Information processing device and method for determining measured candidate positions

Abstract

The present invention provides an information processing device that can efficiently determine candidate locations for radio wave propagation models that can be improved using measurement results, while reducing the number of candidate locations for actual measurement of radio waves in real space. [Solution] An information processing device equipped with a processor, the processor acquires a radio wave propagation model having a radio wave propagation area which is a virtual space in which radio waves propagate, and objects placed in the area having predetermined radio wave propagation characteristics, performs a simulation of radio wave propagation using the model, and determines candidate measurement locations in real space for acquiring measured values ​​to be used to modify the characteristics of the radio wave propagation model based on the simulation results.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus and a method for determining an actual measurement candidate position.

Background Art

[0002] Conventionally, a radio wave shielding area measurement route calculation device for calculating an optimal measurement route for measuring an area where radio waves are shielded by an obstacle and providing it to a measurer is known. This radio wave shielding area measurement route calculation device includes: first storage means for storing position information consisting of the latitude, longitude, and height of an input radio wave transmission source and a building, and planar map information; shielding area calculation means for calculating a radio wave shielding area based on the position information of the radio wave transmission source and the building; measurement route calculation means for calculating a measurement route, which is the order of actually measuring the radio wave intensity near the radio wave shielding area, based on the calculated radio wave shielding area and the planar map information; and measurement route notification means for receiving a request for transmitting the measurement route from a mobile terminal and transmitting the measurement route to the mobile terminal (see Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The radio wave shielding area measurement route calculation device of Patent Document 1 simply calculates candidates for the shielding area, and does not consider improving the radio wave propagation model efficiently using the actual measurement results while reducing the number of actual measurement candidate positions where radio waves are actually measured in the real space.

[0005] The present disclosure provides an information processing apparatus and a method for determining an actual measurement candidate position that can determine an actual measurement candidate position capable of efficiently improving a radio wave propagation model using actual measurement results while reducing the number of actual measurement candidate positions where radio waves are actually measured in the real space. [Means for solving the problem]

[0006] One aspect of the present disclosure is an information processing device comprising a processor, the processor acquiring a radio wave propagation model comprising a radio wave propagation area which is a virtual space in which radio waves are propagated, and objects arranged in the radio wave propagation area which have predetermined radio wave propagation characteristics, performing a simulation of radio wave propagation using the radio wave propagation model, and determining candidate measurement locations in real space for acquiring measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model, based on the results of the simulation.

[0007] One aspect of this disclosure is a method for determining candidate measurement locations, comprising: acquiring a radio wave propagation model having a radio wave propagation area which is a virtual space in which radio waves are propagated, and objects placed in the radio wave propagation area which have predetermined radio wave propagation characteristics; performing a simulation of radio wave propagation using the radio wave propagation model; and determining candidate measurement locations in real space for acquiring measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model, based on the results of the simulation. [Effects of the Invention]

[0008] According to this disclosure, it is possible to reduce the number of candidate locations for actual measurement of radio waves in real space, while efficiently determining candidate locations for improvement of the radio wave propagation model using the measurement results. [Brief explanation of the drawing]

[0009] [Figure 1] This figure shows an example of the configuration of the model processing system in the first embodiment. [Figure 2A] Diagram illustrating the process of determining the candidate measurement locations. [Figure 2B] Another diagram to explain the process of determining the candidate measurement locations. [Figure 3] A diagram showing the correspondence between the measured candidate receiving point and the measured candidate position. [Figure 4]A flowchart illustrating an example of the operation involved in determining the measured candidate position by an information processing device. [Figure 5] A diagram illustrating an example of determining a candidate receiving point for actual measurement. [Figure 6A] A flowchart (Part 1) illustrating an example of operation related to the optimization of radio wave propagation models by an information processing device. [Figure 6B] Flowchart (Part 2) illustrating an example of operation related to the optimization of radio wave propagation models by an information processing device. [Figure 7] This figure shows an example of determining the target location, target path, and target object for optimization. [Figure 8] A graph showing the first example of the difference change in response to the correction of the radio wave propagation characteristics of the target object. [Figure 9] A graph showing a second example of the difference in response to the correction of the radio wave propagation characteristics of the target object. [Figure 10] A graph showing a third example of the difference in response to the correction of the radio wave propagation characteristics of the target object. [Modes for carrying out the invention]

[0010] The embodiments will be described in detail below, with reference to the drawings as appropriate. However, unnecessary details may be omitted. For example, detailed explanations of already well-known matters or redundant explanations of substantially identical configurations may be omitted. This is to avoid the following explanation becoming unnecessarily verbose and to facilitate understanding by those skilled in the art. The accompanying drawings and the following explanation are provided to enable those skilled in the art to fully understand this disclosure and are not intended to limit the subject matter described in the claims.

[0011] (The circumstances leading to the acquisition of the embodiments of this disclosure) Conventionally, radio wave propagation simulations have been performed using radio wave propagation models. It is conceivable that the radio wave propagation characteristics of each object constituting the model can be improved by using the results of actual radio wave measurements in the real space corresponding to the radio wave propagation area of ​​the radio wave propagation model.

[0012] Candidate positions to be measured in real space (real measurement candidate positions) are determined based on, for example, prior on-site inspections or map data. However, if the accuracy of the real measurement candidate positions is insufficient, the accuracy of the improved radio wave propagation model will also be insufficient, and the results of the radio wave propagation simulation will also have insufficient accuracy. Therefore, in order to ensure these accuracies and results, it is necessary to arrange and measure the real measurement candidate positions at a fairly high density. In this case, when the radio wave propagation area is large, the number of real measurement candidate positions in real space corresponding to the radio wave propagation area becomes extremely large, and the man-hours for actual measurement can increase.

[0013] Also, it is assumed that the density of the real measurement candidate positions varies depending on the arrangement of objects within the radio wave propagation area of the radio wave propagation model, as well as the complexity of the radio wave propagation area and the objects. However, it is difficult to recognize what density of real measurement candidate positions is sufficient for actual measurement. Therefore, there is a possibility that the real measurement candidate positions are determined and measured excessively compared to the number of real measurement candidate positions that are presumably necessary.

[0014] Therefore, it is desirable to optimize the real measurement candidate positions so that only the minimum necessary number of real measurement candidate positions is required.

[0015] The radio wave shielding area measurement route calculation device of Patent Document 1 calculates the measurement route, but does not consider which of the measurable points are efficient for actual measurement. Also, the radio wave shielding area measurement route calculation device of Patent Document 1 does not consider performing a radio wave propagation simulation using a radio wave propagation model, and does not consider improving the radio wave propagation characteristics of each object that constitutes the radio wave propagation model using the minimum necessary actual measurement results.

[0016] In the present embodiment, an information processing device and a real measurement candidate position determination method that can determine real measurement candidate positions that can efficiently improve the radio wave propagation model using the actual measurement results while reducing the number of real measurement candidate positions where radio waves are actually measured in real space will be described.

[0017] (First Embodiment) <Configuration of the Model Processing System> Figure 1 shows an example configuration of the model processing system 5. The model processing system 5 includes an information processing device 10 and an antenna device 20. The model processing system 5 acquires a radio wave propagation model for simulating the propagation of radio waves in real space (radio wave propagation simulation) and performs processing using the radio wave propagation model. The information processing device 10 is, for example, a computer device, such as a PC (Personal Computer), a mobile terminal such as a smartphone or tablet, or a server device.

[0018] The information processing device 10 comprises a processor 11, a memory 12, a communication device 13, an input device 14, and a display device 15.

[0019] The processor 11 is configured using, for example, a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or a Graphical Processing Unit (GPU). The processor 11 may also be configured using various integrated circuits (for example, a Large Scale Integration (LSI) or a Field Programmable Gate Array (FPGA)). The processor 11 implements various functions by executing programs held in the memory 12. The processor 11 comprehensively controls each part of the information processing device 10 and performs various processes.

[0020] Memory 12 includes primary storage (e.g., Random Access Memory (RAM) or Read Only Memory (ROM)). Memory 12 may also include secondary storage (e.g., Hard Disk Drive (HDD) or Solid State Drive (SSD)) or tertiary storage (e.g., optical disc or SD card). Memory 12 may also be an external storage medium and may be detachable from the information processing device 10. Memory 12 stores various data, information, or programs.

[0021] The communication device 13 communicates various data or information according to a wired or wireless communication method. The communication method used by the communication device 13 includes, for example, a Local Area Network (LAN), a Wide Area Network (WAN), a mobile phone network, or power line communication.

[0022] The input device 14 includes, for example, various buttons, keys, a mouse, a keyboard, a touch panel, a microphone, or other input devices. The input device 14 accepts input of various data or information. The input device 14 is operated, for example, by a user. The user is, for example, a worker or manager who performs radio wave propagation simulations or visualizes radio waves.

[0023] The display device 15 is, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display. The display device 15 displays various data or information. The display by the display device 15 may be confirmed by, for example, a user.

[0024] Furthermore, if the information processing device 10 is a server device, it may be configured as an on-premises server device or as a cloud-based device on a network. The information processing device 10 may consist of a single computer or may be configured as a distributed system using multiple computers.

[0025] The antenna device 20 measures radio waves within the real-space RS (see Figure 3) corresponding to the radio wave propagation area AR (see Figure 2) of the radio wave propagation model ML (see Figure 2), and analyzes the propagation characteristics of the radio waves. The antenna device 20 is placed at a candidate measurement location MP (see Figure 3), which will be described later. The candidate measurement location MP is a location in the real-space RS that is a candidate for measurement. The antenna device 20 may be fixedly installed at the candidate measurement location MP, or it may be portable and movable. For example, the antenna device 20 measures the received level (received power) and the direction of arrival of the radio waves at the candidate measurement location MP. The antenna device 20 transmits the measurement results, including the received level and the direction of arrival of the radio waves measured at the candidate measurement location MP, to the information processing device 10. The information processing device 10 receives and acquires the measurement results from the antenna device 20 via a communication device 13.

[0026] The antenna device 20 is composed of, for example, a polyhedron antenna. The polyhedron antenna is composed of, for example, a hexahedron antenna, but it may be an antenna of other polyhedrons. Here, the antenna device 20 is mainly exemplified as a hexahedron antenna. The polyhedron antenna may be measured based on the reception level of the face with the maximum reception level on the polyhedron antenna, the reception level of the face adjacent to this maximum face that has a large reception level, and information including arrangement information regarding the arrangement of the faces of the polyhedron antenna or antenna gain characteristic information. The antenna gain characteristic information is information that shows the two-dimensional or three-dimensional gain characteristics of the antenna installed on each face. As a result of the measurement here, for example, information on the direction of arrival of the maximum reception level and information on the reception level in that direction of arrival can be obtained. The arrangement information of the faces of the polyhedron antenna and the antenna gain characteristic information are stored in, for example, memory 12.

[0027] A hexahedral antenna, for example, has a cubic shape with each face rotated 90 degrees. Each face of the hexahedral antenna functions as an antenna, and each face is capable of receiving radio waves, allowing for the detection of reception levels for each face. Therefore, it is possible to detect reception levels for each direction of arrival of radio waves in the two-dimensional plane or three-dimensional space of the real-space RS, and to detect the direction of arrival of the maximum reception level. Furthermore, the hexahedral antenna can have a vertically polarized antenna capable of receiving vertically polarized waves and a horizontally polarized antenna capable of receiving horizontally polarized waves on each face, allowing for the separation of vertical and horizontal polarizations.

[0028] In a hexagonal antenna, the resolution for the direction of arrival is ±45 degrees. Furthermore, a hexagonal antenna can achieve a resolution higher than ±45 degrees by observing the difference between the reception level on the face with the highest reception level and the reception levels on the two adjacent faces (the ones with higher reception levels). This difference, combined with the antenna's pattern, allows the hexagonal antenna to detect the direction of arrival of radio waves with the highest reception level with this high resolution.

[0029] Furthermore, with a hexahedral antenna, reception levels can be measured not only in the four directions along the horizontal plane, but also in the upper and lower planes. Therefore, it is possible to estimate the direction of arrival of radio waves in three dimensions, not just two. Based on this estimation result, the processor 11 can extract the path for radio wave propagation simulation, as will be described later. Note that, in order to estimate the direction of arrival, a polyhedral antenna is not required; other types of antennas are also acceptable, such as array antennas or mechanical antennas that mechanically rotate the antenna's orientation.

[0030] <Overview of Model Processing System Operation> The processor 11 of the information processing device 10 acquires a radio wave propagation model ML and performs processing using the radio wave propagation model ML. The processor 11 performs a radio wave propagation simulation using the radio wave propagation model ML. The radio wave propagation simulation includes, for example, a ray tracing simulation. The radio wave propagation model ML has a radio wave propagation area AR, which is a virtual space where radio waves propagate, and various objects OB placed in the radio wave propagation area AR. The various objects OB are, for example, walls, arbitrary objects (e.g., chairs, desks), obstacles, etc. Each object OB has its own radio wave propagation characteristics. Radio wave propagation characteristics include, for example, the transmittance, reflectance, or other characteristics of radio waves. Radio wave propagation characteristics are modifiable.

[0031] The processor 11 performs optimization to correct (improve) the radio wave propagation characteristics in the radio wave propagation model ML. The processor 11 determines the candidate measurement location MP used in the optimization of the radio wave propagation model ML. This candidate measurement location MP is the location in the real space RS corresponding to the radio wave propagation model ML in the virtual space where the radio wave propagation characteristics are actually measured. The antenna device 20 measures radio waves at the candidate measurement location MP in the real space RS. The processor 11 optimizes the radio wave propagation model ML based on the radio wave propagation characteristics in the radio wave propagation model ML as a result of the radio wave propagation simulation and the radio wave propagation characteristics in the real space RS as a result of the measurement at the candidate measurement location MP. The information processing device 10 can perform a radio wave propagation simulation using the optimized radio wave propagation model ML and can also visualize the results of the radio wave propagation simulation (also called radio wave visualization).

[0032] Furthermore, before optimization, the radio wave propagation characteristics of each object OB can be provisionally set. This provisional setting information is stored, for example, in memory 12. As optimization is performed and the radio wave propagation characteristics are corrected, the simulation results and the measured results will come closer together.

[0033] <Determination of candidate measurement locations>

[0034] Figure 2A is a diagram illustrating the process for determining the measured candidate position MP.

[0035] As shown in Figure 2A, the radio wave propagation model ML has a radio wave propagation area AR. The radio wave propagation area AR is formed, for example, in the shape of a rectangular parallelepiped. When the radio wave propagation area AR is a rectangular parallelepiped, the radio wave propagation model ML has six faces at the ends of the radio wave propagation area AR. The six faces are the top surface, the bottom surface (floor surface), and the four sides which are walls. Figure 2A is a view of the radio wave propagation area AR from above, and the top and bottom surfaces are omitted. The four walls are the top wall W1, the left wall W2, the bottom wall W3, and the right wall W4. The top, bottom, left, and right directions for the walls here indicate the orientation in Figure 2A and are for the sake of simplicity in the explanation; the actual direction is not limited to these. Also, here we consider a simplified model without considering reflection and transmission at the top and bottom surfaces. Note that although the radio wave propagation area AR is shown here as a simple rectangular parallelepiped for simplicity, it may actually have a more complex shape.

[0036] Furthermore, various objects OB may exist within the radio wave propagation area AR. In Figure 2A, the objects OB include four walls (specifically, the upper wall W1, left wall W2, lower wall W3, and right wall W4), as well as objects A, B, and C. Figure 2A also shows the placement of a transmitting point SP, which indicates the transmission position for transmitting radio waves, and a receiving point RP (RP1), which indicates the reception position (measurement position) for receiving and measuring radio waves within the radio wave propagation area AR. Note that the placement of the transmitting point SP and receiving point RP shown here is provisional, and their positions can be changed within the radio wave propagation area AR.

[0037] In the radio wave propagation model ML, it is assumed that radio waves are transmitted to the receiving point RP1 from various paths PT. Each path PT extends in various directions from the receiving point RP1. In Figure 2A, as an example, radio waves reach the receiving point RP1 via four paths PT1 to PT4. The processor 11 derives (for example calculates) the paths PT from the transmitting point SP to the receiving point RP1, taking into account the radio wave propagation characteristics of each object OB in the radio wave propagation model ML. In path PT1, radio waves are transmitted from the transmitting point SP, pass through object A, reflect off the left wall W2, pass through object C, and reach the receiving point RP1. In path PT2, radio waves are reflected off the bottom wall W3 and reach the receiving point RP1. In path PT3, radio waves pass through object B and reach the receiving point RP1. In path PT4, radio waves are reflected off the right wall W4, pass through object B, and reach the receiving point RP1. In radio wave propagation simulations, various patterns can be assumed for the radio wave propagation characteristics of each object OB, such as radio waves only reflecting, radio waves only transmitting, or radio waves both reflecting and transmitting.

[0038] The radio wave propagation model ML is created to simulate the state in real space RS. Therefore, each object OB placed in the radio wave propagation area AR of the radio wave propagation model ML corresponds to the same object placed in the real space RS that corresponds to the radio wave propagation area AR.

[0039] At the receiving point RP1 in the radio wave propagation model ML, the radio waves are influenced by object A, object B, object C, the left wall W2, the bottom wall W3, and the right wall W4. The object OB that influences reception is also called influencing object OB1. Therefore, if radio waves are measured at the real-space location RS corresponding to the receiving point RP1, it may be possible to optimize the radio wave propagation characteristics with respect to the receiving point RP1 due to influencing object OB1 (i.e., object A, object B, object C, left wall W2, bottom wall W3, and right wall W4).

[0040] However, if the reception level of the radio waves propagating along a predetermined path PT is minimal, the influence of the predetermined path PT on the reception quality at the receiving point RP is considered small. In this case, the optimization of each object OB along the predetermined path PT may be insufficient.

[0041] As an example, in Figure 2A, assume that the reception level along path PT1 is minimal. In this case, the influence of path PT1 on the reception quality at receiving point RP1 is small, so the optimization of the radio wave propagation characteristics between object A, object C, and the left wall W2 may be insufficient. On the other hand, the optimization of the radio wave propagation characteristics of the three paths PT2, PT3, and PT4 is considered sufficient.

[0042] In this case, the processor 11 may exclude (i.e., ignore) the path PT1, where the radio wave reception level is minimal, from the paths PT that pass through the receiving point RP1. The processor 11 may determine whether or not the radio wave reception level is minimal based on the radio wave reception level value itself, or it may determine based on the reception levels of other paths PT that pass through the same receiving point RP. In this case, the processor 11 may determine that the radio wave reception level is minimal if the ratio of the reception level of the radio waves passing through the same receiving point RP to the path PT with the maximum reception level is less than a predetermined ratio.

[0043] Figure 2B is another diagram illustrating the process for determining the measured candidate location MP. In Figure 2B, explanations of matters similar to those in Figure 2A are omitted or simplified.

[0044] Figure 2B, compared to Figure 2A, shows that the four walls (upper wall W1, left wall W2, lower wall W3, right wall W4) and objects A-C are positioned within the radio wave propagation area AR, just as in Figure 2A. The positions of objects A-C and the transmitting point SP are also the same within the radio wave propagation area AR. However, the position of the receiving point RP (RP2) is different.

[0045] Assume that radio waves are transmitted to the receiving point RP2 from various paths PT. In Figure 2B, as an example, radio waves reach the receiving point RP2 via four paths PT11 to PT14. In path PT11, the radio waves pass through object A, reflect off the left wall W2, pass through object C, and reach the receiving point RP2. In path PT12, the radio waves pass through object C and reach the receiving point RP2. In path PT13, the radio waves reflect off the bottom wall W3 and reach the receiving point RP2. In path PT14, the radio waves reflect off the right wall W4, pass through object B, and reach the receiving point RP2.

[0046] Therefore, at receiving point RP2, the signal is affected by object A, object B, object C, the left wall W2, the bottom wall W3, and the right wall W4. For this reason, if the radio waves are measured at the real-space position RS corresponding to receiving point RP2, it may be possible to optimize the radio wave propagation characteristics due to the influencing objects OB1 (i.e., object A, object B, object C, the left wall W2, the bottom wall W3, and the right wall W4) at receiving point RP2.

[0047] Here, in Figure 2B, we assume that the received level of the radio waves propagating through path PT11 is minimal. In this case, the influence of path PT11 on reception quality is small, so the optimization of the radio wave propagation characteristics between object A, object C, and the left wall W2 may be insufficient. In this case, the processor 11 may exclude (i.e., ignore) path PT11, where the received level of the radio waves is minimal, from the paths PT that pass through the receiving point RP2.

[0048] However, if the reception level of radio waves propagating through paths PT12 and PT13 is high, it may be possible to sufficiently optimize the radio wave propagation characteristics of object C. In other words, the arrangement of receiver point RP2 shown in Figure 2B is preferable to the arrangement of receiver point RP1 shown in Figure 2A, as it has the potential to optimize the radio wave propagation characteristics of more objects OB. Therefore, it is preferable to select receiver point RP2 rather than receiver point RP1 as the candidate receiver point RPC for actual measurement of radio waves. The position on the real space RS corresponding to the candidate receiver point RPC becomes the candidate measurement position MP.

[0049] Although Figures 2A and 2B show receiving points RP1 and RP2, receiving point RP can be placed at any position within the radio wave propagation model ML. For example, receiving point RP may be placed at any of the grid intersections in Figures 2A and 2B, and there may be a large number of receiving point RP. From such a large number of receiving point RP, the processor 11 determines the minimum necessary number of candidate measured receiving point RPCs and determines the candidate measured position MP corresponding to the candidate measured receiving point RPCs.

[0050] Figure 3 shows the correspondence between the measured candidate receiving point RPC and the measured candidate position MP. In Figure 3, the virtual space, the radio wave propagation area AR, is shown as a rectangle (cuboid shape). Since the radio wave propagation area AR is a model of the real space RS, the real space RS corresponding to the radio wave propagation area AR is also shown as the same rectangle (cuboid shape). The position of the measured candidate receiving point RPC relative to the radio wave propagation area AR and the measured candidate position MP relative to the corresponding real space RS are in the same positional relationship.

[0051] Next, the operation of the information processing device 10 in this embodiment related to the determination of the measured candidate position MP will be described.

[0052] Figure 4 is a flowchart showing an example of the operation related to the determination of the measured candidate position MP by the information processing device 10.

[0053] First, the processor 11 acquires a radio wave propagation model ML (step S11). The processor 11 creates the radio wave propagation model ML using CAD (Computer Aided Design) or the like, based on measurement results from the field (real-space RS) using, for example, a LiDAR (Light Detection and Ranging) device, or map data. Alternatively, the processor 11 may create the radio wave propagation model ML based on user input via, for example, the input device 14, or acquire the radio wave propagation model ML stored in memory 12, or acquire the radio wave propagation model ML from an external device via the communication device 13. Note that in the radio wave propagation model ML used here, the radio wave propagation characteristics of object OB within the radio wave propagation model ML are not optimized.

[0054] The processor 11 performs a radio wave propagation simulation using the radio wave propagation model ML and obtains the simulation results (step S12). The processor 11 obtains the simulation results based on the arrangement of each object OB in the radio wave propagation area AR of the radio wave propagation model ML and the predetermined radio wave propagation characteristics of each object OB. The information on the arrangement of each object OB in the radio wave propagation area AR and the predetermined radio wave propagation characteristics of each object OB is stored, for example, in memory 12 and referenced by the processor 11.

[0055] The simulation results include, for example, information about each path PT through which radio waves propagate to a receiving point RP within the radio wave propagation area AR of the radio wave propagation model ML (path information), and information about the reception level of each path PT at the receiving point RP (reception level information). The sum of the reception levels of each path PT at the receiving point RP is the (overall) reception level at the receiving point RP. Therefore, the simulation results include information about the reception level at the receiving point RP.

[0056] Based on the simulation results, the processor 11 extracts objects OB that have an electromagnetic influence on each receiving point RP within the radio wave propagation area AR (influencing object OB1 at receiving point RP) (step S13). In this case, the processor 11 recognizes each path PT from the transmitting point SP to each receiving point RP based, for example, on the direction of arrival of each radio wave at each receiving point RP. For each receiving point RP, the processor 11 extracts each object OB present on each path PT passing through the receiving point RP as influencing object OB1 at receiving point RP.

[0057] The processor 11 may also exclude from the optimization candidates any route PT whose received signal level is lower than a predetermined received signal level compared to the route PT with the highest received signal level among the recognized route PTs. This is because the reliability of the radio wave propagation characteristics on this route PT is low, and the optimization of the radio wave propagation characteristics of the influencing object OB1 on this route PT may be insufficient.

[0058] The processor 11 extracts the receiver point RPC that has the largest number of influencing objects OB1 at each receiver point RP (also referred to as the maximum influencing receiver point RPB) as the measured candidate receiver point RPC (step S14).

[0059] The processor 11 excludes the influencing object OB1 at the extracted measured candidate receiving point RPC from the object OB to be searched for in order to determine the next measured candidate position MP (step S15). The processor 11 also excludes the extracted measured candidate receiving point RPC from the receiving point RP to be searched for in order to determine the next measured candidate position MP (step S15).

[0060] The processor 11 determines whether the ratio of the remaining unexcluded objects in the radio wave propagation model ML to the total number of objects OB is less than the threshold th1 (step S16).

[0061] If the above ratio is smaller than the threshold th1 (Yes in step S16), the processor 11 terminates the process shown in Figure 4. In other words, the information processing device 10 terminates the process shown in Figure 4 when it has obtained a sufficient number of paths PT that can correct the radio wave propagation characteristics of each object OB.

[0062] On the other hand, if the above ratio is greater than or equal to the threshold th1 (No in step S16), the processor 11 proceeds to the processing in step S13 and repeats the processing in steps S13 to S16. In other words, the processor 11 extracts the maximum influential receiving point RPB, which is the receiving point RP with the largest number of remaining influential objects OB1 as objects OB to be searched at the receiving point RP, as the next measured candidate receiving point RPC. The processor 11 repeats this extraction of measured candidate receiving points RPC until the above ratio becomes smaller than the threshold th1, that is, until a sufficient number of paths PT that can correct the propagation characteristics of the radio waves of each object OB are obtained.

[0063] The processor 11 determines the measured candidate position MP in real space RS corresponding to each extracted measured candidate receiver point RPC. The timing of determining the measured candidate position MP may be after all measured candidate receiver points RPCs have been extracted, or it may be each time a measured candidate receiver point RPC is extracted.

[0064] In this way, the processor 11 determines a candidate measured position MP to be used to modify the radio wave propagation characteristics of the radio wave propagation model ML based on the results of the radio wave propagation simulation. The processor 11 may also extract influencing objects OB1 that affect reception at each receiving point RP and determine a candidate measured position MP based on the extracted results. Alternatively, the processor 11 may determine the candidate measured position MP as the position in real space RS corresponding to the candidate measured receiving point RPC (maximum influencing receiving point RPB) with the largest number of influencing objects OB1. The processor 11 may also repeat the determination of a candidate measured position MP while excluding the candidate measured receiving point RPC and the influencing objects OB1 for the candidate measured receiving point RPC. Furthermore, the processor 11 may exclude from the path PT through which the radio waves arriving at the receiving point RP propagate a second path that is received at a reception level below a certain reception level, relative to the first path that is received at the maximum reception level. Furthermore, the processor 11 may terminate the iteration of determining the measured candidate position MP when the ratio of the number of objects on the path that were not excluded to the total number of objects in the radio wave propagation model ML falls below the threshold th1.

[0065] According to the processing shown in Figure 4, the information processing device 10 can determine the optimal (minimum necessary) measured candidate receiving point RPC that can modify the radio wave propagation characteristics of each object OB in the radio wave propagation model ML, and that is, it can determine the measured candidate position MP in real space RS corresponding to the measured candidate receiving point RPC. Therefore, the burden on the measurement personnel involved in the measurement in real space RS can be reduced and the measurement time can be shortened. In addition, since each measured candidate receiving point RPC is selected in order of the number of influencing objects OB1 at each measured candidate receiving point RPC, the information processing device 10 can efficiently derive the measured candidate receiving point RPC and the measured candidate position MP.

[0066] Next, we will explain the details of determining the candidate RPC (Receiving Point) for actual measurement. Figure 5 is a diagram illustrating an example of determining a candidate receiver point RPC based on actual measurements.

[0067] Figure 5 shows a matrix of information about the receiving point RP and the objects OB. Specifically, the identification information for each receiving point RP (receiving point 1, receiving point 2, ...) is arranged in the x direction, and the identification information for each object OB (left wall, top wall, ..., object A, object B, ...) is arranged in the y direction. A flag indicating an influencing object OB1 is shown at the intersection of the receiving point RP and each object OB. An influencing object OB1 is an object among the objects OB that has an electromagnetic influence on the receiving point RP when radio waves are transmitted from the transmitting point SP. The flag indicating an influencing object OB1 is, for example, "1" to indicate that it is an influencing object.

[0068] Therefore, if a "1" is entered in the matrix, the object OB (influencing object OB1) in the column where the "1" is entered exerts an electromagnetic influence on the receiving point RP in that column. For example, if a "1" is entered at the intersection of receiving point 2 and the lower wall, it indicates that the lower wall exerts an electromagnetic influence on receiving point 2.

[0069] In Figures 2A, 2B, and 5, there are seven objects OB placed within the radio wave propagation model ML. It is assumed that the radio wave propagation characteristics will be modified (optimized) for all seven of these objects OB. Note that receiver point 1 in Figure 5 corresponds to RP1 in Figure 2A (however, the influence of path PT1 is minimal and therefore ignored), and receiver point 2 in Figure 5 corresponds to RP2 in Figure 2B (however, the influence of path PT11 is minimal and therefore ignored).

[0070] First, in the initial state (state A), no receiving point RP has been determined as a candidate receiving point RPC. In this state, the processor 11 counts the number of influencing objects OB1 for each receiving point RP and determines the maximum influencing receiving point RPB, which has the largest number of influencing objects OB1, as the candidate receiving point RPC. In Figure 5, since the number of influencing objects OB1 is largest at receiving point 2 (4), receiving point 2 is determined as the first candidate receiving point RPC. This is because the maximum influencing receiving point RPB, which has the largest number of influencing objects OB1, is the receiving point that has the greatest impact on correcting the radio wave propagation characteristics. In other words, the radio wave propagation characteristics of influencing objects OB1 for that candidate receiving point RPC can be corrected all at once by a single candidate receiving point RPC, which is efficient.

[0071] Next, the system transitions to state B. In state B, the processor 11 excludes receiver point 2, which has been determined as a measured candidate receiver point RPC, from the receiver point RP to be searched. This is because the optimization of the influencing object OB1 with respect to receiver point 2 is already feasible. The processor 11 also excludes the influencing object OB1 (in this case, the lower wall, the right wall, object B, and object C) with respect to receiver point 2 from the object OB to be searched. This is because it is unnecessary to optimize the same influencing object OB1 even if a receiver point other than receiver point 2 is determined as a measured candidate receiver point RPC.

[0072] In Figure 5, the hatching HT1 in the column for receiver 2 indicates that it has been excluded from the search target receiver RP. Additionally, the hatching HT2 in the rows for lower wall W3, right wall W4, object B, and object C indicates that the lower wall W3, right wall W4, object B, and object C have been excluded from the search target object OB.

[0073] By excluding receiving point 2, the lower wall W3, the right wall W4, object B, and object C in state B, the processor 11 determines that receiving point 3 is the next maximum influential receiving point RPB because it has the next highest number of influential object OB1, and determines receiving point 3 as the second measured candidate receiving point RPC.

[0074] Next, the system transitions to state C. In state C, the processor 11 removes receiver point 3, which has been determined as a candidate receiver point RPC, from the searchable receiver points RP, and removes the influencing object OB1 (in this case, the left wall W2 and object A) from the searchable object OB. In Figure 5, the exclusion of receiver point 3 from the searchable receiver points RP is indicated by hatching HT3 in the column for receiver point 3. Similarly, the exclusion of the left wall W2 and object A from the searchable object OB is indicated by hatching HT4 in the rows for the left wall W2 and object A. Due to the exclusion of receiver point 3, the left wall W2, and object A in state C, receiver point 5 remains as a searchable receiver point RP, and the upper wall W1 remains as a searchable object OB.

[0075] In state C, the total number of objects is 7, and the number of remaining objects (objects to be searched) is 1. Therefore, the ratio of the number of remaining objects to the total number of objects is 1 / 7 (approximately 0.14). If the threshold th1 is 0.2, the processor 11 terminates the process of determining the measured candidate receiving point RPC (process in Figure 4) at this point. This process corresponds to Yes in step S16 of Figure 4. Therefore, the measured candidate receiving point RPCs are the two points, receiving point 2 and receiving point 3.

[0076] On the other hand, if the threshold th1 is 0.1, the ratio of the remaining number of objects to the total number of objects is 1 / 7, which is still not below 0.1, so the processor 11 performs the process of determining the next candidate receiver point RPC. This process corresponds to step S16 No. in Figure 4. Referring to state C, the processor 11 determines receiver point 5 as the next candidate receiver point RPC. Therefore, the candidate receiver points RPCs are receiver points 2, 3, and 5. Once receiver point 5 is determined as the candidate receiver point RPC, there are no remaining objects OB (the ratio of remaining objects becomes 0, which is below 0.1), so the process of determining the candidate receiver point RPC (the process in Figure 4) is terminated at this point.

[0077] Thus, the information processing device 10 of this embodiment can use an unoptimized radio wave propagation model ML to sequentially determine the maximum influential receiving point RPB, which has the largest number of influential objects OB1, as a candidate measured receiving point RPC. This allows the information processing device 10 to automatically calculate which receiving point RP in the radio wave propagation model ML corresponds to the position of the real-space RS that should be measured for efficiency. Furthermore, by optimizing the radio wave propagation characteristics of each influential object OB1 for each candidate measured receiving point RPC, the radio wave propagation characteristics of all objects OB in the radio wave propagation model ML can be optimized without omission. The information processing device 10 can easily determine the minimum number of candidate measured receiving points RPC necessary to optimize the radio wave propagation characteristics of all objects OB, and therefore can easily determine the minimum number of candidate measured positions MP in the real-space RS.

[0078] Furthermore, the antenna device 20 performs measurements at the determined candidate measurement locations MP within the real-space RS, and the information processing device 10 is expected to efficiently optimize the radio wave propagation model ML by using these measurement results. In addition, the information processing device 10 is expected to be able to optimize the radio wave propagation model ML in a short time because the number of candidate measurement locations MP is minimized.

[0079] Therefore, the information processing device 10 can optimize the number of candidate measured locations MP so that only the minimum necessary number of locations MP are required. In other words, the information processing device 10 can determine candidate measured locations MP that efficiently improve the radio wave propagation model ML using the measurement results, while reducing the number of candidate measured locations MP for which radio waves are measured in real space RS.

[0080] <Model Optimization> Next, we will discuss the optimization of the ML model for radio wave propagation. First, I will explain the overview of optimizing the ML model for radio wave propagation.

[0081] The antenna device 20 measures radio waves at the determined candidate measurement location MP in the real-space RS and transmits the measurement results to the information processing device 10. The processor 11 acquires the measurement results measured at the determined candidate measurement location MP. The processor 11 acquires the results (simulation results) of a radio wave propagation simulation performed using the radio wave propagation model ML. The processor 11 calculates the difference Er between the measurement results and the simulation results and modifies (optimizes) the radio wave propagation characteristics of the influencing object OB1 with respect to the candidate measurement receiving point RPC so that the difference Er becomes smaller. The radio wave propagation characteristics of the influencing object OB1 include at least one of the reflectance and transmittance of the influencing object OB1. Optimization means bringing the radio wave propagation characteristics within the radio wave propagation area AR of the radio wave propagation model ML closer to the actual radio wave propagation characteristics in the real-space RS corresponding to the radio wave propagation area AR. For each influencing object OB1, the processor 11 optimizes the radio wave propagation characteristics of the influencing object OB1 with respect to the measured candidate receiving point RPC, starting with the measured candidate receiving point RPC with the maximum difference Er.

[0082] The antenna device 20 detects the direction of arrival of the radio wave at the maximum reception level (also referred to as the maximum level arrival direction Rd) at the measured candidate position MP and transmits the detection result to the information processing device 10. The processor 11 focuses on the path PT that passes through the measured candidate reception point RPC and is close to the maximum level arrival direction Rd, and optimizes the parameters that indicate the radio wave propagation characteristics of the influencing object OB1 on that path PT.

[0083] In optimizing radio wave propagation characteristics, if the measured result at the candidate measurement location MP is greater than the simulation result at the candidate measurement receiving point RPC, the processor 11 increases the reflectivity or transmittance of radio waves due to the influencing object OB1 at the candidate measurement receiving point RPC. The simulation result here is the derived value of the radio wave reception level from the radio wave propagation simulation. The measured result here is the measured value of the radio wave reception level. In optimizing radio wave propagation characteristics, if the measured result at the candidate measurement location MP is smaller than the simulation result at the candidate measurement receiving point RPC, the processor 11 decreases the reflectivity or transmittance of radio waves due to the influencing object OB1 at the candidate measurement receiving point RPC.

[0084] In optimizing radio wave propagation characteristics, processor 11 may not make large corrections (adjustments) to the radio wave propagation characteristics all at once, but rather make small corrections gradually. This is to check whether the difference Er is decreasing. Alternatively, processor 11 may make large corrections to the radio wave propagation characteristics all at once to complete the correction early, or it may change the amount of correction as appropriate.

[0085] If the difference Er does not decrease even after correcting the radio wave propagation characteristics of a predetermined influencing object OB1 on the path PT, the processor 11 may correct (optimize) the radio wave propagation characteristics of another influencing object OB1 on the same path PT.

[0086] If the difference Er does not decrease even after optimizing the path PT that extends in a direction close to (e.g., the closest) the direction of arrival of the maximum level Rd, the processor 11 may optimize the radio wave propagation characteristics of the influencing object OB1 in another path PT where the radio wave reception level is large (e.g., the reception level is above a predetermined level) based on the simulation results.

[0087] If the difference Er does not decrease even after optimizing the radio wave propagation characteristics of the influencing object OB1 by changing the path PT, the processor 11 optimizes the radio wave propagation characteristics of the influencing object OB1 of the path PT located within a specific radius range Rt from the measured candidate receiving point RPC, within a certain angular range Cr, with respect to the directional component parallel to the horizontal plane in the direction of arrival of the maximum level Rd. In other words, in matching the direction of arrival of the maximum level Rd with the path PT through which the radio waves used in the radio wave propagation simulation are propagated, the processor 11 extracts the influencing object OB1 within a predetermined angular range Cr with respect to the direction of arrival of the maximum level Rd in three-dimensional space.

[0088] Furthermore, if the processor 11 cannot match the direction of arrival of the maximum level Rd with the path PT through which the radio waves propagate used in the radio wave propagation simulation, that is, if the path PT does not exist within the angular range Cr relative to the direction of arrival of the maximum level Rd in three-dimensional space, it will consider optimization impossible and will not perform optimization of the radio wave propagation characteristics of the influencing object OB1 with respect to this measured candidate receiving point RPC.

[0089] Once the processor 11 has finished optimizing the radio wave propagation characteristics using one measured candidate receiver point RPC, it repeats the same process for the measured candidate receiver point RPC with the largest difference Er. In this case, the processor 11 excludes the measured candidate receiver point RPC that has already been optimized from the next candidate for optimization. However, if the difference Er worsens (increases) as a result of optimizing the radio wave propagation characteristics of the influencing object OB1 for other measured candidate receiver points RPCs, that measured candidate receiver point RPC may be included in the optimization target again.

[0090] Furthermore, for measured candidate receiving points RPCs where the difference Er is within a certain range Ez (a threshold) from the start of the model optimization process, the processor 11 does not optimize the radio wave propagation characteristics of the influencing object OB1. Also, for measured candidate receiving points RPCs where the difference Er falls within a certain range Ez after the optimization of the radio wave propagation characteristics, the processor 11 terminates the optimization process for the radio wave propagation characteristics of the influencing object OB1. The certain range Ez is, for example, ±5dB.

[0091] Next, we will explain the operation related to the optimization of the ML radio wave propagation model.

[0092] Figures 6A and 6B are flowcharts illustrating examples of operations related to the optimization of the radio wave propagation model ML by the information processing device 10.

[0093] First, the processor 11 acquires the radio wave propagation model ML (step S21). Step S21 is the same as step S11 in Figure 4.

[0094] The processor 11 performs a radio wave propagation simulation using the radio wave propagation model ML and obtains the simulation results (step S22). Step S22 is the same as step S12 in Figure 4.

[0095] In parallel with the processing in steps S21 and S22, the processor 11 controls the execution of the measured candidate position determination process and the measurement process.

[0096] The measured candidate position determination process is the process of determining the measured candidate position MP, and is, for example, the same process as the process shown in Figure 4 in the first embodiment.

[0097] The measurement process includes, for example, notifying the antenna device 20 and the terminal of the person taking the measurement who is holding the antenna device 20 of information about candidate measurement locations MP, and obtaining the measurement results from the antenna device 20, which have measured radio waves at each candidate measurement location MP. In addition, for the measurement process, the person in charge of measurement places the antenna device 20 at the candidate measurement location MP on site, the antenna device 20 measures the radio waves at the candidate measurement location MP, and transmits the measurement results to the information processing device 10.

[0098] In this way, the processor 11 acquires measurement results at each candidate measurement location MP in the real space RS (step S23). The measurement results include, for example, information regarding the direction of arrival of the radio waves measured at the candidate measurement location MP (direction of arrival information) and information regarding the received level of the radio waves measured at the candidate measurement location MP (received level information) for each candidate measurement location MP.

[0099] The processor 11 compares the simulation results obtained from the radio wave propagation simulation with the measurement results obtained from the measurement processing and calculates the difference Er between the two results (step S24). Specifically, for each candidate measurement receiving point RPC and candidate measurement location MP, the processor 11 calculates the difference Er between the received level obtained from the radio wave propagation simulation and the received level measured by the measurement processing.

[0100] The processor 11 extracts the measured candidate receiver point RPC with the maximum difference Er as the measured candidate receiver point RPC to be optimized (also referred to as the target receiver point) (step S25).

[0101] The processor 11 determines whether the difference Er at the target receiving point is within a certain range Ez (step S26).

[0102] If the difference Er is within a certain range Ez (Yes in step S26), the processor 11 terminates the processing shown in Figures 6A and 6B. This is because the simulation results and the actual measurement results at the target receiving point are similar, and there is no need to adjust the radio wave propagation characteristics of each object OB relative to the target receiving point.

[0103] If the difference Er is not a value within a certain range Ez (No in step S26), the processor 11 determines whether or not there are any optimizable measured candidate receiver points RPCs remaining (step S27). For example, if there are any measured candidate positions MP among all measured candidate positions MP determined in the measured candidate position determination process that have not been attempted to optimize, it is determined that there are still measured candidate positions MPs remaining. For example, the target receiver point extracted in step S25 remains as an optimizable measured candidate receiver point RPC, specifically as an optimizable measured candidate position MP.

[0104] If there are no more optimizable measured candidate receiver points RPCs remaining (No. in step S27), the processor 11 terminates the processing shown in Figures 6A and 6B. This is because there are no more optimizable measured candidate receiver points RPCs to process next.

[0105] If there are still optimizable candidate receiver points RPCs (Yes in step S27), the processor 11 selects one of the optimizable candidate receiver points RPCs as the target receiver point for optimization. Then, the processor 11 extracts the maximum level arrival direction Rd based on the measurement results (e.g., arrival direction information) at the candidate measurement position MP (also referred to as the target position) in the real space RS corresponding to the target receiver point (step S28).

[0106] The processor 11 determines whether a path PT (also called the target path) exists within an angular range Cr with respect to the direction of arrival Rd of the maximum level, with respect to the target receiving point (step S29). Here, it may be determined whether the direction in which the path PT extends in three-dimensional space is included in the angular range Cr, or whether the path PT is included in the angular range Cr when projected onto a two-dimensional plane.

[0107] If no target route exists (No. in step S29), the processor 11 proceeds to step S25. In other words, the processor 11 excludes the target location where no target route existed, extracts the next measured candidate receiving point RPC with the largest difference Er as the target receiving point, and repeats the processing from step S26 onwards.

[0108] If a target path exists (Yes in step S29), the processor 11 modifies (optimizes) the radio wave propagation characteristics of at least one influencing object OB1 (also referred to as the target object) on the target path (step S30). The radio wave propagation characteristics of the target object are, for example, at least one of the reflectance and transmittance of radio waves at the target object.

[0109] The processor 11 performs a radio wave propagation simulation using the radio wave propagation model ML, which has been modified to reflect the propagation characteristics of radio waves in the target object, and obtains the simulation results. Then, the processor 11 derives (for example calculates) the difference Er (also referred to as the modified difference Er) between the modified simulation results and the measured results (step S31).

[0110] The processor 11 determines whether the difference Er has decreased before and after the correction, that is, whether the difference Er after the correction is smaller than the Er before the correction (step S32).

[0111] If the difference Er has decreased before and after the correction (Yes in step S32), the processor 11 proceeds to step S30 and repeats the correction of the radio wave propagation characteristics of the target object on the target path until the difference Er before and after the correction no longer decreases. In other words, if the difference Er has decreased, the correction of the radio wave propagation characteristics is effective, so further corrections are made.

[0112] If the difference Er has not decreased before and after the correction (No. in step S32), the processor 11 proceeds to step S25. In other words, the processor 11 excludes the optimized measured candidate receiving point RPC, that is, the target location through which the target path, which was corrected for the radio wave propagation characteristics of the target object in step S30, passes, extracts the next measured candidate receiving point RPC with the largest difference Er as the target receiving point, and performs the processing from step S26 onwards again.

[0113] Furthermore, even if the difference Er has not decreased before and after the correction (No. in step S32), if there are other influencing objects OB1 on the target path, the processor 11 may switch the target object for optimization to another influencing object OB1 and repeat the processing in steps S31 to S33 again. Therefore, if the difference Er has not decreased even after the optimization of each influencing object OB1 on the target path is completed, the processor 11 may proceed to step S25 to select another target location.

[0114] Furthermore, even if the difference Er has not decreased before and after the correction (No. in step S32), if there are other paths PT within the angular range Cr with respect to the direction of arrival Rd of the maximum level, the processor 11 may switch the target path for optimization to another path PT and repeat the processing in steps S31 to S33 again. Therefore, if the difference Er has not decreased even after the optimization of each influencing object OB1 on the other switched target path is completed, the processor 11 may proceed to step S25 to select another target position.

[0115] Furthermore, the processor 11 does not modify the radio wave propagation characteristics of object OB if the angular difference between the maximum level arrival direction Rd and any path PT passing through the target receiving point is not within the angular range Cr. This is because the radio wave propagation direction differs between the measured results and the simulation results, making it impossible to determine whether the object's radio wave propagation characteristics are appropriate.

[0116] Furthermore, correcting the radio wave propagation characteristics of the influencing object OB1 for the second measured candidate receiving point RPC may worsen the radio wave propagation characteristics of the influencing object OB1 for the first measured candidate receiving point RPC, which has already been corrected. In other words, even after optimization at a predetermined measured candidate receiving point RPC, the difference Er at that predetermined measured candidate receiving point RPC may become large again. In this case, the processor 11 may re-extract the measured candidate receiving point RPC with the largest difference Er, including the optimized measured candidate receiving point RPC, and repeat the processing from step S26 onward.

[0117] In other words, the processor 11 may sequentially change the target receiving point to other measured candidate receiving points RPC and repeat the derivation of the maximum level arrival direction Rd, the extraction of the target path, and the correction of the radio wave propagation characteristics of the influencing object OB1 on the target path. If, as a result of this repetition, the difference Er with respect to the target receiving point for which the correction of the radio wave propagation characteristics of the influencing object OB1 has already been performed becomes large, the processor 11 may perform the derivation of the maximum level arrival direction Rd based on the target receiving point, the extraction of the target path, and the correction of the radio wave propagation characteristics of the influencing object OB1 on the target path again.

[0118] As shown in the operation examples in Figures 6A and 6B, the information processing device 10 can optimize the radio wave propagation characteristics of the influencing object OB1 with respect to the measured candidate position MP, starting with the measured candidate position MP where the improvement effect is expected to be greatest, by taking into account the simulation results and the measured results. Therefore, the information processing device 10 can efficiently optimize the radio wave propagation model ML and bring it closer to the radio wave propagation characteristics of the real space RS corresponding to the radio wave propagation area AR.

[0119] Next, we will explain a specific example of optimizing a ML (Machine Learning) model for radio wave propagation.

[0120] Figure 7 shows an example of determining the target location, target path, and target object for optimization.

[0121] Figure 7 shows a radio wave propagation model ML with a radio wave propagation area AR, similar to Figure 2A. Also, similar to Figure 2A, radio waves are transmitted and arrive from various paths PT, and the radio waves reach the receiving point RP1 via four paths PT1 to PT4. Furthermore, it is assumed that there is one or more measured candidate receiving points RPC within the radio wave propagation area AR.

[0122] If, among one or more measured candidate receiving points RPC in the radio wave propagation model ML, the measured candidate receiving point RPC with the largest difference Er between the simulation result and the measured result is receiving point RP1, then receiving point RP1 is designated as the target location for optimization. Also, if the path PT located within a certain angular range Cr close to the direction of arrival Rd of the maximum level at receiving point RP1 is path PT4, then path PT4 is designated as the target path for optimization. Furthermore, if the influencing objects OB1 on path PT4 are object B and the right wall W4, then at least one of the influencing objects OB1 on path PT4 is designated as the target object for optimization, and therefore at least one of object B and the right wall W4 is designated as the target object.

[0123] The processor 11 optimizes the radio wave propagation characteristics of the target object based on the simulation results and actual measurement results at the target location. For example, if the received level obtained as an actual measurement result is greater than the received level obtained as a simulation result, the processor 11 increases the transmittance of object B as the target object, or increases the reflectance of the right wall W4 as the target object.

[0124] Figure 8 is a graph showing the first example of the change in differential Er in response to the correction of the radio wave propagation characteristics of the target object. The radio wave propagation model ML is as shown in Figure 7, and the receiving point RP1 is assumed to be the target receiving point.

[0125] Figure 8 illustrates correction pattern A, where the difference Er becomes sufficiently small by correcting the radio wave propagation characteristics of a single target object. For example, processor 11 corrects the radio wave propagation characteristics of the target object by gradually increasing the transmittance of object B. In this case, processor 11 repeats the process of steps S30 to S32 in Figure 6B, for example, to gradually increase the transmittance of object B. In this case, as shown in graph gr1, the difference Er becomes smaller as the number of corrections increases. When the difference Er becomes less than or equal to a threshold th11, which is a predetermined error range, step S32 in Figure 6B becomes No, and processor 11 terminates the correction of the radio wave propagation characteristics of the target object at this target location.

[0126] Note that the number of modifications in path PT4 shown in Figures 8 to 10 is the total number of modifications for at least one target object in path PT4 as the target path. Therefore, for example, if both modifications are made to object B and to the right wall W4, the number of modifications in path PT4 is the sum of the number of modifications for both (see Figures 9 and 10).

[0127] Figure 9 is a graph showing a second example of the change in differential Er in response to the correction of the radio wave propagation characteristics of the target object. The radio wave propagation model ML is the one shown in Figure 7, and the receiving point RP1 is assumed to be the target receiving point.

[0128] Figure 9 illustrates correction pattern B, where the difference Er becomes sufficiently small by correcting the radio wave propagation characteristics of multiple target objects. For example, the processor 11 first corrects the radio wave propagation characteristics of object B by gradually increasing its transmittance. In this case, as shown in graph portion gr21 of graph gr2, the difference Er gradually decreases as the number of corrections increases at the beginning of correcting the radio wave propagation characteristics of object B, but when the number of corrections exceeds a predetermined number, the decrease in the difference Er becomes smaller. Finally, the difference Er becomes almost negligible when correcting object B. Note that at this point (corresponding to the number of corrections k1), the decrease in the difference Er after correction relative to the difference Er before correction (before the start of the series of corrections) is small, but since there are multiple affected objects, the processor 11 also corrects the radio wave propagation characteristics of other target objects.

[0129] In the radio wave propagation model ML shown in Figure 7, in addition to object B, there is also the right wall W4 as an influencing object OB1. Therefore, the processor 11 then switches the target object to the right wall W4 and modifies the radio wave propagation characteristics of the target object by increasing the reflectivity of the right wall W4. In this case, as shown in graph portion gr22 of graph gr2, at the beginning of the modification of the radio wave propagation characteristics of the right wall W4, the difference Er gradually decreases as the number of modification iterations increases, and when the number of modification iterations exceeds a predetermined number, the decrease in the difference Er becomes smaller. Then, when the difference Er becomes less than or equal to the threshold th11 at the point corresponding to the number of modification iterations k2, step S32 in Figure 6B becomes No, and the modification of the radio wave propagation characteristics of each target object at this target location is terminated.

[0130] Figure 10 is a graph showing a third example of the change in differential Er in response to the correction of the radio wave propagation characteristics of the target object. The radio wave propagation model ML is the one shown in Figure 7, and the receiving point RP1 is assumed to be the target receiving point.

[0131] Figure 10 illustrates a correction pattern C where the difference Er does not become sufficiently small even after correcting the radio wave propagation characteristics of multiple target objects. For example, as in Figure 9, processor 11 first corrects the radio wave propagation characteristics of object B, and then corrects the radio wave propagation characteristics of the right wall W4. However, in Figure 10, even after correcting the radio wave propagation characteristics of the right wall W4 (after the decrease in difference Er becomes 0 or minimal), the difference Er is greater than or equal to the threshold th11. However, in the target path PT4, there are only two target objects, object B and the right wall W4, so it is not possible to correct the radio wave propagation characteristics using other objects OB. Therefore, processor 11 terminates the process (model optimization) in Figure 6B, even though the difference Er has not converged to less than or equal to the threshold th11.

[0132] In this way, the information processing device 10 can modify the radio wave propagation characteristics of target objects along the target path passing through the target receiving point. In this case, if the modification of the radio wave propagation characteristics of one target object is sufficient for one target receiving point, the information processing device 10 can complete the process by modifying the radio wave propagation characteristics of one target object. If the convergence of the difference Er is insufficient with the modification of the radio wave propagation characteristics of one target object for one target receiving point, the information processing device 10 can sequentially switch target objects and perform the modification of the radio wave propagation characteristics of the target objects.

[0133] As described above, the information processing device 10 of this embodiment compares the results of the radio wave propagation simulation at the candidate receiver point RPC with the results measured using a reception method that can estimate the direction of arrival of radio waves at the candidate receiver position MP, and extracts the candidate receiver point RPC with the largest difference Er. The information processing device 10 extracts the direction of arrival Rd of the maximum level at that candidate receiver point RPC, and extracts the path PT obtained by the radio wave propagation simulation that is close to that direction of arrival Rd of the maximum level. The information processing device 10 can improve the accuracy of the radio wave propagation model ML by optimizing the reflectivity and transmittance of the object OB on the path PT.

[0134] In other words, the information processing device 10 can optimize the radio wave propagation model ML based on actual measurement results at candidate measurement locations MP, rather than relying solely on statistical processing based on the results of radio wave propagation simulations. Furthermore, by taking into account the actual radio wave propagation conditions in real space RS, the reliability of the optimization of the radio wave propagation model ML is increased. By modifying the radio wave propagation characteristics of an object by taking into account the direction of arrival Rd of the maximum level based on the actual measurement results, a radio wave propagation model ML that is closer to reality can be obtained. In addition, the information processing device 10 can optimize the radio wave propagation model ML efficiently because it can optimize the radio wave propagation model ML using the candidate measurement receiving point RPC, which has the largest discrepancy between the measurement results and the simulation results (i.e., the largest difference Er), as the target receiving point.

[0135] Furthermore, the information processing device 10 can optimize an unoptimized radio wave propagation model ML by measuring radio waves in a real-space RS environment corresponding to the radio wave propagation model ML, and then optimizing the radio wave propagation model ML based on the measurement results. In this process, the information processing device 10 can automatically perform many processes related to determining candidate measurement locations MP and optimizing the radio wave propagation model ML. Therefore, even a person unfamiliar with wireless technology can easily determine candidate measurement locations MP, optimize the radio wave propagation model ML, or both simultaneously, in a short amount of time with similar quality.

[0136] In this embodiment, model optimization is illustrated based on the measured results at the measured candidate position MP in the real-space RS corresponding to the receiving point RP determined by the measured candidate position determination process shown in Figure 4, but this is not limited to this. The measured results used for model optimization are not limited to the measured results at the measured candidate position MP in the real-space RS corresponding to the receiving point RP determined by the measured candidate position determination process shown in Figure 4. For example, the measured results may be those measured at the measured candidate position MP in the real-space RS corresponding to all or part of all receiving points RP that can be received within the radio wave propagation area AR (for example, each intersection point where the grid lines shown in Figures 2A, 2B, and 7 intersect).

[0137] (Summary of the embodiment) Based on the above, this disclosure contains at least the following information. The components and other elements in parentheses are examples of those corresponding to the embodiments described above, but are not limited to these.

[0138] (Item 1) An information processing device (information processing device 10) equipped with a processor (processor 11), The aforementioned processor, A radio wave propagation model (radio wave propagation model ML) is obtained, which includes a radio wave propagation area (radio wave propagation area AR), which is a virtual space in which radio waves propagate, and an object (object OB) placed in the radio wave propagation area and having predetermined radio wave propagation characteristics. Using the aforementioned radio wave propagation model, a simulation of radio wave propagation is performed. Based on the results of the simulation, a candidate measurement location (candidate measurement location MP) is determined in real space (real space RS) for obtaining measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model. Information processing device.

[0139] This allows the information processing device to reduce the number of candidate locations where radio waves are actually measured in real space, while efficiently determining candidate locations for improving the radio wave propagation model using the measurement results. (Item 2) The aforementioned processor, Within the aforementioned radio wave propagation area, objects that affect reception at each receiving point (receiving point RP) capable of receiving radio waves (influencing object OB1) are extracted. Based on the extracted results, the measured candidate position MP is determined. The information processing device described in item 1.

[0140] This allows the information processing device to determine candidate locations for actual measurements where the radio wave propagation characteristics of objects affecting reception can be improved.

[0141] (Item 3) The aforementioned processor, The position in real space corresponding to the first receiving point (measured candidate receiving point RPC) where the number of objects affecting the reception is greatest is determined as the measured candidate position MP. The information processing device described in item 2.

[0142] This allows the information processing device to simultaneously improve the radio wave propagation characteristics of objects affecting reception at the first receiving point, and to determine a candidate measurement location that can improve the radio wave propagation model in a short time.

[0143] (Item 4) The aforementioned processor, The determination of the measured candidate position MP is repeated while excluding the first receiving point and any object that may affect the reception at the first receiving point. The information processing device described in item 3.

[0144] This allows the information processing device to sequentially change the objects affecting reception by sequentially changing the first receiving point, and to determine a list of candidate measurement locations that can extract all objects that are targets for improvement of radio wave propagation characteristics.

[0145] (Item 5) The aforementioned processor, Of the paths (path PT) through which the radio waves arriving at the aforementioned receiving point propagate, a second path that is received at a reception level below a certain level is excluded from the first path that is received at the maximum reception level. The information processing device described in item 2.

[0146] As a result, the information processing device can reduce the number of paths that need to be considered when determining the candidate location by excluding the reception results of paths with little influence from the reception results of each path at the receiving point, thereby reducing the processing load when determining the candidate location. In addition, the information processing device can minimize the impact on the accuracy of determining the candidate location.

[0147] (Item 6) The aforementioned processor, The process of determining the measured candidate location MP is terminated when the ratio of the number of objects on the path that were not excluded to the total number of objects in the radio wave propagation model falls below a threshold (threshold th1). The information processing device described in item 4.

[0148] This allows the information processing device to determine measured candidate locations so that it can improve the radio wave propagation model with the desired accuracy.

[0149] (Item 7) To obtain a radio wave propagation model ML having a radio wave propagation area, which is a virtual space where radio waves propagate, and objects placed in the radio wave propagation area that have predetermined radio wave propagation characteristics, This involves performing a simulation of radio wave propagation using the aforementioned radio wave propagation model ML, Based on the results of the simulation, a candidate measurement location MP is determined in real space for obtaining measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model ML. A method for determining candidate positions based on actual measurements.

[0150] As a result, the method for determining candidate positions by actual measurement yields the same effect as item 1.

[0151] Although various embodiments have been described above with reference to the drawings, it goes without saying that this disclosure is not limited to such examples. It is clear to those skilled in the art that various modifications or alterations can be conceived within the scope of the claims, and these will naturally also fall within the technical scope of this disclosure. Furthermore, the components of the above embodiments may be combined in any way without departing from the spirit of the invention.

[0152] Furthermore, the above embodiment may also apply to a program that implements the function of the measured candidate position determination method, which is supplied to a computer (e.g., an information processing device 10) via a network or various storage media, and which is read and executed by the processor of this computer, as well as a recording medium on which this program is stored. [Industrial applicability]

[0153] This disclosure is useful for an information processing device and a method for determining candidate locations for measured radio waves, which can efficiently determine candidate locations for measured radio waves in real space while reducing the number of candidate locations for measured radio waves, and using the measurement results to improve the radio wave propagation model. [Explanation of Symbols]

[0154] 5 Model Processing Systems 10 Information Processing Devices 11 processors 12 memory 13 Communication devices 14 Input Devices 15 Display Devices 20 Antenna equipment AR radio wave propagation area ML Radio Wave Propagation Model RS Real Space OB object OB1 Influence object SP transmission point PT, PT1, PT2, PT3, PT4, PT11, PT12, PT13, PT14 routes Direction of arrival of Rd maximum level RP, RP1, RP2 receiving points RPB Maximum Influence Receiving Point RPC measurement candidate receiving points W1 upper wall W2 Left Wall W3 lower wall W4 Right Wall

Claims

1. An information processing device equipped with a processor, The aforementioned processor, A radio wave propagation model is obtained, which includes a radio wave propagation area, which is a virtual space in which radio waves propagate, and objects placed in the radio wave propagation area that have predetermined radio wave propagation characteristics. Using the aforementioned radio wave propagation model, a simulation of radio wave propagation is performed. Based on the results of the simulation, candidate measurement locations are determined in real space for obtaining measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model. Information processing device.

2. The aforementioned processor, Objects that affect reception at each receiving point capable of receiving radio waves within the aforementioned radio wave propagation area are extracted. Based on the extracted results, the candidate positions for the actual measurements are determined. The information processing apparatus according to claim 1.

3. The aforementioned processor, The position in real space corresponding to the first receiving point where the number of objects affecting the reception is greatest is determined as the measured candidate position. The information processing apparatus according to claim 2.

4. The aforementioned processor, The determination of the measured candidate position is repeated while excluding the first receiving point and any object that may affect the reception at the first receiving point. The information processing apparatus according to claim 3.

5. The aforementioned processor, Of the paths through which radio waves arriving at the aforementioned receiving point propagate, a second path that receives the radio waves at a reception level below a certain level is excluded from the first path that receives the radio waves at the maximum reception level. The information processing apparatus according to claim 2.

6. The aforementioned processor, The process of determining the candidate positions for measurement is terminated when the ratio of the number of objects on the path that were not excluded to the total number of objects in the radio wave propagation model falls below a threshold. The information processing apparatus according to claim 4.

7. To obtain a radio wave propagation model comprising a radio wave propagation area, which is a virtual space where radio waves propagate, and objects placed in the radio wave propagation area that have predetermined radio wave propagation characteristics, This involves performing a simulation of radio wave propagation using the aforementioned radio wave propagation model, Based on the results of the simulation, the following is determined: In real space, candidate locations for obtaining measured values ​​to be used to modify the radio wave propagation characteristics of the radio wave propagation model are determined. A method for determining candidate positions based on actual measurements.

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