Method and device for determining radio wave environment characteristic data set and storage medium

Abstract

The invention provides a method and device for determining a radio wave environment characteristic data set and a storage medium, and relates to the field of ray simulation. The method comprises the steps that a first three-dimensional model file and a second three-dimensional model file are obtained, the first three-dimensional model file is used for storing a three-dimensional model of a building, and the second three-dimensional model file is used for storing a three-dimensional model of an object to be placed in the building; determining at least one target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file and an object placement constraint condition; based on the first three-dimensional model file, the second three-dimensional model file and the at least one target object placement parameter, generating at least one radio wave simulation parameter set corresponding to the target object placement parameter; and performing ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environment characteristic data set. According to the invention, automatic ray tracing simulation can be realized without depending on manpower.

Description

Technical Field

[0001] This application relates to the field of ray simulation, and in particular to a method, apparatus and storage medium for determining a dataset of radio wave environmental characteristics. Background Technology

[0002] Accurately predicting the propagation characteristics of radio waves in complex industrial environments is an important prerequisite for achieving high-quality network planning and ensuring the continuity and reliability of production operations.

[0003] Currently, deterministic simulation methods based on ray tracing are commonly used. This method builds an accurate 3D scene model and then simulates the propagation path of radio waves (e.g., direct, reflected, diffracted, and transmitted), thereby calculating indicators such as signal strength at various points in space.

[0004] However, this method relies on manual labor to construct the 3D scene model, which leads to low work efficiency and high costs. Summary of the Invention

[0005] This application provides a method, apparatus, and storage medium for determining radio wave environmental feature datasets, which can improve work efficiency without relying on manual labor.

[0006] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a method for determining a radio wave environmental feature dataset. The method includes: acquiring a first three-dimensional model file and a second three-dimensional model file, wherein the first three-dimensional model file stores a three-dimensional model of a building, and the second three-dimensional model file stores a three-dimensional model of an object to be placed within the building; determining at least one target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and object placement constraints, wherein the target object placement parameter indicates the position and orientation of the object to be placed within the building, and includes the object placement position and object placement angle; generating at least one radio wave simulation parameter set corresponding to the target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and at least one target object placement parameter, wherein data in the radio wave simulation parameter set is used for ray tracing simulation; and performing ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset, wherein the radio wave environmental feature dataset is used to characterize the signal quality and multipath components of radio waves within the building after the object is placed.

[0007] In conjunction with the first aspect mentioned above, in one possible implementation, based on the first 3D model file, the second 3D model file, and object placement constraints, at least one target object placement parameter is determined, including: dividing the area into regions according to the functions of buildings in the first 3D model file, determining the target region and its functions; determining the object placement constraints corresponding to the target region based on its functions; simulating the target region using the Monte Carlo method based on the first and second 3D model files to obtain at least one object placement parameter; and determining the object placement parameter as the target object placement parameter if it satisfies the object placement constraints.

[0008] In conjunction with the first aspect above, in one possible implementation, the object placement constraints include at least one of the following: object placement density constraints, which constrain the density of objects placed within a building; object placement spacing constraints, which constrain the distance between objects and other objects or buildings when they are placed; object placement angle constraints, which constrain the rotation angle of objects when they are placed; and object placement collision constraints, which constrain objects from colliding with other objects or buildings when they are placed.

[0009] In conjunction with the first aspect above, in one possible implementation, the data in the radio wave simulation parameter set includes the position and electromagnetic parameters of each facet of the building, as well as the position and electromagnetic parameters of each facet of each object within the building.

[0010] In conjunction with the first aspect mentioned above, in one possible implementation, based on a first 3D model file, a second 3D model file, and at least one target object placement parameter, at least one radio wave simulation parameter set corresponding to the target object placement parameter is generated. This includes: generating a third 3D model file based on the first 3D model file, the second 3D model file, and each target object placement parameter; the third 3D model file is used to store the 3D model after the objects are placed in the building according to the target object placement parameter; reading data from the third 3D model file to obtain the position and material information of each facet of the building, and the position and material information of each facet of each object in the building; determining the electromagnetic parameters of each facet of the building and the electromagnetic parameters of each facet of each object in the building according to the mapping relationship between the material information and the electromagnetic parameters; and writing the position and electromagnetic parameters of each facet of the building and the position and electromagnetic parameters of each facet of each object in the building into the radio wave simulation parameter set.

[0011] In conjunction with the first aspect mentioned above, in one possible implementation, reading data from a third 3D model file to obtain the position and material information of each facet of the building, as well as the position and material information of each facet of each object within the building, includes: reading the data from the third 3D model file line by line, and determining the data of a preset number of lines in the third 3D model file as the position and material information of each facet of the building, as well as the position and material information of each facet of each object within the building; or, if it is detected that the data in the third 3D model file contains a first preset word and a second preset word, determining the data after the first preset word and before the second preset word as the position and material information of each facet of the building, as well as the position and material information of each facet of each object within the building.

[0012] Secondly, this application provides a device for determining a radio wave environmental feature dataset. The device includes: an acquisition unit for acquiring a first three-dimensional model file and a second three-dimensional model file, wherein the first three-dimensional model file stores a three-dimensional model of a building, and the second three-dimensional model file stores a three-dimensional model of an object to be placed inside the building; a determination unit for determining at least one target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and object placement constraints, wherein the target object placement parameter indicates the position and orientation of the object to be placed inside the building, and the target object placement parameter includes the object placement position and the object placement angle; a generation unit for generating at least one radio wave simulation parameter set corresponding to the target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and at least one target object placement parameter, wherein the data in the radio wave simulation parameter set is used for ray tracing simulation; and a simulation unit for performing ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset, wherein the radio wave environmental feature dataset is used to characterize the signal quality and multipath components of radio waves inside the building after the object is placed.

[0013] In conjunction with the second aspect above, in one possible implementation, the determining unit is used to: divide the area according to the function of the building in the first three-dimensional model file, determine the target area and the function of the target area; determine the object placement constraints corresponding to the target area based on the function of the target area; simulate the target area using the Monte Carlo method based on the first three-dimensional model file and the second three-dimensional model file to obtain at least one object placement parameter; and determine the object placement parameter as the target object placement parameter if the object placement parameter satisfies the object placement constraints.

[0014] In conjunction with the second aspect above, in one possible implementation, the object placement constraints include at least one of the following: object placement density constraints, which constrain the density of objects placed within a building; object placement spacing constraints, which constrain the distance between objects and other objects or buildings during placement; object placement angle constraints, which constrain the rotation angle of objects during placement; and object placement collision constraints, which constrain objects from colliding with other objects or buildings during placement.

[0015] In conjunction with the second aspect above, in one possible implementation, the data in the radio wave simulation parameter set includes the position and electromagnetic parameters of each facet of the building, as well as the position and electromagnetic parameters of each facet of each object within the building.

[0016] In conjunction with the second aspect above, in one possible implementation, the generation unit is used to: generate a third 3D model file based on the first 3D model file, the second 3D model file, and the placement parameters of each target object; the third 3D model file is used to store the 3D model after the objects are placed in the building according to the target object placement parameters; read the data in the third 3D model file to obtain the position and material information of each facet of the building, and the position and material information of each facet of each object in the building; determine the electromagnetic parameters of each facet of the building and the electromagnetic parameters of each facet of each object in the building according to the mapping relationship between the material information and the electromagnetic parameters; and write the position and electromagnetic parameters of each facet of the building, and the position and electromagnetic parameters of each facet of each object in the building, into the radio wave simulation parameter set.

[0017] In conjunction with the second aspect above, in one possible implementation, the generation unit is used to: read the data of the third 3D model file line by line, and determine the data of a preset number of lines in the third 3D model file as the position and material information of each facet of the building, and the position and material information of each facet of each object within the building; or, if it is detected that the data of the third 3D model file contains a first preset word and a second preset word, determine the data after the first preset word and before the second preset word as the position and material information of each facet of the building, and the position and material information of each facet of each object within the building.

[0018] Thirdly, this application provides an electronic device, including: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run computer programs or instructions to implement the method for determining a radio wave environment feature dataset as described in the first aspect and any possible implementation of the first aspect.

[0019] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a method for determining a radio wave environmental feature dataset as described in the first aspect and any possible implementation thereof.

[0020] Fifthly, this application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform a method for determining a radio wave environment feature dataset as described in the first aspect and any possible implementation thereof.

[0021] In a sixth aspect, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run computer programs or instructions to implement the method for determining a radio wave environment feature dataset as described in the first aspect and any possible implementation thereof.

[0022] Specifically, the chip provided in this application also includes a memory for storing computer programs or instructions.

[0023] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on a computer-readable storage medium. This computer-readable storage medium may be packaged together with the processor of the device, or it may be packaged separately from the processor of the device; this application does not impose any limitation on this.

[0024] In a seventh aspect, this application provides a system for determining a radio wave environment feature dataset, comprising: an electronic device and a terminal, wherein the electronic device is used to perform the method for determining a radio wave environment feature dataset as described in the first aspect and any possible implementation thereof.

[0025] The descriptions of aspects two through seven in this application can be referenced to the detailed description of aspect one; and the beneficial effects of the descriptions of aspects two through seven can be referenced to the analysis of the beneficial effects of aspect one, which will not be repeated here.

[0026] In this application, the name of the device for determining the aforementioned radio wave environmental feature dataset does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear under other names. As long as the function of each device or functional module is similar to that of this application, it falls within the scope of the claims of this application and its equivalents.

[0027] These or other aspects of this application will become more readily apparent in the following description.

[0028] The method for determining the radio wave environment feature dataset provided in this application generates target object placement parameters that meet the expected requirements through a first 3D model file, a second 3D model file, and object placement constraints. Then, a radio wave simulation parameter set is obtained based on the target object placement parameters, and finally, ray tracing simulation is performed to obtain the radio wave environment feature dataset. This method enables automated and batch construction from 3D models to radio wave simulation parameter sets, solving the core pain point hindering the large-scale application of ray tracing technology—the cost and efficiency issues of high-precision 3D environment modeling. It represents a breakthrough from manual design of single scenes to automatic generation of large-scale scenes, solving the pain points of low efficiency and difficulty in covering diverse scenes, and greatly improving the efficiency and reliability of obtaining large-scale radio wave environment feature datasets. Furthermore, it solves the problem of fragmented ray tracing simulation processes, achieving full automation from original model identification, automatic layout, simulation file generation to batch simulation scheduling, and establishing an automated pipeline from "geometric scene" to "radio wave environment" data twins. It addresses the core pain points of high cost and long cycle time in obtaining large-scale radio wave environment feature datasets, providing efficient, reliable, and massive data support for industrial network planning and optimization, and improving decision-making quality and efficiency. Attached Figure Description

[0029] Figure 1 A schematic diagram of the architecture of a system for determining a radio wave environment feature dataset provided in an embodiment of this application; Figure 2 A flowchart illustrating a method for determining a radio wave environmental feature dataset provided in an embodiment of this application; Figure 3 A flowchart for determining the placement parameters of a target object is provided in an embodiment of this application; Figure 4 This application provides a schematic diagram of object placement as an embodiment. Figure 5 A schematic diagram of the structure of a device for determining a radio wave environmental feature dataset provided in an embodiment of this application; Figure 6 This is a schematic diagram of the hardware structure of a device for determining a radio wave environmental feature dataset, provided in an embodiment of this application. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0032] The terms "first" and "second," etc., used in the specification and drawings of this application are used to distinguish different objects or to distinguish different treatments of the same object, rather than to describe a specific order of objects.

[0033] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0034] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0035] In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0036] Driven by the Industry 4.0 and smart manufacturing trends, factory wireless communication networks (such as 5G private networks and Wi-Fi 6) have become core infrastructure supporting key operations such as flexible manufacturing, equipment interconnection, material tracking, and augmented reality (AR) remote operation and maintenance. Accurately predicting the propagation characteristics of radio waves in complex industrial environments is a crucial prerequisite for achieving high-quality network planning and ensuring the continuity and reliability of production operations.

[0037] Industrial environments differ from traditional office or home environments. Industrial settings have complex internal structures, containing numerous metal equipment, shelves, pipes, and other objects. These objects make the radio wave propagation environment exceptionally complex, resulting in severe signal attenuation and significant multipath effects. Therefore, constructing a radio wave environment model that accurately reflects the layout of a specific factory (i.e., a "digital twin") has significant engineering value for optimizing base station deployment, evaluating network performance, and even predicting potential communication blind spots.

[0038] Currently, deterministic simulation methods based on ray tracing are commonly used for predicting radio wave environments in industrial settings. This method establishes an accurate 3D scene model and then simulates the propagation path of radio waves (e.g., direct, reflected, diffracted, and transmitted waves) to calculate indicators such as signal strength at various points in space. Its prediction accuracy is far higher than that of traditional statistical models.

[0039] Ray tracing is a high-frequency electromagnetic wave propagation prediction method based on geometric optics. Its principle is to treat the transmitting antenna as a point source, emitting a large number of discrete rays into space. By tracing the propagation path of each ray (including direct, reflected, diffracted, and transmitted rays), its interaction with the receiving point is calculated, thereby synthesizing channel characteristics such as field strength and path loss.

[0040] Specifically, the implementation process of the deterministic simulation method based on ray tracing includes the following steps: Step 1: 3D Scene Modeling. Using 3D modeling software (e.g., 3ds Max, Blender) or computer-aided design (CAD) tools, detailed geometric models of objects including factory structures, production equipment, and shelves are manually constructed. Correct electromagnetic parameters, such as dielectric constant and conductivity, are then assigned to the surfaces of objects made of different materials.

[0041] Step 2: Simulation Configuration. Import the constructed 3D model into professional ray tracing simulation software (e.g., Wireless InSite, WinProp, etc.), and then manually set the parameters of the transmitter (Tx), receiver (Rx), simulation frequency, algorithm accuracy, etc.

[0042] Step 3: Perform simulation. Run the simulation to obtain the radio wave propagation results for this single scenario, such as the received power distribution map (Rx power map).

[0043] Step 4: Result Analysis. The simulation results will be further processed and analyzed.

[0044] Furthermore, to obtain environmental data under different layouts, existing solutions typically require manually and sequentially repeating the above steps. That is, manually adjusting the equipment layout → updating the 3D model → reconfiguring and running the simulation. This method is currently the mainstream solution for high-precision channel simulation in the industry.

[0045] However, while deterministic simulation methods based on ray tracing can achieve high-precision simulations, they also have some significant drawbacks that severely limit their application in large-scale scene analysis: First, scene construction relies on manual labor, which is extremely inefficient. The construction and adjustment of 3D scene models all require manual work by experts. Especially when hundreds or thousands of different equipment layout schemes need to be generated, the modeling work is not only arduous and time-consuming, but also costly, making it impossible to quickly respond to large-scale simulation needs.

[0046] Second, the layout schemes lack diversity and rationality. The number of manually designed layout schemes is limited, and they heavily rely on the designer's experience. This makes it difficult to systematically explore the entire layout possibility space. More importantly, manual layout may ignore constraints such as process rules and safety distances in actual industrial production, resulting in geometrically correct scenarios that do not conform to production realities, thus rendering the simulation results worthless.

[0047] Third, the simulation process has a low degree of automation and cannot be processed in batches. From scene modeling to simulation configuration, execution, and result extraction, the entire process involves numerous manual interventions. Furthermore, most of these steps are isolated "data silos," failing to form an automated pipeline, which makes large-scale batch simulations difficult to implement smoothly.

[0048] Fourth, the overall cycle is long and the cost is high. Due to the above reasons, acquiring large-scale and diverse industrial electromagnetic environment data requires an extremely long time cycle and huge human resources costs, which hinders the advancement of data-driven network optimization and decision-making.

[0049] In view of this, the method for determining the radio wave environment feature dataset provided in this application generates target object placement parameters that meet the expected requirements through a first 3D model file, a second 3D model file, and object placement constraints. Then, a radio wave simulation parameter set is obtained based on the target object placement parameters, and finally, ray tracing simulation is performed to obtain the radio wave environment feature dataset. This method enables automated and batch construction from 3D models to radio wave simulation parameter sets, solving the core pain point hindering the large-scale application of ray tracing technology—the cost and efficiency issues of high-precision 3D environment modeling. It achieves a breakthrough from manual design of single scenes to automatic generation of large-scale scenes, solving the pain points of low efficiency and difficulty in covering diverse scenes, and greatly improving the efficiency and reliability of obtaining large-scale radio wave environment feature datasets. Furthermore, it solves the problem of fragmented ray tracing simulation processes, achieving full automation from original model identification, automatic layout, simulation file generation to batch simulation scheduling, and opening up an automated pipeline from "geometric scene" to "radio wave environment" data twins. It addresses the core pain points of high cost and long cycle in obtaining large-scale radio wave environment feature datasets, providing efficient, reliable, and massive data support for industrial network planning and optimization, and improving decision-making quality and efficiency.

[0050] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0051] Figure 1 This is a schematic diagram of the architecture of a system for determining a radio wave environmental feature dataset, provided as an embodiment of this application. Figure 1 As shown, the architecture includes: terminal 101 and electronic device 102.

[0052] Terminal 101 can be at least one of the following devices: smartphone, smartwatch, desktop computer, laptop, virtual reality terminal, augmented reality terminal, wireless terminal, laptop computer, Internet of Things device, edge device, etc. This application embodiment does not limit it.

[0053] In some embodiments, terminal 101 has communication capabilities. For example, terminal 101 can send a first three-dimensional model file and a second three-dimensional model file to electronic device 102. The first three-dimensional model file is used to store a three-dimensional model of a building, and the second three-dimensional model file is used to store a three-dimensional model of an object to be placed inside the building.

[0054] It should be noted that the number of terminals 101 can be one or more. This application embodiment does not limit this.

[0055] Electronic device 102 can be a mobile phone, tablet, computer with wireless transceiver capabilities, virtual reality (VR) terminal, augmented reality (AR) terminal, wireless terminal, computer, independent physical server, server cluster consisting of multiple physical servers, or at least one of the following cloud servers providing basic cloud computing services: cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data or artificial intelligence platforms. This application embodiment does not limit this specific application. Of course, electronic device 102 can also include other functions to provide more comprehensive and diversified services.

[0056] In some embodiments, the electronic device 102 has communication capabilities. For example, communication between the electronic device 102 and the terminal 101.

[0057] In other embodiments, the electronic device 102 has processing capabilities. For example, the electronic device 102 determines at least one target object placement parameter based on a first 3D model file, a second 3D model file, and object placement constraints. As another example, the electronic device 102 generates at least one radio wave simulation parameter set corresponding to the target object placement parameters based on the first 3D model file, the second 3D model file, and at least one target object placement parameter. Yet another example is that the electronic device 102 performs ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset.

[0058] The electronic device 102 can be one or more, and this embodiment of the application does not limit this. For ease of understanding, Figure 1 Only one is shown in the image.

[0059] Terminal 101 and electronic device 102 are connected via a communication link. This communication link can be a wired communication link or a wireless communication link, and this embodiment does not limit it.

[0060] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0061] Figure 2 A flowchart illustrating a method for determining a radio wave environmental feature dataset provided in an embodiment of this application. Figure 2 As shown, this method can be implemented through S201 to S204.

[0062] S201. Obtain the first 3D model file and the second 3D model file.

[0063] The first 3D model file stores the 3D model of the building, and the second 3D model file stores the 3D model of the objects to be placed inside the building.

[0064] For example, the first three-dimensional model file and the second three-dimensional model file can be files in .obj format, or files in .stl format, or files in other formats. This application embodiment does not limit this.

[0065] For example, .obj format files are polygon model files with material properties, a common 3D model file format widely used for storing and exchanging 3D geometric data. .obj files are text files, with each line representing a geometric element or instruction, typically beginning with a keyword followed by data. For instance, when representing vertex coordinates, the keyword is 'v', usually represented as 'vxyz'; when representing facet connections, the keyword is 'f', usually represented as 'f v1 / v2 / v3'.

[0066] Table 1 lists common keywords for .obj format files. Table 1

[0067] For example, the following is a representation of some vertex coordinates and normal vectors in a .obj format file.

[0068] v 122.8874 -3.6145 6.5334 v 122.8118 -3.4305 6.5530 v 122.7084 -3.2606 6.5725 v 122.5796 -3.1091 6.5920 v 122.4287 -2.9795 6.6115 v 122.8825 -2.7518 6.6701 v 122.0758 -2.7986 6.6506 v 122.2594 -2.8752 6.6310 #251596 vertices / / There are 251596 vertices in total. vn -0.0000 0.0000 -1.0000 vn 0.0000 0.0000 -1.0000 vn 0.0003 0.0001 -1.0000 vn 0.0029 0.0005 -1.0000 vn 0.0033 0.0005 -1.0000 For example, .stl format files are pure geometric triangle patch files, which are typically used for categorized modeling when building 3D models. For instance, when building a 3D model, it can be categorized according to different materials. In the .stl format file, "solid" <name>"Indicates the name of the model; "facet normal ni nj nk" defines the normal vector of the triangle facet, i.e., the vector perpendicular to the facet; "vertex vx vy vz" defines the coordinates of each vertex, which is determined by three points; "endfacet" ends the definition of the current triangle facet; "endsolid" indicates the model name; "facet normal ni nj nk" defines the normal vector of the triangle facet, i.e., the vector perpendicular to the facet; "vertex vx vy vz" defines the coordinates of each vertex, which is determined by three points; "endfacet" ends the definition of the current triangle facet; "endsolid" ends the definition of the triangle facet. <name>"This concludes the definition of the entire model."

[0069] For example, the following is a definition representation of the Exported model in .stl format.

[0070] solid Exported / / Model name Exported facet normal 0.0 0.0 -1.0 / / Define the normal vector of the triangular facet outer loop / / Defines the boundary of the triangular facet vertex 0.2554 0.042 -0.0 / / Define the vertex coordinates of the triangular facet vertex 3.2257 -2.9283 -0.0 / / Define the vertex coordinates of the triangular facet vertex 3.0768 -3.0768 -0.0 / / Define the vertex coordinates of the triangle facet endloop / / Ends the definition of the vertices of the current triangle face. endfacet / / Ends the definition of the current triangle facet facet normal 0.0 0.0 -1.0 / / Define the normal vector of the triangular facet outer loop / / Defines the boundary of the triangular facet vertex 0.2554 0.042 -0.0 / / Define the vertex coordinates of the triangular facet vertex 3.0768 -3.0768 -0.0 / / Define the vertex coordinates of the triangle facet vertex 0.9731 -0.9731 -0.0 / / Define the vertex coordinates of the triangle facet endloop / / Ends the definition of the vertices of the current triangle face. endfacet / / Ends the definition of the current triangle facet facet normal 0.0 0.0 -1.0 / / Define the normal vector of the triangular facet outer loop / / Defines the boundary of the triangular facet vertex 0.2554 0.042 -0.0 / / Define the vertex coordinates of the triangular facet S202. Based on the first three-dimensional model file, the second three-dimensional model file, and the object placement constraints, determine at least one target object placement parameter.

[0071] Among them, the target object placement parameters are used to indicate the position and orientation of the object to be placed inside the building. The target object placement parameters include the object placement position and the object placement angle.

[0072] In some embodiments, object placement constraints include at least one of the following: (1) Object placement density constraint: The object placement density constraint is used to constrain the density of objects placed inside a building.

[0073] For example, the object placement density constraint can be an object placement density threshold. For instance, the object placement density constraint can be ρ≤0.5 / ㎡.

[0074] (2) Object placement spacing constraints: Object placement spacing constraints are used to constrain the distance between objects and other objects or buildings when they are placed.

[0075] For example, the object placement spacing constraint can be an object placement spacing threshold. For instance, the object placement spacing constraint can be d ≥ 0.8m.

[0076] (3) Object placement angle constraint conditions: Object placement angle constraint conditions are used to constrain the rotation angle of the object when it is placed.

[0077] (4) Object placement collision constraint conditions: Object placement collision constraint conditions are used to constrain objects from colliding with other objects or buildings when they are placed.

[0078] For example, collision constraints for object placement can be achieved using the collision detection (Gilbert-Johnson-Keerthi, GJK) algorithm.

[0079] Thus, object placement density constraints can control the density of objects per unit area or volume, preventing them from being too sparse or too dense, making the placement more realistic. Object placement spacing constraints ensure that objects do not stack, improving visual clarity. Object placement angle constraints ensure that object placement conforms to their functional attributes. Object placement collision constraints prevent collisions, further aligning with reality. By setting object placement constraints, we can ensure that the generated target object placement parameters meet the spatial layout specifications and safety requirements of actual industrial production, avoiding unreasonable or infeasible layout schemes, increasing the rationality and feasibility of object placement, ensuring the effectiveness and reference value of object placement simulation results, and improving the automation and efficiency of object placement.

[0080] S203. Based on the first three-dimensional model file, the second three-dimensional model file, and at least one target object placement parameter, generate at least one set of radio wave simulation parameters corresponding to the target object placement parameters.

[0081] The data in the radio wave simulation parameter set is used for ray tracing simulation.

[0082] In some embodiments, the data in the radio wave simulation parameter set includes the position and electromagnetic parameters of each panel of a building, as well as the position and electromagnetic parameters of each panel of each object within the building.

[0083] For example, the electromagnetic parameters include dielectric constant ε, conductivity σ, surface roughness, etc.

[0084] Thus, with the radio wave simulation parameters including the position and electromagnetic parameters of the patch, the ray tracing simulation software can achieve automated reading, reduce manual operation, improve efficiency, and reduce errors caused by manual operation.

[0085] Understandably, the propagation of radio waves is closely related to the environment. During propagation, radio waves not only travel in straight lines but also interact with surrounding objects, undergoing transmission, reflection, and refraction. Therefore, the characteristics of radio waves will change under different environmental layouts. In other words, different target object placement parameters will result in different sets of simulated radio wave parameters.

[0086] S204. Based on the radio wave simulation parameter set, perform ray tracing simulation to obtain a radio wave environment feature dataset.

[0087] Among them, the radio wave environmental feature dataset is used to characterize the signal quality and multipath components of radio waves inside a building after an object has been placed there.

[0088] For example, the signal quality of radio waves within a building after an object has been placed can be displayed as a received power distribution map showing the signal quality at various points within the building.

[0089] For example, the multipath component includes the path length, time delay, impulse response, angle of arrival (AoA), and departure angle of each modulated radio wave to the receiving point.

[0090] For example, when generating multiple sets of radio wave simulation parameters, radio wave environmental feature datasets can be generated serially or in parallel using ray tracing simulation software. In this case, computing resources (e.g., central processing unit (CPU) or graphics processing unit (GPU) clusters) can be fully utilized, providing technical support for generating radio wave environmental feature datasets.

[0091] The method for determining the radio wave environment feature dataset provided in this application generates target object placement parameters that meet the expected requirements through a first 3D model file, a second 3D model file, and object placement constraints. Then, a radio wave simulation parameter set is obtained based on the target object placement parameters, and finally, ray tracing simulation is performed to obtain the radio wave environment feature dataset. This method enables automated and batch construction from 3D models to radio wave simulation parameter sets, solving the core pain point hindering the large-scale application of ray tracing technology—the cost and efficiency issues of high-precision 3D environment modeling. It achieves a breakthrough from manual design of single scenes to automatic generation of large-scale scenes, solving the pain points of low efficiency and difficulty in covering diverse scenes, and greatly improving the efficiency and reliability of obtaining large-scale radio wave environment feature datasets. Furthermore, it solves the problem of fragmented ray tracing simulation processes, achieving full automation from original model identification, automatic layout, simulation file generation to batch simulation scheduling, and opening up an automated pipeline from "geometric scene" to "radio wave environment" data twins. It solves the core pain points of high cost and long cycle in obtaining large-scale radio wave environment feature datasets, providing efficient, reliable, and massive data support for industrial network planning and optimization, and improving decision-making quality and efficiency. By using radio wave environment feature datasets, we can efficiently and reliably twinnize the statistical and deterministic characteristics of wireless channels in real industrial environments, providing a solid data foundation for network planning, performance evaluation, and intelligent decision-making, thereby greatly improving simulation efficiency and coverage.

[0092] The above methods are particularly suitable for industrial scenarios in the B2B sector.

[0093] The following is a summary of the above. Figure 2 The process of determining at least one target object placement parameter in step S202 will be explained. Figure 3 A flowchart for determining the placement parameters of a target object is provided in an embodiment of this application, such as... Figure 3 As shown, the process of determining the placement parameters of the target object in step S202 can be implemented through the following steps S301 to S304.

[0094] S301. Divide the area according to the function of the building in the first three-dimensional model file, and determine the target area and the function of the target area.

[0095] For example, the building is divided into regions based on the semantic information in the first three-dimensional model file to obtain the target region and the function of the target region.

[0096] S302. Determine the object placement constraints corresponding to the target area based on the function of the target area.

[0097] For example, different area functions correspond to different object placement constraints.

[0098] S303. Based on the first and second 3D model files, the target area is simulated using the Monte Carlo method to obtain at least one object placement parameter.

[0099] For example, random sampling and optimization are performed using the Monte Carlo method to determine the object placement parameters, namely the object's position and angle. The following formula 1 is satisfied during the process of obtaining the object placement parameters using the Monte Carlo method.

[0100] Formula 1 In the formula, x represents the x-coordinate of the object's position; A function for generating uniformly distributed random numbers; This represents the minimum range of values ​​for x; This indicates the maximum range of values ​​for x; The vertical coordinate representing the position of the object; This represents the minimum range of values ​​for y; This indicates the maximum range of values ​​for y; Indicates the angle at which an object is placed; This indicates the minimum range of possible angles for an object's placement. This indicates the maximum range of possible angles for the object's placement.

[0101] S304. If the object placement parameters meet the object placement constraints, the object placement parameters shall be determined as the target object placement parameters.

[0102] For example, if the object placement parameters satisfy the object placement constraints, it means that the object placement constraints meet the requirements of the object placement rules. If the object placement parameters do not satisfy the object placement constraints, it means that the object placement constraints do not meet the requirements of the object placement rules. In this case, the object placement constraints are discarded and recalculated. This process is repeated multiple times until the target object placement parameters that satisfy the object placement constraints are found.

[0103] As a specific example, Figure 4 This is a schematic diagram of object placement provided in an embodiment of this application. Figure 4 As shown, the coordinates of the four vertices of the target region are (x1, y1), (x2, y2), (x3, y3), and (x4, y4). The distance between object A and object B is d1, and the distance between object B and object C is d2. The rotation angle of object A is θ.

[0104] Thus, by dividing the functions of buildings in the first 3D model file into regions, a logical foundation consistent with real-world laws is laid for the placement of objects in the target area. Through the Monte Carlo method and the setting of object placement constraints, massive layout spaces can be efficiently explored while ensuring layout rationality. Target object placement parameters can be intelligently determined, and target object placement parameters that conform to industrial standard scenarios can be automatically and on a large scale. This achieves a qualitative leap from "manual design of a single scene" to "automatic generation of large-scale compliant scenes," significantly improving efficiency. Through the iterative cycle of "Monte Carlo random generation - object placement constraints," hundreds or thousands of diverse and high-value target object placement parameters are automatically and in batches generated while ensuring layout rationality and safety. This lays the foundation for the subsequent realization of large-scale radio wave environmental feature datasets.

[0105] The following is a summary of the above. Figure 2 The process of generating at least one radio wave simulation parameter set in step S203 will be described. As a possible embodiment of this application, the process of generating at least one radio wave simulation parameter set in step S203 can be implemented by steps 11 to 14.

[0106] Step 11: Generate a third 3D model file based on the first 3D model file, the second 3D model file, and the placement parameters of each target object.

[0107] The third 3D model file is used to store the 3D model after the objects are placed inside the building according to the target object placement parameters.

[0108] For example, the placement parameters of the target object and the second 3D model file are written into the first 3D model file to obtain the third 3D model file. This third 3D model file is a standardized, machine-readable 3D model file, which provides accurate geometric input for subsequent ray tracing simulations and ensures that the simulation environment is consistent with the design layout.

[0109] For example, the third 3D model file can be a .obj file, a .stl file, or a file of other formats, and this application embodiment does not limit this.

[0110] Step 12: Read the data from the third 3D model file to obtain the position and material information of each facet of the building, as well as the position and material information of each facet of each object within the building.

[0111] In some embodiments, the position and material information of the patch are obtained in step 12 above in the following two ways.

[0112] Method 1: Read the data of the third-dimensional model file line by line, and determine the position and material information of each facet of the building, as well as the position and material information of each facet of each object in the building, based on the preset number of lines of data in the third-dimensional model file.

[0113] For example, in the third 3D model file, the position and material information of the facets are located at a fixed number of lines. When reading the third 3D model file line by line, the data at the preset number of lines is read to obtain the position and material information of the facets.

[0114] Method 2: If the data of the third 3D model file contains a first preset word and a second preset word, the data after the first preset word and before the second preset word is determined as the position and material information of each facet of the building, and the position and material information of each facet of each object in the building.

[0115] For example, the first preset word can be "position" and the second preset word can be "radius". The first preset word and the second preset word can also be other words, and this application embodiment does not limit them.

[0116] In this way, by reading the position and material information of the facets in the third-dimensional model file through different methods, a data foundation is provided for the automated generation of radio wave simulation parameter sets, reducing human intervention and improving accuracy and efficiency.

[0117] Step 13: Based on the mapping relationship between material information and electromagnetic parameters, determine the electromagnetic parameters of each facet of the building and the electromagnetic parameters of each facet of each object within the building.

[0118] For example, when the third-dimensional model file is in .obj format, material information is included in the patch connectivity. This material information can be directly associated with the electromagnetic parameters required for ray tracing.

[0119] For example, when the third-dimensional model file is in .stl format, modeling can be categorized according to material information. That is, the models in each file are of the same type of material, i.e., they have the same electromagnetic parameters.

[0120] Step 14: Write the position and electromagnetic parameters of each facet of the building, as well as the position and electromagnetic parameters of each facet of each object within the building, into the radio wave simulation parameter set.

[0121] For example, the radio wave simulation parameter set can be stored as a .csv file.

[0122] As a specific example, Table 2 shows the location information of the points included in the radio wave simulation parameter set, and Table 3 shows the information of the patches in the radio wave simulation parameter set.

[0123] Table 2

[0124] Where x is the x-coordinate of a point; y is the y-coordinate of a point; and z is the z-coordinate of a point.

[0125] Table 3

[0126] Where triangleP1Index, triangleP3Index, and triangleP3Index represent the unique IDs of three points in the triangular facet, corresponding to the vertex positions of the triangle in Table 2. upObjectType represents the electromagnetic parameters of the upper surface of the triangular facet; downObjectType represents the electromagnetic parameters of the lower surface of the triangular facet; roughness represents the roughness of the outer surface of the triangular facet; and nx, ny, and nz represent the outward normal vectors of the triangular facet.

[0127] In this way, the automatic conversion from 3D model to ray tracing simulation input can be achieved, adapting to ray tracing batch simulation algorithms, reducing manual intervention, improving the preparation efficiency of large-scale simulation, and ensuring that simulation parameters are accurately matched with geometric models.

[0128] This application embodiment can divide the device for determining radio wave environmental feature datasets into functional modules or functional units based on the above method example. For example, each function can be divided into its own functional modules or functional units, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module or functional unit. The module or unit division in this application embodiment is illustrative and represents only one logical functional division; other division methods may be used in actual implementation.

[0129] Figure 5 This is a schematic diagram of a device 50 for determining a radio wave environmental feature dataset provided in an embodiment of this application. The device 50 includes: an acquisition unit 501, used to acquire a first three-dimensional model file and a second three-dimensional model file, the first three-dimensional model file being used to store a three-dimensional model of a building, and the second three-dimensional model file being used to store a three-dimensional model of an object to be placed inside the building; a determination unit 502, used to determine at least one target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and object placement constraints, the target object placement parameter indicating the position and orientation of the object to be placed inside the building, the target object placement parameter including the object placement position and the object placement angle; a generation unit 503, used to generate at least one radio wave simulation parameter set corresponding to the target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and at least one target object placement parameter, the data in the radio wave simulation parameter set being used for ray tracing simulation; and a simulation unit 504, used to perform ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset, the radio wave environmental feature dataset being used to characterize the signal quality and multipath components of radio waves inside the building after the object is placed.

[0130] In one possible implementation, the determining unit 502 is used to: divide the area according to the function of the building in the first three-dimensional model file, determine the target area and the function of the target area; determine the object placement constraints corresponding to the target area according to the function of the target area; simulate the target area using the Monte Carlo method based on the first three-dimensional model file and the second three-dimensional model file to obtain at least one object placement parameter; and determine the object placement parameter as the target object placement parameter if the object placement parameter satisfies the object placement constraints.

[0131] In one possible implementation, the object placement constraints include at least one of the following: object placement density constraints, which constrain the density of objects placed within a building; object placement spacing constraints, which constrain the distance between objects and other objects or buildings when they are placed; object placement angle constraints, which constrain the rotation angle of objects when they are placed; and object placement collision constraints, which constrain objects from colliding with other objects or buildings when they are placed.

[0132] In one possible implementation, the data in the radio wave simulation parameter set includes the position and electromagnetic parameters of each facet of the building, as well as the position and electromagnetic parameters of each facet of each object within the building.

[0133] In one possible implementation, the generation unit 503 is used to: generate a third three-dimensional model file based on a first three-dimensional model file, a second three-dimensional model file, and placement parameters for each target object; the third three-dimensional model file is used to store the three-dimensional model after the objects are placed in the building according to the placement parameters; read the data in the third three-dimensional model file to obtain the position and material information of each facet of the building, and the position and material information of each facet of each object in the building; determine the electromagnetic parameters of each facet of the building and the electromagnetic parameters of each facet of each object in the building according to the mapping relationship between the material information and the electromagnetic parameters; and write the position and electromagnetic parameters of each facet of the building, and the position and electromagnetic parameters of each facet of each object in the building, into the radio wave simulation parameter set.

[0134] In one possible implementation, the generation unit 503 is used to: read the data of the third 3D model file line by line, and determine the data of a preset number of lines in the third 3D model file as the position and material information of each facet of the building, and the position and material information of each facet of each object in the building; or, if it is detected that the data of the third 3D model file contains a first preset word and a second preset word, determine the data after the first preset word and before the second preset word as the position and material information of each facet of the building, and the position and material information of each facet of each object in the building.

[0135] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0136] When implemented in hardware, the device for determining the radio wave environmental characteristic dataset can be integrated into, for example... Figure 6 The hardware structure of the device for determining the radio wave environmental characteristic dataset is implemented as shown. Specifically, such as... Figure 6 As shown, the basic hardware structure of the device for determining radio wave environmental feature datasets is introduced.

[0137] Figure 6 This is a schematic diagram of the hardware structure of a device for determining a radio wave environmental feature dataset, provided in an embodiment of this application. Figure 6 As shown, the device for determining the radio wave environmental feature dataset includes at least one processor 601, a communication line 602, and at least one communication interface 604, and may also include a memory 603. The processor 601, memory 603, and communication interface 604 are connected via the communication line 602.

[0138] The processor 601 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0139] Communication line 602 is used to transmit information between the aforementioned components.

[0140] The communication interface 604 is used to communicate with other devices or communication networks. It can use any transceiver-like device, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0141] The memory 603 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of including or storing desired program code having the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0142] In one possible design, the memory 603 can exist independently of the processor 601, meaning the memory 603 can be an external memory of the processor 601. In this case, the memory 603 can be connected to the processor 601 via a communication line 602 to store execution instructions or application code, and its execution is controlled by the processor 601 to implement the method for determining the radio wave environmental feature dataset provided in this application embodiment. In another possible design, the memory 603 can also be integrated with the processor 601, meaning the memory 603 can be an internal memory of the processor 601. For example, the memory 603 can be a cache, used to temporarily store some data and instruction information.

[0143] As one possible implementation, processor 601 may include one or more CPUs, for example Figure 6 CPU0 and CPU1 in the example. As another possible implementation, the device for determining the radio wave environment feature dataset may include multiple processors, such as... Figure 6 The processors 601 and 607 are included. As another possible implementation, the apparatus for determining the radio wave environment feature dataset may further include an output device 605 and an input device 606.

[0144] This application provides a computer program product containing instructions that, when run on a computer, cause the computer to execute the method for determining the radio wave environmental feature dataset described in the above method embodiments.

[0145] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for determining the radio wave environmental feature dataset in the method flow shown in the above method embodiments.

[0146] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires; a portable computer disk drive; a hard disk drive; random access memory (RAM); read-only memory (ROM); erasable programmable read-only memory (EPROM); a register; a hard disk drive; an optical fiber; a compact disc read-only memory (CD-ROM); an optical storage device; a magnetic storage device; or any suitable combination thereof; or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0147] Since the device for determining the radio wave environment feature dataset, the computer-readable storage medium, and the computer program product in the embodiments of this application can be applied to the above method, the technical effects that can be obtained can also be referred to the above method embodiments. The embodiments of this application will not be repeated here.

[0148] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0151] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.< / name> < / name>

Claims

1. A method for determining a dataset of radio wave environmental characteristics, characterized in that, The method includes: Obtain a first 3D model file and a second 3D model file. The first 3D model file is used to store the 3D model of the building, and the second 3D model file is used to store the 3D model of the object to be placed inside the building. Based on the first 3D model file, the second 3D model file, and the object placement constraints, at least one target object placement parameter is determined. The target object placement parameter is used to indicate the position and posture of the object to be placed within the building. The target object placement parameter includes the object placement position and the object placement angle. Based on the first 3D model file, the second 3D model file, and the at least one target object placement parameters, at least one radio wave simulation parameter set corresponding to the target object placement parameters is generated, and the data in the radio wave simulation parameter set is used for ray tracing simulation. Ray tracing simulation is performed based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset. The radio wave environmental feature dataset is used to characterize the signal quality and multipath components of radio waves in a building after an object is placed inside.

2. The method according to claim 1, characterized in that, The step of determining at least one target object placement parameter based on the first 3D model file, the second 3D model file, and object placement constraints includes: The regions are divided according to the functions of the buildings in the first 3D model file, and the target regions and their functions are determined. Determine the object placement constraints corresponding to the target area based on the function of the target area; Based on the first 3D model file and the second 3D model file, the target area is simulated using the Monte Carlo method to obtain at least one object placement parameter; If the object placement parameters satisfy the object placement constraints, the object placement parameters are determined as the target object placement parameters.

3. The method according to claim 1, characterized in that, The object placement constraints include at least one of the following: Object placement density constraint, which is used to constrain the density of objects placed inside the building; Object placement spacing constraints are used to constrain the distance between objects and other objects or the building when they are placed. Object placement angle constraint, which is used to constrain the rotation angle of the object when it is placed. The object placement collision constraint condition is used to constrain the object from colliding with other objects or the building when it is placed.

4. The method according to claim 1, characterized in that, The data in the radio wave simulation parameter set includes the position and electromagnetic parameters of each panel of the building, as well as the position and electromagnetic parameters of each panel of each object within the building.

5. The method according to claim 4, characterized in that, The step of generating at least one set of radio wave simulation parameters corresponding to the placement parameters of the target object based on the first 3D model file, the second 3D model file, and the placement parameters of the at least one target object includes: Based on the first three-dimensional model file, the second three-dimensional model file, and the placement parameters of each target object, a third three-dimensional model file is generated. The third three-dimensional model file is used to store the three-dimensional model after the objects are placed in the building according to the target object placement parameters. Read the data from the third 3D model file to obtain the position and material information of each facet of the building, as well as the position and material information of each facet of each object within the building; Based on the mapping relationship between material information and electromagnetic parameters, the electromagnetic parameters of each facet of the building and the electromagnetic parameters of each facet of each object within the building are determined. The position and electromagnetic parameters of each facet of the building, as well as the position and electromagnetic parameters of each facet of each object within the building, are written into the radio wave simulation parameter set.

6. The method according to claim 5, characterized in that, The process of reading data from the third 3D model file to obtain the position and material information of each facet of the building, and the position and material information of each facet of each object within the building, includes: The data in the third 3D model file is read line by line, and the data in the third 3D model file with a preset number of lines is determined as the position and material information of each facet of the building, and the position and material information of each facet of each object within the building; or, If the data in the third 3D model file contains a first preset word and a second preset word, the data after the first preset word and before the second preset word is determined as the position and material information of each facet of the building, and the position and material information of each facet of each object in the building.

7. A device for determining a dataset of radio wave environmental characteristics, characterized in that, The device includes: The acquisition unit is used to acquire a first three-dimensional model file and a second three-dimensional model file. The first three-dimensional model file is used to store the three-dimensional model of the building, and the second three-dimensional model file is used to store the three-dimensional model of the object to be placed inside the building. The determining unit is used to determine at least one target object placement parameter based on the first three-dimensional model file, the second three-dimensional model file, and object placement constraints. The target object placement parameter is used to indicate the position and posture of the object to be placed within the building. The target object placement parameter includes the object placement position and the object placement angle. The generation unit is used to generate at least one radio wave simulation parameter set corresponding to the target object placement parameters based on the first three-dimensional model file, the second three-dimensional model file and the at least one target object placement parameters. The data in the radio wave simulation parameter set is used for ray tracing simulation. The simulation unit is used to perform ray tracing simulation based on the radio wave simulation parameter set to obtain a radio wave environmental feature dataset. The radio wave environmental feature dataset is used to characterize the signal quality and multipath components of radio waves in a building after an object has been placed inside.

8. An electronic device, characterized in that, include: A processor and a communication interface; the communication interface is coupled to the processor, the processor being used to run computer programs or instructions to implement the method for determining a radio wave environmental feature dataset as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a computer, perform the method for determining a radio wave environmental feature dataset as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed on a computer, cause the computer to perform the method for determining a radio wave environmental feature dataset as described in any one of claims 1-6.

Images