Simulation coverage method and device of signal, storage medium and electronic equipment

Abstract

The application discloses a signal simulation coverage method and device, a storage medium and an electronic equipment. It relates to the field of signal processing. The method comprises the following steps: performing spatial blocking on a simulation area to obtain a sub-block set; performing first ray tracing calculation on the sub-block set according to antenna information of multiple transmitting antennas to obtain a first signal strength distribution matrix; subdividing at least one sub-block in the sub-block set according to the first signal strength distribution matrix to obtain a target sub-block set, wherein the target sub-block set comprises an unsubdivided sub-block and multiple subdivided sub-blocks obtained by subdividing the sub-blocks; performing second ray tracing calculation on the target sub-block set according to the antenna information of the multiple transmitting antennas to obtain a second signal strength distribution matrix; and determining a signal coverage simulation result of the simulation area based on the second signal strength distribution matrix. Through the application, the problem of low simulation efficiency in related art when simulating signal coverage is solved.

Description

Technical Field

[0001] This application relates to the field of signal processing, and more specifically, to a method, apparatus, storage medium, and electronic device for simulating signal coverage. Background Technology

[0002] With the development of technologies such as 5G / 6G network construction, indoor positioning systems, and IoT deployment, simulation experiments and methods for indoor signal propagation (which can also be understood as electromagnetic wave propagation) have become important tools for wireless network planning and optimization. Ray tracing, due to its ability to accurately simulate propagation effects such as direct, reflected, and transmitted light, has become a core technology for signal coverage prediction in indoor scenarios. However, as the complexity of simulation scenarios increases (e.g., multiple antennas, large spaces, and multi-wall structures), ray tracing methods in related technologies face problems such as low computational efficiency, high memory consumption, and difficulty in iterative optimization. For example, the use of a uniform calculation strategy across the entire simulation area in related technologies leads to a significant waste of computational resources in areas with weak or worthless signals. Therefore, related technologies suffer from low simulation efficiency when simulating signal coverage.

[0003] There is currently no effective solution to the aforementioned problems in the relevant technologies. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, storage medium, and electronic device for simulating signal coverage, in order to solve the problem of low simulation efficiency when performing signal coverage simulation in related technologies.

[0005] To achieve the above objectives, according to one aspect of this application, a signal coverage simulation method is provided. The method includes: spatially dividing a simulation region into sub-blocks to obtain a set of sub-blocks, wherein the simulation region includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks; performing a first ray tracing calculation on the set of sub-blocks based on antenna information of the multiple transmitting antennas to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block; further subdividing at least one sub-block in the set of sub-blocks based on the first signal intensity distribution matrix to obtain a target set of sub-blocks, wherein the target set of sub-blocks includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks; performing a second ray tracing calculation on the target set of sub-blocks based on antenna information of the multiple transmitting antennas to obtain a second signal intensity distribution matrix, wherein the second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and the subdivided sub-blocks, respectively, and the accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation; and determining the signal coverage simulation result of the simulation region based on the second signal intensity distribution matrix.

[0006] Optionally, the signal coverage simulation method further includes: determining the signal intensity gradient value of each sub-block based on the first signal intensity distribution matrix; determining the calculation accuracy level of each sub-block based on the antenna information of multiple transmitting antennas and the position information of each sub-block; and subdividing at least one sub-block in the sub-block set according to the calculation accuracy level and the signal intensity gradient value of each sub-block to obtain the target sub-block set.

[0007] Optionally, the signal coverage simulation method further includes: for each sub-block in the sub-block set, determining the first signal strength value of the sub-block and the first signal strength values ​​of the adjacent sub-blocks from the first signal strength distribution matrix; and using differential calculation, determining the signal strength gradient value of the sub-block based on the first signal strength value of the sub-block and the first signal strength values ​​of the adjacent sub-blocks.

[0008] Optionally, the signal coverage simulation method further includes: for each sub-block in the sub-block set, determining the distance from the sub-block to the nearest transmitting antenna based on the antenna information of multiple transmitting antennas and the sub-block's position information; determining the priority of the sub-block based on the distance to the nearest transmitting antenna, wherein the priority is negatively correlated with the distance; determining the calculation accuracy level of the sub-block as the lowest calculation accuracy level when the priority is lower than the priority threshold; determining the ideal maximum signal strength corresponding to the sub-block based on the antenna information of multiple transmitting antennas and the sub-block's position information when the priority is higher than or equal to the priority threshold; and determining the calculation accuracy level of the sub-block based on the ideal maximum signal strength.

[0009] Optionally, the signal coverage simulation method further includes: for each sub-block in the sub-block set, determining the subdivision level threshold of the sub-block according to the calculation accuracy level; if the current subdivision level of the sub-block is less than the subdivision level threshold and the signal strength gradient value of the sub-block is greater than the preset gradient value, subdividing the sub-block into multiple sub-blocks to obtain an updated sub-block set, and updating the current subdivision level of the sub-block; determining the signal strength gradient value of the sub-blocks in the updated sub-block set, and repeatedly subdividing at least one sub-block in the updated sub-block set according to the signal strength gradient value corresponding to the sub-block and the subdivision level threshold of the sub-block to which the sub-block belongs, until there are no subdivisible sub-blocks left, thus obtaining the target sub-block set.

[0010] Optionally, the signal coverage simulation method further includes: before performing a first ray tracing calculation on the sub-block set based on the antenna information of multiple transmitting antennas to obtain a first signal intensity distribution matrix, determining the number of working processes based on the total number of antennas of the multiple transmitting antennas; creating a parallel computing process pool based on the number of working processes; dividing the multiple transmitting antennas into multiple antenna subsets and assigning the multiple antenna subsets to multiple working processes in the parallel computing process pool; performing a first ray tracing calculation on the sub-block set based on the antenna information of the multiple transmitting antennas to obtain a first signal intensity distribution matrix, including: performing a first ray tracing calculation on the sub-block set in parallel by multiple working processes based on the antenna information of the antenna subsets to obtain a third signal intensity distribution matrix corresponding to each transmitting antenna; and determining the first signal intensity distribution matrix based on the third signal intensity distribution matrix corresponding to each transmitting antenna.

[0011] Optionally, the signal coverage simulation method further includes: after determining the signal coverage simulation result of the simulation area based on the second signal strength distribution matrix, if there are changes in the transmitting antennas in the simulation area, determining the proportion of the number of the changed transmitting antennas in the simulation area; if the proportion is less than or equal to a preset proportion, determining the updated first signal strength distribution matrix based on the third signal strength distribution matrix corresponding to multiple transmitting antennas and the antenna information of the changed transmitting antennas; and determining the new signal coverage simulation result of the simulation area based on the updated first signal strength distribution matrix.

[0012] To achieve the above objectives, according to another aspect of this application, a signal coverage simulation device is provided. The device includes: a first processing module for spatially dividing a simulation area into sub-blocks to obtain a set of sub-blocks, wherein the simulation area includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks; a first calculation module for performing a first ray tracing calculation on the set of sub-blocks based on the antenna information of the multiple transmitting antennas to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block; a second processing module for subdividing at least one sub-block in the set of sub-blocks based on the first signal intensity distribution matrix to obtain a target set of sub-blocks, wherein the target set of sub-blocks includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks; a second calculation module for performing a second ray tracing calculation on the target set of sub-blocks based on the antenna information of the multiple transmitting antennas to obtain a second signal intensity distribution matrix, wherein the second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and the subdivided sub-blocks, respectively, and the accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation; and a first determination module for determining the signal coverage simulation result of the simulation area based on the second signal intensity distribution matrix.

[0013] To achieve the above objectives, according to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, the device on which the computer-readable storage medium is located executes the above-described signal overlay simulation method.

[0014] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described signal coverage simulation method during runtime.

[0015] To achieve the above objectives, according to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the signal coverage simulation method described above.

[0016] In this embodiment, by spatially dividing the simulation area into sub-block sets, and based on the antenna information of multiple transmitting antennas, a first ray tracing calculation is performed on the sub-block sets to obtain a first signal strength distribution matrix. This enables rapid evaluation of the signal coverage of each sub-region within the simulation area. By further subdividing at least one sub-block in the sub-block set according to the first signal strength distribution matrix, a target sub-block set is obtained. A second ray tracing calculation is then performed on the target sub-block set to obtain a second signal strength distribution matrix. This allows for differentiation of the calculation accuracy of each sub-block based on the signal coverage of the sub-regions within the simulation area, and dynamic allocation of signal strength calculation resources within the target area. This avoids computational redundancy caused by using high-density grids across the entire target area, thereby effectively improving the simulation efficiency of signal coverage simulation.

[0017] Therefore, the method provided in this application achieves the goal of non-uniform signal strength calculation within the simulation area, realizes the technical effect of improving the simulation efficiency of signal coverage simulation, and solves the technical problem of low simulation efficiency when performing signal coverage simulation in related technologies. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0019] Figure 1 This is a hardware structure block diagram of a computer terminal provided according to an embodiment of this application;

[0020] Figure 2 This is a flowchart of a signal coverage simulation method provided according to an embodiment of this application;

[0021] Figure 3This is a flowchart for determining the calculation accuracy level according to an embodiment of this application;

[0022] Figure 4 This is a schematic diagram illustrating the determination of a set of target sub-blocks according to an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of a parallel computing architecture provided according to an embodiment of this application;

[0024] Figure 6 This is a flowchart illustrating the determination of new signal coverage simulation results according to embodiments of this application;

[0025] Figure 7 This is a schematic diagram of a signal coverage simulation device provided according to an embodiment of this application;

[0026] Figure 8 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] It should be noted that the information collected in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with relevant regulations and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse. For example, interfaces are set up between this system and relevant users or organizations, providing users with corresponding operation entry points for them to choose to agree to or refuse automated decision results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0030] Example 1

[0031] According to an embodiment of this application, an embodiment of a signal coverage simulation method is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a signal coverage simulation method is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor (MCU) or a field-programmable gate array (FPGA), etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output (I / O) interface, a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0033] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0034] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the signal coverage simulation method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the above-mentioned signal coverage simulation method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0035] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0036] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0037] Under the aforementioned operating environment, this application provides the following: Figure 2 The signal coverage simulation method is shown. Figure 2 This is a flowchart of a signal coverage simulation method according to Embodiment 1 of this application.

[0038] Step S201: Spatially divide the simulation area into blocks to obtain a set of sub-blocks. The simulation area includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks.

[0039] Optionally, electronic devices, application systems, servers, and other devices can be used as the execution subject of this application. In this embodiment, the target processing system is used as the execution subject to execute the above-mentioned signal coverage simulation method.

[0040] The simulation area refers to the physical space where signal propagation (or electromagnetic wave propagation) simulation is performed. The simulation area can be defined by geometric structures such as walls and obstacles. The target processing system can determine the simulation area based on user-imported 3D drawings or models. For example, the target processing system receives a building structure drawing imported by the user through a human-computer interaction interface, analyzes the wall coordinates, and automatically calculates the minimum bounding box containing all walls as the boundary of the simulation area. This boundary can be extended outward by a certain distance (e.g., 2 meters) to ensure complete coverage of the antenna's near-field zone.

[0041] The simulation area includes multiple transmitting antennas for transmitting signals. These transmitting antennas are the signal sources for the simulation area; for example, they could be base station antennas or remote radio units in an indoor distribution system. The signal coverage simulation referred to in this embodiment simulates the signal coverage of the simulation area by these transmitting antennas. It should be noted that the transmitting antennas may be simply referred to as antennas in this application.

[0042] In some implementations, the simulation region is spatially divided into sub-blocks to obtain a set of sub-blocks. Spatial division refers to dividing a continuous spatial simulation region into a finite number of discrete units, such as dividing it into multiple cubes or rectangular blocks. For example, based on a preset resolution (e.g., 1m). 1m The simulation area is divided into multiple regular rectangular sub-blocks (1m), each with a unique ID and center coordinates.

[0043] Step S202: Based on the antenna information of multiple transmitting antennas, perform a first ray tracing calculation on the sub-block set to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block.

[0044] In some implementations, antenna information includes, but is not limited to, parameters such as antenna location coordinates, transmit power, operating frequency, and antenna gain pattern.

[0045] In some implementations, a first ray tracing calculation is performed on the sub-block set based on antenna information from multiple transmitting antennas to obtain a first signal intensity distribution matrix. The first ray tracing calculation can be understood as a coarse-grained signal calculation, which corresponds to the fast estimation stage, such as calculating only the direct path or a small number of reflections (e.g., less than or equal to N) to obtain the first signal intensity distribution matrix.

[0046] The first signal strength distribution matrix includes the first signal strength values ​​of each sub-block. For example, the first signal strength distribution matrix is ​​1. The matrix M is the total number of sub-blocks. The i-th element in the first signal strength distribution matrix represents the first signal strength value of the i-th sub-block. The first signal strength value of the sub-block can refer to the first signal strength value at the center coordinates of the sub-block.

[0047] For example, for each sub-block in the sub-block set, the straight-line distance from its center point to each transmitting antenna is calculated. Using the free-space path loss formula combined with the antenna pattern gain, the signal power received by the center point along the direct path to each transmitting antenna is calculated based on this straight-line distance. Thus, based on the signal power received by the center point along the direct path to each transmitting antenna, the first signal strength value at the center point is determined. This process is repeated for all sub-blocks, and the first signal strength value at the center point of each sub-block is used as the first signal strength value of the sub-block to fill the matrix, forming the first signal strength distribution matrix.

[0048] Step S203: Subdivide at least one sub-block in the sub-block set according to the first signal intensity distribution matrix to obtain a target sub-block set, wherein the target sub-block set includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks.

[0049] In some implementations, the grid density can be intelligently adjusted based on the coarse calculation results (i.e., the first signal strength distribution matrix mentioned above). For example, the grid density can be increased (subdivision) in areas requiring high precision, while remaining sparse (unsubdivision) in areas where high precision is not required, thereby constructing a non-uniform, adaptive target grid (i.e., a set of target sub-blocks). The set of target sub-blocks refers to the final grid structure after the subdivision operation. It is no longer a regular grid, but a hybrid structure: some areas retain the original coarse sub-blocks (i.e., unsubdivided sub-blocks), while some areas are replaced with smaller subdivided sub-blocks. Unsubdivided sub-blocks can be areas with small signal gradients or extremely weak signals (below a threshold), which do not require high-precision calculations and remain unchanged; subdivided sub-blocks can be areas with large signal gradients (such as near antennas or wall edges), which are further subdivided to improve calculation accuracy.

[0050] For example, the signal intensity gradient values ​​within each sub-block are calculated based on the first signal intensity distribution matrix to obtain a gradient distribution map. Based on the antenna position, antenna transmit power, and sub-block location information, the computational accuracy level of each sub-block is estimated. According to the computational accuracy level and the signal intensity gradient values ​​of each sub-block, valid sub-blocks to be computed are selected from the sub-block set. These valid sub-blocks are then subdivided (e.g., recursive subdivision using a quadtree) to generate an adaptive grid node coordinate list, which is also the coordinate list corresponding to the target sub-block set. During the subdivision process, the subdivision depth can be determined jointly by the computational accuracy level and the signal intensity gradient values. For example, regions with high gradients and high computational accuracy levels are subdivided to the highest resolution, while regions with low computational accuracy levels are subdivided at fewer levels or not at all.

[0051] S204. Based on the antenna information of multiple transmitting antennas, a second ray tracing calculation is performed on the target sub-block set to obtain a second signal intensity distribution matrix. The second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and subdivided sub-blocks, respectively. The accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation.

[0052] In some implementations, the second ray tracing calculation can be understood as a fine-grained signal calculation. For example, calculating direct rays and multiple (e.g., more than N) reflections to obtain a second signal intensity distribution matrix.

[0053] The second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the undivided sub-blocks and the subdivided sub-blocks, respectively. For example, the second signal intensity distribution matrix is ​​1. The matrix P is the sum of the total number of undivided and subdivided sub-blocks in the target sub-block set. The i-th element in the second signal intensity distribution matrix represents the second signal intensity value of the i-th undivided (or subdivided) sub-block in the target sub-block set. The second signal intensity value of the undivided (or subdivided) sub-block can refer to the second signal intensity value at the center coordinates of the undivided (or subdivided) sub-block.

[0054] For example, for each unsubdivided (or subdivided) sub-block in the target sub-block set, the straight-line distance from its center point to each transmitting antenna is calculated. Using the free-space path loss formula combined with the antenna pattern gain, the signal power received by the center point on the direct path and reflected path of each transmitting antenna is calculated based on this straight-line distance. Thus, based on the signal power received by the center point on the direct path and reflected path of each transmitting antenna, the second signal strength value at the center point is determined. All unsubdivided (or subdivided) sub-blocks are traversed, and the second signal strength value at the center point of each unsubdivided (or subdivided) sub-block is used as the second signal strength value of the unsubdivided (or subdivided) sub-block and filled into the matrix to form the second signal strength distribution matrix.

[0055] S205, the signal coverage simulation results of the simulation area are determined based on the second signal intensity distribution matrix.

[0056] In some implementations, the second signal strength distribution matrix is ​​directly used as the signal coverage simulation result of the simulation area.

[0057] In some implementations, the second signal intensity distribution matrix is ​​mapped to a uniform output grid using an interpolation method to obtain the target signal intensity distribution matrix, which is then used as the signal coverage simulation result for the simulation area. For example, for unsubdivided sub-blocks in the target sub-block set, the signal intensity values ​​of each sub-region in the unsubdivided sub-block (e.g., subdividing the unsubdivided sub-block into four sub-regions) are determined based on the second signal intensity distribution matrix using an interpolation method, thereby converting the non-uniform grid corresponding to the target sub-block set into a uniform grid.

[0058] In some implementations, after obtaining the signal coverage simulation results, the signal coverage simulation results can be visualized, such as by converting them into a signal coverage heatmap.

[0059] In some implementations, after obtaining the signal coverage simulation results, the performance of multiple transmitting antennas can be evaluated based on these results. For example, the simulation area is the area corresponding to the target area, and the target area is the building area whose signal coverage effect is to be evaluated. The target processing system can determine whether the signal coverage of the simulation area by multiple transmitting antennas meets the preset signal coverage conditions based on the signal coverage simulation results. If it does, the signal coverage of the target area can be determined to be qualified. If it does not meet the preset signal coverage conditions, the transmitting antennas actually deployed in the target area are adjusted to optimize the signal coverage effect in the target area.

[0060] In this embodiment, by spatially dividing the simulation area into sub-block sets, and based on the antenna information of multiple transmitting antennas, a first ray tracing calculation is performed on the sub-block sets to obtain a first signal strength distribution matrix. This enables rapid evaluation of the signal coverage of each sub-region within the simulation area. By further subdividing at least one sub-block in the sub-block set according to the first signal strength distribution matrix, a target sub-block set is obtained. A second ray tracing calculation is then performed on the target sub-block set to obtain a second signal strength distribution matrix. This allows for differentiation of the calculation accuracy of each sub-block based on the signal coverage of the sub-regions within the simulation area, and dynamic allocation of signal strength calculation resources within the target area. This avoids computational redundancy caused by using high-density grids across the entire target area, thereby effectively improving the simulation efficiency of signal coverage simulation.

[0061] Therefore, the method provided in this application achieves the goal of non-uniform signal strength calculation within the simulation area, realizes the technical effect of improving the simulation efficiency of signal coverage simulation, and solves the technical problem of low simulation efficiency when performing signal coverage simulation in related technologies.

[0062] Optionally, in the signal coverage simulation method provided in this application embodiment, subdividing at least one sub-block in the sub-block set according to the first signal strength distribution matrix to obtain a target sub-block set includes: determining the signal strength gradient value of each sub-block according to the first signal strength distribution matrix; determining the calculation accuracy level of each sub-block based on the antenna information of multiple transmitting antennas and the position information of each sub-block; and subdividing at least one sub-block in the sub-block set according to the calculation accuracy level and the signal strength gradient value of each sub-block to obtain a target sub-block set.

[0063] In some implementations, the signal strength gradient value of each sub-block is determined based on the first signal strength distribution matrix. The signal strength gradient value represents the amplitude of signal strength variation within a unit distance in space; the larger the value, the more severe the signal fluctuation in that area. For example, for each sub-block in the set of sub-blocks, the signal strength gradient value of that sub-block is calculated using its center point coordinates and the first signal strength values ​​of its adjacent sub-blocks, employing the center difference formula and the adjacent difference formula.

[0064] In some implementations, the computational precision level of each sub-block is determined based on antenna information from multiple transmit antennas and the location information of each sub-block. The computational precision level indicates the degree of fineness allowed for subsequent calculations of signal strength by the sub-block; for example, a sub-block with a higher computational precision level has a higher degree of subdivision (i.e., a higher level of subdivision).

[0065] After determining the computational precision level and signal strength gradient value, at least one sub-block in the sub-block set is further subdivided according to the computational precision level and signal strength gradient value of each sub-block to obtain the target sub-block set. For example, regions with high gradients and high computational precision levels are subdivided to the highest resolution, while regions with low computational precision levels are subdivided at fewer levels or not at all.

[0066] It should be noted that the accuracy level helps to filter out worthless far-field regions and reduce unnecessary subdivisions, while the gradient value helps to obtain high resolution in near-field or reflection regions where the signal changes drastically. By determining the target sub-block set based on the calculated accuracy level and signal intensity gradient value, the effective division of sub-blocks within the sub-block set is achieved, thereby improving the accuracy of the target sub-block set.

[0067] Optionally, in the signal coverage simulation method provided in this application embodiment, determining the signal intensity gradient value of each sub-block according to the first signal intensity distribution matrix includes: for each sub-block in the sub-block set, determining the first signal intensity value of the sub-block and the first signal intensity values ​​of the adjacent sub-blocks of the sub-block from the first signal intensity distribution matrix; and using differential calculation, determining the signal intensity gradient value of the sub-block according to the first signal intensity value of the sub-block and the first signal intensity values ​​of the adjacent sub-blocks.

[0068] In some implementations, the adjacent sub-blocks of a sub-block can be sub-blocks in the four directions of top, bottom, left, and right in the sub-block set.

[0069] For example, for each sub-block in the sub-block set, if the sub-block is located in the inner region (i.e., non-edge region) of the grid topology corresponding to the sub-block set, the signal intensity gradient value of the sub-block can be calculated using the central difference formula. For example, for the inner region sub-block (i,j), the central difference formula is used as follows: P / x≈(P(i+1,j)-P(i-1,j)) / (2Δx), P / y≈(P(i,j+1)-P(i,j-1)) / (2Δy), the magnitude of the gradient (i.e., the signal strength gradient value). P(i,j)=sqrt(( P / x)^2+( P / y)^2), in dBm / m, where P(,) represents the first signal strength value at the corresponding point, Δx represents the side length of the sub-block in the horizontal direction (x-axis), and Δy represents the side length of the sub-block in the vertical direction (y-axis). If the sub-block is located in the edge region of the grid topology corresponding to the sub-block set, the signal strength gradient value of the sub-block can be calculated using forward or backward difference formulas.

[0070] It should be noted that by introducing differential calculation, the abstract signal distribution is transformed into a specific numerical gradient, which helps to objectively measure which regions in the simulation area have gradual signal changes and which regions have drastic signal changes.

[0071] Optionally, in the signal coverage simulation method provided in this application embodiment, the calculation accuracy level of each sub-block is determined based on the antenna information of multiple transmitting antennas and the position information of each sub-block, including: for each sub-block in the sub-block set, determining the distance from the sub-block to the nearest transmitting antenna based on the antenna information of multiple transmitting antennas and the position information of the sub-block; determining the priority of the sub-block based on the distance from the sub-block to the nearest transmitting antenna, wherein the priority is negatively correlated with the distance; determining the calculation accuracy level of the sub-block as the lowest calculation accuracy level when the priority is lower than the priority threshold; determining the ideal maximum signal strength corresponding to the sub-block based on the antenna information of multiple transmitting antennas and the position information of the sub-block when the priority is higher than or equal to the priority threshold; and determining the calculation accuracy level of the sub-block based on the ideal maximum signal strength.

[0072] In some implementations, antenna information includes, but is not limited to, parameters such as antenna position coordinates, transmit power, operating frequency, and antenna gain pattern. For each sub-block in the sub-block set, the distance from the sub-block to the nearest transmit antenna is determined based on the position coordinates of multiple transmit antennas and the sub-block's position information.

[0073] After determining the distance from the sub-block to the nearest transmit antenna, the priority of the sub-block is determined based on this distance. For example, an inverse proportional function or a reciprocal function can be used to calculate the priority.

[0074] After determining the priority, if the priority is lower than the priority threshold, the computational accuracy level of the sub-block is determined to be the lowest computational accuracy level. That is, if the sub-block is very far from all antennas, it is considered that the signal in that area has been submerged in background noise, and complex ray tracing or fine mesh calculation can be skipped, and it can be directly marked as the lowest computational accuracy level.

[0075] If the priority is higher than or equal to the priority threshold, the ideal maximum signal strength corresponding to the sub-block is determined based on the antenna information of multiple transmit antennas and the location information of the sub-block. For example, assuming there are no walls obstructing the signal, no reflection loss, and only free space path loss affecting the signal strength, the theoretical maximum signal strength that the sub-block can achieve is estimated.

[0076] After determining the ideal maximum signal strength, the computational accuracy level of the sub-block is determined based on the ideal maximum signal strength. The ideal maximum signal strength can be positively correlated with the computational accuracy level.

[0077] For example, Figure 3 This is a flowchart for determining the calculation accuracy level according to an embodiment of this application. Figure 3 This embodiment describes an optional method for determining the calculation precision level of a sub-block. The following parameters are obtained in advance:

[0078] Antenna parameters: position coordinates of all antennas (x_i, y_i, z_i), transmit power P_t (dBm), antenna gain G_t (dBi), antenna type (affects radiation pattern).

[0079] Receiver grid: A pre-divided list of receiver coordinates. Each receiver point represents the location where the first signal strength needs to be calculated. The receiver point is also the center point of the sub-block in the sub-block set.

[0080] Wall parameters: vertex coordinates, thickness, and material of the wall (which determine dielectric constant and conductivity, thus affecting reflection loss).

[0081] Frequency parameter: Signal frequency f (Hz), which is set by the user according to the simulation frequency band.

[0082] Threshold parameters: First-level threshold T_skip = -100dBm, second-level threshold T_lowres = -80dBm, priority threshold P_th = 0.1. A priority threshold of 0.1 corresponds to a priority of approximately 0.099 when the distance from the sub-block to the antenna is about 10 meters, meaning that the signal strength in areas more than 10 meters from the antenna is usually lower than the noise level.

[0083] The threshold parameter is a preset value. It can be determined based on the actual environmental noise level and simulation accuracy requirements, or obtained through background noise measurement. For example, the indoor environmental noise floor is approximately -100dBm to -95dBm. When the ideal maximum signal strength is below -100dBm, the signal is considered to be submerged in noise, and no subdivision is performed on the sub-blocks. When the ideal maximum signal strength is between -80dBm and -100dBm, the subdivision level can be reduced.

[0084] For each sub-block, its distance to the nearest transmitting antenna is calculated, and its priority is determined accordingly. Sub-blocks closer to the transmitting antenna have higher priority and can be subject to more refined calculations (i.e., multi-level subdivision); sub-blocks farther away have lower priority and greater signal attenuation, thus requiring less subdivision. Sub-blocks with a priority below the priority threshold can be directly marked as noise regions, with the lowest calculation accuracy, and are not further subdivided. For sub-blocks that pass the priority threshold, the process proceeds to the receiver-level determination: for each receiver, its maximum possible signal strength (i.e., ideal maximum signal strength) is quickly estimated based on the free-space path loss law.

[0085] Specifically, for each sub-block, the distance d_min to the nearest antenna is calculated, and the priority is calculated as priority=1 / (d_min+ε), where ε is a preset constant. Sub-blocks with a priority lower than the priority threshold (e.g., 0.1) are considered to be far from all antennas, have extremely low signal strength, are directly marked as noise regions, have the lowest calculation accuracy level, and are not further subdivided.

[0086] For sub-blocks with a priority ≥ 0.1, the process proceeds to the receiver-level decision stage. For each receiver, the maximum possible signal strength is quickly estimated based on the free-space path loss formula. For example, the maximum possible signal strength is calculated using the following formula:

[0087] P_max_est=P_t,max-(20·log10(d_min)+20·log10(f)+20·log10(4π / c))

[0088] Where P_max_est represents the maximum possible signal strength; P_t,max is the maximum transmit power among all transmitting antennas; d_min is the distance from the receiving point to the nearest antenna; f is set by the user according to the simulation frequency band; c is a physical constant; and the reflection loss of 10dB is an empirical value. Since this is for calculating the maximum possible signal strength, P_t,max and d_min can correspond to different transmitting antennas.

[0089] After determining the maximum possible signal strength, the calculation accuracy level is determined based on the numerical relationship between the maximum possible signal strength and the first and second level thresholds. For example, if the maximum possible signal strength is less than the first level threshold (e.g., -100dBm), the sub-block's calculation accuracy level is determined to be the lowest. If the maximum possible signal strength is greater than or equal to the first level threshold but less than the second level threshold (e.g., -80dB), the sub-block's calculation accuracy level is determined to be the medium calculation accuracy level. If the maximum possible signal strength is greater than or equal to the second level threshold, the sub-block's calculation accuracy level is determined to be the highest calculation accuracy level. The highest calculation accuracy level is higher than the medium calculation accuracy level, and the medium calculation accuracy level is higher than the lowest calculation accuracy level.

[0090] It should be noted that by first using distance (priority) to quickly filter the far field, and then using the ideal maximum signal strength estimation for fine classification, unnecessary computation is effectively reduced and the efficiency of determining the calculation accuracy level is improved.

[0091] Optionally, in the signal coverage simulation method provided in this application embodiment, at least one sub-block in the sub-block set is subdivided according to the calculation accuracy level and the signal intensity gradient value of each sub-block to obtain a target sub-block set, including: for each sub-block in the sub-block set, determining the subdivision level threshold of the sub-block according to the calculation accuracy level; when the current subdivision level of the sub-block is less than the subdivision level threshold and the signal intensity gradient value of the sub-block is greater than a preset gradient value, subdividing the sub-block into multiple sub-blocks to obtain an updated sub-block set, and updating the current subdivision level of the sub-block; determining the signal intensity gradient value of the sub-blocks in the updated sub-block set, and repeatedly subdividing at least one sub-block in the updated sub-block set according to the signal intensity gradient value corresponding to the sub-block and the subdivision level threshold of the sub-block to which the sub-block belongs, until there are no subdivisible sub-blocks, thus obtaining the target sub-block set.

[0092] In some implementations, the higher the computational precision level, the higher the subdivision level threshold. For example, assuming the resolution of a sub-block is 1m × 1m × 1m, if the computational precision level is the highest, the subdivision level threshold is set to level 4, dividing the sub-block into four equal parts each time, resulting in a minimum sub-block resolution of 0.125m × 0.125m × 0.125m. If the computational precision level is medium, the subdivision level threshold is set to level 2, dividing the sub-block into four equal parts each time, resulting in a minimum sub-block resolution of 0.5m × 0.5m × 0.5m. If the computational precision level is the lowest, the subdivision level threshold is set to level 1, meaning no subdivision. By dynamically determining the subdivision level threshold, meaningless over-subdivision in low-value areas is prevented.

[0093] The current subdivision level of a sub-block can be understood as the sub-block's initial form (i.e., the form obtained from the initial division of the simulation region, such as 1m). 1m Starting at 1m, the depth after subdivision is defined. For example, if the initial shape is defined as level 1, after subdividing the sub-block once, its current subdivision level becomes level 2, and so on. The preset gradient value is a fixed empirical threshold used to determine whether the signal changes within the sub-block are drastic. Exceeding this value indicates that there are complex electromagnetic wave propagation phenomena (such as strong reflection or focusing) in the sub-block area, requiring a finer mesh to capture them.

[0094] Traverse the sub-blocks in the sub-block set. If the current sub-level of the traversed sub-block is greater than or equal to the sub-level threshold, or if the signal strength gradient value of the sub-block is less than or equal to the preset gradient value, then the sub-block is not subdivided.

[0095] If the current subdivision level of a traversed sub-block is less than the subdivision level threshold, and the signal strength gradient value of the sub-block is greater than a preset gradient value, then the sub-block is subdivided into multiple sub-blocks, resulting in an updated set of sub-blocks, and the current subdivision level of the sub-blocks is updated. For example, dividing a sub-block into four equal parts, a cube sub-block with side length L is divided into four sub-blocks with side length L / 2. After obtaining the sub-blocks, the original parent-child block (i.e., the subdivided sub-block) is removed from the sub-block set, and the four newly generated sub-blocks are added. The current subdivision level of the original parent-child block is also incremented by 1, for example, changing from level 1 to level 2. After completing the above operations for all sub-blocks in the sub-block set, the updated set of sub-blocks is obtained.

[0096] After obtaining the updated set of sub-blocks, for the sub-sub-blocks in the updated set of sub-blocks, the signal strength gradient value of the sub-sub-block can be determined by determining the signal strength gradient value of the sub-block, or the sub-sub-block can directly inherit the signal strength gradient value of its parent-child block (that is, the sub-block to which the sub-sub-block belongs), or the signal strength gradient value of the sub-sub-block can be determined by interpolation based on the signal strength gradient values ​​of the parent-child block and the signal strength gradient values ​​of the parent-child block.

[0097] After determining the signal strength gradient values ​​of each sub-block, the sub-blocks in the updated sub-block set are traversed. If the current subdivision level of the sub-block to which the sub-block belongs is less than the subdivision level threshold, and the signal strength gradient value of the sub-block is greater than a preset gradient value, then the sub-block is subdivided, and the newly subdivided sub-block is added to the updated sub-block set. The current subdivision level of the top-level parent-child block is also updated; for example, the level of the top-level parent-child block changes from level 2 to level 3. If the current subdivision level of the sub-block to which the sub-block belongs is greater than or equal to the subdivision level threshold, or the signal strength gradient value of the sub-block is less than or equal to the preset gradient value, then the sub-block is not subdivided. After completing the above operations for all sub-blocks in the sub-block set, a newly updated sub-block set is obtained. This process is repeated until no further subdivisible sub-blocks are found. The latest updated sub-block set is then determined as the target sub-block set.

[0098] For example, Figure 4 This is a schematic diagram illustrating the determination of a target sub-block set according to an embodiment of this application. Figure 4This embodiment describes an optional process for determining the target sub-block set. This application utilizes the non-uniformity of indoor signal strength distribution (large signal gradient near the antenna and wall edges, small gradient in open areas) and employs quadtree mesh technology to dynamically allocate computing resources. First, fast ray tracing calculations are performed across the entire field based on the sub-block set to obtain a first signal strength distribution matrix. Then, the signal strength gradient value of each sub-block is calculated, and the sub-blocks are divided using a gradient threshold (i.e., a preset gradient value) of 5 dBm / m as the criterion.

[0099] Whether a sub-block meets the subdivision condition is determined based on the signal strength gradient value and the subdivision level threshold. The subdivision level threshold is determined according to the calculation accuracy level of the sub-block. Each sub-block can be divided into 4 equally sized sub-sub-blocks, and the current subdivision level is incremented by 1. Subdivision stops when the sub-blocks obtained meet any of the following conditions:

[0100] (1) The signal strength gradient value of the sub-block is less than or equal to the gradient threshold G_th (i.e. the signal changes smoothly and no further encryption is needed).

[0101] (2) The current subdivision level of the sub-block is greater than or equal to the subdivision level threshold L_max (to reach the maximum subdivision depth and avoid excessive subdivision that could lead to a rebound in computation).

[0102] For sub-blocks that meet the subdivision criteria, a quadtree recursive subdivision is performed: the current sub-block is divided into four equal sub-blocks, and the previous steps are repeated for each sub-block until the gradient of all sub-blocks is lower than or equal to the gradient threshold or reaches the subdivision level threshold. This results in a set of adaptive mesh sub-blocks, i.e., the target set of sub-blocks. For example, high-gradient regions have dense sub-blocks, while low-gradient regions have sparse sub-blocks. After determining the adaptive mesh sub-blocks, fine-grained ray tracing calculations (including multiple reflections) are performed to obtain accurate signal intensity values, i.e., the second signal intensity distribution matrix. Then, the values ​​on these sub-blocks or sub-sub-blocks are mapped to a unified output mesh (e.g., 60×60×60, i.e., the simulation area is divided into a 60×60×60 mesh) using an interpolation method. The target resolution (e.g., 60×60×60) is set by the user according to the output accuracy requirements.

[0103] In some implementations, a first signal intensity distribution matrix is ​​obtained by first performing full-field fast ray tracing calculation; the signal intensity gradient values ​​of sub-blocks are calculated; sub-blocks that meet the conditions are recursively subdivided into quadtrees based on gradient thresholds and subdivision level thresholds, with high-gradient regions automatically densified to high resolution and low-gradient regions maintaining a sparse grid; fine calculations are performed on the subdivided adaptive grid nodes, and interpolation is used to map them to a unified output grid, thereby realizing the dynamic allocation of computing resources according to signal importance and improving simulation efficiency.

[0104] It should be noted that related technologies lack an early termination mechanism (calculation continues even when the signal attenuates to noise levels) and have a fixed mesh resolution (under-sampling in high-gradient regions and over-computation in low-gradient regions). This application, through a recursive subdivision mechanism, makes the mesh density no longer fixed, but dynamically adjusted according to the local characteristics of the signal field. The mesh is dense in high-gradient regions (such as the antenna near-field and the edge of the reflector) and sparse in low-gradient regions (such as an open hall), effectively matching the non-uniform characteristics of indoor electromagnetic wave distribution, thereby improving simulation efficiency. The adaptive mesh reduces the 6400 computation points of an 80×80 uniform mesh to 1800 (quadtree), and the time complexity is reduced from O( The accuracy is reduced to O(N log N), and the accuracy in the critical area (within 3 meters of the antenna) is only reduced by 0.3-0.7 dBm.

[0105] Optionally, in the signal coverage simulation method provided in this application embodiment, before performing a first ray tracing calculation on the sub-block set based on the antenna information of multiple transmitting antennas to obtain a first signal intensity distribution matrix, the method further includes: determining the number of working processes based on the total number of antennas of the multiple transmitting antennas; creating a parallel computing process pool based on the number of working processes; dividing the multiple transmitting antennas into multiple antenna subsets and assigning the multiple antenna subsets to multiple working processes in the parallel computing process pool; performing a first ray tracing calculation on the sub-block set based on the antenna information of the multiple transmitting antennas to obtain a first signal intensity distribution matrix, including: performing a first ray tracing calculation on the sub-block set in parallel by multiple working processes based on the antenna information of the antenna subsets to obtain a third signal intensity distribution matrix corresponding to each transmitting antenna; and determining the first signal intensity distribution matrix based on the third signal intensity distribution matrix corresponding to each transmitting antenna.

[0106] To overcome the performance bottleneck of single-threaded serial computing in large-scale multi-antenna scenarios, the target processing system can adopt a multi-process parallel computing architecture. This architecture utilizes the physical characteristics that signal propagation calculations from different transmitting antennas are independent and data-free, distributing computational tasks to multiple CPU (Central Processing Unit) cores for parallel execution, thereby significantly shortening simulation time.

[0107] The number of worker processes refers to the actual number of processes participating in parallel computing. The number of worker processes is positively correlated with the total number of antennas. After determining the number of worker processes, a parallel computing process pool is created based on the number of worker processes. The parallel computing process pool includes multiple worker processes used to receive and execute computing tasks.

[0108] The target processing system can divide all transmitting antennas into several non-overlapping antenna subsets according to a certain strategy (such as uniform distribution). Each antenna subset includes at least one transmitting antenna, and each antenna subset is assigned to a worker process for independent processing.

[0109] In some implementations, multiple worker processes perform a first ray tracing calculation on the set of sub-blocks in parallel based on the antenna information of the antenna subset, obtaining a third signal strength distribution matrix corresponding to each transmit antenna. For example, for a worker process in a parallel computing process pool, based on the antenna information of the antenna subset assigned to that worker process, a first ray tracing calculation is performed on the set of sub-blocks to obtain a third signal strength distribution matrix corresponding to each transmit antenna in the antenna subset. The third signal strength distribution matrix corresponding to each transmit antenna includes the signal strength value of each sub-block at that transmit antenna.

[0110] After obtaining the third signal strength distribution matrix corresponding to each of the multiple transmitting antennas, the signal strength values ​​belonging to the same sub-block can be superimposed (e.g., linear superposition in the power domain) based on the third signal strength distribution matrix corresponding to each transmitting antenna to obtain the first signal strength value of that sub-block. Then, the first signal strength distribution matrix can be calculated based on the first signal strength values ​​of each sub-block. For example, after all the working processes have completed their calculations, they each send their calculated third signal strength distribution matrices back to the main process. The main process then determines the first signal strength distribution matrix based on the third signal strength distribution matrices corresponding to each transmitting antenna.

[0111] In some implementations, a second ray tracing calculation is performed on the target sub-block set based on the antenna information of multiple transmitting antennas to obtain a second signal intensity distribution matrix. This includes: performing second ray tracing calculations on the sub-block set in parallel using multiple working processes based on the antenna information of the antenna subset to obtain a fourth signal intensity distribution matrix corresponding to each transmitting antenna; and determining the second signal intensity distribution matrix based on the fourth signal intensity distribution matrix corresponding to each transmitting antenna. This process can refer to the process of obtaining the first signal intensity distribution matrix described above, and therefore will not be repeated here.

[0112] Exemplarily, this embodiment describes an optional parallel operation of multiple working processes. This application leverages the inherent independence of multi-antenna ray tracing calculations (signal propagation calculations for different antennas have no data dependency) to distribute antenna-level computational tasks to multiple working processes on a multi-core CPU for parallel execution. In ray tracing simulations, each antenna acts as an independent signal source. The calculation of its direct and reflected paths depends only on the antenna's own position, power, radiation pattern parameters, and shared scene geometry data (walls, meshes). The calculation processes of other antennas have no data write dependency, and the final total signal strength at the receiving point (e.g., first signal strength value, second signal strength value) is a linear superposition (power domain summation) of the contributions from each antenna. This physical characteristic forms the theoretical basis for the parallel decomposition of antenna-level tasks.

[0113] The target processing system first detects the number of CPU cores N_core on the current computing platform. Based on the total number of antennas numTx, it determines the number of worker processes numWorkers = min(N_core, numTx) and creates a parallel computing process pool containing numWorkers worker processes. Then, read-only data in the simulation scene that does not change with the antennas (including wall geometry parameters, receiver mesh coordinates, material parameters, and antenna radiation models) is broadcast to all worker processes in a shared constant manner to avoid duplicate transmissions. The antenna index set {1,2,...,numTx} is evenly divided into numWorkers non-overlapping antenna subsets, and each worker process is assigned one antenna subset. Each worker process performs ray tracing calculations in parallel in its own independent memory space (e.g., first ray tracing calculation, second ray tracing calculation), including but not limited to direct path power calculation and reflection path power calculation. There are no shared write variables between processes, naturally eliminating data contention. After the calculation is complete, the main process collects the antenna signal strength matrices returned by all worker processes (e.g., the third signal strength distribution matrix, the fourth signal strength distribution matrix), and linearly superimposes the direct and reflected signal power of all antennas according to the receiver point dimension to obtain the total signal strength distribution of the entire field (e.g., the first signal strength distribution matrix, the second signal strength distribution matrix). This architecture enables the performance bottleneck of reflection calculation, which accounts for 70%-80% of the total time, to achieve a speedup close to the number of worker processes, effectively alleviating the overall performance bottleneck. This method utilizes the characteristic that there is no data dependency between antenna calculations, optimizes transmission overhead through read-only data broadcasting and antenna data slice distribution, and eliminates data contention through independent memory spaces for each process, which helps to achieve near-linear parallel acceleration.

[0114] For example, Figure 5 This is a schematic diagram of a parallel computing architecture provided according to an embodiment of this application, such as... Figure 5 As shown, the multi-process parallel computing architecture can be a hierarchical, single-interaction structure, divided into four layers from top to bottom:

[0115] (1) Main process layer: responsible for parallel pool initialization, antenna task splitting, read-only data broadcasting, result aggregation and final heatmap generation;

[0116] (2) Work process layer: contains work processes Worker 1 to Worker N (N=8), each process is assigned a set of antenna subsets (e.g. Worker 1 processes antennas 1-3, Worker 2 processes antennas 4-5).

[0117] (3) Computational subtask layer: Each working process contains two independent subtasks, direct computation and reflection computation, which can be executed in parallel;

[0118] (4) Result aggregation layer: The calculation results of all working processes are sent back to the main process and aggregated according to the receiving point dimension.

[0119] The interaction between the layers can be represented as follows: the master process sends tasks / data to the worker processes, the worker processes send results back to the master process, and there is no data interaction between the worker processes (to ensure parallel efficiency).

[0120] It should be noted that by using a multi-process parallel architecture, large-scale simulation scenarios that were originally infeasible in engineering due to excessive computation time (such as ≥20 antennas, ≥60×60×60 high-resolution mesh) can be transformed into executable tasks that can be completed within a reasonable time. This fundamentally expands the engineering applicability of ray tracing simulation methods, making high-resolution simulations engineering feasible in multi-antenna scenarios without sacrificing accuracy for efficiency, thereby effectively improving simulation efficiency.

[0121] Optionally, in the signal coverage simulation method provided in this application embodiment, after determining the signal coverage simulation result of the simulation area based on the second signal strength distribution matrix, the method further includes: determining the proportion of the number of changed transmitting antennas in the simulation area when there are changes in the transmitting antennas in the simulation area; determining an updated first signal strength distribution matrix based on the third signal strength distribution matrix corresponding to multiple transmitting antennas and the antenna information of the changed transmitting antennas when the proportion of the number of changed antennas is less than or equal to a preset ratio; and determining a new signal coverage simulation result of the simulation area based on the updated first signal strength distribution matrix.

[0122] In some implementations, a change in the transmitting antenna means that, in the current simulation scenario, compared to the previously cached simulation scenario, at least one antenna's parameters (such as position coordinates, transmit power, antenna type, azimuth angle, etc.) have changed, or an antenna has been added / deleted. The target processing system can first detect the difference between the currently input antenna configuration and the last successfully calculated and cached antenna configuration. By calculating the proportion of differing antennas, it determines which calculation strategy to use subsequently.

[0123] For example, if the transmitting antennas within the simulation area change, the system retrieves the antenna list for the current scene and compares it item by item with the antenna list for the simulation scene cached in the cache library. The cache library includes at least the antenna list for the simulation area during the last simulation and the corresponding simulation results. Comparison dimensions include, but are not limited to, antenna position coordinates, transmit power, antenna gain pattern model, elevation / azimuth angle, etc. The system counts the number of antennas whose parameters have changed. For example, if there are 20 antennas in the current simulation scene, and 2 have moved, 1 has changed power, and the remaining 17 are identical, then the number of changed transmitting antennas is 3. The system then obtains the total number of antennas in the current simulation scene, divides the number of changed transmitting antennas by the total number of antennas, and calculates the percentage of changed transmitting antennas.

[0124] When a significant change is detected, meaning the proportion of changes exceeds a preset threshold, the system performs a full calculation. This means it directly recalculates the signal coverage simulation results for the new simulation scenario without referencing historical cached data.

[0125] When a change is determined to be minor, i.e., the proportion of changes is less than or equal to a preset ratio, the system performs incremental calculations. The specific logic is: Old result - Old antenna contribution + New antenna contribution = New result. That is, the signal coverage simulation results are loaded from the historical cache, the contribution of the changed antennas under the old parameters is subtracted, and the new contribution calculated for the changed antennas under the new parameters is added to obtain the new coverage simulation results. For example, for a subset of antennas that have changed, the system starts a parallel computing process pool (or uses a single thread), performs a first ray tracing calculation based on the antenna information of these changed transmitting antennas, obtains the new third signal strength distribution matrix corresponding to these changed antennas, then replaces the corresponding matrices in the third signal strength distribution matrices of multiple transmitting antennas with the new third signal strength distribution matrix, and after the replacement, calculates the updated first signal strength distribution matrix.

[0126] After determining the updated first signal strength distribution matrix, the new signal coverage simulation result for the simulation area is determined based on the updated first signal strength distribution matrix. The method for determining the new signal coverage simulation result is the same as the method described above for determining the signal coverage simulation result based on the first signal strength distribution matrix, and therefore will not be repeated here. Furthermore, during the process of determining the new signal coverage simulation result, the target processing system can determine the updated second signal strength distribution matrix based on the method used to determine the updated first signal strength distribution matrix, and therefore will also not be repeated here.

[0127] For example, Figure 6 This is a flowchart illustrating the determination of new signal coverage simulation results according to embodiments of this application. Figure 6This embodiment describes an optional process for determining new signal coverage simulation results. The simulation area after the transmitting antenna change is defined as the new scene, and the simulation area before the transmitting antenna change is defined as the old scene. The target processing system can obtain the following information:

[0128] New scene parameters: New antenna parameters include location, power, type, orientation, etc., as well as wall geometry parameters, material parameters, signal frequency, and grid configuration;

[0129] Old scene parameters: corresponding parameters read from the historical cache, including old antenna list, old wall data, old signal frequency, etc.; old scene parameters are stored in the cache library. Each record in the cache library contains scene hash value, signal strength matrix of each antenna, timestamp, and validity period; hash value can be generated as a unique identifier for the scene based on all parameters that affect the simulation results (antenna position, power, type, direction, wall geometry, material parameters, frequency, mesh configuration).

[0130] When the transmitting antennas within the simulation area change, i.e., when a new scene is generated, the target processing system can search the cache for historical results that match the hash of the current scene and are not expired. If a match is found, the results are directly loaded and output. If a cache miss occurs, the system reads the previously calculated antenna list from the old cache, including the unique identifier, location coordinates, transmit power, antenna type, and azimuth angle of each antenna. Then, the antenna list for the new scene is compared item by item with the old antenna list. The comparison dimensions include whether the antenna position, transmit power, antenna type, and antenna azimuth angle have changed. Newly added or deleted antennas are directly counted as changed antennas, while antennas with changed order but identical parameters are not counted as changed antennas. After counting the number of changed antennas, the percentage of changed antennas is calculated, which is the ratio of the number of changed antennas to the total number of antennas in the new scene. This ratio represents the proportion of antennas that have changed. When the change rate exceeds 50%, it indicates that more than half of the antenna parameters have changed. In this case, the incremental calculation needs to retain less of the unchanged part, and the overhead of recalculating all antennas is close to that of incremental calculation. Therefore, a full calculation is performed, and the parallel architecture is used to re-perform ray tracing on all antennas. After obtaining the results, the cache is updated. When the change rate does not exceed 50%, it is determined that the proportion of changed antennas is small, and incremental calculation can save time significantly. In this case, the following steps can be performed: load historical results (including the total signal strength distribution matrix and the signal strength distribution matrices of each antenna) from the old cache; subtract the old contribution of the changed antennas from the total result to obtain the total contribution of the unchanged part; re-perform ray tracing calculation only on the changed antennas to obtain the new contribution; superimpose the unchanged part and the new contribution to obtain the total signal strength matrix of the new scene; finally, store the new result (i.e., the new signal coverage simulation result) in the cache and mark it with a timestamp.

[0131] It should be noted that this application utilizes antenna-level computational independence to achieve partial recalculation and result reuse, and drives automatic switching between incremental / full computation by changing the percentage threshold, which can effectively improve the efficiency of iterative parameter tuning.

[0132] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0133] Example 2

[0134] This application also provides a signal coverage simulation device. It should be noted that the signal coverage simulation device of this application can be used to execute the signal coverage simulation method provided in this application. The signal coverage simulation device provided in this application will be described below.

[0135] According to an embodiment of this application, an apparatus for implementing the above-described signal coverage simulation method is also provided, such as... Figure 7 As shown, the device includes:

[0136] The first processing module 701 is used to spatially divide the simulation area into sub-blocks to obtain a set of sub-blocks. The simulation area includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks.

[0137] The first calculation module 702 is used to perform a first ray tracing calculation on the set of sub-blocks based on the antenna information of multiple transmitting antennas to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block;

[0138] The second processing module 703 is used to subdivide at least one sub-block in the sub-block set according to the first signal intensity distribution matrix to obtain a target sub-block set, wherein the target sub-block set includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks.

[0139] The second calculation module 704 is used to perform a second ray tracing calculation on the target sub-block set based on the antenna information of multiple transmitting antennas to obtain a second signal intensity distribution matrix. The second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and subdivided sub-blocks, respectively. The accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation.

[0140] The first determining module 705 is used to determine the signal coverage simulation results of the simulation area based on the second signal intensity distribution matrix.

[0141] In this embodiment, by spatially dividing the simulation area into sub-block sets, and based on the antenna information of multiple transmitting antennas, a first ray tracing calculation is performed on the sub-block sets to obtain a first signal strength distribution matrix. This enables rapid evaluation of the signal coverage of each sub-region within the simulation area. By further subdividing at least one sub-block in the sub-block set according to the first signal strength distribution matrix, a target sub-block set is obtained. A second ray tracing calculation is then performed on the target sub-block set to obtain a second signal strength distribution matrix. This allows for differentiation of the calculation accuracy of each sub-block based on the signal coverage of the sub-regions within the simulation area, and dynamic allocation of signal strength calculation resources within the target area. This avoids computational redundancy caused by using high-density grids across the entire target area, thereby effectively improving the simulation efficiency of signal coverage simulation.

[0142] Therefore, the method provided in this application achieves the goal of non-uniform signal strength calculation within the simulation area, realizes the technical effect of improving the simulation efficiency of signal coverage simulation, and solves the technical problem of low simulation efficiency when performing signal coverage simulation in related technologies.

[0143] Optionally, in the signal coverage simulation device provided in this application embodiment, the second processing module further includes: a first determining submodule, used to determine the signal intensity gradient value of each sub-block according to the first signal intensity distribution matrix; a second determining submodule, used to determine the calculation accuracy level of each sub-block based on the antenna information of multiple transmitting antennas and the position information of each sub-block; and a first processing submodule, used to subdivide at least one sub-block in the sub-block set according to the calculation accuracy level and the signal intensity gradient value of each sub-block to obtain a target sub-block set.

[0144] Optionally, in the signal coverage simulation device provided in the embodiments of this application, the first determining submodule further includes: a first determining unit, configured to determine, for each subblock in the subblock set, a first signal strength value of the subblock and the first signal strength values ​​of the adjacent subblocks of the subblock from the first signal strength distribution matrix; and a second determining unit, configured to determine the signal strength gradient value of the subblock by using differential calculation based on the first signal strength value of the subblock and the first signal strength values ​​of the adjacent subblocks.

[0145] Optionally, in the signal coverage simulation device provided in this application embodiment, the second determining submodule further includes: a third determining unit, used to determine the distance from the sub-block to the nearest transmitting antenna for each sub-block in the sub-block set, based on the antenna information of multiple transmitting antennas and the position information of the sub-block; a fourth determining unit, used to determine the priority of the sub-block based on the distance from the sub-block to the nearest transmitting antenna, wherein the priority is negatively correlated with the distance; a fifth determining unit, used to determine the calculation accuracy level of the sub-block as the lowest calculation accuracy level when the priority is lower than the priority threshold; a sixth determining unit, used to determine the ideal maximum signal strength corresponding to the sub-block based on the antenna information of multiple transmitting antennas and the position information of the sub-block when the priority is higher than or equal to the priority threshold; and a seventh determining unit, used to determine the calculation accuracy level of the sub-block based on the ideal maximum signal strength.

[0146] Optionally, in the signal coverage simulation device provided in this application embodiment, the first processing submodule further includes: an eighth determining unit, used to determine the subdivision level threshold of each sub-block in the sub-block set according to the calculation accuracy level; a first processing unit, used to subdivide the sub-block into multiple sub-blocks when the current subdivision level of the sub-block is less than the subdivision level threshold and the signal strength gradient value of the sub-block is greater than a preset gradient value, to obtain an updated sub-block set, and update the current subdivision level of the sub-block; a second processing unit, used to determine the signal strength gradient value of the sub-blocks in the updated sub-block set, and repeatedly execute subdividing at least one sub-block in the updated sub-block set according to the signal strength gradient value corresponding to the sub-block and the subdivision level threshold of the sub-block to which the sub-block belongs, until there are no subdivisible sub-blocks, to obtain the target sub-block set.

[0147] Optionally, in the signal coverage simulation device provided in the embodiments of this application, the signal coverage simulation device further includes: a second determining module, used to determine the number of working processes based on the total number of antennas of the multiple transmitting antennas; a creating module, used to create a parallel computing process pool based on the number of working processes; and an allocation module, used to divide the multiple transmitting antennas into multiple antenna subsets and allocate the multiple antenna subsets to multiple working processes in the parallel computing process pool.

[0148] The first calculation module further includes: a calculation submodule, used to perform first ray tracing calculations on the sub-block set in parallel based on the antenna information of the antenna subset through multiple working processes to obtain the third signal intensity distribution matrix corresponding to each transmitting antenna; and a third determination submodule, used to determine the first signal intensity distribution matrix based on the third signal intensity distribution matrix corresponding to each transmitting antenna.

[0149] Optionally, in the signal coverage simulation device provided in this application embodiment, the signal coverage simulation device further includes: a third determining module, used to determine the proportion of the number of transmitting antennas that have changed in the simulation area when there are changes in the transmitting antennas in the simulation area; a fourth determining module, used to determine an updated first signal strength distribution matrix based on the third signal strength distribution matrix corresponding to multiple transmitting antennas and the antenna information of the transmitting antennas that have changed when the proportion of the number is less than or equal to a preset ratio; and a fifth determining module, used to determine a new signal coverage simulation result of the simulation area based on the updated first signal strength distribution matrix.

[0150] It should be noted that the first processing module 701, the first calculation module 702, the second processing module 703, the second calculation module 704, and the first determining module 705 correspond to steps S201 to S205 in Embodiment 1. The five modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in Embodiment 1.

[0151] Example 3

[0152] Embodiments of this application may provide an electronic device. Figure 8 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 8 As shown, the electronic device may include: one or more ( Figure 8 (Only one is shown) processor 1002, memory 1004, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0153] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0154] The processor can access the information and application programs stored in the memory via the transmission device to execute the steps described in the above embodiments.

[0155] Those skilled in the art will understand that Figure 8 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 8 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 8 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 8 The different configurations shown.

[0156] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0157] Example 4

[0158] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the signal coverage simulation method provided in Embodiment 1.

[0159] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0160] This application also provides a computer program product that, when executed on a data processing device, is suitable for performing signal coverage simulation method steps.

[0161] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0162] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0163] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, 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 displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0164] 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.

[0165] Furthermore, 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0166] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0167] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A signal coverage simulation method, characterized in that, include: The simulation region is spatially divided into sub-blocks to obtain a set of sub-blocks. The simulation region includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks. Based on the antenna information of multiple transmitting antennas, a first ray tracing calculation is performed on the set of sub-blocks to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block; At least one sub-block in the sub-block set is subdivided according to the first signal intensity distribution matrix to obtain a target sub-block set, wherein the target sub-block set includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks; Based on the antenna information of the multiple transmitting antennas, a second ray tracing calculation is performed on the target sub-block set to obtain a second signal intensity distribution matrix. The second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and the subdivided sub-blocks, respectively. The accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation. The signal coverage simulation results for the simulation area are determined based on the second signal strength distribution matrix.

2. The method according to claim 1, characterized in that, At least one sub-block in the sub-block set is further subdivided according to the first signal intensity distribution matrix to obtain a target sub-block set, including: The signal intensity gradient value of each sub-block is determined based on the first signal intensity distribution matrix; Based on the antenna information of the multiple transmitting antennas and the position information of each sub-block, the calculation accuracy level of each sub-block is determined; Based on the calculation accuracy level and the signal strength gradient value of each sub-block, at least one sub-block in the sub-block set is subdivided to obtain the target sub-block set.

3. The method according to claim 2, characterized in that, Determining the signal intensity gradient value of each sub-block based on the first signal intensity distribution matrix includes: For each sub-block in the set of sub-blocks, the first signal strength value of the sub-block and the first signal strength values ​​of the adjacent sub-blocks of the sub-block are determined from the first signal strength distribution matrix; Differential calculation is used to determine the signal strength gradient value of the sub-block based on the first signal strength value of the sub-block and the first signal strength value of the adjacent sub-blocks.

4. The method according to claim 2, characterized in that, Based on the antenna information of the multiple transmitting antennas and the position information of each sub-block, the calculation accuracy level of each sub-block is determined, including: For each sub-block in the set of sub-blocks, the distance from the sub-block to the nearest transmitting antenna is determined based on the antenna information of the plurality of transmitting antennas and the position information of the sub-block; The priority of a sub-block is determined based on its distance to the nearest transmitting antenna, wherein the priority is negatively correlated with the distance. If the priority is lower than the priority threshold, the calculation accuracy level of the sub-block is determined to be the lowest calculation accuracy level; When the priority is higher than or equal to the priority threshold, the ideal maximum signal strength corresponding to the sub-block is determined based on the antenna information of the plurality of transmitting antennas and the position information of the sub-block; The calculation accuracy level of the sub-block is determined based on the ideal maximum signal strength.

5. The method according to claim 2, characterized in that, Based on the calculation accuracy level and the signal strength gradient values ​​of each sub-block, at least one sub-block in the sub-block set is further subdivided to obtain the target sub-block set, including: For each sub-block in the set of sub-blocks, the subdivision level threshold of the sub-block is determined according to the calculation accuracy level; If the current subdivision level of the sub-block is less than the subdivision level threshold and the signal strength gradient value of the sub-block is greater than the preset gradient value, the sub-block is subdivided into multiple sub-blocks to obtain an updated set of sub-blocks, and the current subdivision level of the sub-block is updated. Determine the signal intensity gradient value of the sub-block in the updated sub-block set, and repeatedly subdivide at least one sub-block in the updated sub-block set according to the signal intensity gradient value corresponding to the sub-block and the subdivision level threshold of the sub-block to which the sub-block belongs, until there are no more subdivisible sub-blocks, thus obtaining the target sub-block set.

6. The method according to claim 1, characterized in that, Before performing a first ray tracing calculation on the sub-block set based on antenna information from multiple transmitting antennas to obtain a first signal intensity distribution matrix, the method further includes: The number of working processes is determined based on the total number of antennas of the plurality of transmitting antennas; Create a parallel computing process pool based on the number of working processes; The plurality of transmitting antennas are divided into a plurality of antenna subsets, and the plurality of antenna subsets are assigned to a plurality of working processes in the parallel computing process pool; Based on the antenna information of multiple transmitting antennas, a first ray tracing calculation is performed on the sub-block set to obtain a first signal intensity distribution matrix, including: Based on the antenna information of the antenna subset, the multiple working processes perform the first ray tracing calculation on the sub-block set in parallel to obtain the third signal intensity distribution matrix corresponding to each transmitting antenna; The first signal strength distribution matrix is ​​determined based on the third signal strength distribution matrix corresponding to each transmitting antenna.

7. The method according to claim 6, characterized in that, After determining the signal coverage simulation results of the simulation area based on the second signal intensity distribution matrix, the method further includes: When there are changes in the transmitting antennas within the simulation area, determine the percentage of transmitting antennas that have changed within the simulation area; When the number ratio is less than or equal to a preset ratio, the updated first signal strength distribution matrix is ​​determined based on the third signal strength distribution matrix corresponding to the multiple transmitting antennas and the antenna information of the changed transmitting antennas. The new signal coverage simulation results for the simulation area are determined based on the updated first signal strength distribution matrix.

8. A signal coverage simulation device, characterized in that, include: The first processing module is used to spatially divide the simulation area into sub-blocks to obtain a set of sub-blocks. The simulation area includes multiple transmitting antennas for transmitting signals, and the set of sub-blocks includes multiple sub-blocks. The first calculation module is used to perform a first ray tracing calculation on the set of sub-blocks based on the antenna information of multiple transmitting antennas to obtain a first signal intensity distribution matrix, wherein the first signal intensity distribution matrix includes the first signal intensity value of each sub-block; The second processing module is used to subdivide at least one sub-block in the sub-block set according to the first signal intensity distribution matrix to obtain a target sub-block set, wherein the target sub-block set includes unsubdivided sub-blocks and multiple subdivided sub-blocks obtained after subdividing the sub-blocks. The second calculation module is used to perform a second ray tracing calculation on the target sub-block set based on the antenna information of the multiple transmitting antennas to obtain a second signal intensity distribution matrix. The second signal intensity distribution matrix includes the second signal intensity values ​​corresponding to the unsubdivided sub-blocks and the subdivided sub-blocks, respectively. The accuracy of the second ray tracing calculation is higher than that of the first ray tracing calculation. The first determining module is used to determine the signal coverage simulation result of the simulation area based on the second signal strength distribution matrix.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the computer-readable storage medium is located to perform the signal coverage simulation method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, executes the signal coverage simulation method according to any one of claims 1 to 7.

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