Measured Correction Method for Radio Wave Propagation Driven by Hybrid Data Model

Abstract

The present invention relates to the field of urban radio wave propagation prediction, and specifically proposes a method for correcting measured radio wave propagation by hybrid driving of data models. This method performs environmental modeling on the area to be calculated, uses the ray tracing algorithm to perform simulation calculations on multiple receiving points, divides the receiving points into a direct wave group and a non-direct wave group according to the characteristics of multipath types, and collects measured power values. Then, according to different grouping strategies, the error values of the measured power values of the correction group and the verification group are calculated respectively, and the inverse distance weighted interpolation method is used to correct the simulation values of the verification group and all receiving points, thereby improving the accuracy of radio wave propagation simulation calculations. The method of the present invention can effectively improve the accuracy of radio wave propagation simulation calculations and provide more reliable technical support for the design, optimization, and evaluation of wireless communication systems.

Description

Technical Field

[0001] The present invention relates to the field of urban radio wave propagation prediction, and particularly to a method for correcting measured radio wave propagation by hybrid driving of data models. Background Art

[0002] Radio wave propagation is the basis of wireless communication, broadcasting, radar and other systems. The characteristics of radio wave propagation directly affect the performance and effect of these systems. Therefore, it is very important to accurately predict and analyze radio wave propagation.

[0003] However, when radio waves propagate in the troposphere, they will exhibit different propagation mechanisms such as reflection, refraction, diffraction, transmission and scattering, and have great randomness. Therefore, it is very difficult to predict the radio wave propagation characteristics in complex environments.

[0004] However, for engineering needs, many radio wave propagation prediction models have been established. These models can be mainly divided into two categories: statistical models and deterministic models.

[0005] The statistical model is a method for predicting the characteristics of radio wave propagation based on a large amount of measured data or probability distributions. The advantage of the statistical model is that it can adapt to complex and random radio wave propagation environments, use a large amount of measured data to improve the accuracy and adaptability of prediction, and is quick and convenient to apply. However, it cannot accurately predict a specific propagation environment, especially cannot reflect the influence of specific terrain and buildings on the propagation path, and the prediction accuracy is low when applied in urban environments.

[0006] The ray tracing algorithm is a deterministic model that uses electromagnetic wave or optical ray theory to analyze and predict radio wave propagation. The deterministic model represented by the ray tracing algorithm combines with a three-dimensional urban map to accurately calculate the radio wave propagation multipath, and the algorithm itself has high accuracy. However, its algorithm has a huge amount of calculation. In order to balance calculation accuracy and efficiency, the terrain and ground object models are usually simplified. Therefore, there are problems such as idealization, simplification, and neglect, and a large amount of theoretical knowledge and professional skills are required. There may be problems such as difficult solution, error accumulation, and sensitivity analysis, resulting in differences between the terrain and ground object models used in the calculation and the real environment, which will in turn affect the prediction accuracy of the model to a certain extent.

[0007] It can be seen that the prediction accuracy is an important indicator for measuring the propagation model, which directly affects the application effects of radio network optimization, interference suppression, etc. Therefore, it is urgent to propose a method for correcting measured radio wave propagation to further improve the prediction accuracy of the radio wave propagation model of the ray tracing algorithm. Summary of the Invention

[0008] The present invention provides a method for correcting measured radio wave propagation by hybrid driving of data models, which solves the problems such as low prediction simulation accuracy of the radio wave propagation model of the ray tracing algorithm caused by the difference between the terrain and ground object model and the real environment, and the significant increase in the calculation amount brought by the overly complex terrain and ground object model.

[0009] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0010] A method for correcting measured radio wave propagation by hybrid driving of data models, comprising the following steps:

[0011] Perform environmental modeling on the area to be calculated;

[0012] Use the ray tracing algorithm to perform simulation calculations on multiple receiving points in the area to be calculated, and the obtained simulation values include simulation power values and multipath type characteristics;

[0013] According to whether the multipath type characteristics include direct waves, divide the multiple receiving points into a direct wave group and a non-direct wave group, and respectively select several measured points within the direct wave group and the non-direct wave group, and collect the measured power values of the measured points;

[0014] Respectively divide the several measured power values of the direct wave group and the non-direct wave group into their respective correction groups and verification groups; based on different grouping strategies, divide different correction groups and verification groups multiple times;

[0015] Based on the measured power values, calculate the error values of the simulation power values of the correction group and the verification group respectively;

[0016] Based on the error values of the simulation power values of the correction group, correct the simulation power values of the verification group to obtain the corrected simulation power values of the verification group;

[0017] Calculate the mean absolute error between the simulation power values and the corrected simulation power values of the verification group respectively under different grouping strategies, and select the grouping strategy with the best error improvement effect;

[0018] Based on the grouping strategy with the best error improvement effect, correct the simulation power values of all receiving points in the area to be calculated to obtain the corrected simulation power values of all receiving points in the area to be calculated.

[0019] Further, respectively select several measured points within the direct wave group and the non-direct wave group, and collect the measured power values of the measured points, including:

[0020] Several measured points are evenly distributed within the direct wave group and the non-direct wave group;

[0021] The acquisition time of each measured point is not less than 1 minute;

[0022] For the multiple measured data collected at each measured point, the median value is taken as the measured power value of that measured point.

[0023] Furthermore, the inverse distance weighted interpolation method is used to calculate the correction amount of the verification group, and the simulation value of the receiving point in the verification group is corrected by the correction amount to obtain the corrected simulation power value of the receiving point in the verification group.

[0024] Furthermore, based on the grouping strategy with the best error improvement effect, the error value of the corrected group simulation power value is obtained, and the inverse distance weighted interpolation method is used to correct the simulation power values of all receiving points in the area to be calculated, so as to obtain the corrected simulation power values of all receiving points in the area to be calculated.

[0025] On the other hand, the present invention provides an electronic device for measured correction of radio wave propagation driven by a hybrid data model, including:

[0026] At least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor can execute the above control method by invoking the program instructions.

[0027] On the other hand, the present invention provides a storage medium for measured correction of radio wave propagation driven by a hybrid data model, and the storage medium includes a stored program, and when the program is executed by a processor, the above control method is implemented.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0029] Under the condition that the accuracy of the terrain and ground object model used in the ray tracing algorithm is limited, the method of the present invention corrects the simulation value by the measured value, which can effectively improve the accuracy of radio wave propagation simulation calculation and provide more reliable technical support for the design, optimization and evaluation of wireless communication systems.

[0030] In the method of the present invention, the inverse distance weighted interpolation method is an interpolation method that takes into account the spatial distribution characteristics. It determines the weight factor according to the distance between the receiving point and the measured point, so that the measured points closer to the receiving point have a greater influence on the correction amount of the receiving point, while the measured points farther away have a smaller influence on the correction amount of the receiving point, thus better reflecting the spatial variation law of radio wave propagation.

[0031] The method of the present invention tries different grouping strategies and selects the grouping strategy with the best error improvement effect, which can more accurately introduce the simulation error value of the corrected group measured points into the radio wave propagation characteristics at different positions in the area to be calculated, thereby improving the correction effect on the simulation values of all receiving points, reducing errors and improving simulation accuracy.

[0032] Of course, it is not necessary for each technical solution of the present invention to achieve all the above advantages at the same time. Brief Description of the Drawings

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings of embodiments can also be obtained based on these drawings.

[0034] Figure 1 is the flowchart of the method of Embodiment 1 of the present invention;

[0035] Figure 2 is the schematic diagram of the test scenario of Embodiment 2 of the present invention;

[0036] Figure 3 is the schematic diagram of the distribution of the emission source and the measured points of Embodiment 2 of the present invention;

[0037] Figure 4 is the schematic diagram of the comparison of the measured values, simulation values and corrected values of the measured points of the verification group in Embodiment 2 of the present invention;

[0038] Figure 5 is the schematic diagram of the physical structure of the electronic device provided in Embodiment 3 of the present invention.

[0039] In the figure, 301 - processor, 302 - communication interface, 303 - memory, 304 - bus. Detailed Embodiments

[0040] The following further describes the present invention in detail in conjunction with the drawings through specific embodiments. Similar elements in different embodiments are labeled with related similar element numbers. In the following embodiments, many details are described to make the present application better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification to avoid the core part of the present application being overwhelmed by excessive description. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0041] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0042] The serial numbers assigned to the components in this document, such as "S1", "S2", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0043] Embodiment 1:

[0044] See also Figure 1 This embodiment discloses a method for correcting radio wave propagation measurement driven by a data model hybrid, which specifically includes the following steps:

[0045] S1. Perform environmental modeling on the area to be calculated.

[0046] Environmental modeling is performed on the area where radio wave propagation calculations are to be performed, and a three-dimensional model of terrain and objects for simulation calculations is obtained based on appropriate simplification of building, terrain and vegetation data.

[0047] S2. Use a ray tracing algorithm to complete the calculation of simulation values ​​of N receiving points, where the simulation values ​​include simulation power values ​​and multipath type characteristics.

[0048] According to the location of the radio wave source, the transmission power, the transmission antenna gain, the receiving point coordinates and the model dielectric constant and other parameters, the ray tracing algorithm is used to complete the simulation calculation of the radio wave propagation at N receiving points, and the simulation power values ​​S1, S2, ... S of the N receiving points in the intended calculation area are obtained. N , and the multipath type characteristics of each receiving point are obtained. The multipath type characteristics include direct waves, first-order reflected waves, first-order diffraction waves, and second-order ray waves formed by the combination of reflection and diffraction.

[0049] S3. According to whether the multipath type characteristics include a direct wave, the N receiving points are divided into a direct wave group and an indirect wave group; and the measured power values ​​of multiple measured points in the direct wave group and the indirect wave group are respectively collected.

[0050] According to whether the multipath type characteristics reaching the receiving point include the direct wave, the N receiving points are divided into a direct wave group R1 and a non-direct wave group R2. Select N1 receiving points as the measured points within the direct wave group R1, and collect measured data for the N1 measured points; similarly, select N2 receiving points as the measured points within the non-direct wave group R2, and collect measured data for the N2 measured points.

[0051] When collecting measured data, the following points need to be noted: First, the positions of the selected measured points should be relatively evenly distributed within the direct wave group R1 and the non-direct wave group R2; Second, the collection time for each measured point is not less than 1 minute. Third, for the multiple measured data collected for each measured point, take the median as the measured power value of this measured point.

[0052] S4. Within the direct wave group R1 and the non-direct wave group R2, divide the measured power values into two groups respectively. The first group is used for measured correction and is called the correction group, and the second group is used for verifying the correction effect and is called the verification group.

[0053] Divide the measured power values of the N1 measured points within the direct wave group R1 into two groups: The first group is the correction group for measured correction, and the measured power values are T111, T112,..., T11 N11 ; The corresponding simulation power values are S111, S112,... S11 N11 . The second group is the verification group for verifying the correction effect, and the measured power values are T121, T122,..., T11 N12 ; The corresponding simulation power values are S121, S122,... S12 N12 .

[0054] Similarly, divide the measured power values of the N2 measured points within the non-direct wave group R2 into two groups: The first group is the correction group for measured correction, and the measured power values are T211, T212,..., T21 N21 ; The corresponding simulation power values are S211, S212,... S21 N21 . The second group is the verification group for verifying the correction effect, and the measured power values are T221, T222,..., T21 N22 ; The corresponding simulation power values are S221, S222,... S22 N22 .

[0055] When grouping the measured power values into the correction group and the verification group, it should be ensured as much as possible that the measured points of the correction group and the verification group are evenly distributed within the area to be calculated, so that the simulation error values of the measured points in the correction group can better reflect the radio wave propagation characteristics at different positions within the area to be calculated, thereby improving the correction effect on the simulation values of the verification group and all receiving points and reducing errors.

[0056] When grouping the measured power values into a correction group and a verification group, different grouping strategies will have a certain impact on the final correction effect. Therefore, in this embodiment, different grouping strategies are adopted to group the measured power values of the measured points R1 and R2 into a correction group and a verification group multiple times.

[0057] S5. Calculate the error values of the simulation power values of the correction group and the verification group for the direct wave group R1 and the non-direct wave group R2 respectively.

[0058] Complete the calculation of the error values according to Equations (1)-(4):

[0059]

[0060] Where:

[0061] △11 i : The error value of the simulation power value of the i-th receiving point in the R1 correction group;

[0062] △12 i : The error value of the simulation power value of the i-th receiving point in the R1 verification group;

[0063] △21 i : The error value of the simulation power value of the i-th receiving point in the R2 correction group;

[0064] △22 i : The error value of the simulation power value of the i-th receiving point in the R2 verification group.

[0065] S6. Correct the simulation power values of the receiving points in the verification group to obtain the corrected simulation power values of the receiving points in the verification group.

[0066] Based on the error values of the receiving points in the correction group, use the inverse distance weighted interpolation method (IDW) to calculate the correction amount of the verification group, and correct the simulation values of the receiving points in the verification group to obtain the corrected simulation power values of the receiving points in the verification group, as shown in Equations (5)-(6):

[0067]

[0068] Where:

[0069] C12 i : The corrected simulation power value of the i-th receiving point in the R1 verification group;

[0070] C22 i : The corrected simulation power value of the i-th receiving point in the R2 verification group;

[0071] mod12 i : The simulation power correction amount of the i-th receiving point in the R1 verification group;

[0072] mod22i : The simulation power correction amount of the i-th receiving point in the R2 verification group.

[0073] Calculate mod12 using the inverse distance weighted interpolation method i and mod22 i , as shown in Equations (7)-(10):

[0074] In the formula:

[0075] w12 ij : The weight factor when the error value of the j-th receiving point in the R1 correction group is used to correct the simulation value of the i-th receiving point in the R1 verification group;

[0076] d12 ij p : The p-th power of the distance from the j-th receiving point in the R1 correction group to the i-th receiving point in the R1 verification group, and p is usually taken as 2 for radio wave propagation correction.

[0077] w22 ij : The weight factor when the error value of the j-th receiving point in the R2 correction group is used to correct the simulation value of the i-th receiving point in the R2 verification group;

[0078] d22 ij p : The p-th power of the distance from the j-th receiving point in the R2 correction group to the i-th receiving point in the R1 verification group, and p is usually taken as 2 for radio wave propagation correction.

[0079] S7. For the multiple different strategy groupings performed in S4, calculate the mean absolute error of the simulation values of the receiving points in the verification group before and after correction for each grouping strategy, and select the grouping strategy with the best error improvement effect.

[0080] Taking the R1 verification group as an example, the calculation of the mean absolute error of the simulation values of the receiving points in the verification group before correction is shown in Equation (11), the calculation of the mean absolute error of the simulation values of the receiving points in the verification group after correction is shown in Equation (12), and the improvement value of the error of the simulation values of the receiving points in the verification group before and after correction is shown in Equation (13). The calculation method of the mean absolute error of the simulation values of the receiving points in the R2 verification group before and after correction is the same as that of the R1 verification group.

[0081]

[0082] In the formula:

[0083] MAE12: The mean absolute error of the simulation values of the receiving points in the R1 verification group before correction;

[0084] MAE12': The mean absolute error of the simulation values of the receiving points in the R1 verification group after correction;

[0085] △MAE12 : The improvement value of the error before and after the correction of the simulation value at the receiving point of the R1 verification group.

[0086] S8. Correct the simulation power values of all receiving points within the area to be calculated to obtain the corrected values of the simulation power values of all receiving points.

[0087] Based on the error value of the simulation power value of the optimal correction group receiving point given by S7, use the inverse distance weighted interpolation method to correct the simulation received power values S1, S2,..., S of N receiving points within the calculation area N to obtain the corresponding corrected simulation power values C1, C2,..., C N , as shown in Equation (14).

[0088]

[0089] If the receiving point is within the direct wave group, the calculation method of mod i is the same as that of mod12 i . If the receiving point is within the non-direct wave group, the calculation method of mod i is the same as that of mod22 i .

[0090] Example 2:

[0091] To verify the measured correction method of radio wave propagation with hybrid drive of data models mentioned in the present invention, this example conducts actual tests on the family area of the South Campus of Xidian University. The test scenario is as Figure 2 shown, and the distribution of the emission source and measurement field points is as Figure 3 shown. The emission source frequency is 2503 MHz. Among them, there are 32 measured points of direct waves and 56 measured points of non-direct waves. One-third of the measured points are selected for correction in the measured points of direct waves and non-direct waves respectively, and two-thirds of the measured points are used to verify the correction effect. The optimal correction group and verification group are selected, and it is obtained that the average absolute error before correction is 8.2 dB, the average absolute error after correction is 5.8 dB, and the accuracy is improved by 2.4 dB. The comparison of the measured power values, simulation power values and simulation power corrected values of the receiving points of the direct wave and non-direct wave verification groups is as Figure 4 shown.

[0092] Example 3:

[0093] This example relates to an electronic device for the measured correction of radio wave propagation with hybrid drive of data models. Figure 5A schematic diagram of the physical structure of the electronic device provided by the embodiment of the present invention. The electronic device may include: a processor 301, a communications interface 302, a memory 303, and a bus 304. Among them, the processor 301, the communications interface 302, and the memory 303 complete communication with each other through the bus 304. The processor 301 can call a computer program stored on the memory 303 and executable on the processor 301 to execute a method for correcting measured radio wave propagation driven by a hybrid data model provided in the above-mentioned Embodiment 1. For example, it includes: performing environmental modeling on the area to be calculated; using a ray tracing algorithm to perform simulation calculations on multiple receiving points in the area to be calculated, and the obtained simulation values include simulation power values and multipath type characteristics; according to whether the multipath type characteristics include direct waves, dividing the multiple receiving points into a direct wave group and a non-direct wave group, respectively selecting several measured points within the direct wave group and the non-direct wave group, and collecting the measured power values of the measured points; dividing the several measured power values of the direct wave group and the non-direct wave group into their respective correction groups and verification groups; based on different grouping strategies, dividing different correction groups and verification groups multiple times; based on the measured power values, respectively calculating the error values of the simulation power values of the correction group and the verification group; based on the error values of the simulation power values of the correction group, correcting the simulation power values of the verification group to obtain the corrected simulation power values of the verification group; respectively calculating the mean absolute error between the simulation power values and the corrected simulation power values of the verification group under different grouping strategies, and selecting the grouping strategy with the best error improvement effect; based on the grouping strategy with the best error improvement effect, correcting the simulation power values of all receiving points in the area to be calculated to obtain the corrected simulation power values of all receiving points in the area to be calculated.

[0094] In addition, when the logical instructions in the above-mentioned memory 303 can be implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present invention, in essence, or the part that contributes to the prior art, or a part of this 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 for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, RandomAccess Memory), a magnetic disk, or an optical disc that can store program codes.

[0095] The above uses specific examples to elaborate on the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the art of the present invention, based on the idea of the present invention, several simple deductions, deformations or substitutions can also be made.

Claims

1. A method for correcting radio wave propagation measurements driven by a hybrid data model, characterized in that: It includes the following steps: Perform environmental modeling on the area to be calculated; Use the ray tracing algorithm to perform simulation calculations on multiple receiving points in the area to be calculated, and the obtained simulation values include simulation power values and multipath type characteristics; According to whether the multipath type characteristics include direct waves, divide the multiple receiving points into a direct wave group and a non-direct wave group, and select several measured points within the direct wave group and the non-direct wave group respectively to collect the measured power values of the measured points; Divide the several measured power values of the direct wave group and the non-direct wave group into their respective correction groups and verification groups respectively; Based on different grouping strategies, divide different correction groups and verification groups multiple times; Based on the measured power values, calculate the error values of the simulation power values of the correction group and the verification group respectively; Based on the error values of the simulation power values of the correction group, correct the simulation power values of the verification group to obtain the corrected simulation power values of the verification group; Calculate the mean absolute error between the simulation power values and the corrected simulation power values of the verification group under different grouping strategies respectively, and select the grouping strategy with the best error improvement effect; Based on the grouping strategy with the best error improvement effect, correct the simulation power values of all receiving points in the area to be calculated to obtain the corrected simulation power values of all receiving points in the area to be calculated.

2. The method for actual measurement correction of radio wave propagation driven by a data model hybrid as claimed in claim 1, wherein Select several measured points within the direct wave group and the non-direct wave group respectively to collect the measured power values of the measured points, including: The several measured points are evenly distributed within the direct wave group and the non-direct wave group; The acquisition time for each measured point is not less than 1 minute; For the multiple measured data collected for each measured point, take the median as the measured power value of the measured point.

3. The method for correcting measured radio wave propagation by hybrid driving of a data model according to claim 1, characterized in that Use the inverse distance weighted interpolation method to calculate the correction amount of the verification group, and correct the simulation values of the receiving points in the verification group through the correction amount to obtain the corrected simulation power values of the receiving points in the verification group.

4. The method for correcting measured radio wave propagation by hybrid driving of the data model according to claim 1, characterized in that Based on the grouping strategy with the best error improvement effect, obtain the error values of the simulation power values of its correction group, and use the inverse distance weighted interpolation method to correct the simulation power values of all receiving points in the area to be calculated to obtain the corrected simulation power values of all receiving points in the area to be calculated.

5. An electronic device for actual measurement correction of radio wave propagation driven by a hybrid data model, characterized in that It includes: At least one processor; And at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor can execute the correction method described in any one of claims 1 to 4 by invoking the program instructions.

6. A storage medium for the measured correction of radio wave propagation driven by a hybrid data model, characterized in that: The storage medium includes the stored program, and when the program is executed by the processor, it implements the correction method described in any one of claims 1 to 4.

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