Radio wave propagation estimation system, parameter setting processing apparatus, and method

Abstract

An object of the present disclosure is to provide a method of automatically setting an input parameter capable of suppressing an increase in calculation time at the time of ray trace calculation.SOLUTION: A parameter setting processing device 10 includes a determination part 15 for evaluating a contribution degree to one or a plurality of objective functions of one or a plurality of parameters contributing to propagation path calculation of a radio wave emitted from a transmission part and reaching a reception part, and a GA calculation part 13 for setting the one or the plurality of parameters using a genetic algorithm on the basis of an evaluation result of the determination part 15.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a radio wave propagation estimation technique in wireless communication. [Background technology]

[0002] Ray-tracing has long been known as a method for analyzing radio wave propagation. Calculations based on ray-tracing (hereinafter referred to as "ray-tracing calculations") use geometrical optics theory (geometrical optics approximation) to treat radio waves traveling from a transmitting point to a receiving point as light (rays), and calculate the propagation path by tracing these rays. Specifically, the calculation takes into account structures such as buildings that obstruct the propagation of radio waves from the transmitting point to the receiving point, and calculates propagation loss (received power), radio wave delay time, direction of emission, direction of arrival, etc.

[0003] Ray-tracing calculations involve input parameters that affect the results of radio wave propagation estimations. Specific examples of such input parameters include the materials of the surrounding environment and the emission interval. Conventionally, the materials of surrounding buildings and fixtures are often set with frequency-dependent conductivity and frequency-independent relative permittivity, based on ITU-R P.2040 (International Telecommunication Union—Radiocommunication Sector: Effects of building materials and structures on radiowave propagation above about 100 MHz).

[0004] Buildings and fixtures are made of various materials, such as reinforced concrete, glass, and wood. To reflect these materials, it is necessary to create a 3D model that closely resembles the actual analysis environment, which requires advanced modeling techniques. When using this method, the cost of creating the model becomes extremely high as the analysis environment becomes larger. On the other hand, a model with accuracy close to the actual analysis environment is not necessarily required. For example, Non-Patent Document 1 attempts to improve accuracy by setting original materials as the materials of the surrounding environment. However, such material parameter tuning requires the user to set optimal parameters depending on the situation, which requires advanced knowledge and skill.

[0005] It is also generally known that the interaction mechanisms (reflection, diffraction, transmission) between rays and structures also affect the estimation accuracy of ray tracing calculations. For example, Non-Patent Document 2 considers a method for improving the estimation accuracy of ray tracing calculations, focusing on the setting of interaction mechanisms as an example of input parameters for ray tracing calculations.

[0006] Here, increasing the setting value of the interaction mechanism increases the search range of the ray to be traced, improving the estimation accuracy of the ray tracing calculation. Therefore, the setting value of the interaction mechanism is generally set to the maximum. However, widening the ray search range increases the calculation time exponentially. On the other hand, not all interaction mechanisms necessarily have a significant effect on the calculation results of the ray tracing calculation. [Prior art documents] [Non-patent literature]

[0007] [Non-Patent Document 1] AW Mbugua, Y. Chen, L. Raschkowski, L. Thiele, S. Jaeckel and W. Fan, “Review on ray tracing channel simulation accuracy in sub-6 GHz outdoor deployment scenarios,” IEEE Open Journal of AP, vol. 2, pp. 22-37, 2021. [Non-patent document 2] D. He, B. Ai, K. Guan, L. Wang, Z. Zhong, and T. Kurner, “The design and applications of high-performance ray-tracing simulation platform for 5G and beyond wireless communications: A tutorial,” IEEE Commun. Surveys Tuts., vol. 21, no. 1, pp. 10-27, 2019. [Non-patent document 3] Tetsuro Imai, Ray Tracing Method for Radio Wave Propagation Analysis: From Fundamentals to Applications, Corona Publishing, 2016 [Non-patent document 4] Z. Yun and MF Iskander, “Ray tracing for radio propagation modeling: Principles and applications”, IEEE Access, vol. 3, pp. 1089-1100, 2015. Summary of the Invention [Problem to be solved by the invention]

[0008] In order to solve the above problem, an object of the present disclosure is to provide a method for automatically setting input parameters that can suppress an increase in calculation time during ray tracing calculation. [Means for solving the problem]

[0009] In order to achieve the above object, the radio wave propagation estimation system, parameter setting processing device, and method employ a technique in which the contribution of parameters that contribute to radio wave propagation path calculation to an objective function is evaluated, and the parameters are set using a genetic algorithm based on the evaluation results.

[0010] Specifically, the parameter setting processing device of the present disclosure includes: a determination unit that evaluates the contribution of one or more parameters that contribute to calculation of a propagation path of a radio wave emitted from a transmitter and arriving at a receiver to one or more objective functions; and a processing unit that sets the one or more parameters using a genetic algorithm based on the evaluation result of the determining unit.

[0011] The method further includes a multiple regression analysis unit that performs multiple regression analysis on the relationship between the one or more response variables and the one or more parameters, The determination unit may use a processing result of the multiple regression analysis performed by the multiple regression analysis unit as the degree of contribution.

[0012] The determination unit evaluates the degree of contribution by comparing the degree of contribution with a predetermined threshold, and outputs a parameter of which the degree of contribution is equal to or less than the predetermined threshold as a setting value, among the one or more parameters; The processing unit may set a parameter that exceeds the predetermined threshold.

[0013] Furthermore, the one or more objective functions are at least one of a propagation loss, a delay spread, and an angle spread; The one or more parameters may be at least one of parameters related to material, emission interval, reflection, diffraction, and transmission.

[0014] The plurality of objective functions may include a calculation time for calculating the propagation path of the radio wave.

[0015] Specifically, the radio wave propagation estimation system of the present disclosure includes: the parameter setting processing device; The radio wave receiving device includes a propagation path calculation device that calculates a propagation path of a radio wave emitted from the transmitting unit and arriving at the receiving unit using one or more parameters set by the processing unit.

[0016] Specifically, the parameter setting processing method of the present disclosure includes: Evaluating the contribution of one or more parameters that contribute to calculation of a propagation path of a radio wave emitted from a transmitter and arriving at a receiver to one or more objective functions; Based on the evaluation result, the one or more parameters are set using a genetic algorithm.

[0017] The device of the present disclosure can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided via a network. The program of the present disclosure is a program for causing a computer to realize each function of the device according to the present disclosure, and a program for causing a computer to execute each procedure of the method executed by the device according to the present disclosure.

[0018] The above disclosures can be combined as much as possible. [Effects of the Invention]

[0019] According to the present disclosure, it is possible to automatically set input parameters that can suppress an increase in calculation time during ray tracing calculation. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a block diagram showing a configuration of a radio wave propagation estimation system according to an embodiment of the present disclosure. [Figure 2] Figure 1 shows an overview of the ray-launching method. [Figure 3] FIG. 10 is a diagram showing a search range according to a radius at a reception point. [Figure 4] 10 is a graph showing the relationship between calculation time and estimation error. [Figure 5] 10 is a flowchart illustrating a process of a parameter setting processing device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the present disclosure is not limited to the embodiments shown below. These implementation examples are merely illustrative, and the present disclosure can be implemented in various forms with various modifications and improvements based on the knowledge of those skilled in the art. Note that components with the same reference numerals in this specification and drawings indicate the same components.

[0022] [Overview of the radio wave propagation estimation system] An overview of a radio wave propagation estimation system 100 according to an embodiment of the present disclosure will be described with reference to Fig. 1. The radio wave propagation estimation system 100 is a system that regards radio waves arriving from a transmitting point to a receiving point as light (rays) and calculates propagation paths by tracking the light based on geometrical optics theory (geometrical optics approximation). The radio wave propagation estimation system 100 includes a parameter setting processing device 10, a ray tracing calculation device 20, and an actual measurement data acquisition device 30.

[0023] The parameter setting processing device 10 calculates a combination of parameters that provides high accuracy in estimating propagation loss by setting input parameter values ​​for ray tracing.

[0024] The ray tracing calculation device 20 calculates the propagation path of light by a predetermined method of the ray tracing method using the input parameters set by the parameter setting processing device 10. The predetermined method will be described later. The ray tracing calculation device 20 functions as the "propagation path calculation device" in this disclosure.

[0025] The actual measurement data acquisition device 30 is configured to acquire data on the propagation path of light that is actually measured by a sensor or the like that is provided integrally or separately. The actual measurement data acquisition device 30 sends the acquired data on the propagation path of light (received power, direction of arrival, etc.) to the GA calculation unit 13. Note that the actual measurement data acquisition device 30 is not an essential component, and the parameter setting processing device 10 may be configured to directly acquire and store the actual measurement data without going through the actual measurement data acquisition device 30.

[0026] [Configuration of parameter setting processing device] 1, the parameter setting processing device 10 includes an objective function selection unit 11, a parameter selection unit 12, a GA calculation unit 13, a multiple regression analysis unit 14, a determination unit 15, and a parameter update unit 16. The GA calculation unit 13 functions as the "processing unit" in the present disclosure.

[0027] The objective function selection unit 11 is a functional unit for selecting objective functions for which parameters are to be set. Specifically, a user selects one or more objective functions and inputs the selected objective functions to the objective function selection unit 11 directly or via an input device provided outside the objective function selection unit 11. However, the objective function selection may be performed automatically by the objective function selection unit 11 depending on the situation. Note that the more objective functions are selected, the more accurate the estimation of the ray tracing calculation becomes, but the longer the calculation time required for parameter setting becomes. Therefore, the objective function may be selected taking into consideration the relationship between the objective function and the calculation time required for parameter setting, which is in such a trade-off relationship.

[0028] Here, the objective functions in the present disclosure include "propagation loss," "delay spread," "angular spread," and "calculation time for ray tracing calculation." In this embodiment, at least one of these may be selected as the objective function. Furthermore, of the above, propagation loss, delay spread, and angular spread relate to improving the estimation accuracy of ray tracing calculation, and at least one of these may be selected as the objective function.

[0029] Furthermore, the calculation time during ray tracing calculation is an evaluation index that is subject to parameter setting from the perspective of minimizing calculation time, separate from improving estimation accuracy. In this way, objective functions are divided into those that are set from the perspective of improving estimation accuracy and those that are set from the perspective of minimizing calculation time during ray tracing calculation. When performing ray tracing calculation, it is expected that multiple explanatory variables (parameters) that affect these objective functions will be input. For this reason, parameters can be set as a multi-objective optimization.

[0030] However, in this embodiment, priority is given to improving the estimation accuracy in the ray tracing calculation. Therefore, in this embodiment, the objective functions have a superiority / inferiority relationship, and the objective function from the perspective of minimizing the calculation time during ray tracing calculation is subordinate to the objective function from the perspective of improving the estimation accuracy. In other words, the calculation time as an objective function is given priority next to the objective function from the perspective of improving the estimation accuracy, and the calculation time does not necessarily have to be selected as the objective function.

[0031] The range of objective functions in the present disclosure is not limited to those listed above, but includes various functions that affect the estimation accuracy of ray tracing calculations and the calculation time required for ray tracing calculations.

[0032] The parameter selection unit 12 is a functional unit for selecting parameters to be used in the ray tracing calculation by the ray tracing calculation device 20. Specifically, the user selects one or more (N>0) parameters and inputs the selected parameters directly to the parameter selection unit 12 or via an input device provided outside the parameter selection unit 12. Here, since the output results of the ray tracing method depend on the input values, it is important to set parameters related to the propagation characteristics. Therefore, the user basically selects parameters that affect the propagation characteristics.

[0033] However, parameter selection may also be performed automatically by the parameter selection unit 12 depending on the situation. Note that the more parameters selected, the more accurate the estimation of the ray tracing calculation will be, but the longer the calculation time will be. Therefore, parameters may be selected taking into consideration the relationship between the number of parameters and the calculation time, which is in such a trade-off relationship.

[0034] Here, the parameters in this embodiment include, for example, parameters related to the material, emission interval, reflection, diffraction, and transmission. In particular, the material constants of conductivity and dielectric constant, the maximum number of reflections and diffractions, and the emission angle are examples of parameters. In this embodiment, at least one of these may be selected as a parameter. However, the scope of the present disclosure is not limited thereto, and various parameters in the surrounding environment between the transmission point and reception point of the ray may be selected.

[0035] The GA calculation unit 13 is a functional unit for setting parameters for an objective function using a genetic algorithm (GA). Generally, in a genetic algorithm, the calculation cost (computational volume) for setting parameters increases significantly as the number and range of parameters to be set increases. Genetic algorithms generally depend on initial values ​​and obtain solution candidates over a wide range, which may result in an optimal solution that does not match the actual environment or a local solution being output. The scope of the present disclosure is not limited to setting parameters using a genetic algorithm, and parameters may be set using other methods. In the present disclosure, the GA calculation unit 13 arbitrarily sets an initial search range for each selected parameter. Specifically, the GA calculation unit 13 may set the minimum or maximum value within a settable range as the initial search range for each selected parameter.

[0036] In this embodiment, each time a parameter is set by the genetic algorithm, the set parameter is sent to the ray tracing calculation device 20. The ray tracing calculation device 20 simulates the propagation path of a ray using the set parameter each time. That is, the ray tracing calculation device 20 calculates the propagation path of a radio wave that is emitted from a transmitter and arrives at a receiver using one or more parameters set by the GA calculation unit 13. The simulation result is input to the multiple regression analysis unit 14.

[0037] The multiple regression analysis unit 14 is a functional unit that calculates the contribution of optimization target parameters to the objective function from the simulation results from the ray tracing calculation device 20. Specifically, the multiple regression analysis unit 14 expresses the relationship between the objective variable and the explanatory variables (parameters) using a multiple regression equation based on the correlation between multiple parameters. In other words, the multiple regression analysis unit 14 performs multiple regression analysis on the relationship between one or more objective variables and one or more parameters. The calculation results by the multiple regression analysis unit 14 are output to the determination unit 15.

[0038] The determination unit 15 is a functional unit for quantitatively determining the degree of influence of each parameter on the objective function based on the calculation results by the multiple regression analysis unit 14. In other words, the determination unit 15 uses the processing results of the multiple regression analysis by the multiple regression analysis unit 14 as the degree of contribution to one or more objective functions, and evaluates the degree of contribution of one or more parameters that contribute to the calculation of the propagation path of the radio waves emitted from the transmitter and arriving at the receiver.

[0039] The determination unit 15 determines whether the contribution (t value) of each parameter to the objective function exceeds a predetermined threshold. That is, the determination unit 15 evaluates the degree of contribution by comparing the degree of contribution with a predetermined threshold.

[0040] Here, the t-value represents the magnitude of the influence that each parameter has on the target variable. It can be said that the greater the absolute value of the t-value, the greater the influence on the target variable. Therefore, the determination unit 15 outputs the calculation result by the previous GA calculation unit 13 as the final optimal value for the parameters whose absolute value of the t-value is below the threshold to the race calculation device 20. That is, the determination unit 15 outputs the parameters whose contribution degree among one or more parameters is below a predetermined threshold as the set value.

[0041] Alternatively, for the parameters determined by the determination unit 15 that the absolute value of the t-value is below the threshold, the search range may be set again as it is or reduced using the GA calculation unit 13. On the other hand, the determination unit 15 transmits information about the parameters whose absolute value of the t-value exceeds the threshold to the parameter update unit 16. The predetermined threshold can be arbitrarily set by the user, but generally, it can be determined that the influence on the objective function is small when the absolute value is 2 or less.

[0042] The parameter update unit 16 is a functional unit for updating the number of parameters based on the processing result of the determination unit 15 and giving an instruction to the GA calculation unit 13 to set the updated parameters under a predetermined condition. Specifically, the parameter update unit 16 excludes M (0 < M < N) parameters whose absolute value of the t-value is below the threshold, and selects the parameters whose absolute value of the t-value exceeds the threshold as the updated parameters. That is, the parameter update unit 16 updates the number of parameters to N = N - M. In addition, the parameter update unit 16 gives an instruction to the GA calculation unit 13 to set the updated parameters with a wider search range.

[0043] The GA calculation unit 13 that receives the instruction from the parameter update unit 16 enlarges the search range for the N = N - M parameters with a large influence on the objective function and searches and sets them by the genetic algorithm. That is, the GA calculation unit 13 re-sets one or more parameters that exceed a predetermined threshold using the genetic algorithm based on the evaluation result of the determination unit 15.

[0044] The larger the search range, the longer the calculation time, so it depends on the calculation environment. For example, even if the search range is wide, it is possible to narrow it down to a certain extent based on the material constants of the buildings and indoor fixtures in the environment to be estimated. Furthermore, the search range for the maximum number of reflections and diffractions and the emission angle can be determined based on previous knowledge and the size of the environment to be estimated (outdoors, indoors, receiving distance, etc.).

[0045] In this way, in this embodiment, the search range for parameters that have a large influence on the objective function is widened. On the other hand, parameters that have a small influence on the objective function are used as setting results in the ray tracing calculation, or are set with a narrower search range. In other words, in this embodiment, parameters are set in order starting from the parameter that contributed most to minimizing the error. In this way, by widely searching for parameters with a large influence, it is possible to find an optimal solution with a better parameter combination.

[0046] According to the radio wave propagation estimation system 100 of the present disclosure, it is possible to set input parameters to improve estimation accuracy while suppressing an increase in calculation time.

[0047] [About the ray tracing method] As described above, the ray tracing calculation device 20 calculates the propagation path of light by a predetermined method within the ray tracing method, using the input parameters set by the parameter setting processing device 10. Here, the ray tracing method as the calculation principle used by the ray tracing calculation device 20 will be described with reference to FIGS. 2 and 3.

[0048] There are two main types of ray tracing methods: (1) Imaging method: A method of determining the reflection point geometrically from the combination of transmitting and receiving points and reflecting surfaces. (2) Ray launching method: A method in which rays are launched discretely at a fixed angle from the transmitting point, and their trajectories are tracked to search for rays that reach the receiving point.

[0049] Here, a transmission point is an example of a "transmitter" in this disclosure, and various radio wave sources correspond to this. Also, a reception point is an example of a "receiving unit" in this disclosure, and various radio wave receiving devices correspond to this.

[0050] The imaging method can accurately determine the trajectory of each individual path from the transmitting point to the receiving point, resulting in higher accuracy, but at the expense of increased calculation time. On the other hand, the ray launching method, as shown in Figure 2, sets a fixed receiving area (receiving sphere) around the receiving point, and considers rays that arrive within that receiving area to have reached the receiving point. In this way, the ray launching method efficiently determines the path trajectory by narrowing the ray search range, resulting in lower accuracy but shorter calculation time. In particular, the ray launching method is expected to improve calculation speed when there are many receiving points compared to the imaging method.

[0051] As described above, the imaging method and the ray launching method have advantages and disadvantages, and therefore the ray tracing calculation may be performed based on either principle by the ray tracing calculation device 20. Whichever ray tracing method the ray tracing calculation device 20 employs, it is possible to improve the accuracy of the ray tracing calculation while suppressing an increase in calculation time.

[0052] For example, as shown in Fig. 3, when the angle between two adjacent i-th and (i+1)-th rays is defined as the launch interval Δθ and this Δθ is treated as a parameter, the ray tracing calculation device 20 may perform ray tracing calculation using the ray launching method. Note that Fig. 3 shows a state in which the transmitting point and the receiving point are separated by a distance r. For example, in Fig. 3, the i-th ray is not searched when the search range is the second or first radius. In contrast, the i+1-th ray is searched when the search range is any of the first to third radii.

[0053] However, the ray tracing method used by the ray tracing calculation unit 20 is not limited to the above. For example, a hybrid method may be used in which a ray launching method is used for the ray search range, and the trajectory of the ray path is ultimately determined by an imaging method.

[0054] [Effects of this disclosure] The effect of the configuration of the present disclosure will be described with reference to Fig. 4. This is a graph showing the relationship between the calculation time and the estimated error RMSE (Root Mean Squared Error) during ray tracing calculation.

[0055] Generally, the more rays searched in a ray tracing calculation, the higher the estimation accuracy of the ray tracing calculation, and the number of rays searched varies greatly depending on the set values ​​of the maximum number of reflections / diffraction and the output angle. Fig. 4 shows the results of an investigation in which the material constants of conductivity and relative permittivity are fixed, and the maximum number of reflections / diffraction and the output angle, which significantly contribute to the calculation time, are changed. Point A in Fig. 4 is the result of a ray tracing calculation performed using parameters set using the radio wave propagation estimation system 100 according to this embodiment.

[0056] The dashed line in Figure 4 indicates an error of 5 dB, and results with higher accuracy are shown below the line. As can be seen from the trend in Figure 4, when an estimation accuracy of 5 dB or less is required, the number of ray searches increases, resulting in an increase in calculation time.

[0057] On the other hand, point A requires the shortest calculation time among the results for which the estimation error is 5 dB or less. In other words, according to this embodiment, it is possible to suppress an increase in calculation time while satisfying accuracy requirements.

[0058] Although the above describes a case where parameters are set so that the error is 5 dB or less and the calculation time is minimized, the scope of the present disclosure is not limited to this. In the radio wave propagation estimation system 100, it is possible to set the extent to which parameters are set.

[0059] [Flowchart] Referring to FIG. 5, the processing flow of the parameter setting processing device 10 will be described.

[0060] In step S1, the GA calculation unit 13 uses a genetic algorithm to set a combination of parameters so that the objective function is minimized.

[0061] In step S2, the multiple regression analysis unit 14 performs multiple regression analysis on the simulation results from the rate trace calculation device 20 and expresses the influence of each parameter on the objective function.

[0062] In step S3, the determination unit 15 determines whether the contribution (t-value) of each parameter to the objective function exceeds a predetermined threshold.

[0063] In step S4, for the parameter whose absolute value of the t-value is less than or equal to the threshold, the determination unit 15 outputs the calculation result (the processing result of step S1) by the previous GA calculation unit 13 as the final optimal value to the rate trace calculation device 20\.

[0064] In step S5, the parameter update unit 16 excludes M (0 < M < N) parameters whose absolute value of the t-value is less than or equal to the threshold, and selects the parameters whose absolute value of the t-value exceeds the threshold as the updated parameters. That is, the parameter update unit 16 updates the number of parameters to N = N - M.

[0065] In step S6, the parameter update unit 16 determines whether the updated number of parameters N is 0. If it is determined that N is 0 (step S6: No), the parameter setting processing device 10 ends the processing.

[0066] On the other hand, if it is determined that N is not 0 (step S7: Yes), in step S7, the parameter update unit 16 instructs the GA calculation unit 13 to widen the search range and set the updated parameters. Upon receiving the instruction from the parameter update unit 16, the GA calculation unit 13 widens the search range for N=NM parameters that have a large influence on the objective function, and searches for and sets them using a genetic algorithm. The parameter setting processing device 10 repeats the above process until N becomes 0.

[0067] The parameter setting processing device 10, ray tracing calculation device 20, and measurement data acquisition device 30 of the present disclosure can also be realized by a computer and a program, and the program can be recorded on a recording medium or provided over a network. The program of the present disclosure is a program for causing a computer to realize each function of the parameter setting processing device 10, ray tracing calculation device 20, and measurement data acquisition device 30 according to the present disclosure, and is a program for causing a computer to execute each procedure of the methods executed by the parameter setting processing device 10, ray tracing calculation device 20, and measurement data acquisition device 30 according to the present disclosure. [Explanation of symbols]

[0068] 10: Parameter setting processing device 11: Objective function selection section 12: Parameter selection section 13:GA calculation part 14: Multiple regression analysis section 15: Judgment section 16: Parameter update section 20: Ray tracing calculation device 30: Measurement data acquisition device 100: Radio wave propagation estimation system

Claims

1. a determination unit that evaluates the contribution of one or more parameters that contribute to calculation of a propagation path of a radio wave emitted from a transmitter and arriving at a receiver to one or more objective functions; a processing unit that sets the one or more parameters using a genetic algorithm based on the evaluation result of the determination unit, Parameter setting processing device.

2. a multiple regression analysis unit that performs multiple regression analysis on the relationship between the one or more response variables and the one or more parameters, the determination unit uses a processing result of the multiple regression analysis performed by the multiple regression analysis unit as the degree of contribution. The parameter setting processing device according to claim 1 .

3. the determination unit evaluates the degree of contribution by comparing the degree of contribution with a predetermined threshold, and outputs a parameter of the one or more parameters whose degree of contribution is equal to or less than the predetermined threshold as a setting value; The processing unit sets a parameter that exceeds the predetermined threshold. The parameter setting processing device according to claim 2 .

4. the one or more objective functions are at least one of a path loss, a delay spread, and an angular spread; The one or more parameters are at least one of parameters related to a material, an emission interval, reflection, diffraction, and transmission. The parameter setting processing device according to claim 3 .

5. the plurality of objective functions include a calculation time for calculating the propagation path of the radio wave; The parameter setting processing device according to claim 4 .

6. A parameter setting processing device according to any one of claims 1 to 5; a propagation path calculation device that calculates a propagation path of a radio wave emitted from a transmitter and arriving at a receiver using one or more parameters set by the processing unit, Radio wave propagation estimation system.

7. Evaluating the contribution of one or more parameters that contribute to calculation of a propagation path of a radio wave emitted from a transmitter and arriving at a receiver to one or more objective functions; setting the one or more parameters using a genetic algorithm based on the evaluation result of the evaluation; Parameter setting processing method.

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