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Stochastic Channel Modeling for Railway Tunnel Scenarios at 25 GHz

  • He, Danping (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications) ;
  • Ai, Bo (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications) ;
  • Guan, Ke (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications) ;
  • Zhong, Zhangdui (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications) ;
  • Hui, Bing (5G Giga Service Research Laboratory, ETRI) ;
  • Kim, Junhyeong (5G Giga Service Research Laboratory, ETRI, School of Electrical Engineering, Korea Advanced Institute of Science and Technology) ;
  • Chung, Heesang (5G Giga Service Research Laboratory, ETRI) ;
  • Kim, Ilgyu (5G Giga Service Research Laboratory, ETRI)
  • Received : 2017.09.15
  • Accepted : 2017.11.30
  • Published : 2018.02.01

Abstract

More people prefer using rail traffic for travel or for commuting owing to its convenience and flexibility. The railway scenario has become an important communication scenario in the fifth generation era. The communication system should be designed to support high-data-rate demands with seamless connectivity at a high mobility. In this paper, the channel characteristics are studied and modeled for the railway tunnel scenario with straight and curved route shapes. On the basis of measurements using the "Mobile Hotspot Network" system, a three-dimensional ray tracer (RT) is calibrated and validated for the target scenarios. More channel characteristics are explored via RT simulations at 25.25 GHz with a 500-MHz bandwidth. The key channel parameters are extracted, provided, and incorporated into a 3rd-Generation-Partnership-Project-like stochastic channel generator. The necessary channel information can be practically realized, which can support the link-level and system-level design of the communication system in similar scenarios.

Keywords

References

  1. K. Guan et al., "On Millimeter Wave and THz Mobile Radio Channel for Smart Rail Mobility," IEEE Trans. Veh. Technol., vol. 66, no. 7, Nov. 2016, pp. 5658-5674. https://doi.org/10.1109/TVT.2016.2624504
  2. B. Ai et al., "Future Railway Services-Oriented Mobile Communications Network," IEEE Commun. Mag., vol. 53, no. 10, Oct. 2015, pp. 78-85. https://doi.org/10.1109/MCOM.2015.7295467
  3. X. Cheng et al., "An Improved Parameter Computation Method for a MIMO V2V Rayleigh Fading Channel Simulator under Non-isotropic Scattering Environments," IEEE Commun. Lett., vol. 17, no. 2, Feb. 2013, pp. 265-268. https://doi.org/10.1109/LCOMM.2013.011113.121535
  4. X. Cheng et al., "Communicating in the Real World: 3D MIMO," IEEE Wirel. Commun., vol. 21, no. 4, Aug. 2014, pp. 136-144. https://doi.org/10.1109/MWC.2014.6882306
  5. J. Zhang, Y. Zhang, Y. Yu, R. Xu, Q. Zheng, and P. Zhang, "3-D MIMO: How Much Does It Meet Our Expectations Observed from Channel Measurements?" IEEE J. Sel. Areas Commun., vol. 35, no. 8, Aug. 2017, pp. 1887-1903. https://doi.org/10.1109/JSAC.2017.2710758
  6. X. Chen, "Experimental Investigation and Modeling of the Throughput of a 2 9 2 Closed-Loop MIMO System in a Reverberation Chamber," IEEE Trans. Antennas Propag., vol. 62, no. 9, Sept. 2014, pp. 4832-4835. https://doi.org/10.1109/TAP.2014.2330599
  7. 5GCHAMPION project, Accessed Dec. 10, 2017. http://www.5gchampion.eu
  8. J. Kim and I.G. Kim, "Distributed Antenna System-Based Millimeter Wave Mobile Broadband Communication System for High Speed Trains 2013," Int. Conf. ICT Convergence (ICTC), Jeju, Rep. of Korea, Oct. 14-26, 2013, pp. 218-222.
  9. CMCC, "R1-163887 Update Evaluation Assumptions for NR High Speed Scenario," 3rd Generation Partnership Project (3GPP) RAN1#84-BIS, Apr. 2016.
  10. Mitsubishi Electric and ETRI, "R1-165484 WF on Evaluation Assumption for High Speed-Train Scenario 30 GHz," 3rd Generation Partnership Project (3GPP) RAN1#85, May 2016.
  11. Mitsubishi Electric, ETRI, and Ericsson, "R1-165926 WF on Additional Evaluation Assumptions for High Speed Train Scenario: Macro + Relay around 30 GHz," 3rd Generation Partnership Project (3GPP) RAN1#85, May 2016.
  12. X. Yin and X. Cheng, "Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications," Singapore: Wiley-IEEE Press, 2016.
  13. M.K. Samimi and T.S. Rappaport, "3-D Millimeter-Wave Statistical Channel Model for 5G Wireless System Design," IEEE Trans. Microw. Theory Techn., vol. 64, no. 7, July 2016, pp. 2207-2225. https://doi.org/10.1109/TMTT.2016.2574851
  14. S. Hur et al., "Proposal on Millimeter-Wave Channel Modeling for 5G Cellular System," IEEE J. Sel. Topics Signal Process., vol. 10, no. 3, Apr. 2016, pp. 454-469. https://doi.org/10.1109/JSTSP.2016.2527364
  15. W. Fan et al., "Measured Wideband Characteristics of Indoor Channels at Centimetric and Millimetric Bands," EURASIP J. Wirel. Commun. Netw., vol. 2016, no. 1, Feb. 2016, pp. 58:1-58:13.
  16. J. Zhang et al., "6-100 GHz Research Progress and Challenges from a Channel Perspective for Fifth Generation (5G) and Future Wireless Communication," Sci. China Inform. Sci., vol. 60, no. 8, June 2017, p. 080301. https://doi.org/10.1007/s11432-016-9144-x
  17. B. Ai et al., "Radio Wave Propagation Scene Partitioning for High-Speed Rails," Int. J. Antennas Propag., vol. 2012, no. 21, Oct. 2012, pp. 1072-1075.
  18. J. Meinila et al., "WINNER II channel models," in Radio Technologies and Concepts for IMT-Advanced, Chichester, United Kingdom: John Wiley & Sons, 2008, pp. 39-92.
  19. 3GPP, "Study on channel model for frequency spectrum above 6 GHz (Release 14)," TR 38.900 V14.3.1, July 2017.
  20. S.W. Choi et al., "Performance Evaluation of Millimeter-Wave-Based Communication System in Tunnels," IEEE Globecom Workshops (GC Wkshps), San Diego, CA, USA, Dec. 6-10, 2015, pp. 1-5.
  21. S. Priebe, M. Kannicht, M. Jacob, and T. Kurner, "Ultra Broadband Indoor Channel Measurements and Calibrated Ray Tracing Propagation Modeling at THz Frequencies," J. Commun. Netw., vol. 15, no. 6, Dec. 2013, pp. 547-558. https://doi.org/10.1109/JCN.2013.000103
  22. D. He et al., "Stochastic Channel Modeling for Kiosk Applications in the Terahertz Band," IEEE Trans. Terahertz Sci. Technol., vol. 7, no. 5, Sept. 2017, pp. 502-513. https://doi.org/10.1109/TTHZ.2017.2720962
  23. V. Degli-Esposti, F. Fuschini, E.N. Vitucci, and G. Falciasecca, "Measurement and Modelling of Scattering from Buildings," IEEE Trans. Antennas Propag., vol. 55, no. 1, Jan. 2007, pp. 143-153. https://doi.org/10.1109/TAP.2006.888422
  24. 3GPP, "Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations," 3GPP TR 25.996, 2011, pp. 38-39.
  25. S. Jaeckel, L. Raschkowksi, K. Borner, and L. Thiele, "QuaDRiGa: A 3-D Multi-cell Channel Model with Time Evolution for Enabling Virtual Field Trials," IEEE Trans. Antennas Propag., vol. 62, no. 6, June 2014, pp. 3242-3256. https://doi.org/10.1109/TAP.2014.2310220

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