JP5529306B1 - Information processing apparatus and information processing method - Google Patents

Abstract

An information processing apparatus and an information processing method capable of detecting a change in the operating status of a sector by a simple method and improving the accuracy of population estimation are provided.
An information processing apparatus is configured to perform a first operation based on traffic data obtained by counting the number of location registration signals from a mobile terminal acquired for each sector formed by one or more radio base stations in a predetermined time unit. A totaling unit that counts the number of location registration signals collected in each period for each sector, and totals the number of location registration signals collected in a second period after the first period for each sector; And detecting means for detecting a change in the operating status of the sector between the first period and the second period for each sector based on the counting result.
[Selection] Figure 2

Description

  The present invention particularly relates to an information processing apparatus and an information processing method for detecting a change in sector operation status of a radio base station.

  The portable terminal performs location registration with respect to the sector which is the power range of the antenna of the radio base station. 2. Description of the Related Art Conventionally, a technique for estimating the population in each sector based on the number of mobile terminals whose locations are registered with respect to the sector of each radio base station is known. In order to accurately estimate the population of an area on an actual map by such a technique, it is necessary to accurately estimate the geographical coverage (sector power range) for each sector.

JP 2003-32731 A

  The estimation of the sector influence range for each sector is performed based on data such as position information (eg, GPS position information) acquired from the mobile terminal. In order to acquire a sufficient amount of data for estimation, In areas where the population density is low, a long period may be required. For this reason, there may be a difference between the data collection period for estimating the sector power range for each sector and the population estimation target period, and the operating status of the sectors in both periods may be different. In such a case, at the time of population estimation, the population distribution is estimated based on a sector power range different from the actual one, and the population estimation accuracy may be reduced.

  Therefore, if it is possible to detect changes in the operating status of the sector during both periods before performing such population estimation, it is possible to prevent the population estimation from being performed based on a sector power range different from the actual one. it is conceivable that. In addition, it is expected that the estimation accuracy can be improved by performing pre-processing according to changes in the operating status of the sector. In this connection, a technology is known in which a radio base station identifies a position on a map of a terminal based on a received voltage value of a base station control signal received from a mobile terminal, and creates a map of a service area of the base station. (See, for example, Patent Document 1 above).

  However, in the method of Patent Document 1, calculation processing for grasping the position of each mobile terminal based on information received from the mobile terminal, and the position of the mobile terminal farthest from the radio base station for each azimuth group are mapped. Complex calculation processing such as calculation processing mapped above is necessary, and it is difficult to say that changes in the operating status of the sector can be easily detected.

  Therefore, an object of the present invention is to provide an information processing apparatus and an information processing method capable of detecting changes in the operating status of a sector by a simple method and improving the accuracy of population estimation.

The information processing apparatus according to the present invention is collected in the first period based on traffic data obtained by counting the number of location registration signals from mobile terminals obtained for each sector formed by one or more radio base stations. Based on the summation means for summing up the number of location registration signals for each sector, and for summing up the number of location registration signals collected in the second period after the first period for each sector, Detecting means for detecting, for each sector, a change in the operating status of the sector between the first period and the second period. For each period of the first period and the second period, the aggregating means is based on adjacent sector information in which information indicating adjacent sectors adjacent to the sector is associated in advance for each sector, and a position registration signal for each sector alone The sector-only traffic value based on the number and the traffic value including the adjacent sector based on the sum of the number of position registration signals of the sector and the adjacent sector of the sector are aggregated for each sector. The detecting means detects a change in the operating status of each sector based on the sector-only traffic value and the adjacent-sector-incorporated traffic value in each of the first period and the second period.

An information processing method according to the present invention is an information processing method executed by the information processing apparatus, and counts the number of location registration signals from portable terminals acquired for each sector formed by one or more radio base stations. Based on the traffic data, the number of location registration signals collected in the first period is totaled for each sector, and the number of location registration signals collected in the second period after the first period is calculated for each sector. And a detecting step for detecting, for each sector, a change in the operating status of the sector between the first period and the second period based on the counting result in the counting step. In the counting step, for each period of the first period and the second period, a position registration signal for each sector alone based on adjacent sector information in which information indicating adjacent sectors adjacent to the sector is associated in advance for each sector. The sector-only traffic value based on the number and the traffic value including the adjacent sector based on the sum of the number of position registration signals of the sector and the adjacent sector of the sector are aggregated for each sector. In the detection step, a change in the operating status of the sector is detected for each sector based on the sector-only traffic value and the adjacent sector-incorporated traffic value in each of the first period and the second period.

  According to such a form, the location registration signal for each sector in each of the first period and the second period based on operational data (traffic data) collected and aggregated by a radio base station or the like on a daily basis. Numbers can be aggregated. A change in the operating status of the sector can be detected on the basis of the total result. More specifically, for example, the sector operation in the data collection period (first period) and the population estimation target period (second period) for estimating the geographical coverage (sector power range) for each sector. When the situation is different, a change in the operating status of the sector can be detected by a simple method based on the traffic data. Further, when a change in the operating status of the sector is detected, it is possible to prevent the population from being estimated based on a sector power range different from the actual one. Furthermore, it is possible to give an opportunity to execute the process according to the detected change in the operating status of the sector before the population is estimated. As described above, it is possible to improve the population estimation accuracy.

For example, when the fluctuation of the traffic value of the sector alone is large between the first period and the second period, and the fluctuation of the traffic value including the adjacent sector is also large, the fluctuation of the traffic value is It is highly probable that it is not due to changes in operating conditions but to changes in population distribution. On the other hand, when the fluctuation of the traffic value of the sector alone is large and the fluctuation of the traffic value including the adjacent sector is small between the first period and the second period, the accommodation relationship between the adjacent sectors is changed. It is highly probable that the sector's power range has changed. In the information processing apparatus and the information processing method , in accordance with the above-described concept, the traffic value including the adjacent sector including the adjacent sector of the sector is considered together with the traffic value of the sector alone. This makes it possible to determine whether the change in traffic value is due to a change in the population distribution or a change in the operating status of the sector. Therefore, it is possible to detect a change in the operating status of the sector with higher accuracy.

  Further, in the information processing apparatus, the detection unit is configured such that, for each sector, the sector single traffic value in the first period is equal to or greater than a predetermined threshold, and the sector single traffic value in the second period is equal to or less than the predetermined threshold. In addition, sector inactivity indicating a sector operation stop as a change in the operation status of the sector may be detected. As a result, it is possible to detect a change in the operating status of the sector (sector non-operating) by a simple calculation process while suppressing erroneous detection by excluding sectors with low traffic from the target of non-operating detection.

  Further, in the information processing apparatus, the detection unit includes, for each sector, each unit period obtained by dividing the second period every predetermined time when the sector single traffic value in the first period is equal to or greater than a predetermined threshold. It is determined whether or not the number of location registration signals of the sector alone in the unit period is 0, and the number of unit periods in which the number of location registration signals of the sector alone is 0 is equal to or greater than a predetermined number, Sector non-operation indicating the operation stop of the sector may be detected as a change in the operation status of the sector. As a result, the non-operating state (sector-only position registration signal generated in a part of the second period is suppressed while suppressing erroneous detection by excluding sectors with low traffic from the target of non-operating detection. It is possible to detect the sector non-operation more accurately based on the detected number of periods.

  Further, in the information processing apparatus, the detection unit includes, for each sector, a ratio between the sector single traffic value in the first period and the sector single traffic value in the second period, and the adjacent sector-included traffic value in the first period. And a change in the sector power indicating the change in the power of the sector as a change in the operating status of the sector may be detected based on the ratio between the traffic value including the adjacent sector in the second period. As a result, a change in the operating status of the sector (sector power change) can be detected by a simple calculation process.

  In the information processing apparatus, the first period collects measurement data including information in which the positioning position information of the mobile terminal obtained by the predetermined positioning is associated with the sector identifier of the sector where the mobile terminal is located. The information processing apparatus is configured to convert a predetermined calculated value for each sector, which is generated based on the measurement data collected in the first period, into a value for each predetermined output unit area. You may further provide the correction | amendment means which correct | amends the conversion information used based on the detection result by a detection means. As a result, the conversion information generated based on the measurement data collected in the data collection period (first period) for creating the conversion information is appropriately reflected on the detected change in the operating status of the sector. Information can be corrected. Therefore, more appropriate conversion information can be obtained as the conversion information used in population estimation.

  In the information processing apparatus, when the detection unit detects a sector non-operation, the correction unit outputs an output having a portion geographically overlapping the sector power range of the sector in which the sector non-operation is detected in the conversion information. The portion related to the unit area may be replaced with the second conversion information created based on the measurement data after excluding the information about the sector in which the sector malfunction was detected from the measurement data collected in the first period. . Further, when the sector power change is detected by the detection means, the correction means, regarding the portion related to the output unit area having a portion geographically overlapping with the sector power range of the sector in which the sector power change is detected in the conversion information, You may substitute with the 3rd conversion information produced | generated based on the position registration signal and the propagation delay amount of the said position registration signal. In this way, population conversion can be estimated by appropriately replacing the conversion information for the location corresponding to the sector where the change in sector operation status (sector inactivity / sector power change) has occurred. More appropriate conversion information can be used as the conversion information used in the process.

  According to the present invention, it is possible to detect a change in the operating status of a sector by a simple method and improve population estimation accuracy.

1 is a system configuration diagram of a communication system including an information processing apparatus according to an embodiment of the present invention. It is a block diagram which shows the function structure of the area conversion information creation apparatus containing the information processing apparatus which concerns on this embodiment. It is a figure which shows the example of an adjacent sector. It is a figure which shows the example of the estimation point of k neighborhood method. It is a figure which shows the example of an area influence diagram. It is a figure which shows the initial area conversion information based on the area influence chart of FIG. It is a figure which shows the example of a data collection period when a data collection period does not overlap, and a population estimation object period. It is a figure which shows the example of a data collection period in case data collection periods overlap, and a population estimation object period. It is a figure which shows the data flow in the process of a total part and a sector operating condition change detection part. It is a figure which shows the flow of the data in the process of an area conversion information correction | amendment part. It is a figure which shows the example of a detection of a sector power change. It is explanatory drawing of the correction process with respect to a non-working sector. It is a figure which shows non-operation partial area conversion information. It is a figure which shows the hardware constitutions of the information processing apparatus which concerns on this embodiment. It is a flowchart which shows operation | movement of the total part of the information processing apparatus which concerns on this embodiment, and a sector operation condition change detection part. It is a flowchart which shows operation | movement of the information processing apparatus area conversion information correction part which concerns on this embodiment. It is a figure which shows the example of arrangement | positioning other than this embodiment of the estimation point which estimates the main power sector by k vicinity method.

  An embodiment of an information processing apparatus and an information processing method according to the present invention will be described with reference to the drawings. If possible, the same parts are denoted by the same reference numerals, and redundant description is omitted.

  FIG. 1 is a system configuration diagram of a communication system 1000 including an information processing apparatus according to the present embodiment. As shown in FIG. 1, the communication system 1000 includes a mobile terminal 100, a BTS (radio base station) 200, an RNC (radio control device) 300, an exchange 400, various processing nodes 700, and a management center 500. Yes. The management center 500 includes a social sensor unit 501, a petamining unit 502, a mobile demography unit 503, and a visualization solution unit 504.

  The exchange 400 collects location information of the mobile terminal 100 via the BTS 200 and the RNC 300. The RNC 300 can measure the position of the mobile terminal 100 using a position registration signal from the mobile terminal 100, a delay value in the RRC connection request signal, or the like when communication connection is performed with the mobile terminal 100. The exchange 400 can receive the position information of the mobile terminal 100 measured in this way when the mobile terminal 100 executes communication connection. The exchange 400 stores the received position information, and outputs the collected position information to the management center 500 at a predetermined timing or in response to a request from the management center 500.

  The various processing nodes 700 acquire the position information of the portable terminal 100 through the RNC 300 and the exchange 400, perform recalculation of the position depending on the case, and collect it at a predetermined timing or in response to a request from the management center 500 The obtained position information is output to the management center 500.

  As described above, the management center 500 includes the social sensor unit 501, the petamining unit 502, the mobile demography unit 503, and the visualization solution unit 504. In each unit, the location information of the mobile terminal 100 is used. Perform statistical processing.

  The social sensor unit 501 is a server device that collects data including location information of the mobile terminal 100 from each exchange 400 and various processing nodes 700 or offline. The social sensor unit 501 receives data periodically output from the exchange 400 and the various processing nodes 700, or acquires data from the exchange 400 and the various processing nodes 700 according to a predetermined timing in the social sensor unit 501. It is configured to be able to do.

  The petamining unit 502 is a server device that creates statistical information from data received from the social sensor unit 501. For example, the petamining unit 502 removes personal identification from the measurement data including the position information of the mobile terminal 100 received from the social sensor unit 501. Then, the estimated population and the like for each predetermined output unit area are calculated as statistical information based on the processed data.

  The mobile demography unit 503 is a server device that performs aggregation processing using the statistical information created in the petamining unit 502, that is, count processing for each item. For example, the mobile demography unit 503 can count the number of users residing in a certain area, and can total the distribution of the residing areas.

  The visualization solution unit 504 is a server device that processes the data aggregated in the mobile demography unit 503 so as to be visible. For example, the visualization solution unit 504 can map the aggregated data on a map. The data processed by the visualization solution unit 504 is provided to companies, government offices, or individuals, and used for store development, road traffic surveys, disaster countermeasures, environmental countermeasures, and the like. It should be noted that the information statistically processed in this way is processed so that individuals are not specified so as not to infringe privacy.

  The social sensor unit 501, the petamining unit 502, the mobile demography unit 503, and the visualization solution unit 504 are all configured by the server device as described above, and although not shown, the basic configuration of a normal information processing device Needless to say, it includes a CPU, a RAM, a ROM, an input device such as a keyboard and a mouse, a communication device that communicates with the outside, a storage device that stores information, and an output device such as a display and a printer.

  FIG. 2 is a block diagram illustrating a functional configuration of the area conversion information creation device 1 including the information processing device 20. The area conversion information creation device 1 is one of the devices constituting the petamining unit 502 described above, and creates area conversion information (conversion information) used to calculate an estimated population value for each output unit area (area). It is a device to do. “Area conversion information” is information used to convert an estimated population value calculated for each sector formed by the base station into an estimated population value for each output unit area, as will be described later.

  As illustrated in FIG. 2, the area conversion information creation device 1 includes an initial area conversion information generation unit 10, an information processing device 20, and an area conversion information output unit 30. The area conversion information creating apparatus 1 includes a map data storage unit 51, a measurement data storage unit 52, a traffic data storage unit 53, and an adjacent sector information storage unit 54 that store various data in advance. The information processing apparatus 20 includes a totaling unit 21, a sector operation status change detection unit 22, and an area conversion information correction unit 23.

  First, various data used for processing of the area conversion information creation device 1 will be described.

  The map data storage unit 51 stores, for example, map data indicating the shape of land that is the target of population estimation in prefectures and the like. “Map data” may employ polygon data on a plane in which the shape of the land is specified by information indicating latitude and longitude.

  In the measurement data storage unit 52, measurement data measured on the mobile terminal 100 side is collected and stored by the social sensor unit 501 described above. “Measurement data” includes position information (latitude / longitude) of the mobile terminal 100 acquired by GPS, a sector identifier for identifying the sector where the mobile terminal 100 is located, and a reference signal associated with the sector identifier. Area quality information including reception power, signal-to-noise ratio, path loss (propagation loss of radio waves from the radio base station), and the like are included. Here, the sector identifier included in the measurement data may include a plurality of sector identifiers (sector identifiers of sectors having the first to nth powers).

  The traffic data storage unit 53 stores operation data (traffic data) collected by the social sensor unit 501 described above. “Traffic data” is data in which the number of location registration signals from the portable terminal 100 acquired for each sector in a predetermined time (for example, 10 minutes) is tabulated. That is, the traffic data is data obtained by tabulating the number of users accommodated in the sector for each sector in a predetermined time unit.

  The adjacent sector information storage unit 54 stores, for each sector, information indicating a list of adjacent sectors geographically adjacent to the sector (adjacent sector list). FIG. 3 is a conceptual diagram showing an example of adjacent sectors. However, FIG. 3 schematically shows an example of adjacent sectors to the last, and does not define the actual adjacent relationship of sectors. FIG. 3A is a diagram illustrating an example in the case of no sector division. Each of the areas indicated by AG in the figure indicates a single sector formed by the base station. In this case, the sectors adjacent to the sector A are sectors B to G. Therefore, in this case, “sectors B, C, D, E, F, G” are stored in the adjacent sector list as sectors adjacent to the sector A. FIGS. 3B and 3C are diagrams showing examples of adjacent sectors when the number of sectors per base station is divided into three and six, respectively. An area surrounded by a broken line in each figure indicates an area including the sector A1 and a sector adjacent to the sector A1.

  In addition, the geographically identical area includes a geographical coverage area of a plurality of sectors having different frequency bands (for example, 2.0 GHz band, 1.7 GHz band, 800 MHz band, etc.). (Hereinafter referred to as “sectoral power range”) may overlap. In this case, sectors that are in the same geographical area and correspond to different frequency bands can be considered as adjacent sectors. In other words, geographically adjacent sectors can be regarded as adjacent sectors in the same frequency band, and sectors corresponding to different frequency bands can be regarded as adjacent sectors in the geographically identical region. However, in the present embodiment, in order to simplify the description, a case will be described in which only a sector corresponding to a certain frequency band is targeted.

  Next, various processing units of the area conversion information creation device 1 will be described in order.

  The initial area conversion information generation unit 10 is a functional element that generates initial area conversion information (corresponding to “conversion information” in the claims). As an example in this embodiment, the initial area conversion information generation unit 10 estimates the sector power range of each sector so that the power ranges do not overlap between sectors by the k-nearest neighbor method, and the estimated sector power range of each sector is calculated. Based on this, initial area conversion information is generated. The initial area conversion information is information that is corrected as necessary by the information processing apparatus 20 to be described later and is the basis of area conversion information that is finally used for population estimation.

  A procedure for generating initial area conversion information will be described. First, the initial area conversion information generation unit 10 acquires map data from the map data storage unit 51, and determines the area indicated by the map data according to the size (area) of the output unit area as a grid cell (hereinafter referred to as “area”). Divided into “power estimation cells”). For each area power estimation cell, the initial area conversion information generation unit 10 determines, for example, whether or not the center point of the area power estimation cell is within the aggregation target area based on the latitude and longitude of the center point and the map data. The center point determined to be within the area to be counted is set as an estimated point, and information relating the latitude and longitude of the estimated point is acquired. The “estimated point” is a position coordinate of a target for estimating a sector (main power sector) as a main power by the k-nearest neighbor method.

  FIG. 4 shows an example of estimated points created by the above-described method when Kanagawa Prefecture data is acquired as map data. A black circle point written at the center of the area power estimation cell is an estimated point. Here, the interval between the estimation points, that is, the length of one side of the area force estimation cell is not limited to the above example, and may be set, for example, at intervals of several tens of meters. Note that the estimation point determination method is not limited to the above-described method. For example, if an area subject to aggregation (land in Kanagawa Prefecture) is included in the area power estimation cell, the area power estimation cell of the area power estimation cell The center point may be an estimated point. In addition, for example, when the area power estimation cell includes both the land of the prefecture to be counted and the land of the prefecture not to be counted, the estimated point of the area power estimation cell Set the weighting according to the area ratio occupied by the neighboring prefectures to be counted and multiply the calculated value for the area power estimation cell by the weight to obtain the total value in the counting target area. Also good.

  The initial area conversion information generation unit 10 acquires measurement data collected in a predetermined data collection period (first period) from the measurement data storage unit 52, and uses the position information (latitude and latitude) of the mobile terminal 100 from each measurement data. Longitude) and sector identifier are extracted. If the measurement data includes a plurality of sector identifiers, the sector identifier having the first power is extracted. Then, the initial area conversion information generation unit 10 acquires a learning point that associates the extracted position information and sector identifier. The “learning point” is learning information used when the main power sector at each estimation point is estimated by the k-nearest neighbor method. Here, the “data collection period” refers to a period necessary for the initial area conversion information generation unit 10 to obtain a sufficient amount of learning points for generating the initial area conversion information.

  The initial area conversion information generation unit 10 obtains the estimated points and the learning points as described above, and then executes on the map in an execution unit region (for example, about 10 km square secondary mesh) that collectively executes the analysis by the k-nearest neighbor method. Divide the area. The execution unit area is appropriately determined according to the processing capability of the area conversion information generation apparatus 1, for example. The initial area conversion information generation unit 10 performs an analysis by a k-nearest neighbor method using a learning point for each estimated point included in each execution unit region, and determines a sector identifier of a main power sector estimated for the estimated point. get.

  The initial area conversion information generation unit 10 acquires information of an area power map in which the sector identifier of the main power sector is mapped to the area power estimation cell including each estimated point by the above-described processing. FIG. 5 shows an example of the area influence chart. In FIG. 5, the smallest cell surrounded by a broken line indicates an area power estimation cell which is a mesh of about 50 m square in which the main power sector is estimated by the above-described method. One alphabetic character (A to E) in the cell indicates a sector identifier. The cell in which the alphabet is not described is a cell in which the sector corresponding to the sector identifier other than the sector identifiers A to E is estimated as the main power sector, and is ignored here. A 500 m square area surrounded by thick frame lines each including 10 area influence estimation cells vertically and horizontally indicates an output unit area.

  The output unit area is, for example, a cubic mesh (reference area mesh) of about 1 km square, a half area mesh of about 500 m square, a quarter area mesh of about 250 m square, and an eighth of about 125 m square. One regional mesh is used. In the example of FIG. 5, a half area mesh is used as the output unit area. Each output unit area is given a regional mesh code, that is, an area identifier. For the sake of explanation, the area identifiers of the upper left, upper right, lower left, and lower right output unit areas in FIG. 5 are represented as “TL”, “TR”, “BL”, and “BR”, respectively.

  The initial area conversion information generation unit 10 calculates the sector power ratio for each output unit area for each sector, thereby associating the initial area conversion with the sector identifier, the area identifier, and the sector power ratio as shown in FIG. Generate information. The sector power ratio is a value obtained by allocating the sector power ratio to each output unit area so that the total sum is 1 for each sector. That is, the sector power ratio of a sector for a certain output unit area is the number of area power estimation cells in which the sector is the main power in the output unit area, and the cell in which the sector is the main power in all output unit areas. It is the value divided by the number (total number of cells). Therefore, for example, the sector power ratio of the sector with the sector identifier “A” to the output unit area with the area identifier “TL” is obtained as “0.882352 (= 30/34)”. For example, when a predetermined total value for the sector with the sector identifier “A” is multiplied by the power ratio “0.882352”, the area identifier “TL” is output from the predetermined total value for the sector with the sector identifier “A”. A total value associated (distributed) with the unit area is calculated.

  Note that the output unit area does not necessarily have to be a square area as described above. For example, an area in units of municipalities may be used as the output unit area. In that case, by assigning a code that identifies the municipality to each area power estimation cell, the ratio of the number of area power estimation cells corresponding to each municipality included in each sector (sector power ratio to each municipality) And the initial area conversion information can be created in the same manner as described above.

  Next, the information processing apparatus 20 will be described. First, using FIG. 7 and FIG. 8, the relationship between the data collection period (first period) in which measurement data used for generating the initial area conversion information is collected and the population estimation target period (second period) Will be described. FIG. 7 is a diagram illustrating an example of a data collection period and a population estimation target period when the data collection periods do not overlap. FIG. 8 is a diagram illustrating an example of a data collection period and a population estimation target period when the data collection periods overlap.

  First, the example of FIG. 7 will be described. A period T1 between time points t0 and t1 illustrated in FIG. 7 corresponds to a data collection period (first period) for the initial area conversion information generation unit 10 to generate the initial area conversion information A. Similarly, the period between the time points t1 and t2 and the period between the time points t2 and t3 are data collection periods (first periods) for the initial area conversion information generation unit 10 to generate the initial area conversion information B and C, respectively. It corresponds to. As described above, the initial area conversion information generation unit 10 generates (updates) the initial area conversion information based on the periodically collected measurement data.

  The population estimation target period is, for example, each period repeated in a preset population estimation cycle unit (for example, one hour unit), and any date and time zone can be the population estimation target period. A period T2 in FIG. 7 shows an example of a population estimation target period (second period) after the data collection period T1.

  Next, the example of FIG. 8 will be described. In this example, data collection for generating the initial area conversion information B is started at a time t4 before the completion time t1 of the data collection period T1 for generating the initial area conversion information A. Similarly, data collection for generating the initial area conversion information C is started before the completion time t2 of the data collection period for generating the initial area conversion information B (time t1 in this example). Thus, if the data collection periods are overlapped (overlapped) and the data collection is performed in parallel, the initial area conversion information is updated more frequently than in the case of FIG. Can be expected to maintain its freshness. However, since the frequency of updating the initial area conversion information increases, the processing amount becomes larger than that in the case of FIG.

  7 and 8, the initial area conversion information A reflects the sector operation status in the period T1, but does not reflect the sector operation status after the period T1. Absent. Therefore, there may be a difference (change) between the sector operation status in the data collection period T1 and the sector operation status in the population estimation target period T2.

  In such a case, with respect to the estimated value for each sector calculated based on the number of location registration signals collected in the population estimation target period T2, the initial area conversion information A is used as it is for the estimated value for each output unit area. If the conversion is performed, a conversion reflecting the sector operation status contrary to the fact may be performed, so that an estimated value for each output unit area may not be obtained correctly (decrease in accuracy). Therefore, the information processing apparatus 20 detects a change in the sector operation status between the data collection period T1 and the population estimation target period T2, and corrects the initial area conversion information A as necessary based on the detection result. .

  Next, each functional element provided for the information processing apparatus 20 in FIG. 2 to realize the above-described processing will be described with reference to FIGS. 9 and 10 as appropriate. FIG. 9 is a diagram illustrating a data flow in the processing of the totaling unit 21 and the sector operation status change detection unit 22. FIG. 10 is a diagram illustrating a data flow in the process of the area conversion information correction unit 23.

  The totaling unit 21 refers to the traffic data stored in the traffic data storage unit 53 and calculates the number of location registration signals collected during the data collection period (first period) and the population estimation target period (second period). It is a counting means for counting. Further, the totaling unit 21 refers to the adjacent sector list stored in the adjacent sector information storage unit 54, thereby obtaining the total value of the number of position registration signals of the sector itself and the number of position registration signals of sectors adjacent to the sector. Tally.

  Specifically, the aggregating unit 21 calculates the average value (baseS, for each day type (weekdays / holidays (Saturdays, Sundays, and holidays)) and for each time zone (every hour) of the number of position registration signals in the sector alone in the data collection period. Sector-specific traffic value), the number of location registration signals in the sector alone during the population estimation period (lastS, sector-only traffic value), the number of location registration signals of the sector itself in the data collection period, and the position of the sector adjacent to the sector The average value (baseG, traffic value including adjacent sector) of each day type and time zone of the total value with the number of registered signals, the position registration signal number of the sector itself in the population estimation target period, and the position of the sector adjacent to the sector A total value (lastG, traffic value including adjacent sector) with the number of registered signals is acquired for each sector (processing block P21 in FIG. 9). Here, for example, when the positional relationship between the sectors is shown in FIG. 3A, the sum of the number of position registration signals of “sectors A to F” becomes the aggregation target of baseG and lastG of sector A.

  Here, baseS and baseG can be tabulated at the time of updating the initial area conversion information (time points t1, t2, and t3 in FIG. 7). For example, the calculation results of lastS and lastG that are tabulated for each population estimation cycle By sequentially accumulating and updating, it is possible to distribute or reduce the calculation time (calculation amount) required to add up the baseS and baseG at the time of updating the initial area conversion information.

  The sector operating status change detection unit 22 detects, for each sector, the change in the operating status of the sector between the data collection period and the population estimation target period based on the counting results (baseS, lastS, baseG, lastG) by the counting unit 21. It is a detection means to detect. Specifically, the sector operation status change detection unit 22 detects “sector inactivity” and “sector power change” as changes in the sector operation status.

  “Sector non-operation” indicates that the sector that was operating during the data collection period has been stopped during the population estimation target period. Examples of the cause of the sector malfunction include a base station failure, removal, and operation stoppage due to construction.

  “Sector power change” indicates that the power of the sector has been changed between the data collection period and the population estimation target period. The causes of the sector power change include, for example, changes in the surrounding environment of the base station, changes in operating parameters of the wireless communication system, and changes in the tilt angle of the base station antenna.

  As a change in the operating status of sectors other than those described above, “new establishment of sectors” for the purpose of enhancing the coverage area of the base station and increasing the capacity may be considered. However, when a sector is newly established in an already covered area, it is assumed that a sector power change is also performed in order to avoid the occurrence and increase of interference between sectors. Therefore, it is considered that the new sector can be handled by including it in the sector power change.

  Next, specific detection processing by the sector operating status change detection unit 22 will be described. First, the sector operation status change detection unit 22 acquires baseS and baseG corresponding to the day type and time zone of the population estimation target period, and also acquires lastS and lastG for each sector.

  The sector operation status change detection unit 22 excludes a sector with a constant low traffic from the detection target of the sector inactivity (“low traffic detection process” in FIG. 9). This is to suppress erroneous detection in a process for detecting sector inactivity described later. Specifically, the sector operation status change detection unit 22 determines, for example, whether or not “baseS ≦ k0” is satisfied, detects a sector that satisfies “baseS ≦ k0” as a low traffic sector, and detects other sectors. Detect as non-low traffic sector. Here, k0 is a predetermined threshold value.

  The sector operating status change detection unit 22 detects a sector with a small traffic value in the population estimation target period as a non-operating sector for a sector detected as a non-low traffic sector ("non-operating detection process" in FIG. 9). Specifically, the sector operating status change detection unit 22 determines whether or not “lastS ≦ k1” is satisfied, for example, and detects a sector that satisfies “lastS ≦ k1” as an inactive sector. Here, k1 is a predetermined threshold value.

  In addition, the determination of sector inactivity may be performed based on whether or not a state in which a traffic value is lost for a predetermined period or longer (a state in which the traffic value is 0) continues within a population estimation target period. As described above, in the present embodiment, it is assumed that the population estimation target period that is the aggregation unit of lastS and lastG is 1 hour, and the aggregation unit period of traffic data is 10 minutes. In this case, lastS and lastG include traffic data for 6 slots, with 10 minutes as one slot (unit period). Therefore, the sector operation status change detection unit 22 determines whether or not the number of position registration signals of the sector alone corresponding to the slot is 0 for each slot included in the population estimation target period (second period). The sector may be detected as an inactive sector when the number of slots in which the number of position registration signals of the sector alone is 0 is a predetermined number or more.

  The sector operating status change detection unit 22 detects a traffic trend (for example, an average value of the number of location registration signals) of the sector alone during the data collection period for sectors that are detected as non-low traffic sectors but not detected as non-operating sectors. The ratio (ratio) of change in the sector-only traffic value (lastS) during the population estimation period is large (above a predetermined threshold), and the population estimation target for the traffic trend (baseG) including adjacent sectors during the data collection period A sector having a small change rate (ratio) of the adjacent sector including traffic value (lastG) during a period (less than a predetermined threshold) is detected as a sector whose power has been changed (power change sector). 1 detection process "). For example, the sector operation status change detection unit 22 determines whether or not both of the following formulas (1) and (2) are satisfied for the sector to be detected, and when it is determined that both are satisfied, the sector is changed in power Detect as a sector. Here, k2 and k3 are predetermined threshold values.

lastS / baseS ≧ k2 (1)
lastG / baseG ≦ k3 (2)

  In the above determination, “10 × log (lastS / baseS)” expressed in decibels (dB) and “10 × log (lastS / baseS)” and Different ratios such as “10 × log (lastG / baseG)” may be used. In this case, it can be determined by whether or not both of the following formulas (3) and (4) are satisfied. Here, k4 and k5 are predetermined threshold values.

ratioS = 10 × log (lastS / baseS) ≧ k4 (3)
ratioG = 10 × log (lastG / baseG) ≦ k5 (4)

  FIG. 11 is a diagram illustrating an example of detecting a sector power change according to the above equations (3) and (4). FIG. 11A is a diagram showing the sector influence ranges of the sector A and the sectors B to G adjacent to the sector A estimated based on the measurement data collected during the data collection period. FIG. 11B is a diagram showing the sector power range (range surrounded by a one-dot chain line) of the actual sector A in the population estimation target period. As shown in these figures, in the population estimation target period, the sector power range of sector A is larger than the sector power range estimated based on the measurement data collected during the data collection period. On the other hand, the sector power range of sectors B, C, and G is eroded by the sector power range of sector A and is reduced.

  FIG. 11C shows an example of the traffic value (B) in the data collection period, the traffic value (L) in the population estimation target period, and the traffic fluctuation ratio (10 × log (L / B)) in the above case. FIG. As shown in this figure, while the traffic value of sector A has greatly increased with the change of power of sector A (power increase), part of the sector power range has been eroded with the change of power of sector A. The traffic values of the sectors B, C, and G thus decreased respectively. Therefore, the traffic fluctuation with adjacent sectors (A to G) is not so large. That is, while the traffic fluctuation ratio (ratio S) of sector A alone is as large as “7.78 dB”, the traffic fluctuation ratio (ratio G) including adjacent sectors (A to G) is as small as “0.58 dB”. .

  As described above, when the traffic fluctuation (ratio G) including the adjacent sector is small with respect to the fluctuation of the traffic fluctuation (ratio S) in the sector alone, as a result of changing the power of the sector, traffic is accommodated between the adjacent sectors. It is likely that the situation has changed. On the other hand, when both ratioS and ratioG change greatly, it is considered that a change (population increase) has occurred in the population distribution in the peripheral area including the adjacent sector.

  Therefore, for example, by setting (adjusting) the threshold value k3 for ratio S to “6 dB” and the threshold value k4 for ratio G to “1 dB”, the sector operation status change detection unit 22 in the case of FIG. And it determines with satisfy | filling (4), and detects the sector A as a power change sector. On the other hand, when the population distribution has changed and both ratioS and ratioG have fluctuated significantly (for example, when ratioS is “7” and ratioG is “5”), the above formula (3 ) But does not satisfy the above equation (4), the sector operating status change detection unit 22 does not detect the sector A as a power change sector. That is, a sector in which no power change is actually performed is not erroneously detected as a power change sector.

  In addition, the sector operating state change detection unit 22 also increases the sector single traffic value (lastS) during the population estimation target period in accordance with the same idea as described above for sectors detected as low traffic sectors. A sector in which the power of a sector with a small change rate (less than a predetermined threshold) of the traffic value including the adjacent sector (lastG) in the population estimation target period to the traffic trend including the adjacent sector during the collection period (baseG) This is detected as (power change sector) ("power change 2 detection process" in FIG. 9). For example, the sector operating status change detection unit 22 determines whether or not both of the following formulas (5) and (6) are satisfied for the sector to be detected, and when it is determined that both are satisfied, the sector is changed in power Detect as a sector. Here, k6 and k7 are predetermined threshold values.

lastS ≧ k6 (5)
lastG / baseG ≦ k7 (6)

  In the above determination, the rate of change such as “10 × log (lastG / baseG)” expressed in decibels (dB) is used instead of the rate of change of the traffic value including the adjacent sector (“lastG / baseG”). May be determined.

  The sector operating status change detection unit 22 outputs a list of sectors (inactive sector list and power change sector list) in which sector inactivity and sector power change are detected to the area conversion information correction unit 23 described later.

  The area conversion information correction unit 23 is a correction unit that corrects the initial area conversion information generated by the initial area conversion information generation unit 10 based on the detection result by the sector operation status change detection unit 22. Specifically, the area conversion information correction unit 23 receives the inactive sector list and the power change sector list output by the sector operating status change detection unit 22 and acquires a list of the inactive sector and the power change sector. Then, the area conversion information correction unit 23 executes a correction process to be described later for each sector shown in the list.

  First, the correction process for the inactive sector (processing block P23A in FIG. 10) will be described. The area conversion information correction unit 23 performs the following processing on the sector detected as an inactive sector.

  The area conversion information correction unit 23 extracts an output unit area (hereinafter, also simply referred to as “area”) having a portion that overlaps the sector influence range of the inactive sector (“area extraction process 1” in FIG. 10). ). Extraction of such an area (hereinafter, referred to as “non-operating area”), for example, prepares sector-area correspondence information in which a sector identifier is associated with an area where a learning point including the sector identifier exists, This can be done by referring to the sector-area correspondence information. For example, the sector-area correspondence information is prepared in advance by generating and storing the sector-area correspondence information when the initial area conversion information generation unit 10 generates the initial area conversion information. Can do.

  Subsequently, the area conversion information correction unit 23 excludes the learning points based on the measurement data related to the non-working sector from the learning points included in the non-working area created by the area conversion information generation unit 10. That is, the learning point including the sector identifier of the inactive sector is excluded. And the learning point which selected the sector which has the 2nd power about the measurement data which the said non-working sector has the 1st power is newly created. Through these processes, the area conversion information correction unit 23 acquires the corrected learning points included in the non-working area (“data exclusion process” in FIG. 10).

  Subsequently, the area conversion information correction unit 23 performs the above-described k-nearest neighbor analysis on each estimated point in the non-working area using the corrected learning point, and determines the main power sector corresponding to each estimated point. presume. Thereby, the area conversion information correction | amendment part 23 acquires the area power map based on the corrected learning point about a non-working area, and area conversion information based on the said area power map (non-working partial area conversion information, 2nd Conversion information) is generated ("non-operation partial area conversion information generation" in FIG. 10). Thereafter, the area conversion information correction unit 23 replaces the portion related to the non-working area of the initial area conversion information with the non-working partial area conversion information (“correction process” in FIG. 10).

  With reference to FIG. 12, the case where the sector with the sector identifier D (non-operating sector D) becomes inoperative after the initial area conversion information generation unit 10 estimates the area influence diagram shown in FIG. A correction process for an inactive sector will be described.

  First, the area conversion information correction unit 23 acquires information on the non-working sector D from the non-working sector list obtained from the sector working state change detection unit 22, and based on the sector-area correspondence information, the sector of the non-working sector D is obtained. A non-working area having a portion geographically overlapping with the power range is extracted. In this example, four areas of area identifiers “TL”, “TR”, “BL”, and “BR” are extracted as non-operating areas.

  Subsequently, the area conversion information correction unit 23 uses the corrected learning points for each estimated point (center point of each cell) included in the above four areas (TL, TR, BL, BR). Analysis of the k-nearest neighbor method is executed, and the main power sector corresponding to each estimation point is estimated. As a result, as shown in FIG. 12 (b), sectors other than the inactive sector D in each shaded cell in FIG. 12 (a) (cells in which the inactive sector D was originally estimated as the main power sector) A new area power map estimated as the main power sector is obtained. The sector power of the sector indicated by the sector identifier “F” is a sector power that has been buried by the sector power of the non-working sector D, and indicates a sector power that becomes apparent only after the sector power of the non-working sector D disappears. .

  The area conversion information correction unit 23 creates the inactive partial area conversion information based on the newly acquired area influence chart by excluding information on the inactive sector D and executing the k-nearest neighbor method again. . FIG. 13 shows the non-working partial area conversion information created in this way. Thereafter, the area conversion information correction unit 23 replaces the initial area conversion information shown in FIG. 6 with the inactive partial area conversion information (“correction process” in FIG. 10).

  Next, correction processing for the power change sector (processing block P23B in FIG. 10) will be described. The area conversion information correction unit 23 performs the following process on the sector detected as the power change sector.

  The area conversion information correction unit 23 extracts an area (output unit area) having a portion geographically overlapping the sector power range of the power change sector (“area extraction process 2” in FIG. 10). Extraction of such an area (hereinafter referred to as “power change area”) may be performed with reference to the sector-area correspondence information, similarly to the extraction of the non-working area described above.

  In the power change area, estimating the area power diagram after the power change requires a certain period (data collection period) for collecting measurement data as described above. Here, let us consider a case in which a power change sector is detected by the sector operating state change detection unit 22 with a period T2 shown in FIG. 7 as a population estimation target period. In this case, the initial area conversion information reflecting the sector power after the power change cannot be generated at least until the time t2 when the collection of measurement data necessary for generating the initial area conversion information B is completed.

  Therefore, until the initial area conversion information B is generated, the area conversion information correction unit 23 generates area conversion information separately generated by a method different from the initial area conversion information generation unit 10 as area conversion information for the power change area. (Substitution) in FIG. 10 ("correction process" in FIG. 10). As such area conversion information that can be substituted, area conversion information (third conversion information) generated based on a PRACH (random access channel) propagation delay amount can be cited.

  Here, a supplementary description will be given of a case where a change in sector power is detected during the period T2. For example, when the sector power is changed in the latter half of the data collection period T2, it is conceivable that a sufficient amount of data reflecting the sector power after the power change is not acquired even at time t2. That is, the initial area conversion information B is not initial area conversion information that reflects the sector power after the power change, and data for generating area conversion information that reflects the sector power after the power change is acquired. Can also assume the case where it is necessary to wait until the completion of the next data collection period (time t3).

  Therefore, as a measure to efficiently and quickly collect data reflecting the sector power after the power change, the time immediately after the sector power change is detected is the start of the next data collection period for generating the initial area conversion information It is conceivable to set the time. In this way, it is possible to start collecting data immediately after the sector power change, immediately after the sector power change, and to acquire a sufficient amount of data reflecting the sector power after the power change more quickly. . In order to take such a measure, for example, the sector operating state change detection unit 22 may set the time point when the sector power change is detected as the start time of the data collection period.

  Moreover, it supplements about the correction process of the area conversion information with respect to a non-working area and a power change area. When the output unit area is reduced (when a half area mesh of about 500 m square is used as the output unit area as in the present embodiment), there is a possibility that the processing division loss in the correction process will increase. On the other hand, when the output unit area is increased (for example, when the area of the municipality is used as the output unit area), the area extracted as a non-working area or a power change area increases, and the scale of the correction process increases. There is a fear. In addition, since an area that is not actually affected by sector inactivity or sector power change is also included in the non-operation area or power change area, there is a possibility that unnecessary calculation processing increases. As a means for solving such a problem, it is conceivable that the size of the output unit area is moderate (for example, a secondary mesh of about 10 km square).

  Returning to FIG. 2, the area conversion information output unit 30 converts the initial area conversion information (corrected area conversion information) corrected by the area conversion information correction unit 23 into the population estimate value calculated for each sector. Output for use by a population estimation device (not shown) that calculates population estimation values for each output unit area.

  Next, the hardware configuration of the information processing apparatus 20 will be described with reference to FIG. FIG. 14 is a diagram illustrating a hardware configuration of the information processing apparatus 20. As illustrated in FIG. 14, the information processing apparatus 20 includes a CPU 201 that executes an operating system, application programs, and the like, a main storage unit 202 that includes a ROM and a RAM, an auxiliary storage unit 203 that includes a hard disk memory, and the like. A communication control unit 204 that performs data communication, an output unit 205 configured by a liquid crystal monitor, an operation unit 206 configured by a keyboard and a mouse as input devices, and a recording medium 208 such as a CD-ROM or DVD And a recording medium reading unit 207.

  Each function of the information processing apparatus 20 illustrated in FIG. 2 is realized by reading and executing a predetermined software program in the main storage unit 202 under the control of the CPU 201. At that time, the CPU 201 controls data reading and writing operations in the main storage unit 202 and the auxiliary storage unit 203 in accordance with the processing procedure of the software program, and controls operations of the operation unit 206, the output unit 205, and the communication control unit 204. .

  Next, the operation of the information processing apparatus 20 will be described with reference to FIGS. 15 and 16, and the information processing method according to the present embodiment will be described. FIG. 15 is a flowchart showing the operations of the counting unit 21 and the sector operation status change detection unit 22. FIG. 16 is a flowchart showing the operation of the area conversion information correction unit 23.

  First, the operations of the counting unit 21 and the sector operation status change detection unit 22 will be described with reference to FIG.

  First, the totaling unit 21 totals the sector-only average traffic value (baseS) and the adjacent-sector-included average traffic value (baseG) in the data collection period (first period) for each sector and each time zone, and estimates the population. The sector-only traffic value (lastS) and the traffic value including adjacent sectors for the target date and time (second period) are aggregated (step S100, aggregation step).

  Subsequently, the sector operating status change detection unit 22 detects a change in the operating status of the sector (sector inactivity and sector power change) based on the counting results (baseS, baseG, lastS, lastG) by the counting unit 21 (steps). S200, detection step). Hereinafter, specific contents of the detection step will be described. Any determination or processing is performed by the sector operation status change detection unit 22.

  First, it is determined whether or not “baseS ≦ k0” is satisfied for a certain sector (step S201). If it is determined that “baseS ≦ k0” is satisfied (step S201: YES), the sector is detected as a low traffic sector (step S202). Subsequently, it is determined whether or not both the expressions “lastS ≧ k6” and “lastG / baseG ≦ k7” are satisfied (step S203). If it is determined that both formulas are satisfied, the sector is detected as a power change sector, and information on the sector is output to the power change sector list (step S203: YES, step S204). If it is determined that both formulas are not satisfied at the same time, a change in the operating status of the sector is not detected (step S203: NO).

  If it is determined in step S201 that “baseS ≦ k0” is not satisfied (step S201: NO), the sector is detected as a non-low traffic sector (step S205). Subsequently, it is determined whether or not “lastS ≦ k1” is satisfied (step S206). If it is determined that “lastS ≦ k1” is satisfied, the sector is detected as an inactive sector, and information on the sector is output to the inactive sector list (step S207). In step S206, the inactive sector is determined by determining whether or not the number of location registration signals of the sector alone corresponding to the slot is 0 for each slot included in the population estimation target period as described above. When the number of slots whose single location registration signal is 0 is equal to or greater than a predetermined number, the sector may be detected as an inactive sector. If it is determined that “lastS = 0” is not satisfied, it is subsequently determined whether or not both “lastS / baseS ≧ k2” and “lastG / baseG ≦ k3” are satisfied (step S208). If it is determined that both formulas are satisfied, the sector is detected as a power change sector, and information on the sector is output to the power change sector list (step S208: YES, step S204). If it is determined that both formulas are not satisfied at the same time, a change in the operating status of the sector is not detected (step S208: NO).

  Next, the operation of the area conversion information correction unit 23 will be described with reference to FIG.

  First, the area conversion information correction unit 23 acquires the inactive sector list and the power change sector list output by the sector operating status change detection unit 22 (step S301). Subsequently, the area conversion information correction unit 23 extracts the non-working area and the power change area based on the non-working sector list and the power change sector list and the sector-area correspondence information, and the non-working area and the power change area. A non-working area list and a power change area list indicating a list are created (step S302).

  Subsequently, the area conversion information correction unit 23 selects one area (step S303) and refers to the power change area list to determine whether the area is a power change area (step S304). Here, when it is determined that the area is a power change area (step S304: YES), the area conversion information correction unit 23 uses the PRACH propagation delay data as the portion related to the power change area of the initial area conversion information. Replacement with the used area conversion information (step S305). Thereafter, if the processing has been completed for all areas, the processing ends (step S308: YES). If the processing has not been completed for all areas, one of the remaining areas is selected (step S308: NO, step S303).

  When it is determined in step S304 that the area is not a power change area (step S304: NO), the area conversion information correction unit 23 refers to the non-operating area list to determine whether the area is a non-operating area. It is determined whether or not (step S306). Here, when it is determined that the area is a non-operating area (step S306: YES), the area conversion information correction unit 23 uses the non-operating sector data as the non-operating area portion of the initial area conversion information. Is replaced with the area conversion information created with the measurement data excluding (step S307). Thereafter, if the processing has been completed for all areas, the processing ends (step S308: YES). If the processing has not been completed for all areas, one of the remaining areas is selected (step S308: NO, step S303).

  If it is determined in step S306 that the area is not a non-operating area (step S306: NO), the replacement of the area portion of the initial area conversion information is not performed. Thereafter, if the processing has been completed for all areas, the processing ends (step S308: YES). If the processing has not been completed for all areas, one of the remaining areas is selected (step S308: NO, step S303).

  As described above, in the information processing apparatus 20 according to the present embodiment, the counting unit 21 performs a data collection period (first data) based on operational data (traffic data) collected and totaled by a base station or the like on a daily basis. And the number of location registration signals for each sector in each period of the population estimation target period (second period). Then, the sector operating status change detection unit 22 detects a change in the operating status of the sector (sector non-operating, sector power change) based on the counting results (baseS, baseG, lastS, lastG) by the counting unit 21. Therefore, according to the information processing apparatus 20, a change in the operating status of the sector can be detected by a simple calculation process based on the traffic data.

  In addition, when detecting the change in the operating status of the sector, the sector operating status change detection unit 22 includes the adjacent sector-incorporated traffic value (baseG, including the adjacent sector of the sector together with the sector-only traffic value (baseS, lastS). lastG). This makes it possible to accurately determine whether the change in traffic value is caused by a change in the population distribution or a change in the operating status of the sector.

  Further, the area conversion information correction unit 23 generates the initial area conversion information generated by the initial area conversion information generation unit 10 based on the detection results (non-operating sector list, power change sector list) by the sector operating status change detection unit 22. More appropriate area conversion information can be obtained by replacing (correcting) a part of. For example, the population estimation accuracy can be improved by causing the above-described population estimation device (not shown) to use the corrected area conversion information obtained in this way.

  Note that, in the above embodiment, when the initial area conversion information based on the area power diagram based on the assumption that the power ranges do not overlap between sectors (superposition is not allowed) is corrected according to changes in the operating status of the sector. Explained. Here, the weighted k-nearest neighbor method using the reciprocal of the distance from the estimated point as the weight is used as a method for estimating the area power diagram as described above, but the method for estimating the area power diagram is not limited to this.

  Further, the information processing apparatus according to the present invention estimates an area power map based on the assumption that the power range overlap between sectors is allowed, and creates initial area conversion information based on the area power map Is also applicable. As an estimation method of the area power diagram based on the premise of allowing the overlapping of the power range between sectors, for example, there is Kriging. In addition, as a method for estimating the area power diagram based on the premise that the power range overlap between sectors applied to the present invention is allowed, the information included in the above measurement data, that is, the estimation target sector Anything may be used as long as it satisfies the condition of estimation using only area quality information and position information of the mobile terminal.

  In the above embodiment, as an example of the arrangement of the estimation points (cell areas including the estimation points) for estimating the main power sector by the k-nearest neighbor method, a square arrangement (rectangular cells are arranged uniformly) has been described as an example. The method of arranging the estimated points is not limited to this. For example, a hexagonal arrangement, a rhombus arrangement, a triangular arrangement, and an arrangement with an adaptive size according to population density information given as prior information may be used. FIG. 17 is a diagram illustrating an arrangement example of estimated points other than the present embodiment. FIG. 17A is a diagram illustrating an example in which square cells are uniformly arranged. FIG. 17B is a diagram illustrating an example in which square cells having different sizes are adaptively arranged according to prior information (population density and the like). FIG. 17C is a diagram illustrating an example in which hexagonal, diamond, and triangular cells are adaptively arranged according to prior information (population density and the like). FIG. 17D is a diagram illustrating an example in which hexagonal cells are uniformly arranged. FIG. 17E is a diagram illustrating an example in which rhombus cells are uniformly arranged. FIG. 17F is a diagram illustrating an example in which triangular cells are uniformly arranged. In these figures, the center point of each cell is the position of the estimated point.

  DESCRIPTION OF SYMBOLS 1 ... Area conversion information creation apparatus, 10 ... Area conversion information generation part, 20 ... Information processing apparatus, 21 ... Total part, 22 ... Sector operation condition change detection part, 23 ... Area conversion information correction part, 30 ... Area conversion information output , 51 ... Map data storage unit, 52 ... Measurement data storage unit, 53 ... Traffic data storage unit, 54 ... Neighboring sector information storage unit, 100 ... Mobile terminal, 200 ... BTS, 201 ... CPU, 202 ... Main storage unit, DESCRIPTION OF SYMBOLS 203 ... Auxiliary memory | storage part, 204 ... Communication control part, 205 ... Output part, 206 ... Operation part, 207 ... Recording medium reading part, 208 ... Recording medium, 300 ... RNC, 400 ... Switch, 500 ... Management center, 501 ... Society Sensor unit 502 ... Petamining unit 503 ... Mobile demography unit 504 ... Visualization solution unit 1000 ... Shin system.

Claims (8)

The number of location registration signals collected in the first period is calculated for each sector based on the traffic data obtained by counting the number of location registration signals from the mobile terminal acquired for each sector formed by one or more radio base stations. Totaling means for summing up, for each sector, the number of location registration signals collected in a second period after the first period;
Detection means for detecting a change in the operating status of the sector between the first period and the second period for each sector based on the counting result by the counting means;
Equipped with a,
For each period of the first period and the second period, the aggregating means is based on adjacent sector information in which information indicating adjacent sectors adjacent to the sector is associated with each sector in advance. The sector-only traffic value based on the number of location registration signals and the adjacent sector-included traffic value based on the sum of the number of location registration signals of the sector and the adjacent sector of the sector are tabulated for each sector,
The detecting means detects a change in the operating status of a sector for each sector based on the sector-only traffic value and the adjacent-sector-included traffic value in each of the first period and the second period.
Information processing device. The detection means, for each sector, when the sector single traffic value of the first period is equal to or greater than a predetermined threshold, and the sector single traffic value of the second period is equal to or less than a predetermined threshold, detecting the sector unavailability indicating the operation stop of the sector as a change in operating status of the sector, the information processing apparatus according to claim 1. The detection means, for each sector, when the sector-only traffic value in the first period is equal to or greater than a predetermined threshold, the unit for each unit period obtained by dividing the second period every predetermined time. It is determined whether or not the number of location registration signals of the sector alone in the period is 0. If the number of unit periods in which the number of location registration signals of the sector alone is 0 is equal to or greater than a predetermined number, Detecting sector inactivity indicating a sector outage as a change in operating status,
The information processing apparatus according to claim 1 . The detection means includes, for each sector, a ratio between the sector-only traffic value in the first period and the sector-only traffic value in the second period, and the adjacent-sector-included traffic value in the first period. And a sector power change indicating a sector power change as a change in the operating status of the sector based on the ratio of the traffic value including the adjacent sector in the second period,
The information processing apparatus according to any one of claims 1 to 3 . The first period is a period in which measurement data including information in which positioning position information of a mobile terminal obtained by predetermined positioning is associated with a sector identifier of a sector where the mobile terminal is located is collected.
The information processing device is used to convert a predetermined calculated value for each sector, which is generated based on measurement data collected in the first period, into a value for a predetermined output unit area. Is further provided with a correction means for correcting based on the detection result by the detection means,
The information processing apparatus according to claim 4 . When the detection unit detects a sector non-operation, the correction unit includes a portion relating to the output unit region having a portion geographically overlapping a sector power range of the sector in which the sector non-operation is detected in the conversion information For the second conversion information generated based on the measurement data after excluding information on the sector in which the sector inactivity was detected from the measurement data collected in the first period,
The information processing apparatus according to claim 5 . When a change in sector power is detected by the detection means, the correction means relates to the output unit area having a portion geographically overlapping the sector power range of the sector in which the change in sector power is detected in the conversion information Is replaced with the third conversion information generated based on the position registration signal and the propagation delay amount of the position registration signal,
The information processing apparatus according to claim 5 or 6 . An information processing method executed by an information processing apparatus,
The number of location registration signals collected in the first period is calculated for each sector based on the traffic data obtained by counting the number of location registration signals from the mobile terminal acquired for each sector formed by one or more radio base stations. A totaling step of totalizing, for each sector, the total number of location registration signals collected in a second period after the first period;
Based on the counting result of the aggregation step, for each of the sectors, seen including and a detection step of detecting a change in the sector of the operating status between the first period and the second period,
In the counting step, for each period of the first period and the second period, based on adjacent sector information in which information indicating adjacent sectors adjacent to the sector is associated in advance for each sector, each sector alone The sector-only traffic value based on the number of location registration signals and the adjacent sector-included traffic value based on the sum of the number of location registration signals of the sector and the adjacent sector of the sector are tabulated for each sector,
In the detection step, based on the sector-only traffic value and the adjacent-sector-included traffic value in each of the first period and the second period, a change in sector operation status is detected for each sector.
Information processing method.