Measurement route design method, measurement route design device, and program

Abstract

According to the present invention, a computer is used to execute: a collection procedure of collecting first measurement information measured by a passive measurement; a communication state estimation procedure of estimating an estimation map representative of the communication state of each of a plurality of positions by using the first measurement information; and a design procedure of designing the measurement route of an active measurement by using the estimation map.

Description

[Technical Field]

[0001] The present disclosure relates to a measurement route design method, a measurement route design device, and a program. [Background technology]

[0002] Methods for detecting degradation of communication conditions based on data collected in the real world can be classified into two types: methods based on passive measurement and methods based on active measurement.

[0003] Passive measurement is a method of collecting measurement information, such as communication status reports, from user terminals that are distributed discretely in real space. Existing methods for detecting degradation of communication conditions based on passive measurement include, for example, the method described in Non-Patent Document 1. Active measurement, on the other hand, is a method in which a telecommunications carrier dispatches vehicles or UAVs (Unmanned Aerial Vehicles) equipped with measuring equipment to collect measurement information by measuring the communication conditions on-site. Many methods exist in the field of sensing that estimate some state based on active measurement; for example, Non-Patent Document 2 describes a method related to shape estimation using a measurement robot. Measurement information collected by passive and active measurement includes, for example, measurement location, measurement date and time, communication cell ID, radio wave strength, etc.

[0004] In recent years, wireless networks have become increasingly dense and higher frequency bands are being used, raising concerns about an increase in areas with poor communication performance due to an increase in the number of base station failures and the growing impact of obstructions. Furthermore, there is concern that base station failures and obstructions will increase communication degradation in localized areas (e.g., 10 to 100 meters) that will become more severe over time. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] F. Sohrabi and E. Kuehn, "Construction of the RSRP map using sparse MDT measurements by regression clustering," Proceedings of 2017 IEEE International Conference on Communications, pp. 1-6, May 2017. [Non-patent document 2] I. Abraham, A. Prabhakar, MJZ Hartmann and TD Murphey, "Ergodic Exploration Using Binary Sensing for Nonparametric Shape Estimation," IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 827-834, Apr. 2017. Summary of the Invention [Problem to be solved by the invention]

[0006] However, existing methods based on passive measurements are expected to have difficulty detecting degradation in communication conditions because the radius of communication cells shrinks as wireless networks become denser, reducing the amount of measurement information per cell. As a result, there may be areas where it is not possible to collect the amount of measurement information necessary to detect degradation in communication conditions.

[0007] On the other hand, because active measurement is generally expensive, it is often practically difficult to collect comprehensive measurement information from a wide area where you want to detect degradation in communication conditions. Furthermore, because suspected locations of communication degradation are scattered throughout the real world, it is difficult to determine effective measurement locations and routes for active measurement at low cost, even by manual methods based on know-how.

[0008] The present disclosure has been made in consideration of the above points, and provides a technology for efficiently detecting communication degradation. [Means for solving the problem]

[0009] A measurement route design method according to one embodiment of the present disclosure includes a computer-implemented collection procedure for collecting first measurement information measured by passive measurement, a communication status estimation procedure for estimating an estimated map representing the communication status at each location using the first measurement information, and a design procedure for designing a measurement route for active measurement using the estimated map. [Effects of the Invention]

[0010] According to the present disclosure, a technique for efficiently detecting communication degradation is provided. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of the overall configuration of a communication degradation detection system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a communication degradation detection device according to the present embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a communication degradation detection device according to the present embodiment. [Figure 4] 10 is a flowchart illustrating an example of a process for collecting passive measurement information. [Figure 5] 1 is a flowchart showing an example of measurement route design and active measurement processing (first embodiment); [Figure 6] 10 is a flowchart showing an example of measurement route design and active measurement processing (embodiment 2); [Figure 7] 10 is a flowchart illustrating an example of a communication degradation detection process. DETAILED DESCRIPTION OF THE INVENTION

[0012] An embodiment of the present invention will be described below, focusing on a communication degradation detection system 1 that can efficiently detect communication degradation in a high-density wireless network (i.e., a wireless network in which base stations are densely arranged and the radius of the communication cell is relatively small).

[0013] To efficiently detect communication degradation, this embodiment combines passive and active monitoring, and considers using both measurement information collected by passive monitoring and measurement information collected by active monitoring to detect communication degradation. Generally, the measurement location in passive monitoring is dependent on the location of the user terminal and therefore cannot be controlled. However, active monitoring allows measurement at any location. Therefore, measurement information collected by active monitoring can be used to complement measurement information collected by passive monitoring. This is because, while measuring the entire area where communication degradation is desired to be detected using active monitoring generally requires significant costs, by selecting only effective locations that complement measurement information collected by passive monitoring (e.g., locations in an area where measurement information collected by passive monitoring is sparse) and performing active monitoring at those locations, it is believed that measurement information capable of detecting communication degradation throughout the entire area can be collected within limited cost. Hereinafter, measurement information collected by passive monitoring will also be referred to as "passive measurement information," and measurement information collected by active monitoring will also be referred to as "active measurement information." On the other hand, when there is no distinction between the two or when it is clear from the context which is which, we will simply refer to it as "measurement information."

[0014] Note that, as an existing passive measurement method, for example, a method called MDT (Minimization of Drive Test) is known. Furthermore, as existing methods for detecting degradation of communication conditions based on passive measurement, the method described in Non-Patent Document 1 above and various other methods are known. Most of these conventional methods use a spatial interpolation method called Kriging. In addition to this, there are also methods that use deep learning to estimate base station failures.

[0015] On the other hand, there are many existing active measurement methods in the field of sensing, including the method described in Non-Patent Document 2 mentioned above, as well as various other known methods.

[0016] <Outline of communication degradation detection> In this embodiment, areas with poor communication performance are detected through the following six steps.

[0017] Step 1. Collect passive measurement information from user devices.

[0018] Step 2: Using the collected measurement information, the communication conditions at each location are estimated, and an estimated map is created showing the results.

[0019] Step 3. Design a measurement route for active measurement based on the estimated map obtained in Step 2 above.

[0020] Step 4. Conduct active measurement along the measurement route designed in Step 3 above to collect active measurement information.

[0021] Step 5: If the upper limit of the cost constraints, such as the number of measurements in active measurement, is met, terminate the active measurement and proceed to Step 6; if not, return to Step 2 and create an estimated map again.

[0022] Step 6: Create an estimated map of the communication situation using the measurement information collected through passive and active measurements, and detect areas with poor communication performance by comparing this estimated map with the expected communication situation.

[0023] At this time, in the above step 3, a measurement route for active measurement is designed using Bayesian optimization. That is, after estimating the communication situation using a Gaussian process in the above step 2, in the above step 3, the estimation result and a predetermined acquisition function are used to design a measurement route that optimizes the acquisition function. Note that in the above step 6, as in step 3, an estimation map is also created by estimating the communication situation using a Gaussian process.

[0024] <Problem definition and solution method> The problem setting and the method for solving the problem in this embodiment will be described.

[0025] We define optimal active measurement as the active measurement that minimizes the probability of overlooking communication degradation when it occurs, and consider the problem of sequentially finding optimal active measurements that satisfy certain constraints given passive measurement information.

[0026] Additionally, a location where communication degradation is occurring is defined as a point where the signal strength from a base station is lower than the value expected at the time of design by a threshold. A constraint on the number of active measurements is imposed as a constraint on the active measurement. That is, the number of active measurements is limited to a predetermined number T or less. Furthermore, the active measurements are performed along a continuous route, and the distance between two consecutive measurement points is assumed to be equal to or less than a predetermined constant value dist.

[0027] Active measurement allows us to obtain new measurement information about the communication situation, so in the above problem setting, instead of determining the measurement route of active measurement at the start of measurement, we can re-determine the next measurement position for each measurement. In other words, we can design the measurement route of active measurement sequentially.

[0028] In this embodiment, as a solution to the above problem, a method for designing a measurement route using a heuristic algorithm that uses Bayesian optimization is provided. Hereinafter, the communication conditions are assumed to be radio wave strength, and the measurement information includes at least the measurement point (measurement location) and radio wave strength. However, the communication conditions are not limited to radio wave strength, and may include information other than radio wave strength. Furthermore, the measurement information may include information such as the measurement date and time, a communication cell ID, etc., in addition to the measurement point and radio wave strength.

[0029] A Gaussian process is used to estimate the radio wave strength at each location. Furthermore, when designing a measurement route, an upper confidence bound (UCB) is used as a Monte Carlo acquisition function based on the estimated radio wave strength, and a measurement route that optimizes it is designed. However, UCB is only an example, and other acquisition functions may be used. As a method for designing such a measurement route, this embodiment provides two methods: a method based on a greedy algorithm (Example 1) and a method using the traveling salesman problem (TSP) (Example 2), as will be described later.

[0030] <Overall configuration of communication degradation detection system 1> An example of the overall configuration of a communication degradation detection system 1 according to this embodiment is shown in Fig. 1. As shown in Fig. 1, the communication degradation detection system 1 according to this embodiment includes a communication degradation detection device 10, a plurality of user terminals 20, and an active measurement observation device 30. Here, the communication degradation detection device 10 and each user terminal 20 are communicatively connected via a communication network including, for example, the Internet. Similarly, the communication degradation detection device 10 and the active measurement observation device 30 are communicatively connected via a communication network including, for example, the Internet.

[0031] The communication degradation detection device 10 collects passive measurement information from each user terminal 20, and then sequentially designs measurement routes that enable optimal active measurement, and collects active measurement information measured by the active measurement from the active measurement observation equipment 30. The communication degradation detection device 10 also detects communication degradation areas using the passive measurement information and the active measurement information.

[0032] The user terminals 20 are various terminals that transmit passive measurement information to the communication degradation detection device 10. Examples of the user terminals 20 include smartphones, wearable devices, and in-vehicle devices. Note that FIG. 1 shows n user terminals 20 (user terminal 201, user terminal 202, ..., user terminal 20 n ) is shown.

[0033] The observation device 30 for active measurement performs active measurement along a measurement route designed by the communication degradation detection device 10, and transmits measurement information measured by the active measurement to the communication degradation detection device 10. Examples of the observation device 30 for active measurement include various vehicles (automobiles, motorcycles, bicycles, etc.) equipped with a measurement device capable of measuring communication conditions, UAVs (unmanned aerial vehicles, drones, etc.), robots, and autonomous vehicles. However, the observation device 30 for active measurement is not limited to these, and may also be, for example, a portable terminal (smartphone, tablet terminal, wearable device, etc.) equipped with a measurement device capable of measuring communication conditions.

[0034] 1 is an example, and the overall configuration of the communication degradation detection system 1 is not limited to this. For example, the communication degradation detection system 1 may include a plurality of active measurement observation devices 30.

[0035] <Hardware Configuration of Communication Degradation Detection Device 10> An example of the hardware configuration of the communication degradation detection device 10 according to this embodiment is shown in Fig. 2. As shown in Fig. 2, the communication degradation detection device 10 according to this embodiment includes an input device 101, a display device 102, an external I / F 103, a communication I / F 104, a RAM (Random Access Memory) 105, a ROM (Read Only Memory) 106, an auxiliary storage device 107, and a processor 108. Each of these pieces of hardware is connected to each other via a bus 109 so as to be able to communicate with each other.

[0036] The input device 101 is, for example, a keyboard, a mouse, a touch panel, a physical button, etc. The display device 102 is, for example, a display, a display panel, etc. Note that the communication degradation detection device 10 does not necessarily have to include at least one of the input device 101 and the display device 102, for example.

[0037] The external I / F 103 is an interface with an external device such as a recording medium 103a. Examples of the recording medium 103a include a CD (Compact Disc), a DVD (Digital Versatile Disk), an SD memory card (Secure Digital memory card), and a USB (Universal Serial Bus) memory card.

[0038] The communication I / F 104 is an interface for connecting the communication degradation detection device 10 to a communication network. The RAM 105 is a volatile semiconductor memory (storage device) that temporarily stores programs and data. The ROM 106 is a non-volatile semiconductor memory (storage device) that can store programs and data even when the power is turned off. The auxiliary storage device 107 is a non-volatile storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The processor 108 is one of various arithmetic devices such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit).

[0039] 2 is an example, and the communication degradation detection device 10 may have other hardware configurations. For example, the communication degradation detection device 10 may have multiple auxiliary storage devices 107 and multiple processors 108, or may have various types of hardware other than the hardware shown in the figure.

[0040] <Functional configuration of communication degradation detection device 10> FIG. 3 shows an example of the functional configuration of the communication degradation detection device 10 according to this embodiment. As shown in FIG. 3, the communication degradation detection device 10 according to this embodiment includes a measurement information collection unit 201, a communication status estimation unit 202, a measurement route design unit 203, a measurement route setting unit 204, and a communication degradation detection unit 205. These units are realized, for example, by a processor 108 or the like executing one or more programs installed in the communication degradation detection device 10. The communication degradation detection device 10 according to this embodiment also includes a database 206. The database 206 can be realized, for example, by the auxiliary storage device 107 or the like. Note that the database 206 may also be realized, for example, by a storage device or the like connected to the communication degradation detection device 10 via a communication network.

[0041] The measurement information collector 201 collects passive measurement information from each user terminal 20. The measurement information collector 201 also collects active measurement information from the observation device 30 for active measurement.

[0042] The communication situation estimation unit 202 estimates the communication situation at each location by a Gaussian process using the measurement information collected by the measurement information collection unit 201. The estimation result is an estimated map.

[0043] The measurement route design unit 203 uses the communication conditions at each location estimated by the communication condition estimation unit 202 and the acquisition function to find a measurement route that optimizes the acquisition function. In this way, an optimal measurement route for active measurement is designed.

[0044] The measurement route setting unit 204 sets the measurement route designed by the measurement route design unit 203 in the active measurement observation device 30. As a result, active measurement is performed by the active measurement observation device 30 along the measurement route. However, the measurement route setting unit 204 may also display the measurement route on a terminal used by the driver or the like who drives the active measurement observation device 30.

[0045] The communication degradation detection unit 205 detects areas where communication is degraded by comparing the communication conditions at each location estimated by the communication condition estimation unit 202 with the originally expected communication conditions.

[0046] The database 206 stores the measurement information collected by the measurement information collection unit 201 .

[0047] <Processing details> Hereinafter, each process executed by the communication degradation detection device 10 according to this embodiment will be described in detail.

[0048] <Passive measurement information collection process> First, the process of collecting passive measurement information will be described with reference to FIG.

[0049] The measurement information collecting unit 201 of the communication degradation detecting device 10 collects passive measurement information from each user terminal 20 (S101).

[0050] Then, the measurement information collecting unit 201 of the communication degradation detecting device 10 stores the passive measurement information collected in the above S101 in the database 206 (S102).

[0051] <<Measurement Route Design and Active Measurement Processing (Example 1)>> Next, the design of a measurement route and the active measurement process in the first embodiment will be described with reference to FIG. 5. In this embodiment, a case will be described in which a measurement route is designed based on a greedy method and active measurement is performed along the measurement route. In designing a measurement route based on the greedy method, the active measurement observation device 30 is moved sequentially as far as possible toward the point where the acquisition function is highest. However, every time active measurement is performed, the radio wave intensity is estimated and the acquisition function is updated.

[0052] The measurement information collecting unit 201 of the communication degradation detecting device 10 acquires passive measurement information stored in the database 206 as an observation set D (S201). Hereinafter, the observation set D is defined as D={(x i ,y i )|i=1,···,|D|}, where x i is the measurement point included in the i-th measurement information, y i is the measurement point x i This represents the radio wave strength at

[0053] The measurement route design unit 203 of the communication degradation detection device 10 calculates a variable x representing the current measurement point. p That is, the measurement route design unit 203 sets the starting point to the variable x p is initialized to the starting point. The starting point is a predetermined point where active measurement begins.

[0054] The communication degradation detecting device 10 repeats S204 to S210 T times from iter=1 to iter=T, where it is a variable indicating the number of repetitions (S203). S204 to S210 in a certain repetition will be described below.

[0055] In S204, the communication status estimation unit 202 of the communication degradation detection device 10 estimates the communication status at each location by a Gaussian process using the observation set D. That is, when a variable representing the measurement point is x and a variable representing the call strength is y, y is expressed as a function of mean μ(x) and variance σ 2 (x) is a normally distributed random variable y~N(μ(x),σ2 (x)), the communication situation estimation unit 202 uses the observation set D to calculate μ(x) and σ 2 (x) is calculated. Note that the Gaussian process itself is an existing method, so a detailed explanation of it will be omitted.

[0056] In S205, the measurement route design unit 203 of the communication degradation detection device 10 calculates the mean μ(x) and variance σ 2 (x) to calculate the acquisition function UCB(x).

[0057] In S206, the measurement route design unit 203 of the communication degradation detection device 10 determines the point x where the acquisition function UCB(x) is maximized as x * Set to.

[0058] In S207, the measurement route design unit 203 of the communication degradation detection device 10 determines the current measurement point x p From point x * The point where we have progressed as far as possible within the distance dist towards x p The point as far as possible is a point that can be reached by the active measurement observation device 30, and for example, if the active measurement observation device 30 is a vehicle, it refers to a point that can be reached by driving on a road.

[0059] In S208, the measurement route setting unit 204 of the communication degradation detection device 10 sets the current measurement point x p is set in the active measurement observation equipment 30. As a result, the measurement point x p The radio wave strength of y p is measured by the active measurement observation device 30, and the measurement point x p and radio wave strength y p The active measurement information including the above is transmitted to the communication degradation detection device 10.

[0060] In S209, the measurement information collecting unit 201 of the communication degradation detecting device 10 p and radio wave strength y pThe active measurement information including the above is collected from the active measurement observation device 30.

[0061] In S210, the measurement information collecting unit 201 of the communication degradation detecting device 10 calculates (x p ,y p ) to the observation set D.

[0062] When the above steps S204 to S210 have been repeated T times, the measurement information collector 201 of the communication degradation detection device 10 stores the observation set D in the database 206 (S211). This results in the acquisition of the observation set D, which is made up of passive measurement information and active measurement information that complements the passive measurement information. As will be described later, this observation set D is used to detect communication degradation areas.

[0063] <<Measurement Route Design and Active Measurement Processing (Example 2)>> Next, the design of a measurement route and active measurement processing in the second embodiment will be described with reference to FIG. 6. In this embodiment, a case will be described in which a measurement route is designed using the traveling salesman problem (TSP) and active measurement is performed along the measurement route. In designing a measurement route using the TSP, T active measurements are divided into d portions, and radio wave intensity is estimated and the measurement route is redesigned for each T / d active measurement. Here, d is a value determined in advance by a user or the like. For simplicity, it is assumed below that T is a multiple of d. If T is not a multiple of d, for example, "the largest integer not exceeding T / d" can be used instead of "T / d" as appropriate.

[0064] The measurement information collecting unit 201 of the communication degradation detecting device 10 acquires the passive measurement information stored in the database 206 as an observation set D (S301). Hereinafter, the observation set D is defined as D={(x i ,y i )|i=1,···,|D|}, where x i is the measurement point included in the i-th measurement information, y i is the measurement point x i This represents the radio wave strength at

[0065] The measurement route design unit 203 of the communication degradation detection device 10 calculates a variable x representing the current measurement point. p That is, the measurement route design unit 203 sets the starting point to the variable x p Initialize to the starting point.

[0066] The communication degradation detecting device 10 repeats S304 to S308 d times from division=1 to division=d, with division being a variable representing the number of divisions (S303). S304 to S308 in a certain repetition will be described below.

[0067] In S304, the communication status estimation unit 202 of the communication degradation detection device 10 estimates the communication status at each location by a Gaussian process using the observation set D. That is, when a variable representing the measurement point is x and a variable representing the call strength is y, y is expressed as a function of mean μ(x) and variance σ 2 (x) is a random variable y~N(μ(x),σ 2 (x)), the communication situation estimation unit 202 uses the observation set D to calculate μ(x) and σ 2 Calculate (x).

[0068] In S305, the measurement route design unit 203 of the communication degradation detection device 10 calculates the mean μ(x) and variance σ 2 (x) to calculate the acquisition function UCB(x).

[0069] In S306, the measurement route design unit 203 of the communication degradation detection device 10 selects the top S points with the highest values ​​of the acquisition function UCB(x) as {x1, . . . , x S}. This can be determined by, for example, a gradient method. Note that S is a predetermined value.

[0070] In S307, the measurement route design unit 203 of the communication degradation detection device 10 p}∪{x1,···,x S}, calculate the route R that is the solution to the traveling salesman problem. The travel cost of the traveling salesman problem is the distance between each point. The solution to the traveling salesman problem can be calculated using known methods.

[0071] In S308, the communication degradation detecting device 10 repeats S309 to S312 T / d times from iter=1 to iter=T / d, with iter being a variable indicating the number of repetitions. S309 to S312 in a certain repetition will be described below.

[0072] In S309, the measurement route design unit 203 of the communication degradation detection device 10 determines the current measurement point x p The point at a distance dist along the route R from p Set to.

[0073] In S310, the measurement route setting unit 204 of the communication degradation detection device 10 sets the current measurement point x p is set in the active measurement observation equipment 30. As a result, the measurement point x p The radio wave strength of y p is measured by the active measurement observation device 30, and the measurement point x p and radio wave strength y p The active measurement information including the above is transmitted to the communication degradation detection device 10.

[0074] In S311, the measurement information collecting unit 201 of the communication degradation detecting device 10 p and radio wave strength y p The active measurement information including the above is collected from the active measurement observation device 30.

[0075] In S312, the measurement information collecting unit 201 of the communication degradation detecting device 10 calculates (x p ,y p ) to the observation set D.

[0076] When the above steps S304 to S308 have been repeated d times, the measurement information collector 201 of the communication degradation detection device 10 stores the observation set D in the database 206 (S313). This results in the acquisition of the observation set D, which is composed of passive measurement information and active measurement information that complements the passive measurement information. As will be described later, this observation set D is used to detect communication degradation areas.

[0077] <Communication degradation detection process> Finally, the communication degradation detection process will be described with reference to Fig. 7. It is assumed that the observation set D is composed of passive measurement information and active measurement information.

[0078] The measurement information collecting unit 201 of the communication degradation detecting device 10 acquires the observation set D stored in the database 206 (S401).

[0079] Next, the communication status estimation unit 202 of the communication degradation detection device 10 estimates the communication status at each location by a Gaussian process using the observation set D (S402). That is, when the variable representing the measurement point is x and the variable representing the call strength is y, y is expressed as a function of mean μ(x) and variance σ 2 (x) is a random variable y~N(μ(x),σ 2 (x)), the communication situation estimation unit 202 uses the observation set D to calculate μ(x) and σ 2 (x) is calculated. This allows obtaining an estimated map that shows the estimated results of the radio wave strength at each position (i.e., the distribution of the radio wave strength at each position).

[0080] Then, the communication degradation detection unit 205 of the communication degradation detection device 10 detects a communication degradation area by comparing the estimated map obtained in S402 with the originally expected communication conditions (S403). That is, the communication degradation detection unit 205 compares the estimated map with the originally expected communication conditions, and if the radio wave strength at a certain position in the estimated map is lower than the radio wave strength representing the originally expected communication conditions by more than a threshold, detects the position as a communication degradation area.

[0081] <Summary> As described above, the communication degradation detection device 10 according to this embodiment can perform optimal active monitoring when passive measurement information is given, while satisfying constraints related to active monitoring (e.g., cost constraints such as the number of measurements and distance). This makes it possible to detect communication degradation occurring in a high-density network at low cost. It also makes it possible to detect communication degradation occurring in areas with little passive measurement information, thereby reducing areas of communication degradation that would have been overlooked by conventional methods. This makes it possible to prevent localized communication degradation, which increases with network density, from becoming so severe that it becomes fatal, thereby improving service quality.

[0082] The present invention is not limited to the above-described specifically disclosed embodiments, and various modifications, changes, and combinations with known technologies are possible without departing from the scope of the claims. [Explanation of symbols]

[0083] 1. Communication degradation detection system 10. Communication degradation detection device 20 User terminal 30 Active measurement equipment 101 Input Device 102 Display device 103 External I / F 103a Recording media 104 Communication I / F 105 RAM 106 ROM 107 Auxiliary storage 108 processors 109 Bus 201 Measurement Information Collection Department 202 Communication Status Estimation Unit 203 Measurement Route Design Department 204 Measurement route setting section 205 Communication Degradation Detection Unit 206 Database

Claims

1. A collection procedure for collecting first measurement information measured by passive measurement, which is a measurement method for collecting measurement information from user terminals discretely distributed in real space; a communication status estimation step of estimating an estimated map representing a communication status at each location using the first measurement information; a design procedure for designing a measurement route for active measurement, which is a measurement method in which a communication carrier measures communication conditions by dispatching a mobile object equipped with a measurement device, using the estimation map; A computer-implemented measurement route design method.

2. The communication status estimation step includes: The measurement route design method according to claim 1 , further comprising: estimating a communication situation at each location by a Gaussian process using the first measurement information; and estimating the estimation result as an estimated map.

3. The design procedure is as follows:

3. The measurement route design method according to claim 1, wherein the measurement route is designed using the estimation map and a predetermined acquisition function, with a position that maximizes the acquisition function being set as the measurement position where the next active measurement is to be performed.

4. The design procedure is as follows: using the estimation map and a predetermined acquisition function, identifying a predetermined number of positions having the largest values ​​of the acquisition function; A route that travels between the specified number of locations and the measurement location of the current active measurement is calculated as a solution to a traveling salesman problem; 3. The measurement route design method according to claim 1, wherein the measurement route is designed by setting a position reached by movement along the route within a predetermined cost as the next measurement position for active measurement.

5. The communication status estimation step includes: re-estimating the estimation map using second measurement information indicating measurement results of active measurement along the measurement route; The design procedure is as follows: The measurement route design method according to claim 1 , further comprising the step of redesigning the measurement route using the re-estimated estimation map.

6. The measurement route design method according to claim 1 , further comprising a setting step of setting the measurement route in a vehicle or UAV that is a moving body that performs the active measurement.

7. A collection unit configured to collect first measurement information measured by passive measurement, which is a measurement method for collecting measurement information from user terminals that are discretely distributed in real space; a communication situation estimation unit configured to estimate an estimated map representing a communication situation at each position using the first measurement information; a design unit configured to use the estimation map to design a measurement route for active measurement, which is a measurement method in which a communication carrier measures communication conditions by dispatching a mobile object equipped with a measurement device; and A measurement route design device having the above.

8. A program for causing a computer to execute the measurement route design method according to any one of claims 1 to 5.

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