Advanced Simulation Methods of Antennas and Radio Propagation for 5G and Beyond Communications Systems
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Lei Xiong, Haiyang Miao, Bo Ai, Tutun Juhana, Adit Kurniawan, "Channel Characteristics of HighSpeed Railway Station Based on RayTracing Simulation at 5G mmWave Band", International Journal of Antennas and Propagation, vol. 2019, Article ID 3137583, 10 pages, 2019. https://doi.org/10.1155/2019/3137583
Channel Characteristics of HighSpeed Railway Station Based on RayTracing Simulation at 5G mmWave Band
Abstract
In order to satisfy the increasing demand for the higher transmission capacity of “smart station”, millimeter wave (mmWave) technology is expected to play a significant role in the high data rate communication system. Based on the raytracing simulation technology, this paper would study wireless channel characteristics of the threedimensional (3D) model of highspeed railway station at the mmWave band. Key parameters such as path loss exponent, shadow fading factor, delay spread, Rician Kfactor, angular spread, power angle spectrum, and spatial correlation are extracted and investigated. These channel characteristics are of value for the selection of antenna arrays and even the design of future 5G communication networks in the railway environment.
1. Introduction
Nowadays, with the convenience and flexibility of highspeed railway (HSR), more and more people prefer to take rail traffic for travel or for work. In order to meet these goals in regard to safety, convenience, and efficiency, the investigations about the fifthgeneration (5G) wireless communication system have become a trend [1–4] in different railway scenes. At present, the first 5G smart railway station has been established at Shanghai Hongqiao Railway Station, which is expected to have the ability to guarantee the 5G network depth coverage in this year. Smart railway station would show the wisdom of railway technology to the public from the perspective of operation and service, including indoor navigation, face identification, and 5Gguided robot. In other words, smart station has been the vital application environment in intelligent transportation systems (ITSs) [5, 6] and the analysis of the wireless channel model in the railway system for the 5G communication system is essential.
To meet the demand for seamless high data rate wireless connectivity for railway services, the efficient transmission technologies like massive multipleinput multipleoutput (MIMO) is proposed [7] to improve system capacity and data rate. The largescale fading characteristics of different railway scenarios have been summarized for the first time in [8]. Based on [8], it is noted that railway station [9, 10] is significantly different from common public network scenarios or other highspeed railway scenarios (such as viaducts, cuttings, tunnels, etc.) [11]. In [11], the authors also explored channel characteristics in different HSR scenarios by the 3D ray tracing (RT) [12–14] which could compensate for the shortcoming of traditional models and accurately analyze the special channel characteristics in 5G systems. Previous simulations focused on the singleinput singleoutput (SISO) system and MIMO channel for indoor and outdoor communication [15–17], but they missed the research of multipath parameters such as spatial correlation in the railway system. As a result, there is still an urgent demand for a complete investigation by considering largescale parameters, smallscale parameters, and spatial parameters [18, 19] for station scenario in MIMO systems.
This paper mainly focuses on the medium HSR station, which is the most common station scenario with two platforms and four lines. First of all, channel parameters such as path loss exponent, shadow fading factor, multipath delay, and angular spread can be obtained based on RT. The experiment will be carried out at the HSR station where base station antennas are arranged on the tower. On the contrary, the strengths of the massive MIMO system to compensate for the high path loss of the mmWave band have made high carrier frequencies become an integral component of the upcoming 5G networks. Because of the available larger transmission bandwidths, the 5G network is able to supply high data rates and enhance the quality of experience. Although propagation signals at higher frequencies have the higher path loss and are more susceptible to rapid signal degradations caused by moving or fixed obstacles [20], higher frequencies can allow the deployment of smaller antennas which enables the function of multiantenna technology to be integrated into the antenna array. In this paper, not only have the channel characteristics that can guide 3D channel modeling in 5G environment been discussed but optimized deployment recommendations have also been provided for antenna configuration based on the spatial correlation in massive MIMO systems at 37.0–42.5 GHz mmWave band.
The rest of the paper is organized as follows. The defined highspeed railway station scenario and simulation parameters are presented in Section 2. The wireless channel model for the station scenario is provided in Section 3. According to simulation results, we point out the main channel characteristics to discuss the antenna deployment in Section 4. Conclusions are drawn in Section 5.
2. RayTracing Simulation
2.1. Scenario Modeling
As shown in Figure 1, the 3D scenario model with a 450 m (length) highspeed railway station is established by SketchUp in the threedimensional Cartesian coordinate system. There are 6 types of objects and 6 materials (Table 1) in the scenario model. The LOS paths, scattering, and up to 2ndorder reflections are considered, and the initialized dielectric parameters are listed in Table 2.


Then, referring to the CRH380A, the highspeed train model is built in Figure 2. With simulation and measurement results, the effect of adjacent train compartments almost can be ignored for the received signal, which indicates the front of the train could be considered individually in the simulation environment.
2.2. RayTracing Simulation Parameters
In Figure 1, the height of the singletube tower next to the highspeed railway station is 40 m [21]. The distance from the center line of the tower to the edge of station platform is 10 m, and the distance to the Xaxis is 225 m. The omnidirectional vertical polarization antenna is employed in this work. As the transmitter (Tx) antenna, the base station antenna is deployed on a platform of tower [21] whose height is 38.5 m and vertical distance to the center line of the tower is 0.8 m. Hence, the coordinates can be set to (30.5, 225, 38.5).
In the top view of Figure 1, simulating on Line 1, the process of passing the train through the station on Line 1 is divided into Area I where the train is approaching the tower and Area II where the train is leaving the tower. The top antenna is the receiver (Rx) which is located at the middle line on the top of train, and the vertical distance to the rear section of the train is 13 m. The Rx antenna moves along the positive direction of Yaxis, and the height is 4.16 m which is the sum of the distance to the top of train (0.15 m), the height of the train (3.70 m), and the height from the bottom of the train to the ground (0.31 m). The Yaxis coordinate of Rx antenna is 0 : 2:450 on Line 1. The key configurations of raytracing simulation are listed in Table 3.

3. Wireless Channel Model
In signal processing and wireless communication, the channel transfer function at frequency f is expressed as the coherent sum of different multipath components coupling with the polarimetric Tx and Rx antenna radiation patterns () [22].where N denotes the number of multipath, a_{n} and are the signal amplitude and phase, respectively, , , , and are the azimuth angle of departure/arrival and elevation angle of departure/arrival, respectively [23], all of which are for the nth multipath component.
In addition, in the wireless channel model, the lineofsight (LOS) paths and the nonlineofsight (NLOS) paths are usually separated because the LOS paths are obvious, whereas the NLOS paths are based on the simulation transmission modes of the RT platform including reflection, scattering, and diffraction.
4. Wireless Channel Characteristics
In this section, the simulation results of highspeed railway station on Line 1 are presented and analyzed. Furthermore, suggestions on optimized antenna array deployment are also provided.
4.1. Path Loss and Shadow Fading
Path loss refers to the loss caused by the diffusion of electromagnetic wave energy when the wave propagates. From the macroscopic point of view, it is reflected in the function of the received signal power changing with distance.
By analyzing the channel data obtained by the RT simulation platform, with the change of Yaxis coordinate of the Rx antenna, the path loss is shown in Figure 3.
In Figure 3, the path loss is almost symmetrical with respect to the Yaxis coordinate of Tx, whose maximum is 132.2 dB when the Yaxis coordinate is 22 m. In [24], assuming that the receiving sensitivity of the Rx antenna is −125.23 dBm and combining the parameters of Table 3, the maximum allowable of path loss is about 148.73 dB considering penetration loss.
In this paper, the fitting results of path loss, by the model in (2) that combines the path loss and shadow fading [25], are shown in Figure 4:where A is the interception, d is the distance between the Tx antenna and the Rx antenna (unit: m), and n is the path loss exponent. indicates the zero mean Gaussian random variable with a standard deviation σ which is the shadow fading factor reflecting the largescale fading that is caused by obstacle occlusion on the wireless channel.
(a)
(b)
From Section 2, Line 1 is divided into Area I and Area II. The fitted parameter values are shown in Table 4.

According to Figure 4 and Table 4, on Line 1, as a result of a few obstacles (such as canopy) in the scenario, the fitting path loss exponent (n = 2.26) is slightly larger than that in the free space path loss (FSPL) model (n = 2). In Area I, n is 2.69 because of more obstacles. It should be noted that n is 1.83 in Area II on account of the superposition of the LOS path, more reflection, and scattering which can be found in [11] regarding rich multipath propagation at mmWave channels. In addition, all shadow fading factors σ in the scenario are close to 6 dB which is the value of the LOS environment for rural macro (RMa) scenario in 3GPP [26].
4.2. RMS Delay Spread
Figure 5 shows the mean root mean square (RMS) delay spreads and cumulative distribution functions (CDFs) of RMS delay spreads.
(a)
(b)
In Figure 5(a), the RMS delay spread curve is almost symmetric. The RMS delay spreads near Tx antenna are larger than the two ends of the station. The mean RMS delay spread 0.28 ns on Line 1 is less than the measurement result of delay spread 0.8 ns in rural [4] because the semiclosed station space limits the range of multipaths [11]. Simultaneously, due to the highspeed railway station is a semilimited type, the rays are occluded and reflected by various buildings and the train body during the propagation process. LOS paths provide the primary energy, and the RMS delay spreads are relatively small. In Figure 5(b), all values of RMS delay spread on Line 1 are less than 1.2 ns, which mean most of the powerful multipath components are concentrated around LOS path in the time delay domain. The mean values of RMS delay spread are shown in Table 5, and values of two areas are almost the same which suggest Line 1 has the similar channel characteristics in the time delay domain.

4.3. Rician KFactor
From the analysis of previous chapters, there are LOS paths and a large number of NLOS paths on Line 1. So it is indispensable to analyze the relationship between LOS path and NLOS path with the Rician Kfactor [27].
With the Yaxis coordinate position of Rx antenna changing, the Rician Kfactor is shown in Figure 6(a). Additionally, Figures 6(b)–6(d) demonstrate CDFs and fitting results of Rician Kfactor. The mean values of the Rician Kfactor are summarized in Table 5.
(a)
(b)
(c)
(d)
As shown in Figure 6(a), with the Rx antenna close to Tx antenna (Area I), the overall process of Rician Kfactor is a decreasing trend. Rician Kfactors near Tx antenna are the smallest, whose fluctuation is relatively serious. Conversely, in Area I and Area II, the Rician Kfactors become larger with the distance between Tx antenna and Rx antenna increasing, which denotes the fading is getting weaker.
In Table 5, the mean of Rician Kfactor on Line 1 is 28.72 dB that is far greater than 0 dB, which means LOS path contributed the main energy. The similar observation at mmWave band could be found in rural scenario [4] regarding the mean value 25.7 dB. As shown in Figures 6(b)–6(d), it should also be noted from the fitting results that Rician Kfactors obey the Gaussian distribution owing to the wideband channel characteristic of the 5G communication system. Furthermore, when the bandwidth is wider, the multipath resolution capability that leads to a decrease in the power of the NLOS component of the main path gets stronger, so Rician Kfactors become greater in the 5G wideband channel system.
4.4. Spatial Parameters
4.4.1. RMS Angular Spread
On Line 1, the RMS angular spreads of angle of arrival (AoA) and angle of departure (AoD) are shown in Figure 7(a). ASA, ESA, ASD, and ESD are angular spreads of the azimuth angle of arrival, the elevation angle of arrival, the azimuth angle of departure, and the elevation angle of departure, respectively. The CDFs of angular spreads are illustrated in Figure 7(b).
(a)
(b)
In Figure 7, the ESA is relatively larger, and most (≥80%) values are greater than 10.7°, while the 80% of ASA are less than 7.8°, which explains there are more scatterers from the elevation domain at the Rx and the train body plays a major role. Then, the ESD is relatively smaller, and most () values are less than 1.7° whereas the ASD is relatively larger and 80% are greater than 5.5°, which explains there are less scatterers at the elevation domain at the Tx. Besides, the measurement scenario in [28] is similar to the station scenario in the paper, and the results in [28] agree with the simulation results in the paper. Since there is a similar environment that more reflectors and scatterers in both scenarios, the scenarios have the same characteristic that the maximum of angular spread does not exceed 70°.
4.4.2. Power Angle Spectrum
In Figure 7(a), the angular spreads at two ends of the station are relatively small. That is why we need to focus on the power angle spectrum (PAS) [29] at two ends of the station. In this section, Figure 8 shows the PAS of AoA and AoD when the Yaxis coordinates of the Rx antenna are 6 m and 444 m, respectively.
(a)
(b)
In Figure 8(a), at the Yaxis coordinate 6 m, the main beam at Rx could be horizontal because values of normalized power are relatively the largest as the elevation angle of AoA is about 90°. Fortunately, elevation angle directions of the main beam are also distributed around 90° at the Yaxis coordinate 444 m. Furthermore, the relatively large ESA and horizontal beam at Rx show that the linear Rx antenna array should be perpendicular to the top of the train in order to achieve the low correlation among beams.
In Figure 8(b), at the 6 m, while the azimuth angle of AoD is about −20°, the normalized powers are the largest, which implies that the azimuth angle direction of the main beam at Tx could be about −20°. Conversely, at the 444 m, the azimuth angle directions of main beam are mainly distributed around 20°, but the elevation angles always approach 100°. Then, the ASDs of Tx antenna are greater than ESDs in Figure 7(a), which means the antenna array could be horizontal and perpendicular to rails on the tower platform. Considering the direction of the main beam in Figure 8(b), the antenna array should be rotated counterclockwise or clockwise horizontally to be perpendicular to the direction of main beam for the low correlation.
4.5. Spatial Correlation
As we all know, the diversity gain and multiplexing gain of the MIMO system [30, 31] are directly related to the spatial characteristics of the channel. The above is the investigation of some spatial characteristic parameters at 5G mmWave band. In addition, as the important aspect of MIMO channels [32], the spatial correlation among beams must be discussed to achieve the suitable antenna spacing.
In this section, in order to improve the performance of the location where there is worser signal coverage, the angular spreads at that position are selected for correlation calculation to ensure the user experience of the overall scenario.
According to Figure 7(b), more than 90% of ASA and 90% of ESA are beyond 4.15° and 9.71°, respectively, and over 90% of ASD and 90% of ESD are larger than 4.64° and 0.92°, respectively, which result in the necessity of investigation about the spatial correlation among antenna elements in the case of relatively worser angular spread. The correlation coefficient between Rx antenna elements with ASA (4.15°) and ESA (9.71°) is shown in Figure 9(a), and the correlation coefficient of Tx antenna elements is drawn in Figure 9(b) as the ASD is 4.64° and ESD is 0.92°.
(a)
(b)
The wavelength at 40 GHz is approximately 7.5 mm. From Figure 9(a), the relative distance of Rx antenna array elements is at least 68 times to ensure that correlation coefficient between adjacent antenna elements is less than 0.1, but the antenna element spacing is around 51 cm that is too large to meet the engineering requirements. If the correlation coefficient can be relaxed to 0.5, it indicates the antenna element spacing only will be about 2.25∼3.75 cm that might meet the requirement for application at the Rx.
In Figure 9(b), when the correlation coefficient of adjacent Tx antenna elements is less than 0.5, antenna spacing can be set to about 3∼30 times of wavelength which means around 2.25∼22.50 cm.
5. Conclusion
In this paper, channel characteristics of 5G mmWave band have been investigated at the highspeed railway station. Based on the measurement and simulation results, key channel parameters, such as path loss, delay spread, Rician Kfactor, angular spread, PAS, and spatial correlation, are all analyzed. Some important results and suggestions are summarized as follows:(1)When Tx antennas are installed on the tower, the maximum path loss on Line 1 is about 132.2 dB, which is so large that multiantenna technology is expected to ensure signal coverage strength and increase system capacity.(2)The highspeed railway station is a semilimited space where the values of RMS delay spreads are almost less than 1.2 ns on Line 1, which is reasonable and acceptable in 5G systems.(3)In the scenario, the Rician Kfactors obey the Gaussian distribution which is owing to the large bandwidth in 5G systems.(4)When the Tx and Rx both adopt uniform linear antenna arrays, the antenna spacing could be 2.25∼22.50 cm at Tx, whereas the Rx antenna spacing might be set to 2.25∼3.75 cm.(5)The Rx antenna array should be vertical to the top of the train, while the horizontal Tx antenna array should be rotated counterclockwise or clockwise horizontally to obtain low correlation due to the propagation direction of the main beam.(6)By analyzing the train’s moving speed and the angle between the train’s moving direction and incident wave direction, it can be found that the angle is approaching 90° as the Rx reaches the Tx, which makes Doppler shift decline. Due to simulation on Line 1 where the train needs to stop at the platform and the speed is relatively low, this paper does not focus on the Doppler effect and more related research could be conducted in future work.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this paper.
Acknowledgments
This work was supported by the National Key Research and Development Program under Grant 2016YFE0200900, NSFC under Grants 61725101 and U1834210, Beijing Natural Haidian Joint Fund under Grant L172020, Major Projects of Beijing Municipal Science and Technology Commission under Grant Z181100003218010, and the Royal Society Newton Advanced Fellowship (Grant no.: NA191006).
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Copyright © 2019 Lei Xiong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.