A method for planning wireless networks within a high-speed train set

Abstract

This invention provides a method for planning a wireless network within a high-speed train, belonging to the field of train communication. The method extracts key internal structural factors affecting radio wave propagation within the train by establishing a geometric model of the target scenario, and then constructs a segmented path loss model. It establishes a communication system model and a channel model based on the asymmetrical structural features inside the carriages, deriving mathematical expressions for wireless network coverage performance indicators. Combining the communication quality requirements within the train and relevant model formulas, it determines the maximum coverage distance of radio waves, determines the initial deployment locations of base stations based on the actual layout within the train, optimizes the size of cell overlap areas using wireless network coverage performance indicators, adjusts base station locations, and obtains the final deployment plan. This invention solves the problem that wireless communication technologies with random fluctuation characteristics cannot meet the high communication quality requirements of next-generation train communication networks.

Description

Technical Field

[0001] This invention belongs to the field of train communication, and in particular relates to a method for planning a wireless network within a high-speed train set. Background Technology

[0002] The rapid development of intelligent trains has placed higher demands on train communication networks in terms of scalability and communication performance. Building a new generation of train communication networks that combine wired and wireless technologies is an inevitable trend in the future development of intelligent trains. However, the internal environment of current high-speed trains is complex, with numerous scatterers, which leads to randomness and instability in internal wireless communication. This makes it difficult to meet the deterministic and reliable requirements of train communication networks. Therefore, reasonable network planning is needed for this unique radio wave propagation scenario inside high-speed trains.

[0003] Studying radio wave propagation mechanisms is a crucial foundation for the design, optimization, and performance evaluation of wireless communication network planning schemes. As a long, narrow, enclosed metal structure, a train carriage experiences multiple refractions and reflections of radio waves within its interior, resulting in complex propagation paths. This unique propagation mechanism has attracted considerable attention from researchers. To further explore the special characteristics of the interior environment of high-speed trains, researchers have established a time-varying multidimensional spectral characteristic model of the interior environment of high-speed trains based on extensive simulation and experimental data. They have also analyzed the signal propagation characteristics under line-of-sight, non-line-of-sight, and quasi-line-of-sight propagation conditions, proposing a unified three-state model.

[0004] In existing wireless network planning schemes, formulating reasonable base station deployment and cell planning schemes is the foundation and core of network planning, design, and performance evaluation. Due to the narrow and enclosed nature of the interior of high-speed trains, large-scale, wide-area network planning schemes used in outdoor areas struggle to achieve precise coverage of small, enclosed areas within the train. Therefore, research on network planning inside high-speed trains largely follows the principle of antenna selection and layout optimization in indoor scenarios. 5G wireless communication systems, with their significant bandwidth advantages, millisecond-level transmission latency, and ultra-high connection density, can perfectly meet the exponentially growing communication demands across various industries and provide crucial technical support for large-scale access of various terminals and diverse vertical industry applications. Therefore, 5G indoor wireless network planning and construction has become a key focus for researchers in recent years. For enclosed indoor scenarios, coverage planning methods are generally used in engineering to improve signal quality. 5G indoor wireless network planning has also provided relatively detailed planning methods: first, collecting user demand information for the scenario and conducting relevant network tests; then, using the actual data obtained from the tests to debug the indoor model given by the communication standard, thereby obtaining a model that conforms to the actual radio wave propagation conditions of the scenario, and using this as a basis for link budgeting. Next, the network requirements for indoor coverage are determined and capacity planning is carried out. The capacity of the cells is calculated based on actual scenario test data or simulation data to ensure the coverage performance of the planned network. Finally, the indoor scenario is divided into regions based on the density of communication services and the communication priority of each region is marked. This allows for targeted network planning for the indoor scenario, ensuring comprehensive and accurate coverage of the target area.

[0005] Based on the above analysis, the shortcomings of existing research and the solutions provided by this invention regarding the radio wave propagation mechanism inside high-speed trains and the deployment of base stations and cell planning schemes within the trains are as follows:

[0006] Regarding the propagation mechanism of radio waves inside high-speed trains, researchers have primarily focused on the external frame of the train carriages, neglecting the impact of the internal structure, such as passenger seats, luggage racks, electrical boxes, inner doors, and windshields, and their complex layout, on signal propagation. Existing models for radio wave propagation inside trains heavily rely on measured or simulated data, and analyses of propagation characteristics are largely based on trends and fluctuations in specific data, without providing a concrete analysis of the relationship between the internal radio wave propagation mechanism and complex environmental factors.

[0007] Regarding base station deployment and cell planning schemes inside high-speed trains, relatively complete technologies and planning schemes exist for indoor scenarios. However, the placement and layout of objects indoors are random and uncertain. Therefore, most of the aforementioned indoor wireless network planning schemes only consider the impact of relatively fixed external frames such as walls and windows on signal propagation, ignoring the internal structure. However, high-speed trains contain numerous relatively fixed internal structures such as seats, luggage racks, and windshields, which significantly affect wireless signal propagation. Ignoring these internal structures during network planning introduces substantial errors. Furthermore, the aforementioned indoor wireless network planning schemes treat the scenario as symmetrical to simplify calculations during link budget and capacity analysis. However, high-speed trains contain numerous asymmetrical structures; therefore, applying existing symmetrical indoor wireless network planning methods will introduce significant errors. In summary, using the aforementioned existing indoor wireless network planning schemes for high-speed train interiors will result in serious resource waste or substandard network service quality. Summary of the Invention

[0008] To address the aforementioned shortcomings in existing technologies, this invention provides a method for planning a wireless network within a high-speed train, which solves the problem that wireless communication technologies with random fluctuation characteristics cannot meet the high communication quality requirements of next-generation train communication networks.

[0009] To achieve the above objectives, the technical solution adopted by this invention is: a method for planning a wireless network within a high-speed train set, comprising the following steps:

[0010] A geometric model of the target scenario is established, from which key internal structural factors influencing radio wave propagation within the trainset are extracted. Through geometry-based propagation analysis, the intrinsic relationship between these key internal structural factors and the segmentation of the propagation model is explored, establishing a segmented propagation model framework that can be constructed using only the environmental layout. Specifically, considering the characteristics of the propagation environment within the trainset, the internal environment of the high-speed trainset is defined as a mixed line-of-sight (MLoS) propagation environment; the segmented propagation model framework is the propagation model constructed for this mixed line-of-sight (MLoS) propagation environment within the trainset.

[0011] Based on the segmented propagation model framework, and combined with the asymmetric internal structure characteristics of the train, a communication system model and a hybrid channel model for narrow and enclosed asymmetric scenarios are established, and a mathematical expression for the wireless network coverage performance index is derived. The wireless network coverage performance index includes the average user capacity at the cell edge and the user capacity that meets the interruption probability requirements.

[0012] Based on the probability of user outages and the communication quality requirements within the train set, the maximum coverage distance of the radio waves within the train set is determined. Then, based on the actual layout within the train set, the required number and deployment locations of base stations are determined. Using wireless network coverage performance indicators, the size of the overlapping area of ​​cells is optimized. Finally, a base station deployment and cell planning scheme is formulated to achieve reliable wireless coverage in asymmetrical scenarios within the train and to complete the rational planning of the wireless network within the high-speed train set.

[0013] Furthermore, the hybrid line-of-sight MLoS propagation environment includes three propagation phases:

[0014] The propagation phases include a mixed propagation phase of line-of-sight (LoS) propagation and a phase of line-of-sight (OLoS) propagation that blocks OLoS, a phase of line-of-sight (OLoS) propagation that blocks OLoS alone, and a phase of line-of-sight (NLoS) propagation that blocks NLoS alone.

[0015] Furthermore, the expression for the segmented propagation model is as follows:

[0016]

[0017] in, This represents the path loss parameter in a mixed line-of-sight MLoS propagation environment. , as well as Both represent intercepts. , and Both represent path loss parameters. Indicates the distance between the transmitter and receiver. This represents the distance between the breakpoint and the transmitter during the hybrid propagation phase and the single line-of-sight (OLoS) phase. This indicates the distance between the transmitting antenna and the nearest interior end door of the carriage;

[0018] right It can be obtained by constructing similar triangles inside the carriage, and the calculation formula is as follows:

[0019]

[0020] in, L Indicates the length of the passenger seat. H Indicates the height of the seat. Indicates the spacing between seats. Indicates the height of the transmitting end. Indicates the height of the plane where the receiving end is located. Q This indicates the distance between the transmitter and the first seat. p The seat number represents the seat whose highest point is exactly tangent to the signal transmission path between the transmitter and receiver, and its value is the maximum value that makes the following equation true:

[0021]

[0022] The expression for the hybrid channel model is as follows:

[0023]

[0024] in, This indicates the receiving power of the terminal inside the train set. This indicates the transmission power of the base station inside the vehicle. This represents a constant that depends on the carrier frequency of the transmitted signal. Indicates the distance between the transmitter and receiver. Let Y represent the path loss exponent, and let Y be a random variable used to characterize the combined fading characteristics of shadow fading and fast fading, expressed as:

[0025]

[0026] in, The probability density function represents the power distribution of the random variable Y. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Represents random variables Y The power.

[0027] Furthermore, the communication system model includes a communication system with three transmitting base stations, and the communication system includes a target base station. and interfering base stations and The internal number of the train set is k base station The signal coverage areas on both sides are modeled as the major axis. and long axis The minor half-axis is b An ellipse.

[0028] Furthermore, the expression for the effective signal received by the target user in the communication system model is as follows:

[0029]

[0030]

[0031]

[0032] in, This represents the probability density function of the valid signal received by the target user in the communication system model. This represents the valid signal received by the target user in the communication system model. and All represent the log-normal distribution parameters of the effective signal. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Indicates the target base station The transmission power, Indicates the relationship with the target base station Constant parameters related to the transmit carrier frequency, Indicates the target user and the target base station The distance between them Indicates the target base station The path loss index relative to the transmission environment of the target user. Indicates the target base station Path loss incurred when communicating with the target user;

[0033] The expression for the total interference signal received by the target user in the communication system model is as follows:

[0034]

[0035]

[0036]

[0037]

[0038] in, This represents the probability density function of the total interference signal received by the target user in the communication system model. , and These represent the location, scale, and shape parameters of the log-skewed normal distribution, respectively. i This represents the total interference signal received by the target user in the communication system model. and Let represent the probability density function and cumulative distribution function of the standard normal distribution, respectively. Indicates base station The log-normal distribution parameters of the emitted interference signal, Indicates interference with base stations The transmission power, Indicates interference with base stations Constants related to the transmit carrier frequency. Indicates the target user and the interfering base station The distance between them Indicates interference with base stations The path loss index relative to the transmission environment of the target user. Indicates interference with base stations Path loss incurred when communicating with the target user;

[0039] The expression for the signal-to-interference-plus-noise ratio (SINR) of the target user in the communication system model is as follows:

[0040]

[0041] in, This represents the signal-to-interference-plus-noise ratio (SIR) of the target user in the communication system model. This represents the valid signal received by the target user in the communication system model. Indicates thermal noise power. I This represents the total interference signal received by the target user in the communication system model. and Both represent composite random variables of shadow fading and fast fading.

[0042] Furthermore, the expression for the average user capacity at the cell edge is as follows:

[0043]

[0044]

[0045] in, This represents the average user capacity at the cell edge. R This represents the maximum value in the edge area of ​​the cell. This represents the inner boundary value of the cell's edge region. Indicates user capacity. z Indicates the degree of information irritation. Indicates the bandwidth of the target user. The probability density function representing the signal-to-interference ratio (SIR). This represents the probability density function of the standard normal distribution. The cumulative distribution function represents the standard normal distribution. Indicates the scale parameter. Indicates shape parameters, Indicates positional parameters.

[0046] Furthermore, the expression for the user capacity that meets the interruption probability requirement is as follows:

[0047]

[0048] in, This represents the user capacity that meets the interruption probability requirements. Indicates the probability of interruption. Indicates the bandwidth of the target user. This indicates the minimum acceptable signal-to-interference-plus-noise ratio (SIR).

[0049] Furthermore, the aforementioned base station deployment and cell planning scheme specifically includes:

[0050] The probability of user outage is defined as the probability that the path loss during radio wave propagation is greater than the maximum tolerable path loss. The maximum coverage distance of radio waves in each area of ​​the train crew is determined by combining the probability of user outage with the actual communication quality requirements within the train crew.

[0051] Based on the maximum coverage distance of each area and the internal structure of the vehicle, the deployable location of the first base station is determined and the size of the overlapping area is roughly calculated to preliminarily determine the number of base stations required for each scheme and their deployment locations. Finally, multiple possible preliminary deployment schemes with the first base station located in different locations are obtained.

[0052] For each preliminary deployable scheme, an optimization problem is established based on the initially determined number of base stations and their deployment locations. The objective is to minimize the number of base stations placed inside the vehicle, while constraints include the average user capacity at the cell edge and the user capacity meeting the outage probability requirements, as well as the coverage quality requirements within the vehicle. The size of the cell overlap area is then optimized.

[0053]

[0054] in, m Indicates the number of base stations. Indicates the first k The size of the overlapping region, Indicates the first Maximum coverage distance on the left side of each base station Indicates the first k Maximum coverage distance on the right side of each base station L Indicates the total length of the train. This represents the minimum permissible average user capacity at the cell edge. This represents the minimum permissible user capacity that meets the interruption probability requirement. This represents the average user capacity at the cell edge. This represents the user capacity that meets the interruption probability requirements.

[0055] Based on the optimized design results of the cell overlap area size, the deployment location of each base station is optimized. In particular, when the radio wave mechanism on the left and right sides of the optimized base station changes, the overlap area involved by the base station that has changed needs to be optimized according to the changed situation.

[0056] Multiple possible deployment schemes for the first base station located in different locations were compared in terms of both engineering cost and network performance. The optimal base station deployment and cell planning scheme was selected from those schemes, which requires the fewest number of base stations and minimizes interference within the train set. This scheme achieves reliable wireless coverage in small-scale asymmetric scenarios inside the train and completes the planning of the wireless network inside the high-speed train set.

[0057] Furthermore, the expression for the user interruption probability is as follows:

[0058]

[0059]

[0060]

[0061]

[0062]

[0063] in, Indicates the probability of user interruption. This represents a parameter whose value is... , n This represents the path loss parameter. J , E , F and G Both represent variables. This represents the maximum allowable path loss. Represents the error function. R This represents the maximum value in the edge area of ​​the cell. This represents the constant intercept in the path loss formula. The standard deviation of shadow fading.

[0064] Furthermore, the expression for the maximum coverage distance is as follows:

[0065]

[0066]

[0067]

[0068] in, Indicates the maximum coverage distance. This represents the maximum transmission distance of standalone non-line-of-sight (NLoS) propagation under the same total transmission loss. This indicates the actual transmission distance during the hybrid propagation phase. This represents the actual transmission distance during the line-of-sight (LoS) phase of a single-line-of-sight propagation. and They represent and The equivalent propagation distance of radio waves compared to standalone non-line-of-sight (NLoS) propagation under the same path loss. and The difference between them.

[0069] The beneficial effects of this invention are:

[0070] (1) In view of the characteristics of the narrow and enclosed interior of high-speed train sets, the abundance and complex layout of scatterers, and the problem that existing studies have blurred and simplified the special scene, which cannot accurately depict the characteristics of the scene inside the train set, this invention creatively proposes the concept of MLoS hybrid propagation environment, defines the type of space environment inside the train set and clarifies its characteristics, and fills the gap in the research on radio wave propagation environment in this scene.

[0071] (2) In view of the fact that existing models do not clearly define the intrinsic relationship between the internal environment of the train and the fluctuation of the radio wave propagation mechanism, and that existing models are highly dependent on actual test data and have poor universality, this invention proposes a universally applicable geometry-based segmented radio wave propagation model, which fills the research gap between the propagation model and the specific geometric structure in this scenario.

[0072] (3) This invention addresses the problem that traditional indoor network planning schemes often ignore complex indoor scatterers and treat the scene as a symmetrical scene to simplify calculations when performing link budget and capacity analysis, which can lead to large errors when applied to the complex environment inside the train. It creatively proposes an asymmetric three-base station communication system model and a channel model that considers the complex internal layout and composite fading, which accurately characterizes the coverage characteristics of the space inside the train and fills the gap in the research on radio wave coverage in this scenario.

[0073] (4) This invention derives the user capacity evaluation index for network coverage performance in the proposed asymmetric coverage scenario, and provides an evaluation index formula for the special propagation environment inside high-speed trains. Based on the index formula, detailed steps for base station deployment and cell planning optimization in the asymmetric environment inside the train are given, making up for the deficiencies of the wireless network planning scheme in this scenario. Attached Figure Description

[0074] Figure 1 This is a flowchart of the method of the present invention.

[0075] Figure 2 This is a diagram illustrating the technical solution of the present invention.

[0076] Figure 3 This is a schematic diagram of the mixed propagation stage of LoS and OLoS in this embodiment.

[0077] Figure 4 This is a schematic diagram of the individual OLoS propagation stage in this embodiment.

[0078] Figure 5 This is a schematic diagram of the individual NLoS propagation stage in this embodiment.

[0079] Figure 6 This diagram illustrates the breakpoint locations of the mixed propagation phase of LoS and OLoS and the single propagation phase of OLoS in this embodiment.

[0080] Figure 7 This is a schematic diagram of the similar triangle construction in this embodiment.

[0081] Figure 8 This is a schematic diagram of the base station coverage model inside the vehicle group in this embodiment.

[0082] Figure 9 This embodiment presents a schematic diagram of a base station communication system scenario modeling. Detailed Implementation

[0083] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0084] Example

[0085] like Figures 1-2 As shown, this invention provides a method for planning a wireless network within a high-speed train set, the implementation of which is as follows:

[0086] S1. Establish a geometric model of the target scenario and extract key internal structural factors affecting the propagation of radio waves within the train crew. Explore the intrinsic relationship between key internal structural factors and segmented propagation models through geometry-based propagation analysis. Establish a segmented propagation model framework that can be constructed simply by considering the layout within the environment. The propagation environment inside the train crew is defined as a mixed line-of-sight (MLoS) propagation environment. The segmented propagation model framework is a propagation model constructed for the mixed line-of-sight propagation environment inside the train crew. The mixed line-of-sight propagation environment includes three propagation stages: a mixed propagation stage of line-of-sight (LoS) propagation and obstructed line-of-sight (OLoS) propagation, a propagation stage of obstructed line-of-sight (OLoS) propagation alone, and a propagation stage of non-line-of-sight (NLoS) propagation alone.

[0087] S2. Based on the segmented propagation model framework and considering the internal structural characteristics of the train carriage, a communication system model and a hybrid channel model are established for a narrow, enclosed, asymmetrical scenario. Mathematical expressions for wireless network coverage performance indicators are derived, including the average user capacity at the cell edge and the user capacity meeting the outage probability requirements. The communication system model comprises a communication system with three transmitting base stations, including a target base station. and interfering base stations and The internal number of the train set is k base station The signal coverage areas on both sides are modeled as the major axis. and long axis The minor half-axis is b An ellipse;

[0088] S3. Based on the user interruption probability and the communication quality requirements within the train set, determine the maximum coverage distance of the radio waves within the train set. Then, based on the actual layout within the train set, determine the required number and deployment locations of base stations. Utilize wireless network coverage performance indicators to optimize the size of overlapping cell areas. Finally, formulate a base station deployment and cell planning scheme to achieve reliable wireless coverage in asymmetrical scenarios within the high-speed train set, completing the planning of the wireless network within the high-speed train set. Specifically:

[0089] The user outage probability is defined as the probability that the path loss during radio wave propagation exceeds the maximum tolerable path loss. The maximum radio wave coverage distance for each area within the vehicle is determined by combining the user outage probability with the actual communication quality requirements within the vehicle. Based on the maximum coverage distance of each area and the internal structure of the vehicle, the deployable location of the first base station is determined, and the size of the overlap area is roughly calculated to initially determine the number and deployment locations of base stations required for each scheme. This results in several possible preliminary deployment schemes with the first base station located in different positions. For each preliminary deployable scheme, an optimization problem is established based on the initially determined number and deployment locations of base stations, with the objective of minimizing the number of base stations placed within the vehicle, and considering factors such as the average user capacity at the cell edge and the user capacity meeting the outage probability requirements. With the coverage quality requirements inside the train set as a constraint, the size of the cell overlap area is optimized. Based on the optimization design of the cell overlap area size, the deployment location of each base station is optimized. In particular, when the radio wave mechanism on the left and right sides of the optimized base station changes, the overlap area involved by the base station that has changed needs to be optimized according to the changed situation. Multiple possible deployment schemes with the first base station located in different positions are compared from the aspects of engineering cost and network performance. The optimal base station deployment and cell planning scheme is selected from the least number of base stations required and the least interference inside the train set. This achieves reliable wireless coverage in the narrow, enclosed, and asymmetrical scenario inside the high-speed train set, and completes the planning of the wireless network inside the high-speed train set.

[0090] In this embodiment, the research content of the present invention can be divided into two parts, such as... Figure 2 As shown, the first part is the analysis of radio wave propagation inside a high-speed train, and the second part is the deployment of base stations and cell planning schemes inside the high-speed train. First, a geometric model of the target scenario is established, from which key internal structural factors affecting radio wave propagation within the train are extracted (i.e., key factors extracted from the train's internal structure in the figure). Through geometry-based propagation analysis, the intrinsic relationship between influencing factors and model segmentation is explored, and a segmented propagation model framework that only requires a rough layout within the environment is established (i.e., a low-data-dependency general propagation model that comprehensively considers the train's internal structure in the figure). Then, based on the obtained path loss model inside the train, and combined with the train's internal structure, a communication system model and channel model are established for a narrow, enclosed, asymmetrical scenario, and mathematical expressions for relevant coverage indicators are further derived. To maximize coverage and minimize the number of base stations while meeting the coverage quality requirements inside the train set, the required number of base stations and their approximate deployment locations are determined. Furthermore, mathematical models of indicators such as user outage probability and user capacity are used to optimize the design of the cell overlap area, thereby correcting the deployment location of the base stations. Finally, a reasonable base station deployment and cell planning scheme is formulated to achieve reliable wireless coverage in the narrow, enclosed, and asymmetrical scenarios inside the high-speed train set.

[0091] In this embodiment, the radio wave propagation analysis inside the high-speed train is as follows:

[0092] Radio wave propagation environments are typically categorized into three types based on their propagation characteristics: line-of-sight (LoS), non-line-of-sight (NLoS), and obstructed line-of-sight (OLoS). LoS refers to a propagation scenario where the signal travels in a straight line to the receiver, with no obstruction along the transmission path. NLoS refers to a propagation scenario where the signal reaches the receiver through reflection, diffraction, or scattering, completely obstructing the transmission path. OLoS refers to a propagation scenario where the signal reaches the receiver through a combination of propagation mechanisms, partially obstructing the transmission path. However, the interior of a high-speed train is a long, narrow, enclosed space with numerous scatterers, resulting in highly complex radio wave propagation characteristics. Within the same area, the propagation of wireless signals can be complicated by various intermingled propagation mechanisms due to variations in the train's internal structural layout, making it difficult to clearly classify the propagation environment within the train.

[0093] Therefore, this invention combines the specific internal structure of train carriages with geometric analysis to study the unique environmental characteristics inside high-speed train sets. Based on the traditional LoS, NLoS, and OLoS propagation environments, it innovatively proposes the concept of Mixed Line of Sight (MLoS) propagation environment, thus more accurately characterizing the specific features of the propagation environment inside train sets. The Mixed Line of Sight (MLoS) propagation environment can be subdivided into three propagation stages: a mixed propagation stage of LoS and OLoS, a single OLoS propagation stage, and a single NLoS propagation stage.

[0094] Firstly, during the mixed LoS and OLoS propagation phase, because the signal receivers are randomly located within the carriage, and the carriage contains numerous scattering objects with mixed layouts, such as passenger seats, the radio wave propagation mechanism between the transmitter and receiver will continuously switch between LoS and OLoS propagation in an area close to the transmitting antenna. For example... Figure 3 As shown in the figure, the dashed line represents the signal propagation path. It can be seen from the figure that for point A, which is close to the transmitting antenna, and point C, where the propagation path between the transmitter and receiver is exactly tangent to the top of the seat, the radio wave propagation mechanism is LoS (Local-Short ...

[0095] Secondly, during the individual OLoS propagation phase, once the receiver is a certain distance from the transmitting antenna, the propagation of radio waves between the transmitter and receiver will inevitably be obstructed by passenger seats in the propagation environment. At this point, the situation where the propagation path is exactly tangent to the seat back and not blocked by the seat in front no longer exists. Figure 4 Points E and F are shown in the diagram. Therefore, to accurately characterize the characteristics of radio wave propagation in this stage, this stage is defined as the standalone OLoS propagation stage.

[0096] Finally, regarding the NLoS propagation phase alone, when the receiver is located on the other side of a closed end door inside the carriage, the closed end door completely blocks the propagation of the wireless signal. In this case, it can be considered that the propagation of the wireless signal only involves NLoS propagation. Figure 5 As shown at point G. Therefore, to accurately characterize the characteristics of radio wave propagation in this stage, this stage is defined as the standalone NLoS propagation stage.

[0097] Based on the above analysis, this invention establishes a segmented propagation model for the MLoS propagation environment inside the train set, using the logarithmic distance propagation model as a foundation. First, it is necessary to determine the locations of the two breakpoints in the three stages of hybrid propagation, i.e., their distances from the transmitting antenna. and For the breakpoint between the mixed propagation phase of LoS and OLoS and the single OLoS propagation phase, before this breakpoint, when the signal transmission path is exactly tangent to the highest point of a seat, there are no other seats obstructing this path, such as... Figure 6 As shown at point E, after this breakpoint, there are other seats obstructing the path, such as... Figure 6 Point F is shown in the diagram. Therefore, let the length of the passenger seat be... L The height of the seat is H The spacing between seats is The seat number is p The height of the transmitting antenna is The height of the plane where the receiving end is located is The distance between the transmitting antenna and the first seat is Q. It is possible to construct a path where the signal transmission path is exactly parallel to the first seat. p Similar triangles ABC and ADE are formed when the highest points of the seats are tangent to each other, such as... Figure 7 As shown.

[0098] Then, based on the relevant properties, we can obtain the following formula (1):

[0099] (1)

[0100] in, Let represent the length of side DE in triangle ADE. Then, find the maximum value that makes equation (2) true.p The value can be obtained , p Let represent the seat number where the highest point is exactly tangent to the signal transmission path between the transceiver and the receiver. Its value is the maximum value that makes the following equation true, as shown in equation (3):

[0101] (2)

[0102] (3)

[0103] in, This indicates the distance between the breakpoint and the transmitter in the mixed LoS and OLoS propagation phase and the single OLoS phase. This indicates the distance between the breakpoint of a single OLoS phase and a single NLoS phase and the transmitter, i.e., the distance between the transmitting antenna and the nearest end door inside the carriage.

[0104] After determining the breakpoints at each stage, a segmented propagation model for the MLoS state can be established as shown in equation (4):

[0105] (4)

[0106] in, This represents the path loss parameter in the MLoS propagation environment. , as well as Both represent intercepts. , and Both represent path loss parameters. This represents the distance between the transmitter and receiver. The expression for the hybrid channel model is: ,in, This indicates the receiving power of the terminal inside the train set. This indicates the transmission power of the base station inside the vehicle. This represents a constant that depends on the carrier frequency of the transmitted signal. Indicates the distance between the transmitter and receiver. Let Y represent the path loss exponent, and let Y be a random variable used to characterize the combined fading characteristics of shadow fading and fast fading, expressed as: ,in, Represents random variables Y The probability density function of the power distribution. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Represents random variables Y The power.

[0107] In this embodiment, the deployment of base stations and cell planning scheme inside the high-speed train are as follows:

[0108] The performance of wireless communication network coverage is crucial for evaluating the rationality and reliability of wireless network planning schemes. Therefore, to obtain a comprehensive method for base station deployment and cell planning within high-speed train sets, in-depth research on communication network coverage performance is necessary. To better assess network coverage performance and provide a solid theoretical foundation for subsequent network planning schemes, this invention selects the average user capacity at the cell edge and the correct reception capacity during cell outages as indicators to measure network coverage performance and derives their specific formulas.

[0109] To derive the specific formula for the index, this invention establishes a communication scenario including asymmetric cells for research. The scenario includes three base stations, which are the target base station. and interfering base stations and The internal markings of the train set are as follows: k base station The present invention models the signal coverage range on its left and right sides as having a major axis of... , The minor semi-axis is b An ellipse, such as Figure 8 As shown, the overall system model of the three-base station system is as follows: Figure 9 As shown in the figure, the dark shaded areas represent the overlapping portions between adjacent cells. In this communication system, because the overlapping cells are asymmetrical, the sizes of their overlapping areas also vary, denoted by [missing information - likely symbols or symbols]. and To express.

[0110] In a three-base station communication system scenario, the effective signal received by the target user comes only from the target base station. The distribution of the received signal follows a log-normal distribution, therefore its specific mathematical expression can be written in the following form:

[0111] (5)

[0112] (6)

[0113] (7)

[0114] in, This represents the probability density function of the valid signal received by the target user in the communication system model. This represents the valid signal received by the target user in the communication system model. and All represent the log-normal distribution parameters of the effective signal. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Indicates the target base station The transmission power, Indicates the relationship with the target base station Constant parameters related to the transmit carrier frequency, Indicates the target user and the target base station The distance between them Indicates the target base station The path loss index relative to the transmission environment of the target user. Indicates the target base station Path loss incurred when communicating with the target user;

[0115] Unlike valid signals, in a three-base station communication system scenario, the interference signals received by the target user exist in two forms: those from interfering base stations and those from other base stations. Interference signals With interference from base stations Interference signals Therefore, the total interference signal received by the target user should be the superposition of the two interference signals mentioned above. Regarding the interference signal... and Its distribution is the same as that of the effective signal, both following a log-normal distribution, which can be expressed as:

[0116] (8)

[0117] in, This indicates that the target user in the communication system model receives a number that is... i Interference base stations The probability density function of the emitted interference signal, and All indicate interference with base stations. The log-normal distribution parameters of the emitted interference signal ( The specific calculation formulas for these two parameters are as follows:

[0118] (9)

[0119] (10)

[0120] in, Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the hybrid channel model of path loss, shadow fading, and fast fading. Indicates interference with base stations The transmission power, Indicates interference with base stations Constants related to the transmit carrier frequency. Indicates the target user and the interfering base station The distance between them Indicates interference with base stations The path loss index relative to the transmission environment of the target user, and the interfering base station. The path loss incurred when communicating with the target user can be used In a three-base station communication system scenario, the geometric relationship between the distances between the target user and the target base station, as well as between the two adjacent interfering base stations, can be expressed as:

[0121] (11)

[0122] (12)

[0123] in, Indicates interference with base stations Distance to target users Indicates interference with base stations Distance to target users , , Specifically, such as Figure 9 As shown, Indicates the target base station The distance between you and your target users.

[0124] For total interference signal I It is the superposition of the two interference signals that follow a log-normal distribution, and therefore it follows a log-normal sum distribution. For ease of data processing and analysis, this invention approximates the log-normal sum distribution as a log-skewed normal distribution for simplification. Therefore, the total interference signal... I The final formula is as follows:

[0125] (13)

[0126] (14)

[0127] (15)

[0128] (16)

[0129] in, This represents the probability density function of the total interference signal received by the target user in the communication system model. , and These represent the location, scale, and shape parameters of the log-skewed normal distribution, respectively. i This represents the total interference signal received by the target user in the communication system model. and Let represent the probability density function and cumulative distribution function of the standard normal distribution, respectively. Indicates interference with base stations The log-normal distribution parameters of the emitted interference signal, Indicates interference with base stations The transmission power, Indicates interference with base stations Constants related to the transmit carrier frequency. Indicates the target user and the interfering base station The distance between them Indicates interference with base stations The path loss index relative to the transmission environment of the target user. Indicates interference with base stations Path loss incurred when communicating with the target user.

[0130] After obtaining the specific expressions for the effective signal and interference signal received by the target user, the signal-to-interference-plus-noise ratio (SIR) of the target user can be expressed as:

[0131] (17)

[0132] in, This represents the signal-to-interference-plus-noise ratio (SIR) of the target user in the communication system model. Indicates the spacing between seats. i Indicates the number of the interfering base station. and Both represent composite random variables of shadow fading and fast fading. The thermal noise power is represented by [the variable name]. Since the interference power of the channel is much greater than the thermal noise power in the complex propagation scenario inside a high-speed train, the thermal noise power can be ignored in this scenario, representing the composite fading random variable of the interference signal. and Both are statistically independent and both follow a log-normal distribution.

[0133] This invention utilizes a log-skewed normal distribution to approximate the signal-to-interference-plus-noise ratio (SIR / NNR) distribution. Therefore, its probability density function, which approximately satisfies a log-skewed normal distribution, can be expressed as:

[0134] (18)

[0135] in, This represents the probability density function of the standard normal distribution. This represents the cumulative distribution function of the standard normal distribution. Furthermore, based on the properties of the sloping distribution, the position parameter in formula (18) is... Scale parameters and shape parameters The specific calculation formula is as follows:

[0136] (19)

[0137] (20)

[0138] (twenty one)

[0139] The effective signal in the above formula S Log-normal distribution parameters and As already given above, the total interference signal I Log-normal distribution parameters and and signal-to-interference-plus-noise ratio Z Log-normal distribution parameters and The calculation formula is as follows:

[0140] (twenty two)

[0141] (twenty three)

[0142] (twenty four)

[0143] (25)

[0144] The mathematical form of the cumulative distribution function of the signal-to-interference-plus-noise ratio is as follows:

[0145] (26)

[0146] in, The Owen T function is defined as follows:

[0147] (27)

[0148] Based on the specific mathematical formulas for the effective signal, interference signal, and signal-to-interference-plus-noise ratio derived above, this invention further derives the formulas for accessing the target base station in the studied three-base station communication system scenario. target user capacity as follows:

[0149] (28)

[0150] The average user capacity at the cell edge is the instantaneous average of the capacity of all edge users in the target base station's cell. Therefore, its expression can be derived as follows:

[0151] (29)

[0152] in, This represents the average user capacity at the cell edge. R This represents the maximum value in the edge area of ​​the cell. This represents the inner boundary value of the cell's edge region. For user capacity, z For the sake of trust, dryness and impatience are more important. Indicates the bandwidth of the target user. The probability density function representing the signal-to-interference ratio (SIR). This represents the probability density function of the standard normal distribution. The cumulative distribution function represents the standard normal distribution. Indicates the scale parameter. Indicates shape parameters, Indicates positional parameters.

[0153] The correct reception capacity for cell outages is the average rate at which the communication system can correctly receive information under a certain probability of communication signal outages allowed by the system. It depends on the system's permissible probability of signal outages. This invention defines an outage capacity where the user's signal-to-interference-plus-noise ratio (SIR) is less than the system's minimum permissible SIR. An interruption occurs at a certain time, therefore the cell interruption probability can be expressed as:

[0154] (30)

[0155] in, This represents the probability of a cell outage. and Let represent the cumulative distribution function and probability density function of the signal-to-interference-ratio, respectively. Indicates the degree of information irritation. It represents probability.

[0156] Furthermore, when the interruption probability is The formula for calculating the interruptible capacity of a cell user can be expressed as follows:

[0157] (31)

[0158] in, This indicates the interruptible capacity of users in the community.

[0159] At this point, the specific calculation formula for the average data rate that the system can correctly receive, i.e., the cell's outage correct reception capacity, can be expressed as follows:

[0160] (32)

[0161] in, This represents the user capacity that meets the interruption probability requirements. Indicates the probability of interruption. Indicates the bandwidth of the target user. This indicates the minimum acceptable signal-to-interference-plus-noise ratio (SIR).

[0162] Based on the above derivation results of network coverage performance indicators, the five steps of the base station deployment and cell planning method proposed in this invention will be described in detail below, namely, prediction of wireless coverage inside the vehicle group, preliminary determination of base station location, design of cell overlap area size, optimization of base station location, and comparison of scheme performance.

[0163] Step 1: Predicting Wireless Coverage Inside the Train Crew

[0164] This invention utilizes the maximum coverage distance of wireless signals to measure the coverage performance of the train's internal environment. To calculate the maximum coverage distance of wireless signals in different areas within the train while ensuring network communication performance, it is first necessary to determine the Maximum Allowable Path Loss (MAPL). MAPL depends on transmit power, feeder loss, antenna gain, vehicle body loss, shadow fading margin, equipment aging margin, and other factors. Combining the communication quality requirements for signal transmission within the train under specific conditions with other loss parameters defined in relevant standards, the tolerable maximum path loss (MAPL) within the train can be determined. In this invention, the user interruption probability is defined as the probability that the path loss encountered during radio wave propagation exceeds the maximum allowable path loss (MAPL). By providing a reasonable user interruption probability, the maximum coverage distance that ensures the performance of the train's communication network is determined.

[0165] To obtain the relevant mathematical formulas for the user interruption probability, a geometric model of the train's internal environment was first constructed. Based on the internal layout and the aforementioned research results, the train's internal environment was divided into different regions. Then, by combining the specific propagation environment type and internal structure of each region, the path loss model applicable to the propagation of wireless signals within the divided regions was further determined. Its specific expression can be written as follows:

[0166] (33)

[0167] in, Indicates path loss. It is a constant. This represents the path loss parameter. d Indicates the distance between the transmitting and receiving ends. W Let represent a random variable characterizing the fading properties, which follows a normal distribution with a mean of zero, and the parameters are... W The specific probability density function formula can be expressed in the following form:

[0168] (34)

[0169] in, express W The specific probability density function, This represents the standard deviation of shadow fading.

[0170] The path loss in the vehicle interior can be further obtained through convolution calculations. L The probability density function is given by the following formula:

[0171] (35)

[0172] in, Indicates path loss in the vehicle interior area L The probability density function, , n For path loss parameters, This indicates the maximum coverage distance of a base station within a certain area inside the vehicle. Indicates the intercept. The standard deviation of shadow fading, The variable is represented as follows:

[0173] (36)

[0174] The user interruption probability can be further given by combining the above formula. The specific expression is as follows:

[0175] (37)

[0176] variables in the formula J , E , F , G The specific expression is as follows:

[0177] (38)

[0178] (39)

[0179] (40)

[0180] (41)

[0181] in, Indicates the probability of user interruption. This represents a parameter whose value is... , n This represents the path loss parameter. J , E , F and G Both represent variables. This represents the maximum allowable path loss. Represents the error function. R This represents the maximum value in the edge area of ​​the cell. This represents the constant intercept in the path loss formula. The standard deviation of shadow fading.

[0182] For single-LoS and single-NLoS propagation environments, which do not have multiple propagation stages, the calculation of the maximum transmission distance is relatively simple. Given the maximum user interruption probability that the system can tolerate, the maximum propagation distance in an independent propagation environment can be obtained using the above formula. For MLoS hybrid propagation environments, since there are multiple propagation stages, the maximum transmission distance is determined by the transmission distance of the radio wave in each stage, requiring separate calculation for each stage. In this invention, an equivalent substitution method is used to calculate the equivalent propagation distance of the radio wave in a single-NLoS stage, assuming the path loss is the same as the first two stages of an MLoS environment. and To calculate the additional propagation distance of the first two stages compared to the single NLoS stage. and Then, the total propagation distance is obtained through a superposition mechanism. The equivalent distance calculation formula is as follows:

[0183] (42)

[0184] (43)

[0185] in, This represents the path loss during the mixed propagation phase of LoS and OLoS. This represents the intercept during the mixed propagation phase of LoS and OLoS. This represents the path loss parameter during the mixed propagation phase of LoS and OLoS. This represents the actual transmission distance during the mixed LoS and OLoS propagation phase, specifically the distance between the breakpoint and the transmitter between the mixed LoS and OLoS propagation phase and the single OLoS propagation phase. This represents the intercept during a single NLoS propagation phase. This represents the path loss parameter during a single NLoS propagation phase. This represents the path loss during a single OLoS propagation phase. This represents the intercept during a single OLoS propagation phase. This represents the path loss parameter for a single OLoS propagation stage. This represents the actual transmission distance of a single OLoS propagation phase, i.e., the distance between the breakpoint and the transmitter between a single OLoS propagation phase and a single NLoS propagation phase. difference.

[0186] Then, the difference between the actual transmission distance of the first two stages of the MLoS hybrid propagation environment and the equivalent propagation distance of the single NLoS propagation stage can be calculated using the following equations (44) and (45). and Finally, by calculating the difference... and Maximum transmission distance in a single NLoS environment with the same total transmission loss By adding them together, the maximum transmission distance in a hybrid propagation environment can be obtained. Its specific expression can be represented in the form of the following formula (46):

[0187] (44)

[0188] (45)

[0189] (46)

[0190] in, Indicates the maximum coverage distance. This represents the maximum transmission distance of NLoS in a single non-line-of-sight propagation scenario under the same total transmission loss. This indicates the actual transmission distance during the mixed propagation phase of LoS and OLoS. This represents the actual transmission distance during a single OLoS propagation phase. and They represent and Equivalent propagation distance of radio waves compared to the NLoS phase alone, under the same path loss conditions. and The difference between them.

[0191] Step 2: Preliminary determination of base station location

[0192] After calculating the maximum base station coverage distance in each area within the train set, preliminary deployment of base stations can be carried out. Combining the available base station locations within the carriages with the maximum wireless signal coverage distance at these locations, the initial base station location that can meet the full coverage requirements of the train's communication network can be preliminarily determined. There may be multiple initial base station locations that meet the coverage requirements, and for each possible initial base station location, there is a corresponding base station deployment scheme. For each possible base station deployment scheme, the general cell overlap ratio for indoor base station deployment is used here. The size of the overlapping area of ​​cells within the vehicle group is roughly calculated to preliminarily determine the number of base stations required for each scheme and the initial location of each base station.

[0193] Step 3: Design of the size of the overlapping area in the community

[0194] This invention selects the average user capacity at the cell edge and the correct reception capacity during cell outages as indicators to evaluate the coverage performance of the train communication network, thereby specifically designing the size of the overlap area. Based on the aforementioned derivation of the relevant user capacity formulas, it is found that the average user capacity at the cell edge and the correct reception capacity during cell outages are distance-dependent variables. That is, the performance of the target user in the communication system is closely related to the size of the cell overlap area. Therefore, to balance the impact of the cell overlap area size on communication and coverage performance, this invention establishes an optimization problem to reasonably calculate the cell overlap area. This optimization problem aims to minimize the number of base stations placed inside the train set, and under the premise of ensuring cell coverage probability, it is defined in the following form: (47)

[0195] in, m Indicates the number of base stations. Indicates the first k The size of the overlapping region, Indicates the first Maximum coverage distance on the left side of each base station Indicates the first k Maximum coverage distance on the right side of each base station L Indicates the total length of the train. This represents the minimum permissible average user capacity at the cell edge. This represents the minimum permissible user capacity that meets the interruption probability requirement. This represents the average user capacity at the cell edge. This represents the user capacity that meets the interruption probability requirements.

[0196] In this optimization problem, constraint 1 ensures that the entire area inside the train set is covered by the wireless network, thus ensuring the full coverage performance of the network inside the train set; constraints 2 and 3 ensure reliable communication of the train communication network inside the train set, thus ensuring the communication quality of the network inside the train set.

[0197] The optimization problem can be solved by combining the specific formulas given above and the specific requirements of the target scenario for the train communication network in terms of user interruption probability and user capacity. First, the MAPL and the allowable user interruption probability in the specific scenario are considered. The maximum coverage distance of each base station can be predicted, thereby obtaining the specific coverage distance in constraint 1. R Then, based on the specific parameters of the target scenario, plot the relationship curves between the overlap area size and the average capacity of users at the cell edge and the correct reception capacity during cell outages. Next, consider the minimum allowable average capacity of users at the cell edge for the target scenario. and the minimum permissible cell outage correct reception capacity The previously given relationship curves can further determine the range of selectable cell overlap areas. Finally, by combining the formula in Constraint 1, the range of cells that overlap can be calculated. m The smallest size of each overlapping region is the optimized result.

[0198] Based on the above analysis, the specific sizes of different types of overlapping areas within the train set can be determined under the premise of meeting the performance requirements of the train communication network.

[0199] Step 4: Base Station Location Optimization

[0200] By specifically designing and refining the size of the overlapping area within the cells of the vehicle group, the initial base station deployment locations determined in each deployment scheme can be adjusted based on the optimized results. When adjusting base station deployment locations, it is important to check whether the radio wave mechanisms on the left and right sides of the adjusted base station have changed. If changes have occurred, the overlapping area involved in the changed base station needs to be re-optimized according to the changed situation. Then, the locations of subsequent base stations are adjusted based on the optimized results. Through the above operations, the number of base stations and specific base station deployment locations required for the final optimized scheme can be obtained.

[0201] Step 5: Performance Comparison of Solutions

[0202] Since there may be multiple initial base station deployment locations in step two, there are various possible base station deployment and cell planning schemes. Therefore, to obtain the optimal scheme, we can further compare and filter the possible schemes in terms of engineering cost and network performance. Here, we mainly compare the scheme deployment cost and the scheme coverage performance. Regarding the scheme deployment cost, we mainly consider the number of base stations required by the scheme, prioritizing the scheme with fewer required base stations and lower construction and maintenance costs. Regarding the scheme coverage performance, we mainly consider the coverage resource utilization of cells within the vehicle group, user capacity, and interference within the vehicle group, prioritizing the scheme with less wasted coverage resources, better user capacity indicators, and less interference within the vehicle group. By comparing the above aspects, we can obtain the scheme with the optimal deployment cost and coverage performance as the final network planning scheme.

[0203] In summary, regarding the propagation analysis within high-speed trains, the elongated and enclosed radio wave propagation environment of a high-speed train is significantly influenced by its numerous scatterers and complex structural layout. Existing propagation models often simplify the complex internal layout and focus more on the impact of the train's external frame on wave propagation. Furthermore, these models are mostly data fitting models based on measured data from specific scenarios, failing to analyze the intrinsic relationship between the train's internal structure and the applicable propagation model, resulting in poor universality. This invention extracts and studies key internal factors (such as passenger seats, internal end doors, and windshields) that are relatively fixed in location and significantly affect signal propagation, based on the characteristics of the high-speed train's internal environment. It analyzes their intrinsic relationship with radio wave propagation and uses geometric methods to construct a general propagation model that comprehensively considers the train's internal structure.

[0204] Regarding the deployment of base stations and cell planning within high-speed trains, the elongated and enclosed nature of high-speed trains, a unique radio wave propagation environment, makes it impossible to use outdoor coverage planning schemes designed for large, open areas. Furthermore, the complex internal structure and asymmetrical layout of high-speed trains lead to significant resource waste or substandard network performance when applying traditional indoor symmetrical coverage planning schemes. This invention, taking into account the relatively fixed facilities and their layout within the train, addresses the asymmetrical environment by establishing an accurate propagation model, optimizing the number and deployment of base stations, and conducting refined cell planning. This results in a reasonable base station deployment and cell planning scheme within the train, achieving reliable network planning in the complex and asymmetrical environment of high-speed trains with abundant scattering elements.

Claims

1. A method for planning a wireless network within a high-speed train set, characterized in that, Includes the following steps: A geometric model of the target scenario is established, from which key internal structural factors affecting the propagation of radio waves within the train set are extracted. Through geometry-based propagation analysis, the intrinsic relationship between these key internal structural factors and the segmentation of the propagation model is explored. A segmented propagation model framework, which can be constructed using only the basic layout of the target environment, is established. Specifically, the internal environment of the high-speed train set is defined as a mixed line-of-sight (MLoS) propagation environment, taking into account its characteristics. The segmented propagation model framework is a propagation model constructed for this mixed line-of-sight (MLoS) propagation environment within the train set. Based on the segmented propagation model framework, and combined with the asymmetric internal structure characteristics of the train, a communication system model and a hybrid channel model for narrow and enclosed asymmetric scenarios are established, and a mathematical expression for the wireless network coverage performance index is derived. The wireless network coverage performance index includes the average user capacity at the cell edge and the user capacity that meets the interruption probability requirements. The expression for the segmented propagation model is as follows: in, This represents the path loss parameter in a hybrid line-of-sight (MLoS) environment. , as well as Both represent intercepts. , and Both represent path loss parameters. Indicates the distance between the transmitter and receiver. This indicates the distance between the breakpoint and the transmitter in the hybrid propagation phase and the individual OLoS phase. This indicates the distance between the transmitting antenna and the nearest interior end door of the carriage; right It can be obtained by constructing similar triangles inside the carriage, and the calculation formula is as follows: in, L Indicates the length of the passenger seat. H Indicates the height of the seat. Indicates the spacing between seats. Indicates the height of the transmitting end. Indicates the height of the plane where the receiving end is located. Q This indicates the distance between the transmitter and the first seat. p The seat number represents the seat whose highest point is exactly tangent to the signal transmission path between the transmitter and receiver, and its value is the maximum value that makes the following equation true: The expression for the hybrid channel model is as follows: in, This indicates the receiving power of the terminal inside the train set. This indicates the transmission power of the base station inside the vehicle. This represents a constant that depends on the carrier frequency of the transmitted signal. Indicates the distance between the transmitter and receiver. Let Y represent the path loss exponent, and let Y be a random variable used to characterize the combined fading characteristics of shadow fading and fast fading, expressed as: in, Represents random variables Y The probability density function of the power distribution. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Represents random variables Y The power; Based on the user interruption probability and the communication quality requirements inside the train set, the maximum coverage distance of the radio waves inside the train set is determined. Then, based on the actual layout inside the train set, the number and deployment location of the required base stations are determined. Using the wireless network coverage performance indicators, the size of the cell overlap area is optimized. Finally, a base station deployment and cell planning scheme is formulated to achieve reliable wireless coverage in asymmetrical scenarios inside the train and complete the rational planning of the wireless network inside the high-speed train set. The aforementioned base station deployment and cell planning scheme is specifically as follows: The probability of user outage is defined as the probability that the path loss during radio wave propagation is greater than the maximum tolerable path loss. The maximum coverage distance of radio waves in each area of ​​the train crew is determined by combining the probability of user outage with the actual communication quality requirements within the train crew. Based on the maximum coverage distance of each area and the internal structure of the vehicle, the deployable location of the first base station is determined and the size of the overlapping area is roughly calculated to preliminarily determine the number of base stations required for each scheme and their deployment locations. Finally, multiple possible preliminary deployment schemes with the first base station located in different locations are obtained. For each preliminary deployable scheme, an optimization problem is established based on the initially determined number of base stations and their deployment locations. The objective is to minimize the number of base stations placed inside the vehicle, while constraints include the average user capacity at the cell edge and the user capacity meeting the outage probability requirements, as well as the coverage quality requirements within the vehicle. The size of the cell overlap area is then optimized. in, m Indicates the number of base stations. Indicates the first k The size of the overlapping region, Indicates the first Maximum coverage distance on the left side of each base station Indicates the first k Maximum coverage distance on the right side of each base station L Indicates the total length of the train. This represents the minimum permissible average user capacity at the cell edge. This represents the minimum permissible user capacity that meets the interruption probability requirement. This represents the average user capacity at the cell edge. This represents the user capacity that meets the interruption probability requirements. Based on the optimized design results of the cell overlap area size, the deployment location of each base station is optimized. In particular, when the radio wave mechanism on the left and right sides of the optimized base station changes, the overlap area involved by the base station that has changed needs to be optimized according to the changed situation. Multiple possible deployment schemes for the first base station located in different locations were compared in terms of both engineering cost and network performance. The optimal base station deployment and cell planning scheme was selected from those schemes, which requires the fewest number of base stations and minimizes interference within the train set. This scheme achieves reliable wireless coverage in small-scale asymmetric scenarios inside the train and completes the planning of the wireless network inside the high-speed train set.

2. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The hybrid line-of-sight MLoS propagation environment includes three propagation phases: The propagation phases include a mixed propagation phase of line-of-sight (LoS) propagation and a phase of line-of-sight (OLoS) propagation obstruction, a phase of line-of-sight (OLoS) propagation obstruction alone, and a phase of line-of-sight (NLoS) propagation alone.

3. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The communication system model includes a communication system with three transmitting base stations, and a target base station within the communication system. and interfering base stations and The internal number of the train set is k base station The signal coverage areas on both sides are modeled as the major axis. and long axis The minor half-axis is b An ellipse.

4. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The expression for the effective signal received by the target user in the communication system model is as follows: in, This represents the probability density function of the valid signal received by the target user in the communication system model. This represents the valid signal received by the target user in the communication system model. and All represent the log-normal distribution parameters of the effective signal. Represents a constant, whose value is , and All represent the log-normal composite fading parameters in the segmented propagation model. Indicates the target base station The transmission power, Indicates the relationship with the target base station Constant parameters related to the transmit carrier frequency, Indicates the target user and the target base station The distance between them Indicates the target base station The path loss index relative to the transmission environment of the target user. Indicates the target base station Path loss incurred when communicating with the target user; The expression for the total interference signal received by the target user in the communication system model is as follows: in, This represents the probability density function of the total interference signal received by the target user in the communication system model. , and These represent the location, scale, and shape parameters of the log-skewed normal distribution, respectively. i This represents the total interference signal received by the target user in the communication system model. and Let represent the probability density function and cumulative distribution function of the standard normal distribution, respectively. Indicates base station The log-normal distribution parameters of the emitted interference signal, Indicates interference with base stations The transmission power, Indicates interference with base stations Constants related to the transmit carrier frequency. Indicates the target user and the interfering base station The distance between them Indicates interference with base stations The path loss index relative to the transmission environment of the target user. Indicates interference with base stations Path loss incurred when communicating with the target user; The expression for the signal-to-interference-plus-noise ratio (SINR) of the target user in the communication system model is as follows: in, This represents the signal-to-interference-plus-noise ratio (SIR) of the target user in the communication system model. This represents the valid signal received by the target user in the communication system model. Indicates thermal noise power. I This represents the total interference signal received by the target user in the communication system model. and Both represent composite random variables of shadow fading and fast fading.

5. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The expression for the average user capacity at the cell edge is as follows: in, This represents the average user capacity at the cell edge. R This represents the maximum value in the edge area of ​​the cell. This represents the inner boundary value of the cell's edge region. Indicates user capacity. z Indicates the degree of information irritation. Indicates the bandwidth of the target user. The probability density function representing the signal-to-interference ratio (SIR). This represents the probability density function of the standard normal distribution. The cumulative distribution function represents the standard normal distribution. Indicates the scale parameter. Indicates shape parameters, Indicates positional parameters.

6. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The expression for the user capacity that meets the interruption probability requirement is as follows: in, This represents the user capacity that meets the interruption probability requirements. Indicates the probability of interruption. Indicates the bandwidth of the target user. This indicates the minimum acceptable signal-to-interference-plus-noise ratio (SIR).

7. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The expression for the user interruption probability is as follows: in, Indicates the probability of user interruption. This represents a parameter whose value is... , n This represents the path loss parameter. J , E , F and G Both represent variables. This represents the maximum allowable path loss. Represents the error function. R This represents the maximum value in the edge area of ​​the cell. This represents the constant intercept in the path loss formula. The standard deviation of shadow fading.

8. The method for planning a wireless network within a high-speed train set according to claim 1, characterized in that, The expression for the maximum coverage distance is as follows: in, Indicates the maximum coverage distance. This represents the maximum transmission distance of NLoS in a single non-line-of-sight propagation scenario under the same total transmission loss. This indicates the actual transmission distance during the hybrid propagation phase. This represents the actual transmission distance during the line-of-sight (LoS) propagation phase. and They represent and Equivalent propagation distance of radio waves compared to standalone non-line-of-sight (NLoS) propagation under the same path loss. and The difference between them.

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