-free massive MIMO? In: Proceedings of IEEE Global Communications Conference (GLOBECOM), Washington, 2016

    Google Scholar 

  29. Li J, Wang D, Zhu P, et al. Downlink spectral efficiency of distributed massive MIMO systems with linear beamforming under pilot contamination. IEEE Trans Veh Technol, 2018, 67: 1130–1145

    Google Scholar 

  30. Jakes W C. Microwave Mobile Communications. New York: Wiley, 1974

    Google Scholar 

  31. Krishnan R, Khanzadi M R, Krishnan N, et al. Linear massive MIMO precoders in the presence of phase noise–a large-scale analysis. IEEE Trans Veh Technol, 2016, 65: 3057–3071

    Google Scholar 

  32. Carvalho E de, Björnson E, Larsson E G, et al. Random access for massive MIMO systems with intra-cell pilot contamination. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016. 3361–3365

    Google Scholar 

  33. Truong K T, Lozano A, Heath R W, et al. Optimal training in continuous flat-fading massive MIMO systems. In: Proceedings of European Wireless Conference, Barcelona, 2014

    Google Scholar 

  34. Kay S M. Fundamental of Statistical Signal Processing: Estimation Theory. Englewood: Prentice-Hall, 1993

    MATH  Google Scholar 

  35. Jose J, Ashikhmin A, Marzetta T L, et al. Pilot contamination and precoding in multi-cell TDD systems. IEEE Trans Wirel Commun, 2011, 10: 2640–2651

    Google Scholar 

  36. Björnson E, Larsson E G, Marzetta T L. Massive MIMO: ten myths and one critical question. IEEE Commun Mag, 2016, 54: 114–123

    Google Scholar 

  37. Björnson E, Larsson E G, Debbah M. Massive MIMO for maximal spectral efficiency: how many users and pilots should be allocated? IEEE Trans Wirel Commun, 2016, 15: 1293–1308

    Google Scholar 

  38. Van Chien T, Bjornson E, Larsson E G. Joint power allocation and user association optimization for massive MIMO systems. IEEE Trans Wirel Commun, 2016, 15: 6384–6399

    Google Scholar 

  39. Hoydis J, Brink S ten, Debbah M. Massive MIMO in the UL/DL of cellular networks: how many antennas do we need? IEEE J Sel Areas Commun, 2013, 31: 160–171

    Google Scholar 

  40. Kammoun A, Muller A, Bjornson E, et al. Linear precoding based on polynomial expansion: large-scale multi-cell MIMO systems. IEEE J Sel Top Signal Process, 2014, 8: 861–875

    Google Scholar 

  41. Li J M, Wang D M, Zhu P C, et al. Downlink spectral efficiency of multi-cell multi-user large-scale DAS with pilot contamination. In: Proceedings of IEEE International Conference on Communications (ICC), London, 2015. 2011–2016

    Google Scholar 

  42. Heath J R W, Wu T, Kwon Y H, et al. Multiuser MIMO in distributed antenna systems with out-of-cell interference. IEEE Trans Signal Process, 2011, 59: 4885–4899

    MathSciNet  MATH  Google Scholar 

  43. Zhang J, Andrews J G. Adaptive spatial intercell interference cancellation in multicell wireless networks. IEEE J Sel Areas Commun, 2010, 28: 1455–1468

    Google Scholar 

  44. Hosseini K, Yu W, Adve R S. Large-scale MIMO versus network MIMO for multicell interference mitigation. IEEE J Sel Top Signal Process, 2014, 8: 930–941

    Google Scholar 

  45. Hosseini K, Yu W, Adve R S. Modeling and analysis of ergodic capacity in network MIMO systems. In: Proceedings of IEEE Globecom Workshops (GC Wkshps), Austin, 2014. 808–814

    Google Scholar 

  46. Hosseini K, Yu W, Adve R S. A stochastic analysis of network MIMO systems. IEEE Trans Signal Process, 2016, 64: 4113–4126

    MathSciNet  MATH  Google Scholar 

  47. Seifi N, Heath R W, Coldrey M, et al. Joint transmission mode and tilt adaptation in coordinated small-cell networks. In: Proceedings of IEEE International Conference on Communications Workshops (ICC), Sydney, 2016. 598–603

    Google Scholar 

Download references

Acknowledgements

This work was supported in part by National Natural Science Foundation of China (NSFC) (Grant Nos. 61501113, 61571120, 61271205, 61521061, 61372100,), and Jiangsu Provincial Natural Science Foundation (Grant Nos. BK20150630, BK20151415).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiamin Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, J., Wang, D., Zhu, P. et al. Impacts of practical channel impairments on the downlink spectral efficiency of large-scale distributed antenna systems. Sci. China Inf. Sci. 62, 22303 (2019). https://doi.org/10.1007/s11432-018-9413-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-018-9413-6

Keywords

Navigation