Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz


Lei Ma, Ke Guan, Dong Yan, Danping He, Bo Ai, Junhyeong Kim, Heesang Chung: Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz. In: 2020 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1-6, 2020, ISSN: 1558-2612.

Abstract

The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth-generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud-computing Ray-Tracing platform – CloudRT, extensive raytracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.

BibTeX (Download)

@inproceedings{Ma2020a,
title = {Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz},
author = {Lei Ma and Ke Guan and Dong Yan and Danping He and Bo Ai and Junhyeong Kim and Heesang Chung},
doi = {10.1109/WCNC45663.2020.9120474},
issn = {1558-2612},
year  = {2020},
date = {2020-05-01},
urldate = {2020-05-01},
booktitle = {2020 IEEE Wireless Communications and Networking Conference (WCNC)},
pages = {1-6},
abstract = {The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth-generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud-computing Ray-Tracing platform \textendash CloudRT, extensive raytracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.},
keywords = {5G, High-speed railway, mmWave, radio propagation, ray-tracing, smart rail mobility},
pubstate = {published},
tppubtype = {inproceedings}
}