Recent advances and future challenges for massive MIMO channel measurements and models

大规模多输入多输出通信系统的信道测量与建模的最新进展及未来挑战

Abstract

The emerging fifth generation (5G) wireless communication system raises new requirements on spectral efficiency and energy efficiency. A massive multiple-input multiple-output (MIMO) system, equipped with tens or even hundreds of antennas, is capable of providing significant improvements to spectral efficiency, energy efficiency, and robustness of the system. For the design, performance evaluation, and optimization of massive MIMO wireless communication systems, realistic channel models are indispensable. This article provides an overview of the latest developments in massive MIMO channel measurements and models. Also, we compare channel characteristics of four latest massive MIMO channel models, such as receiver spatial correlation functions and channel capacities. In addition, future challenges and research directions for massive MIMO channel measurements and modeling are identified.

创新点

大规模多输入多输出通信技术以其在提高频谱效率和能量效率方面的优越性,成为日前最受关注的5G关键技术之一。为了更好地设计、评价和优化大规模多输入多输出无线通信系统,一个贴合实际的信道模型是必不可少的。本文详尽地介绍了大规模多输入多输出通信系统的信道测量与建模的最新进展、未来挑战及研究方向,同时比较了四种最新的大规模多输入多输出信道模型的信道特性,比如接收端空间相关函数和信道容量。

This is a preview of subscription content, access via your institution.

References

  1. 1

    Nokia Networks. Looking ahead to 5G. White Paper. http://info.networks.nokia.com/LookingAheadto5G 5G Requirements wp.html

  2. 2

    Samsung. 5G vision. White Paper. http://www.samsung.com/global/business-images/insights/2015/Samsung-5GVision-2.pdf

  3. 3

    Dahlman E, Mildh G, Parkvall S, et al. 5G radio access. Ericsson Rev, 2014, 6: 1–7. http://sixtysix.wirelab.ericsson.net /res/thecompany/docs/publications/ericsson review/2014/er-5g-radio-access.pdf

    Google Scholar 

  4. 4

    Qualcomm. 1000x data challenge. White Paper. https://www.qualcomm.com/documents/1000x-mobile-data-challenge

  5. 5

    Huawei. 5G a technology vision. White Paper. https://www.huawei.com/ilink/en/download/HW 314849

  6. 6

    CMCC. CMCC technology vision 2020 plus. White Paper. http://www.gtigroup.org/CMCC Technology Vision 2020 Plus White Paper.pdf

  7. 7

    METIS. Scenarios, requirements and KPIs for 5G mobile and wireless system. http://publications.lib.chalmers.se /records/fulltext/213055/local 213055.pdf

  8. 8

    IMT-2020 Promotion Group. 5G visions and requirements. White Paper. http://www.imt-2020.cn/en/documents/listByQuery?currentPage=1&content=

  9. 9

    5GNOW. 5G cellular communications scenarios and system requirements. http://is-wireless.com/wp-content/uploads/2015/07/5GNOW-Deliverables-5G-Cellular-Communications-Scenarios-and-System-Requirements.pdf

  10. 10

    Wang C X, Haider F, Gao X, et al. Cellular architecture and key technologies for 5G wireless communication networks. IEEE Commun Mag, 2014, 52: 122–130

    Article  Google Scholar 

  11. 11

    Tse D, Viswanath P. Fundamentals of Wirless Communication. Cambridge: Cambridge University Press, 2005

  12. 12

    Larsson E G, Tufvesson F, Edfors O, et al. Massive MIMO for next generation wireless systems. IEEE Commun Mag, 2014, 52: 186–195

    Article  Google Scholar 

  13. 13

    Rusek F, Persson D, Lau B K, et al. Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Signal Processing Mag, 2012, 30: 40–60

    Article  Google Scholar 

  14. 14

    Ma Z, Zhang Z Q, Ding Z G, et al. Key techniques for 5G wireless communications: network architecture, physical layer, and MAC layer perspectives. Sci China Inf Sci, 2015, 58: 041301

    Google Scholar 

  15. 15

    Jungnickel V, Manolakis K, Zirwas W, et al. The role of small cells, coordinated multipoint, and massive MIMO in 5G. IEEE Commun Mag, 2014, 52: 44–51

    Article  Google Scholar 

  16. 16

    Osseiran A, Boccardi F, Braun V, et al. Scenarios for 5G mobile and wireless communications: the vision of the METIS project. IEEE Commun Mag, 2014, 52: 26–35

    Article  Google Scholar 

  17. 17

    Payami S, Tufvesson F. Channel measurements and analysis for very large array systems at 2.6 GHz. In: Proceedings of 6th European Conference on Antennas and Propagation (EUCAP), 2012, Prague. 1–8

    Google Scholar 

  18. 18

    Kyösti P, Meinilä J, Hentilä L, et al. WINNER D1.1.2 WINNER II channel models. ver 1.1, 2007

  19. 19

    Liu L, Oestges C, Poutanen J, et al. The COST 2100 MIMO channel model. IEEE Commun Mag, 2012, 19: 92–99

    Google Scholar 

  20. 20

    Zhu M F, Eriksson G, Tufvesson F. The COST 2100 channel model: parameterization and validation based on outdoor MIMO measurements at 300 MHz. IEEE Trans Wirel Commun, 2013, 12: 888–897

    Article  Google Scholar 

  21. 21

    Verdone R, Zanella A. Pervasive Mobile and Ambient Wireless Communications: COST Action 2100. London: Springer, 2012

    Google Scholar 

  22. 22

    Li J, Zhao Y. Channel characterization and modeling for large-scale antenna systems. In: Proceedings of 14th International Symposium on Communications and Information Technologies (ISCIT), Incheio, 2014. 559–563

    Google Scholar 

  23. 23

    Gao X, Edfors O, Rusek F, et al. Linear pre-coding performance in measured very-large MIMO channels. In: Proceedings of IEEE Vehicular Technology Conference (VTC Fall), San Francisco, 2011. 1–5

    Google Scholar 

  24. 24

    Hoydis J, Hoek C, Wild T, et al. Channel measurements for large antenna arrays. In: Proceedings of International Symposium on Wireless Communication Systems (ISWCS), Paris, 2012. 811–815

    Google Scholar 

  25. 25

    Shepard C, Yu H, Anand N, et al. Argos: practical many-antenna base stations. In: Proceedings of 18th Annual International Conference on Mobile Computing and Networking, Istanbul, 2012. 53–64

    Google Scholar 

  26. 26

    Bernland A, Gustafsson M. Estimation of spherical wave coefficients from 3-D positioner channel measurements. IEEE Antenn Wirel Propag Lett, 2012, 11: 608–611

    Article  Google Scholar 

  27. 27

    Rusek F, Edfors O, Tufvesson F. Indoor multi-user MIMO: measured user orthogonality and its impact on the choice of coding. In: Proceedings of 6th European Conference on Antennas and Propagation (EUCAP), Prague, 2012. 2289–2293

    Google Scholar 

  28. 28

    Payami S, Tufvesson F. Delay spread properties in a measured massive MIMO system at 2.6 GHz. In: Proceedings of IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), London, 2013. 53–57

    Google Scholar 

  29. 29

    Gao X, Edfors O, Rusek F, et al. Massive MIMO in real propagation environments. IEEE Trans Wirel Commun, in press

  30. 30

    Gao X, Tufvesson F, Edfors O, et al. Measured propagation characteristics for very-large MIMO at 2.6 GHz. In: Conference Record of 46th Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, 2012. 295–299

    Google Scholar 

  31. 31

    Chiu C Y, Yan J B, Murch R D. 24-port and 36-port antenna cubes suitable for MIMO wireless communications. IEEE Trans Antenn Propag, 2008, 56: 1170–1176

    Article  Google Scholar 

  32. 32

    Gao X, Edfors O, Liu J, et al. Antenna selection in measured massive MIMO channels using convex optimization. In: Proceedings of IEEE Global Communications Conference, Atlanta, 2013. 129–134

    Google Scholar 

  33. 33

    Vieira J, Rusek F, Tufvesson F. Reciprocity calibration methods for massive MIMO based on antenna coupling. In: Proceedings of IEEE Global Communications Conference, Austin, 2014. 3708–3712

    Google Scholar 

  34. 34

    Vieira J, Malkowsky S, Nieman K, el al. A flexible 100-antenna testbed for massive MIMO. In: Proceedings of IEEE Global Communications Conference, Austin, 2014. 1–7

    Google Scholar 

  35. 35

    Poon S Y, Ho M. Indoor multiple-antenna channel characterization from 2 to 8 GHz. In: Proceedings of IEEE International Conference on Communications, Anchorage, 2003. 3519–3523

    Google Scholar 

  36. 36

    Gao X, Glazunov A A, Weng J, et al. Channel measurement and characterization of interference between residential femto-cell systems. In: Proceedings of 5th European Conference on Antennas and Propagation (EUCAP), Rome, 2011. 3769–3773

    Google Scholar 

  37. 37

    Glazunov A A, Prasad S, Handel P. Experimental characterization of the propagation channel along a very large virtual array in a reverberation chamber. Prog Electromagn Res B, 2014, 59: 205–217

    Article  Google Scholar 

  38. 38

    Koivunen J, Almers P, Kolmonen V M, et al. Dynamic multi-link indoor MIMO measurements at 5.3 GHz. In: Proceedings of 2nd European Conference on Antennas and Propagation, Edinburgh, 2007. 1–6

    Google Scholar 

  39. 39

    Gao X, Tufvesson F, Edfors O. Massive MIMO channels-measurements and models. In: Proceedings of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2013. 280–284

    Google Scholar 

  40. 40

    Pi Z Y, Khan F. A millimeter-wave massive MIMO system for next generation mobile broadband. In: Proceedings of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2012. 693–698

    Google Scholar 

  41. 41

    Molisch A F, Tufvesson F. Propagation channel models for next-generation wireless communications systems. IEICE Trans Commun, 2014, E97-B: 2022–2034

    Article  Google Scholar 

  42. 42

    Zheng K, Ou S L, Yin X F. Massive MIMO channel models: a survey. Hindawi International J Antenn Propag, 2014. 1–10

    Google Scholar 

  43. 43

    Weichselberger W, Herdin H, Özcelik H, et al. A stochastic MIMO channel model with joint correlation of both link ends. IEEE Trans Commun, 2006, 5: 90–100

    Google Scholar 

  44. 44

    Mohammed S K, Larsson E G. Per-antenna constant envelope precoding for large multi-user MIMO systems. IEEE Trans Commun, 2013, 61: 1059–1071

    Article  Google Scholar 

  45. 45

    Zhang J W, Yuan X J, Ping L. Hermitian precoding for distributed MIMO systems with individual channel state information. IEEE J Sel Areas Commun, 2013, 31: 241–250

    Article  Google Scholar 

  46. 46

    Wen C K, Jin S, Wong K K. On the sum-rate of multiuser MIMO uplink channels with jointly-correlated Rician fading. IEEE Trans Commun, 2011, 59: 2883–2895

    Article  Google Scholar 

  47. 47

    Noh S, Zoltowski M D, Love D J. Pilot beam pattern design for channel estimation in massive MIMO systems. IEEE J Sel Top Signal Process, 2014, 8: 787–801

    Article  Google Scholar 

  48. 48

    Couillet R, Debbah M, Silverstein J W. A deterministic equivalent for the analysis of correlated MIMO multiple access channels. IEEE Trans Inf Theory, 2011, 57: 3493–3514

    MathSciNet  Article  Google Scholar 

  49. 49

    Taricco G. Asymptotic mutual information statistics of separately correlated Rician fading MIMO channels. IEEE Inf Theory, 2008, 54: 3490–3504

    MathSciNet  Article  MATH  Google Scholar 

  50. 50

    Riegler E, Taricco G. Asymptotic statistics of the mutual information for spatially correlated Rician fading MIMO channels with interference. IEEE Inf Theory, 2010, 56: 1542–1559

    MathSciNet  Article  Google Scholar 

  51. 51

    Veeravalli V V, Liang Y, Sayeed A M. Correlated MIMO wireless channels: capacity, optimal signaling, and asymptotics. IEEE Inf Theory, 2005, 51: 2058–2072

    MathSciNet  Article  MATH  Google Scholar 

  52. 52

    Zhang M, Smith P J, Shafi M. An extended one-ring MIMO channel model. IEEE Trans Wirel Commun, 2007, 6: 2759–2764

    Article  Google Scholar 

  53. 53

    Chen J, Lau V K N. Two-Tier precoding for FDD multi-Cell massive MIMO time-varying interference networks. IEEE J Sel Areas Commun, 2014, 32: 1230–1238

    Article  Google Scholar 

  54. 54

    Wu S, Wang C X, Aggoune E-H M, et al. A non-stationary 3-D wideband twin-cluster model for 5G massive MIMO channels. IEEE J Sel Areas Commun, 2014, 32: 1207–1218

    Article  Google Scholar 

  55. 55

    Wu S B, Wang C X, Aggoune E-H M. Non-stationary wideband channel models for massive MIMO systems. In: Proceedings of 2nd Symposium on Wireless Sensor and Cellular Networks, Jeddah, 2013. 1–8

    Google Scholar 

  56. 56

    Wu S B, Wang C X, Haas H, et al. A non-stationary wideband channel model for Massive MIMO communication systems. IEEE Trans Wirel Commun, 2015, 14: 1434–1446

    Article  Google Scholar 

  57. 57

    Raschkowski L, Kyosti P, Kusume K, et al. METIS channel models. https://www.metis2020.com/wp-content/uploads /deliverables/METIS D1.4 v1.0.pdf

  58. 58

    Ozcelik H, Czink N, Bonek E. What Makes a Good MIMO Channel Model? In: Proceedings of IEEE 61st Vehicular Technology Conference, Stockholm, 2005. 156–160

    Google Scholar 

  59. 59

    Sayeed A M. Deconstructing multiantenna fading channels. IEEE Trans Signal Process, 2002, 50: 2563–2579

    Article  Google Scholar 

  60. 60

    Medbo J, Borner K, Haneda K, et al. Channel modelling for the fifth generation mobile communications. In: Proceedings of 8th European Conference on Antennas and Propagation (EuCAP), Hague, 2014. 219–223

    Google Scholar 

  61. 61

    Andrews J G, Buzzi S, Choi W, et al. What will 5G be? IEEE J Sel Areas Commun, 2014, 32: 1065–1082

    Article  Google Scholar 

  62. 62

    Saleh A A M, Valenzuela R A. A statistical model for indoor multipath propagation. IEEE J Sel Areas Commun, 1987, 5: 128–137

    Article  Google Scholar 

  63. 63

    Molisch A F, Balakrishnan K, Cassioli D, et al. IEEE 802.15.4a channel model—final report. https://mentor.ieee.org /802.15/dcn/04/15-04-0662-04-004a-channel-model-final-report-r1.pdf

  64. 64

    Porcino D, Hirt W. Ultra-wideband radio technology: potential and challenges ahead. IEEE Commun Mag, 2003, 41: 66–74

    Article  Google Scholar 

  65. 65

    Fort A, Ryckaert J, Desset C, et al. Ultra-wideband channel model for communication around the human body. IEEE J Sel Areas Commun, 2006, 24: 927–933

    Article  Google Scholar 

  66. 66

    Molisch A F, Foerster J R, Pendergrass M. Channel models for ultrawideband personal area networks. IEEE Wirel Commun, 2004, 10: 14–21

    Article  Google Scholar 

  67. 67

    Maltsev A, Sadri A, Maslennikov R, et al. Channel models for 60 GHz WLAN systems. Doc.: IEEE 802.11-09/0334r6, 2010

  68. 68

    Rappaport T S, Sun S, Mayzus R, et al. Millimeter wave mobile communications for 5G cellular: it will work! IEEE Access, 2013, 1: 335–349

    Article  Google Scholar 

  69. 69

    3GPP TR 36.873. Study on 3D channel model for LTE. V2.0.0, 2014

  70. 70

    Cheng X, Yao Q, Wen M W, et al. Wideband channel modeling and ICI cancellation for vehicle-to-vehicle communication systems. IEEE J Sel Areas Commun, 2013, 31: 434–448

    Article  Google Scholar 

  71. 71

    Cheng X, Wang C X, Ai B, et al. Envelope level crossing rate and average fade duration of non-isotropic vehicle-tovehicle Ricean fading channels. IEEE Trans Intell Transp Syst, 2013, 15: 62–72

    Article  Google Scholar 

  72. 72

    Karedal J, Tufvesson F, Czink N, et al. A geometry-based stochastic MIMO model for vehicle-to-vehicle communications. IEEE Trans Wirel Commun, 2009, 8: 3646–3657

    Article  Google Scholar 

  73. 73

    Zajic A G, Stüber G L. Three-dimensional modeling and simulation of wideband MIMO mobile-to-mobile channels. IEEE Trans Wirel Commun, 2009, 8: 1260–1275

    Article  Google Scholar 

  74. 74

    Yuan Y, Wang C X, Cheng X, et al. Novel 3D geometry-based stochastic models for non-isotropic MIMO vehicle-tovehicle channels. IEEE Trans Wirel Commun, 2014, 13: 298–309

    Article  Google Scholar 

  75. 75

    Ghazal A, Wang C X, Ai B, et al. A nonstationary wideband MIMO channel model for high-mobility intelligent transportation systems. IEEE Trans Intell Transp Syst, 2015, 16: 885–897

    Google Scholar 

  76. 76

    Chen C, Zhong Z, Ai B. Stationarity intervals of time-variant channel in high speed railway scenario. China Commun, 2012, 9: 64–70

    Google Scholar 

  77. 77

    Wu S B, Wang C X, Aggoune E-H M, et al. A novel Kronecker-based stochastic model for massive MIMO channels. In: Proceedings of IEEE/CIC International Conference on Communications in China, Shenzhen, 2015

    Google Scholar 

  78. 78

    Chuah C N, Tse D N C, Kahn J M, et al. Capacity scaling in MIMO wireless systems under correlated fading. IEEE Trans Inf Theory, 2002, 48: 637–650

    MathSciNet  Article  MATH  Google Scholar 

  79. 79

    Wu S B, Wang C X, Aggoune E-H M, et al. A unified framework for 5G wireless channel models. IEEE Trans Wirel Commun, submitted for publication

  80. 80

    Tulino A M, Verdu S. Random matrix theory and wireless communications. Found Trends Commun Inf Theory, 2004, 1: 1–182

    Article  MATH  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Cheng-Xiang Wang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, CX., Wu, S., Bai, L. et al. Recent advances and future challenges for massive MIMO channel measurements and models. Sci. China Inf. Sci. 59, 1–16 (2016). https://doi.org/10.1007/s11432-015-5517-1

Download citation

Keywords

  • 5G
  • massive MIMO channel measurements
  • massive MIMO channel models
  • non-stationary statistical properties
  • channel capacity

Keywords

  • 021301

关键词

  • 5G
  • 大规模多输入多输出系统的信道测量
  • 信道建模
  • 非平稳统计特性,信道容量