Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A novel 3D GBSM for mmWave MIMO channels

  • 127 Accesses

  • 1 Citations


In this paper, a novel three dimensional (3D) wideband geometry-based stochastic model (GBSM) for millimeter wave (mmWave) multiple-input multiple-output (MIMO) channels is proposed. A homogeneous Poisson point process (PPP) is used to generate the clusters in 3D space. The transmitter (Tx) and receiver (Rx) are surrounded by two spheres. The scatterers distributed in the two spheres are introduced to mimic the clustering effects of multipath components (MPCs) in delay and angular domains. The large-scale path loss model and line-of-sight (LOS) probability model are taken into account to make the channel model realistic. In addition, mmWave channel measurements are conducted in an indoor environment. Simulation results based on the two-sphere channel model are compared with measurement results and good agreements are achieved, which validates the proposed channel model. The results indicate that the proposed channel model has good adaptivity and can model the mmWave channel accurately.

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


  1. 1

    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

  2. 2

    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

  3. 3

    Boccardi F, Heath R W, Lozano A, et al. Five disruptive technology directions for 5G. IEEE Commun Mag, 2014, 52: 74–80

  4. 4

    Wang C X, Wu S B, Bai L, et al. Recent advances and future challenges for massive MIMO channel measurements and models. Sci China Inf Sci, 2016, 59: 021301

  5. 5

    Ge X H, Tu S, Mao G Q, et al. 5G ultra-dense cellular networks. IEEE Wirel Commun, 2016, 23: 72–79

  6. 6

    Feng R, Huang J, Sun J, et al. A novel 3D frequency domain SAGE algorithm with applications to parameter estimation in mmWave massive MIMO indoor channels. Sci China Inf Sci, 2017, 60: 080305

  7. 7

    Yong S K. TG3c channel modeling sub-committee final report. IEEE Standard 802.15-07-0584-01-003c. 2007

  8. 8

    Maltsev A. Channel models for 60 GHz WLAN systems. IEEE Standard 802.11-09/0334r8. 2010

  9. 9

    Maltsev A. Channel models for IEEE 802.11ay. IEEE Standard 802.11-15/1150r9. 2016

  10. 10

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

  11. 11

    Spencer Q H, Jeffs B D, Jensen M A, et al. Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel. IEEE J Sel Areas Commun, 2000, 18: 347–360

  12. 12

    Maltsev A, Pudeyev A, Karls I, et al. Quasi-deterministic approach to mmWave channel modeling in a non-stationary environment. In: Proceedings of IEEE Globecom Workshops, Austin, 2014. 966–971

  13. 13

    Weiler R J, Peter M, Keusgen W, et al. Quasi-deterministic millimeter-wave channel models in MiWEBA. J Wirel Com Netw, 2016, 84: 1–16

  14. 14

    Kyösti P. WINNER II Channel Models. Hoboken: John Wiley & Sons, 2008

  15. 15

    Jaeckel S, Raschkowski L, Börner K, et al. QuaDRiGa: a 3-D multi-cell channel model with time evolution for enabling virtual field trials. IEEE Trans Antenn Propag, 2014, 62: 3242–3256

  16. 16

    Wu S B, Wang C X, Aggoune 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

  17. 17

    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

  18. 18

    Wu S B, Wang C X, Aggoune H M, et al. A general 3D non-stationary 5G wireless channel model. IEEE Trans Commun, 2018. doi: 10.1109/TCOMM.2017.2779128

  19. 19

    Wang C X, Bian J, Sun J, et al. A survey of 5G channel measurements and models. IEEE Commun Surv Tut, 2018. in press

  20. 20

    Bian J, Sun J, Wang C X, et al. A WINNER+ based 3-D non-stationary wideband MIMO channel model. IEEE Trans Wirel Commun, 2018, 17: 1755–1767

  21. 21

    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

  22. 22

    Yuan Y, Wang C X, He Y J, et al. 3D wideband non-stationary geometry-based stochastic models for non-isotropic MIMO vehicle-to-vehicle channels. IEEE Trans Wirel Commun, 2015, 14: 6883–6895

  23. 23

    Ghazal A, Wang C X, Ai B, et al. A nonstationary wideband MIMO channel model for high-mobility intelligent transportation systems. IEEE Trans Intel Transport Syst, 2014, 16: 885–897

  24. 24

    Ghazal A, Yuan Y, Wang C X, et al. A non-stationary IMT-advanced MIMO channel model for high-mobility wireless communication systems. IEEE Trans Wirel Commun, 2017, 16: 2057–2068

  25. 25

    Liu Y, Wang C X, Lopez C F, et al. 3D non-stationary wideband circular tunnel channel models for high-speed train wireless communication systems. Sci China Inf Sci, 2017, 60: 082304

  26. 26

    Zeng L Z, Cheng X, Wang C X, et al. A 3D geometry-based stochastic channel model for UAV-MIMO channels. In: Proceedings of IEEE Wireless Communications and Networking Conference, San Francisco, 2017

  27. 27

    Jiang H, Zhang Z C, Wu L, et al. Novel 3D irregular-shaped geometry-based channel modeling for semi-ellipsoid vehicle-to-vehicle scattering environments. IEEE Wirel Commun Lett, 2018. doi: 10.1109/LWC.2018.2829892

  28. 28

    Gustafson C, Haneda K, Wyne S, et al. On mm-wave multipath clustering and channel modeling. IEEE Trans Antenn Propag, 2014, 62: 1445–1455

  29. 29

    Haneda K, Järveläinen J, Karttunen A, et al. A statistical spatio-temporal radio channel model for large indoor environments at 60 and 70 GHz. IEEE Trans Antenn Propag, 2015, 63: 2694–2704

  30. 30

    Rappaport T S, MacCartney G R, Samimi M K, et al. Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design. IEEE Trans Commun, 2015, 63: 3029–3056

  31. 31

    Ko J, Cho Y J, Hur S, et al. Millimeter-wave channel measurements and analysis for statistical spatial channel model in in-building and urban environments at 28 GHz. IEEE Trans Wirel Commun, 2017, 16: 5853–5868

  32. 32

    Bai T Y, Heath R W. Analyzing uplink SINR and rate in massive MIMO systems using stochastic geometry. IEEE Trans Commun, 2016, 64: 4592–4606

  33. 33

    Andrews J G, Bai T Y, Kulkarni M N, et al. Modeling and analyzing millimeter wave cellular systems. IEEE Trans Commun, 2016, 65: 403–430

  34. 34

    Alkhateeb A, Nam Y H, Rahman M S, et al. Initial beam association in millimeter wave cellular systems: analysis and design insights. IEEE Trans Wirel Commun, 2017, 16: 2807–2821

  35. 35

    MacCartney G R, Samimi M K, Rappaport T S. Omnidirectional path loss models in New York City at 28 GHz and 73 GHz. In: Proceedings of IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communication, Washington, 2014. 227–231

  36. 36

    Järveläinen J, Nguyen S L H, Haneda K, et al. Evaluation of millimeter-wave line-of-sight probability with point cloud data. IEEE Wirel Commun Lett, 2016, 5: 228–231

  37. 37

    Pedersen T, Steinböck G, Fleury B H. Modeling of reverberant radio channels using propagation graphs. IEEE Trans Antenn Propag, 2012, 60: 5978–5988

  38. 38

    Wu X Y, Wang C X, Sun J, et al. 60-GHz millimeter-wave channel measurements and modeling for indoor office environments. IEEE Trans Antenn Propag, 2017, 65: 1912–1924

  39. 39

    Huang J, Wang C X, Feng R, et al. Multi-frequency mmWave massive MIMO channel measurements and characterization for 5G wireless communication systems. IEEE J Sel Areas Commun, 2017, 35: 1591–1605

  40. 40

    Zhang B, Zhong Z, Zhou X, et al. Path loss characteristics of indoor radio channels at 15 GHz. In: Proceedings of European Conference on Antennas and Propagation, Davos, 2016. 1–5

  41. 41

    Huang J, Feng R, Sun J, et al. Comparison of propagation channel characteristics for multiple millimeter wave bands. In: Proceedings of IEEE Vehicular Technology Conference, Sydney, 2017. 1–5

Download references


This work was supported by National Natural Science Foundation of China (Grant No. 61771293), Taishan Scholar Program of Shandong Province, EU H2020 ITN 5G Wireless Project (Grant No. 641985), EU FP7 QUICK Project (Grant No. PIRSES-GA-2013-612652), and EU H2020 RISE TESTBED Project (Grant No. 734325).

Author information

Correspondence to Cheng-Xiang Wang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Huang, J., Wang, C., Liu, Y. et al. A novel 3D GBSM for mmWave MIMO channels. Sci. China Inf. Sci. 61, 102305 (2018). https://doi.org/10.1007/s11432-018-9480-4

Download citation


  • 3D GBSM
  • mmWave channels
  • homogeneous PPP
  • LOS probability
  • channel measurements