access icon free 3D non-stationary unmanned aerial vehicles' MIMO channel model

The unmanned aerial vehicle (UAV) channel measurements have shown that the propagation environment of UAV channel is non-stationary. In this study, a three-dimensional (3D) non-stationary UAV multiple-input multiple-output (MIMO) channel model is proposed. In order to sufficiently describe the propagation environment of UAV-MIMO channel, the stationary scatterers and moving scatterers are investigated in the proposed model, which are mimicked using 3D cylinder and two-dimensional (2D) disc, respectively. The Doppler shifts associated with moving scatterers are also considered in the proposed model. The movement of UAV, receiver, and moving scatterers results in non-stationarities, and time-variant distances, azimuth angles, and elevation angles are investigated in the proposed model. The statistical properties of the moving scatterers are also investigated in the proposed channel model. In order to validate the proposed model, the spatial correlation is compared with the measurement results, and the numerical results show that the proposed channel model is applicable to describe the UAV-MIMO communication systems.

Inspec keywords: radiowave propagation; Doppler shift; telecommunication control; statistical analysis; autonomous aerial vehicles; radio receivers; wireless channels; MIMO communication

Other keywords: UAV-MIMO communication systems; moving scatterers; nonstationary UAV multiple-input multiple-output channel model; Doppler shifts; 2D disc; 3D nonstationary unmanned aerial vehicle MIMO channel model; UAV-MIMO channel propagation environment; stationary scatterers; 3D cylinder; two-dimensional disc; UAV-MIMO channel measurements; statistical properties; unmanned aerial vehicle channel measurements

Subjects: Radio links and equipment; Other topics in statistics; Radiowave propagation; Other topics in statistics; Control applications in radio and radar; Mobile robots

References

    1. 1)
      • 16. Zhu, Q., Jiang, K., Chen, X., et al: ‘A novel 3D non-stationary UAV-MIMO channel model and its statistical properties’, China Commun., 2018, 15, (12), pp. 147158.
    2. 2)
      • 22. Kyosti, P., Meinila, J., Hentila, L., et al: ‘WINNER II channel models’, WINNER II, Tech. Rep. IST-4-027756, Munich, Germany, April 2008, D1.1.2, v1.2.
    3. 3)
      • 12. Lian, Z., Jiang, L., He, C.: ‘A 3-D GBSM based on isotropic and non-isotropic scatterers for HAP-MIMO channel’, IEEE Commun. Lett., 2018, 22, (5), pp. 10901093.
    4. 4)
      • 6. Jin, K., Cheng, X., Ge, X., et al: ‘Three dimensional modeling and space-time correlation for UAV channels’. IEEE Vehicular Technology Conf. (VTC-Spring), Sydney, Australia, June 2017, pp. 15.
    5. 5)
      • 14. Cheng, X., Wang, C.-X., Cheng, X., et al: ‘An adaptive geometry-based stochastic model for non-isotropic MIMO mobile-to-mobile channels’, IEEE Trans. Wireless Commun., 2009, 8, (9), pp. 48244835.
    6. 6)
      • 15. Zajic, A.G.: ‘Impact of moving scatterers on vehicle-to-vehicle narrow-band channel characteristics’, IEEE Trans. Veh. Technol., 2014, 63, (7), pp. 30943106.
    7. 7)
      • 10. 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, (4), pp. 20572068.
    8. 8)
      • 13. Jiang, H., Zhang, Z., Wu, L., et al: ‘Three dimensional geometry-based UAV-MIMO channel modeling for A2G communication environments’, IEEE Commun. Lett., 2018, 22, (7), pp. 14381441.
    9. 9)
      • 11. Lian, Z., Jiang, L., He, C.: ‘A 3-D wideband model based on dynamic evolution of scatterers for HAP-MIMO channel’, IEEE Commun. Lett., 2017, 21, (3), pp. 684687.
    10. 10)
      • 20. Zhang, J., Pan, C., Pei, F., et al: ‘Three-dimensional fading channel models: A survey of elevation angle research’, IEEE Commun. Mag., 2014, 52, (6), pp. 218226.
    11. 11)
      • 7. Matolak, D.W., Sun, R.: ‘Air-ground channel characterization for unmanned aircraft systems-part I: methods, measurements, and models for over-water settings’, IEEE Trans. Veh. Technol., 2017, 66, (1), pp. 2644.
    12. 12)
      • 3. Romeu, J., Aguasca, A., Alonso, J., et al: ‘Small uav radiocommunication channel charcaterization’. Proc. the Fourth European Conf. on Antennas and Propagation, Barcelona, Spain, April 2010, pp. 15.
    13. 13)
      • 1. Matolak, D.W., Sun, R.: ‘Air-ground channel measurements and modeling for uas’. Proc. Integrated Communications, Navigation and Suriveillance Conf. (ICNC), Herndon, USA, April 2013, pp. 125.
    14. 14)
      • 9. Yuan, Y., Wang, C.-X., He, Y., et al: ‘3D wideband non-stationary geometry-based stochastic models for non-isotropic MIMO vehicle-to-vehicle channels’, IEEE Trans. Wirel. Commun., 2015, 14, (12), pp. 68836895.
    15. 15)
      • 19. Abdi, A., Kaveh, M.: ‘A space-time correlation model for multielement antenna systems in model fading channels’, IEEE J. Sel. Areas Commun., 2002, 20, (3), pp. 550560.
    16. 16)
      • 4. Michailidis, E.T., Kanatas, A.G.: ‘Three-dimensional HAP-MIMO channels: modeling and analysis of space-time correlation’, IEEE Trans. Veh. Technol., 2010, 59, (5), pp. 22322242.
    17. 17)
      • 2. Yanmaz, E., Kuschnig, R., Bettstetter, C.: ‘Channel measurements over 802.11a-based uav-to-ground links’. Proc. IEEE GLOBECOM Workshops (GC Wkshps), Houston, USA, December 2011, pp. 12801284.
    18. 18)
      • 18. Nikolaidis, V., Moraitis, N., Kanatas, A.G.: ‘Dual polarised MIMO LMS channel measurements and characterization in a pedestrian environment’. 10th European Conf. Antennas and Propagation (EuCAP), Davos, Switzerland, 2016.
    19. 19)
      • 21. Zajic, A.G., Stuber, G.L.: ‘Three-dimensional modeling and simulation of wideband MIMO mobile-to-mobile channels’, IEEE Trans. Wirel. Commun., 2009, 8, (3), pp. 12601275.
    20. 20)
      • 5. Zeng, L., Cheng, X., Wang, C.-X., et al: ‘A 3D geometry-based stochastic channel model for UAV-MIMO channels’. Proc. IEEE Wireless Communications and Networking Conf. (WCNC), San Francisco, USA, 2017, pp. 15.
    21. 21)
      • 17. Jiang, H., Zhang, Z., Wu, L., et al: ‘A non-stationary geometry-based scattering vehicle-to-vehicle MIMO channel model’, IEEE Commun. Lett., 2018, 22, (7), pp. 15101513.
    22. 22)
      • 8. Xiao, H., Burr, A.G., Song, L.: ‘A time-variant wideband spatial channel model based on the 3GPP model’. Proc. IEEE Vehicular Technology Conf. (VTC-Fall), Montreal, Canada, September 2006, pp. 15.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2019.0149
Loading

Related content

content/journals/10.1049/iet-com.2019.0149
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading