A Vehicle–Ground Integration Information Network Scheme Based on Small Base Stations

Abstract

The transmission bandwidth of a vehicle–ground connection is low when an EMU (electric multiple unit) is running in a high-speed scenario. To this end, this paper focuses on the need to solve the problem of the poor bandwidth of the vehicle–ground integration information network, and proposes a vehicle–ground integration information network scheme for EMUs based on small base stations. Based on the existing wi-fi system of the EMU, in order to realize the coverage of the 5G signal in the carriage, this paper—through the deployment of the technical characteristics of 5G—sinks the customized UPF (user plane function) and MEC (mobile edge computing) to the train carriage, and expands the internet channels of the train carriage. Relying on the technologies of MEC and CDN (content delivery network) for high-speed railways, network extension service products can satisfy passengers’ needs around network rate and delay. On the one hand, this can relieve the pressure of the network backhaul and save the bandwidth resources of the vehicle–ground integration information network. On the other hand, it can help operators to reduce the investment of network construction, operation, and maintenance. As a result, the proposed scheme can inspire the products that match the extended service needs of the passenger, realize the technical and innovation value of the 5G mobile network, and achieve business model innovation in high-speed mobile scenarios.

1. Introduction

The internet has greatly changed people’s production and life since its birth, and it has become an indispensable element in modern society. However, the surface network is influenced by the regional economy, geographical environment, and natural disasters; therefore, the service coverage and reliability and other aspects cannot meet the increasing variety of application requirements. After years of research and development, the SGIN (space–ground integration information network) is still in the initial stage: the network service quality in high-speed mobile scenes still cannot meet the demand of passengers.

With the rapid development of HSTs (high-speed trains), an increasing volume of wireless communication data is required to be transferred to train passengers. HST users demand a high network capacity and reliable communication services regardless of their locations or speeds [1]. Therefore, it is necessary to improve 5G signal services along railway lines. Due to the occlusion of the 4G signal by the carriage body, passengers often experience communication interruption, web page jam, and slow loading during their voice calls and network usage [2,3]. As a possible solution, 5G technology could provide users with a consistent service, such as the fiber-optic access rate, the “zero” delay experience, the ultra-high traffic volume, connection density, mobility, and so on, which can better meet the needs of passengers for high-quality network services in the sealed scene of an EMU [3]. Because HSTs have the characteristics of a high mobility and sealed carriages, the construction work of the 5G network along the railway lines faces many challenges, such as the high base station construction density, Doppler shift, frequent connection switching, and a large penetration loss [4,5]. After seven years of mass construction on the 4G network, the number of base stations reached 4.5 million in order to meet the needs of the network LTE continuous coverage. However, if the traditional construction scheme is adopted for 5G base stations, users may hardly experience the performance boosting of the 5G technology and railway operators cannot benefit from the technical innovations. Thus, it is necessary to carry out research for 5G signal enhancement [6]. According to an analysis of the development of the network application market in the past few years, the dividend of traffic will not drive the significant growth of operators’ revenue, and the ARPU (average revenue per user) is slowly declining. Under the policy background of “increasing speed but reducing fees”, it is difficult for operators to complete the large-scale deployment of a 5G network in such a short time, as in the case of the 3G and 4G network deployment mode [7]. Therefore, operators urgently need a more cost-effective network construction mode along the railway that ensures the performance and efficiency of 5G traffic.

At present, European train operators have started to deploy in-train repeater systems to increase mobile users’ service quality [8]. There is extensive literature that discusses the aspects of static repeater deployments for mobile cellular networks [9,10]. The method of the repeater is to use “vehicle relay equipment” and “external antenna” for 5G on HST deployment, which has a small investment and a simple network but also has the following disadvantages. Firstly, the repeater and the donor station have overlapping coverage, and the latency difference causes interference. The repeater receives multiple signals from the outdoor macro station, and the SINR (signal to interference noise ratio) deteriorates after amplification. Especially in a railway station setting, the overall noise of the macro station is raised. Secondly, due to the same frequency inside and outside the vehicle and poor SINR, it is difficult to achieve multi-channel communication [11]. In addition, China’s railway has proposed the goal of diversified operation based on HST. In 2017, a wi-fi operating service system was set up on HSTs to provide leisure and entertainment services for passengers. To further integrate the wi-fi system and solve the problems mentioned above, the research content of this paper is proposed. This paper puts forward a small-station-supplemented 5G public network signal enhancement scheme with macro stations along the railway, which will realize multiple goals such as the deployment of multiple operators’ 5G public networks on EMUs, avoiding 5G signal penetration loss, widening the 5G public network macro station intervals, and reducing operator construction, operation, and maintenance costs in a one-shot strategy.

The structure of the paper is as follows. An introduction to the current 5G key problems in the railway industry and related works are given in Section 2. In Section 3, based on the characteristics of a high-speed railway operation environment, the network signal enhancement scheme based on small stations is proposed, including the design of the UPF (user plane function) and MEC (mobile edge computing) schemes. Section 4 verifies the feasibility of the proposed scheme according to experimental verification and simulation on the Beijing-Zhangjiakou high-speed railway. Section 5 summarizes a few concluding remarks.

2. Problem Statement

2.1. Poor Network Quality for Passenger Service

At first, this paper provides a background introduction on the wireless service of HST. Compared with aviation, highway, waterway, and other modes of traveling, the railway has the characteristics of flexibility, stability, and safety. At the same time, it can connect large and medium-sized cities as one of the traffic networks with the largest number of passengers. In the setting of high-speed movement, the EMU body penetration loss and Doppler frequency shift will decrease the quality of wireless service. In addition, the C-Band currently used by the 5G wireless communication system has a higher frequency and weaker penetration, and the penetration loss is higher than the frequency band in 4G, as shown in

Table 1. Penetration losses in different frequency bands [12].

Measuring Frequency	The Model of Tested HST and Scenario
	The Model of CR400BF
	The Coverage Based on Leaky Cable/dB	The Coverage Based on Antenna/dB
800–900 MHz	30.4	27.8
1800–1900 MHz	32.3	30.1
2100 MHz	31.8	30.9
2300 MHz	32.6	29.3
2600 MHz	34.8	29.8
3500 MHz	36.4	35.4
4900 MHz	35	35.8

. The reasons are as follows: the railway line is generally long and narrow with a linear distribution, the angle between the base station signal and the train is small, and the high-speed train adopts a closed compartment design, which increases the signal loss. At the same time, with newer types of trains, the material of the train’s cabin has better shielding properties, which makes the penetration loss even larger.

High-speed railway trains run at a speed of around 250 km/h, which has a great impact on the signal transmission, especially when the signal direction is the reverse of the base station during the switch. This leads to signals becoming stuck, or even off the network, and therefore greatly reduces the user experience. What is more, high-speed movement will cause drastic signal reception fluctuations, such as Doppler shifts, which will affect the reception of wireless signals.

Table 2. The values of uplink Doppler shift.

FR	1800 MHz	3500 MHz	4900 MHz
200 km/h	667 Hz	1286 Hz	1816 Hz
250 km/h	833 Hz	1619 Hz	2267 Hz
300 km/h	1000 Hz	1929 Hz	2722 Hz
350 km/h	1167 Hz	2269 Hz	3176 Hz
450 km/h	1500 Hz	2984 Hz	4083 Hz

shows the values of the Doppler shift at different frequencies. In general, a faster train motion speed leads to a larger Doppler shift. At a speed of 350 Km/h, the mobile communication bandwidth performance is greatly reduced—about 30%. Besides this, the Doppler shift is related to the frequency and increases with increasing frequency. The maximum Doppler shift calculation is as follows:

$$dp=2\left(f·v\right)/c$$

(1)

where dp is Doppler shifts, f is the frequency (Hz), v is the velocity of the train (m/s), c is the velocity of light (m/s).

In addition, using large-scale antennas is the current tactic to improve the base station capacity. For example, in low-speed scenarios, China Unicom Telecom adopts 200 MHz 3.5 GHz 64TR equipment, which can achieve a peak rate up to 8 Gbps downloads and 3 Gbps uploads based on accurate channel estimation. However, in high-speed scenarios, the traffic rate is reduced due to the temporal degeneration of the channel and the poor feasibility of spatial multiplexing.

However, with the rapid development of information technology, webcasting, and telecommuting, and with the gradual popularity of remote teaching applications [13], three major operators have provided unlimited package services, which accelerated the outbreak of mobile communication in 2017. Affected by the epidemic in 2020, various applications of mobile business and network conferences further stimulate the demand of network bandwidth. In addition, the birth of more high-definition entertainment video applications demands that the network traffic demand continue to grow. Services based on the existing 3G and 4G technology internet access mode cannot meet the strong demand of passengers on high-speed trains during this period, therefore it is urgent to use 5G technology to improve the quality of passenger network services.

2.2. High Construction and Operation Costs of 5G

With the rapid advance of the 5G commercial process, it is an inevitable choice for the railway industry to adopt 5G technology as the EMU vehicle–ground communication access method to achieve a greater bandwidth and lower transmission delay. The rapid change in the wireless channel, the frequent cell switching, the Doppler shift, and the shielding of the wireless signal by the train body lead to the attenuation of the wireless signal energy [14]. The complex environment along the railway brings severe challenges to the construction and network optimization of the 5G network along the high-speed railway. The 5G signal encounters a greater transmission loss and train body penetration loss in the high-speed railway mobile scenario. In particular, high-speed trains are of linear coverage, as shown in Figure 1.

If the base station has lower incident angles to the high-speed trains, the signal will be even worse. In the mobile cellular communication along the railway, the path loss from the base station to the mobile terminal is mainly affected by the spatial link loss and penetration loss. The paper refers to the latest 3GPP channel model (3GPP TR38.901), an extension of the widely used 3GPP channel model with several additional modeling components [15]. It supports a wide frequency range (0.5–100 GHz). The 3GPP TR 38.901 documentation provides eight scenario propagation models, the viaduct scenario is the main HSTs reference setting, and thus the RMa (rural macro) path loss model is usually selected. As shown in Equations (2)–(4):

$$P{L}_{\mathrm{RMa}-\mathrm{LOS}}=\left\{\begin{array}{cc}P{L}_1\hfill & 10 \mathrm{m}\le d_{2\mathrm{D}}\le d_{\mathrm{BP}}\hfill \\ P{L}_2\hfill & d_{\mathrm{BP}}\le d_{2\mathrm{D}}\le 10 \mathrm{km}\hfill \end{array}\right.$$

(2)

$$\begin{array}{ll}P{L}_1=\hfill & 20{\log }_{10}(40\pi d_{3\mathrm{D}}{f}_c/3)+\min (0.03h^{1.72},10){\log }_{10}(d_{3\mathrm{D}})\hfill \\ & -\min (0.044h^{1.72},14.77)+0.002{\log }_{10}(h)d_{3\mathrm{D}}\hfill \end{array}$$

(3)

$$P{L}_2=P{L}_1(d_{\mathrm{BP}})+40{\log }_{10}(d_{3\mathrm{D}}/d_{\mathrm{BP}})$$

(4)

where d_BP = 2π × h_BS × h_UT f_c/c, f_c is the center frequency in Hz, c = 3.0 × 10⁸ m/s is the propagation velocity in free space, h_BS and h_UT are the antenna heights at the BS (base station) and the UT (user terminal). The distance d_2D and d_3D definitions are indicated in Figure 2.

The path loss is affected by the transmission frequency and the relative distance of the base station. The higher the frequency is, the higher the path loss. Assuming that the 4G frequency is 2.4 GHz, 5G is 3.5 GHz, and cells are circular simulated, the coverage distance of the 4G base station is 1.5 times larger than that of the 5G base station, and the coverage area is 2.1 times larger than that of 5G. The 5G macro station cost is rather high, and it is difficult to construct 5G macro stations, and to acquire, operate, and maintain site resources, which makes operators invest much but yield few. Taking the Beijing section of the Beijing-Zhangjiakou high-speed railway (70.5 Km) as an example, the number of 5G base stations of China Mobile is 139 (2.6 GHz band), whose coverage rate is 98.1%; the number of 5G base stations of China Electric Union is 147 (3.5 GHz band) with a coverage rate of 86.6%. Due to the increase in the 5G working frequency band, and the shortened coverage distance of the macro station, the distance of 5G base stations is shortened to around 400 to 600 m, which nearly halves the distance between 4G base stations. In terms of operation and maintenance, due to the higher energy consumption of 5G base stations, which is about three times that of 4G base stations, the 5G network operation and maintenance cost for telecom operators is also high. Therefore, it is urgent to find a new signal enhancement scheme for the railway industry to reduce the cost of 5G network construction, operation, and maintenance.

3. Problem Solution and Proposed Approach

In the 4G era, small base stations, as a piece of more flexible equipment with milliwatts or watts level specifications, were widely used in various industries because of their advantages of small volume, being lightweight, flexible and easy to deploy, and low construction cost. In the 5G era, the frequency band has increased to 2.6 GHz (2515 MHz–2675 MHz), 3.5 GHz (3400 MHz–3600 MHz), and 4.9 GHz (4800 MHz–4900 MHz), respectively, so the coverage capacity of the signal station has been greatly reduced [16]. The upward shift of the 5G working frequency band, and the penetration loss of the 5G signal across the carriage increases by around 6–10 dB, leading to the 5G signal quality being far from the users’ demands of coverage and capacity. As the small base station is small, with strong self-optimization, self-configuration, self-interference management, and transmission ability, the dense deployment of small base stations in a dense space will not incur serious interference problems. With their advantages of small volume, being easy to deploy, strong anti-interference ability, and low construction cost, the small base stations can supplement or even eliminate the lack of network signal coverage and even blind spots along the railway cooperating with the deployment of macro stations along the railway, realizing the coverage of the 5G network signal under high-speed mobile scenarios at a low cost. This paper aims to meet the coverage quality of the 5G public network signal while reducing the costs of construction and maintenance of the 5G network. Based on the principle of minimizing the cost, this paper integrates 5G public network signal enhancement equipment with on-board LAN equipment by multiplexing the carriage wireless LAN system equipment of existing trains.

3.1. Network Architecture Design

At present, the high-speed railway EMU has realized the coverage of on-board wireless LAN, as shown in Figure 3. Its equipment connects to the central server through the carriage server, and to the macro station along the railway through the roof antenna to realize the interconnection of external data. In this design, the on-board wireless LAN system can provide spaces for 5G equipment installation. Through the sharing and re-usage of the on-board equipment installation space of these two systems, the installation difficulty is reduced, and the integration of these two systems realizes the dual coverage of the 5G public network signal and wi-fi signal in the carriage.

The overall network architecture is shown in Figure 4. The 5G coverage in the EMU compartment is realized through the bus on 5G stations. The system consists of a train network, backhaul network, and specialized 5G core network for the HST, providing end-to-end 5G services for passengers. A customized UPF and MEC sunk to the vehicle-end can also help passengers to cache popular resources and offload local traffic. Besides providing passengers with basic telecommunication services such as phone calls and SMS messages, it also relieves the pressure of the vehicle–ground backhaul network, and saves the vehicle site and network bandwidth resources. Meanwhile, the computing services sunk to the network edge provide an integration port for third parties, and provide passengers with edge cloud computing services.

The unified management platform is responsible for the unified management of small stations, including parameter configuration and status monitoring, etc. It is also responsible for the unified management of on-board users, mainly including controlling user information management, user storage, user registration, access management, session management, user network policy management, and user data forwarding [17]. The unified management platform is a fusion core that can process both 4G and 5G messages and deploy some necessary elements. In the long term, other optional network elements can be deployed, including NSSF, NEF, UDM, AUSF.

All network elements and operators jointly work on user network processing. Its architecture and interfaces are shown in Figure 5. The main interfaces between the unified management platform and the operator core network are N12 and N8, which are respectively used to retrieve the five authentication components of users and complete the authentication on the network side, and acquire the business functions of users’ contracts from the user center database. To reduce the delay caused by train dispersion, Beijing, Wuhan, and Guangzhou are selected for load sharing and data backup according to the national railway network and operator backbone network deployment management platform and the deployment of the China Railway network and telecom operators. The train network can be divided into the train backbone network and the train access network. The train backbone network establishes the carriage network interconnection through the ten-gigabit switch and the CAT7 ethernet connection, while the train access network realizes the compartment branch coverage of the train carriages based on the 5G small stations, and each small station completes the data interaction with the operator core network and ethernet through the ground management platform. The 4G/5G small station, integrating the Wi-Fi6 module, achieves the coverage of 4G, 5G, and wi-Fi signal in the carriage.

3.2. Design of Backhaul for 5G

In the small station scheme, the signaling plane data and user plane data of all on-board devices are transmitted to the unified management platform through the vehicle–ground backhaul network. However, the signaling plane messages have very high requirements on link quality. Thus, it is very important to provide a stable, reliable, fast, and low-delay vehicle–ground backhaul channel.

TR38.913 has been used in 3GPP studies and proposes preliminary specifications of 5G delay technology [18]. It can be concluded that the delay of the signaling plane should be less than 10 ms and up to 600 ms in special satellite communication scenarios. There was no delay requirement for high-speed rail scenarios. Taking the train running in Urumuqi and the ground unified management platform being built in Guangzhou as an example, the delay caused by the signaling plane is calculated as follows:

(1)

According to the design of the eMBB, the airport delay $D_a$ from the vehicle-mounted 5G gateway to the 5G railway-side macro station is 4 ms.

(2)

The distance between Urumqi and Guangzhou is 8000 km. Thus, the transmission delay $D_t$ is equal to 40 ms under the optical fiber transmission delay of 5 µs/km.

(3)

According to the 20 nodes in each province, 120 nodes exist in six provinces. The node forwarding delay $D_f$ equals 54 ms with a 450 µs delay each node.

(4)

Then, the total delay $D_{total}=2D_a+D_t+D_f=8+40+54=102 \mathrm{ms}$.

Therefore, for HST scenarios, the signaling delay is about 100 ms, far less than the upper bound 600 ms of satellite communication, which meets the core network delay range.

In order to meet the above signaling delay requirements, the onboard 5G gateway realizes a fast vehicle–ground transmission through the following key technologies to ensure the transmission delay on the air. The 5G gateway is mainly responsible for vehicle–ground communication and transferring the management data of on-board small stations and 4G/5G user data to the unified management platform safely and reliably through the dedicated VPN tunnel. The backhaul transmission gateway realizes fast transmission through six channels on dual carrier boards (single carrier board supports mobile, telecom, unicom, broadcast radio, and television). Taking an 8-carriage vehicle as an example, the small stations of carriages 1–4 establish an IPsec tunnel through the first carrier board to communicate with the ground unified management platform. The small stations of carriage 5–8 establish an IPsec tunnel through the second carrier board to communicate with the unified ground management platform. The two boards support the backup function mutually. When one board is down, all communications are directed to the other board.

3.3. Local Streaming Model

In the small station scheme, the on-board users are connected to the ground unified management platform through the 5G communication network. Therefore, the 5G communication gateway needs to transmit a large flow of business data with a low traffic delay. In order to reduce the pressure on the vehicle–ground transmission system, reduce the service delay, improve users’ browsing experience, and provide rich content services, a local streaming technology is needed. There are many access modes (4G/5G/wi-fi), so the local streaming of various access modes needs to be fully considered. UPF and MEC need to be deployed in carriages to realize the triage of 5G users. ETSI defines MEC as: “providing IT services and a cloud computing environment on the edge of the mobile internet “ [19], which emphasizes applications, services, and contents in a local, close, and distributed deployment. To a certain extent, UPF sinking technology satisfies the 5G mobile broadband needs of low delay, high reliability, and a large-scale communication terminal connection in the business scene.

In this scenario, the key requirements of agile connection, real-time business, data optimization, and application intelligence of passengers’ and commercial business can be satisfied by closely deploying the MEC with an integration platform for network, computing, storage, and application core capabilities. Furthermore, a new business model can be generated, new income opportunities can be created, and all parties can work together to form a good future.

ETSI (MEC031) clearly defines the integration of MEC and 5GC, including UPF and edge computing platform functionality. According to the White Paper MEC28 (deployment and application of MEC in a 5G network), MEC and 5GC are integrated through the UPF connection. According to the integration architecture of MEC and 5G, along with the characteristics of the project, the combination architecture of UPF and MEC in this solution is shown in Figure 6.

It is important to choose the correct UPF according to the user location when the proposed scheme is used to deal with the users’ requests. Currently, this function is realized by the rule of “choose UPF according to station ID“ with the advanced configuration of the link between on-board small base stations and the corresponding relation of UPF inside the SMF. When a user has a data service request, the correct UPF can be selected by checking the user’s station ID, which solves various data requests of passengers in the high-speed moving scenario.

3.4. Local Cache Model

Due to the characteristics of 5G technology, load-carrying and controlling are separated and about 35% of the flow can be sunk to the vehicle edge computing server. The railway industry itself has a smaller amount of data than carrier networks. Thus, the low latency and high efficiency can be achieved by deploying edge MEC.

At present, the standard EMU of the Chinese high-speed railway realizes the local application service of the carriage based on the wireless LAN in the carriage. Video-based business demands a lot of network bandwidth. In order to avoid the impact of the large bandwidth flow on the vehicle–ground network pipeline, the optimization strategy of UPF sinking into the carriage is designed [20]. In order to avoid users constantly requesting media resources from remote resource platforms, high-speed railway edge cloud business relying on on-board UPF/MEC technology provides CDN services for users. For audio, video, website, e-commerce, and UGC (user generated content) business scenarios, this strategy provides users with the distribution and caching of video, pages, pictures, and other small contents. With this strategy, users can directly access them on-board, which effectively solves the problems of high delay and provides a stable, smooth, and diverse browsing experience for users [21]. The high-speed railway CDN cache acceleration function zone can be divided into static resource acceleration and dynamic resource acceleration. Static resource acceleration includes on-demand acceleration, download acceleration, and page acceleration, while dynamic resource acceleration includes specified domain name acceleration, specified content acceleration, etc.

4. Experimental and Simulation Results

4.1. Test Environment

An intelligent EMU numbered CR400BF-C-5162 carries the test environment of the small base station scheme on the Beijing–Zhangjiakou high-speed railway lines. The 5G gateway is connected to the public network through the 5G macro base station along the railway line, and then to the mobile firewall. With a VPN tunnel deployed on the 5G gateway and firewall, the network connection between the on-board small station and the testing core network is realized. The test system supports bands N41, N77, and N78, while the operating frequency covers 2496 MHz–2690 MHz, 3300 MHz–3800 MHz, and the TDD duplex mode band under FR1 at 4400 MHz–5000 MHz. The test networking diagram is shown in Figure 7.

4.2. Testing the Quality of Network Signal along the Beijing–Zhangjiakou High-Speed Railway

During the data service test, macro station signals along the railway were tested through 5G gateway CPE synchronization. As shown in Figure 8 and Figure 9, the 5G signal coverage is good, and the signal is relatively stable in the section between the north of Beijing station and Qinghe station. SS-SINR (synchronization signal—signal to interference noise ratio) values are steadily distributed around 20 dB. The sampling ratio of SS-RSRP (synchronization signal reference signal received power) ≥ −80 dbm is up to 86.86%, the mean value of SS-RSRP is −66.87 dBm, and the mean value of SS-SINR is 9.63 dBm.

4.3. Small Station Registration

The on-board small base station is successfully registered in the testing core network as shown in Figure 10. The mobile phone can be registered to the mobile trial core network during the test. When mobile phone is switched between flight mode and work mode five times, it can be registered successfully five times without losing the connection. During the data service test, the network end-to-end delay was synchronously tested, resulting in approximately 30 ms (maximum 120 ms, minimum 2 ms).

4.4. Simulation and Test of Content Delivery Network Cache Function

To verify the function of CDN, the on-board CDN was simulated and tested in order to make more efficient use of the limited storage space inside the train and take the passengers’ browsing experience into account. It shows the single server of each carriage dynamically allocating the cache space of streaming media resources, under the principle of proximity to meet the requests of clients.

As shown in Figure 11, the total capacity of each hard disk is set to S. Due to physical link limitation, the maximum bandwidth between each hard disk is 450M. For example, there are eight train carriages grouped into cluster A and cluster B, where carriages 1–4 are cluster A and 5–8 are cluster B.

According to the actual working conditions the of wi-fi system of the EMU, the simulation parameters are preliminarily determined. If the duration of a single film is 90 min, and the minimum unit time is 1 min, the storage space requirement of streaming media resources of a single EMU $S_{sum}$ equals 3TB. Given the film code stream $r$ as 4 Mbps, the maximum transmission rate of the on-board backbone network B equals 450 Mbps.

Figure 12a,b demonstrates the changing relationship between the maximum number of concurrent users of a single carriage n and $S_x$ under the different arrival rate λ of random requests for any resource by the terminal. When $\lambda \ge 2$, the relation curve of $n$ with $S_x$ almost coincides. When $0<\lambda \le 2$, the same optimal patch can be used a higher number of times. When the resource dynamic cache space $S_x$ is 500 GB and the number of carriages in each cluster $x$ is 4, the number of channels $C$ of each carriage ranges from 54 to 67. When $S_x$ equals 800 GB and $x$ is set to 4, $C$ ranges from 80 to 95. When $S_x$ equals 500 GB and $x$ is 8, the number of $C$ is from 47 to 55, while when $S_x$ equals 800 GB and $x$ is 8, the number of $C$ is from 60 to 72.

According to the analyzed results of background data collected by high-speed railway CDN, for the average transmission time of streaming media resources: $T_C$ is set to 4 s, and $S_h$ to 500 MB. The change relationship between $S_x$ and transmission time T_C of streaming media resources under different values of $S_{sum}$ is shown in Figure 13. The results show that with the increase in $S_x$, $T_2$ gradually becomes smaller. The larger the total $S_x$ is, the smaller the $T_c$ is, and the better the client experience is. In extreme cases, if the total resources are less than the available disk capacity of each carriage streaming media service, all resources can be preset to each streaming media server, and $T_c$ becomes 0.

5. Conclusions

In this paper, a new scheme base on small stations simplifies the supporting requirements for 5G construction along railway lines, breaks the dilemma of site selection for 5G base stations, and alleviates the contradiction between network coverage and investment cost. In terms of 5G layout and optimization, this scheme reduces the costs of 5G operation and maintenance, and solves the problems of signal coverage and capacity in high-speed scenarios. Specifically, the scheme transfers the outside users into the train carriage, and reduces the signaling storm caused by the switching of numerous users. The deployment of the new scheme will bring the 5G network closer to the high-speed railway business and railway passengers, which can help operators to break away from the traditional “pipeline” function and provide users with more content-oriented services. At the same time, this new scheme can lay a solid foundation for the deployment of the next generation mobile communication network 6G along the railway.