Communication system, data processing method, and program

Abstract

Provided is a communication system comprising: a data acquisition unit that acquires in-range status data indicating the in-range status of each user terminal in a plurality of cells including cells having different frequencies, and available frequency data indicating frequencies available to each of the plurality of user terminals in the range of the plurality of cells; and an instruction unit that, on the basis of the in-range status data and the available frequency data, determines a user terminal, from among the user terminals in the range of one cell of the plurality of cells, to be handed over from the one cell to another cell having a different frequency from the one cell, and instructs that user terminal to perform handover from the one cell to the other cell. The communication system may also include a RAN control function and an AI processing (RAN Intelligent Controller (RIC), etc.) function.

Description

Communication system, data processing method, and program

[0001] The present invention relates to a communication system, a data processing method, and a program.

[0002] Patent Document 1 describes a control method for a wireless communication system including a base station device having a plurality of frequency bands and a terminal device configured to communicate with the base station device, the control method calculating radio resources for satisfying requirements in at least one of the plurality of frequency bands based on requirements related to communication quality necessary for an application used by the terminal device, and selecting a frequency band for the terminal device from the plurality of frequency bands when the calculated radio resources exceed a first predetermined value. [Prior Art Documents] [Patent Documents] [Patent Document 1] JP 2017-092762 A

[0003] In conventional mobile communication networks, communication terminals are located in frequency bands with strong radio wave strength, and perform inter-frequency handovers (Interfreq Handovers) according to the priority of frequency bands described in the SIB information of base stations. Since many communication terminals are located in frequency bands with high priority and strong radio wave strength, load balancing does not work well, resulting in frequency imbalance.

[0004] In the communication system according to the present embodiment, for example, in the area coverage of an operator's radio base station having multiple frequencies, the communication capacity of the area is maximized by distributing user communication traffic in the frequency direction. In the communication system according to the present embodiment, for example, an AI (Artificial Ingelligence) executed on the network side calculates the number of communication terminals present in each area based on UE capability information and TA presence information of communication terminals connected to the network. The AI ​​may predict, based on past experience, the frequency on which day and time communication traffic is likely to be concentrated, and may execute an Interfreq HO procedure from the network side to the target communication terminal without waiting for Connection Reconfiguration from the communication terminal.

[0005] As a specific example, the communication system 10 according to this embodiment includes a distributed infrastructure having a RAN control function for controlling a RAN (Radio Access Network) and an AI processing function for performing AI processing, and a management infrastructure for managing multiple distributed infrastructures, and each of the multiple distributed infrastructures controls handover between different frequencies between multiple radio base stations.

[0006] Types of AI processing include AI processing related to RAN control (sometimes referred to as RAN-controlled AI processing) and AI processing not related to RAN control (sometimes referred to as non-RAN-controlled AI processing).

[0007] An example of RAN control AI processing is RIC (RAN Intelligent Controller). RIC is a technology that uses AI to optimize RAN radio resources and automate RAN operations. RIC includes Non-RT RIC and Near-RT RIC (Near-Real Time RIC). Non-RT RIC is sometimes called Centralized RIC. Non-RT RIC is located inside SMO (Service Management and Orchestration), which manages and orchestrates the RAN. Non-RT RIC generates and notifies policies related to RAN control and sends information to Near-RT RIC. For example, the Non-RT RIC performs machine learning using data collected from the RAN to generate a trained model for RAN control and transmits it to the Near-RT RIC. The Near-RT RIC is sometimes called a Distributed RIC. Compared to the Non-RT RIC, the Near-RT RIC is located closer to the RAN nodes (RU (Radio Unit), DU (Distributed Unit), CU (Central Unit)) and controls the RAN nodes, resources, etc. The Near-RT RIC performs processing with higher real-time performance than the Non-RT RIC. The Near-RT RIC performs inference processing related to RAN control using, for example, a trained model acquired from the Non-RT RIC. RAN control AI processing is not limited to the RIC.

[0008] The non-RAN control AI processing may correspond to a so-called MEC (Multi-access Edge Computing) application. Examples of the non-RAN control AI processing include a monitoring AI execution process that determines the situation within the imaging range of an input captured image, and a response AI execution process that outputs a response to an input user inquiry. However, this is not limited to these.

[0009] According to one embodiment of the present invention, there is provided a communication system. The communication system may include a data acquisition unit that acquires presence status data indicating presence status of user terminals in each of a plurality of cells including cells using different frequencies, and available frequency data indicating frequencies available to each of the plurality of user terminals located in the plurality of cells. The communication system may also include an instruction unit that determines, based on the presence status data and the available frequency data, a user terminal located in one of the plurality of cells to be handed over from the one cell to another cell using a different frequency from the one cell, and instructs the user terminal to hand over from the one cell to the other cell.

[0010] In the communication system, the instruction unit may instruct a user terminal located in a sparse cell among the plurality of cells, the sparse cell having the presence status determined to be a sparse state, to hand over to a cell using a different frequency from the sparse cell in which the user terminal is located, and, upon completion of handover of the user terminal located in the sparse cell from the sparse cell, cause a radio base station generating the sparse cell to stop generating the sparse cell. When there are a plurality of sparse cells, the instruction unit may instruct a user terminal located in the sparse cell having the highest frequency among the plurality of sparse cells to hand over to a cell using a different frequency from the sparse cell in which the user terminal is located, and, upon completion of handover of the user terminal located in the sparse cell from the sparse cell, cause the radio base station generating the sparse cell to stop generating the sparse cell.

[0011] In any of the communication systems, the instruction unit may instruct a user terminal located in a congested cell among the plurality of cells, the location status of which is determined to be congested, to perform a handover to an unpopulated cell, the location status of which is determined to be unpopulated.

[0012] Any of the communication systems may include a prediction unit that predicts which of the plurality of cells will have a location status that is congested, and the instruction unit may instruct a user terminal that is present in the cell predicted by the prediction unit to be congested to hand over from the cell to a cell using a frequency different from that of the cell before the cell becomes congested. The prediction unit may predict which cell will have a location status that is congested based on location status data that indicates past location statuses of user terminals in each of the plurality of cells.

[0013] In any of the communication systems, the prediction unit may predict, for each of the plurality of cells, whether or not a presence status will be congested, based on presence status data indicating presence statuses of user terminals in cells located within a predetermined range based on the cell. The prediction unit may predict, for each of the plurality of cells, whether or not a presence status will be congested, based on the presence status data indicating presence statuses of user terminals in cells located within a predetermined range based on the cell, and usage frequency data indicating frequencies used by user terminals located in cells located within the predetermined range based on the cell.

[0014] In any of the communication systems, the prediction unit may predict that the coverage area will be congested for a cell among the plurality of cells in which a railway line is installed in the area to be covered, based on train schedule data indicating when trains are scheduled to run on the railway line.

[0015] According to one embodiment of the present invention, there is provided a data processing method executed by a computer. The data processing method may include a data acquisition step of acquiring location status data indicating location statuses of user terminals in each of a plurality of cells including cells using different frequencies, and available frequency data indicating frequencies available to each of the plurality of user terminals located in the plurality of cells. The data processing method may include a command step of determining, based on the location status data and the available frequency data, a user terminal located in one of the plurality of cells to be handed over from the one cell to another cell using a different frequency from the one cell, and commanding the user terminal to hand over from the one cell to the other cell.

[0016] According to one embodiment of the present invention, there is provided a program for causing a computer to execute the data processing method.

[0017] The above summary of the invention does not list all of the necessary features of the present invention, and subcombinations of these features may also constitute inventions.

[0018] FIG. 1 is a schematic diagram illustrating an example of a communication system 10. FIG. 2 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 3 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 4 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 5 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 6 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 7 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 8 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 9 is an explanatory diagram illustrating the processing content of the communication system 10. FIG. 10 is an explanatory diagram illustrating the processing content of the communication system 10.

[0019] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0020] FIG. 1 schematically illustrates an example of a communication system 10. The communication system 10 includes a distributed infrastructure 200. The communication system 10 may include multiple distributed infrastructures 200. The communication system 10 may include a management infrastructure 100 that manages the multiple distributed infrastructures 200. In the communication system 10 according to this embodiment, for example, the management infrastructure 100 and the multiple distributed infrastructures 200 may cooperate to control a RAN 302 and perform AI processing. The RAN 302 provides mobile communication services to a UE (User Equipment) 30. The UE 30 may be an example of a user terminal.

[0021] The RAN 302 may be a virtualized vRAN (Virtual RAN), and the communication system 10 may control the vRAN. The RAN 302 may be a physical RAN, and the communication system 10 may control the physical RAN. In this embodiment, a case where the RAN 302 is a vRAN will be mainly described as an example.

[0022] The AI ​​processing performed by the communication system 10 includes RAN-controlled AI processing (sometimes referred to as RAN_AI). The AI ​​processing performed by the communication system 10 may include non-RAN-controlled AI processing (sometimes referred to as non-RAN_AI).

[0023] The distributed infrastructure 200 may be a data center located in various locations. The distributed infrastructure 200 may be configured with multiple devices. The distributed infrastructure 200 may be realized on a virtualization platform made up of multiple devices. The distributed infrastructure 200 may also be realized by a single device. In other words, the distributed infrastructure 200 may be a distributed device.

[0024] The management infrastructure 100 may be a data center that manages multiple distributed infrastructures 200. The management infrastructure 100 may be configured with multiple devices. The management infrastructure 100 may be realized on a virtualization infrastructure made up of multiple devices. The management infrastructure 100 may also be realized by a single device. In other words, the management infrastructure 100 may be a management device.

[0025] The management infrastructure 100 may be referred to as a Core Brain, and the distributed infrastructure 200 may be referred to as a Regional Brain. While FIG. 1 illustrates an example in which a single-level management infrastructure 100 is arranged below the management infrastructure 100, this is not limiting. The distributed infrastructure 200 may have multiple levels. For example, when a two-level distributed infrastructure 200 is arranged below the management infrastructure 100, the management infrastructure 100 may be referred to as a Core Brain, the distributed infrastructure 200 at the level below that may be referred to as a Regional Brain, and the distributed infrastructure 200 at the level further below that may be referred to as a Sub-Regional Brain.

[0026] The distributed infrastructure 200 may be arranged with one or more central processing units (CPUs). The distributed infrastructure 200 may be arranged with one or more graphics processing units (GPUs). The distributed infrastructure 200 may be arranged with multiple super chips, each of which has a CPU and a GPU connected via an interconnect. The interconnect may have memory consistency and may be capable of achieving high bandwidth and low latency. In this way, the distributed infrastructure 200 may have CPU resources and GPU resources as computational resources.

[0027] 2 to 8 are explanatory diagrams illustrating processing contents in the communication system 10. In Figures 3 to 8, the numbering of the UEs 30 is omitted. In this example, the radio base station 310 generates a 900 MHz band cell 312, a 1700 MHz band cell 314, and a 2100 MHz band cell 316, the radio base station 320 generates a 900 MHz band cell 322 and a 2100 MHz band cell 324, the radio base station 330 generates a 2540 MHz band cell 332 and a 3500 MHz band cell 334, the radio base station 340 generates a 2540 MHz band cell 342 and a 3500 MHz band cell 344, and the radio base station 350 generates a 2540 MHz band cell 352 and a 3500 MHz band cell 354.

[0028] 3 shows an example of the presence status of a plurality of UEs 30 when the UEs 30 are controlled to be present in cells of frequency bands with strong received radio waves as in the conventional case. In the conventional control, the standby frequency is determined depending on the strength of the radio waves received by the UEs 30, so that the standby frequency is biased as shown in FIG.

[0029] In contrast, the distribution infrastructure 200 according to the present embodiment may distribute the frequencies on which the UEs 30 wait by using the presence status of the multiple UEs 30 and the corresponding frequency information of each of the multiple UEs 30. This allows the multiple UEs 30 to be distributed among multiple cells, as illustrated in Fig. 4, thereby improving the efficiency of communication traffic.

[0030] The distributed infrastructure 200 may execute a process for optimizing the overall power consumption. For example, in a conventional case where the UE 30 is configured to be present in a cell of a frequency band with a strong received radio wave strength, as shown in FIG. 5 , even if the communication traffic in the entire target area is low and the frequencies in which the UE 30 are present vary, the presence status of the UE 30 depends on the strength of the received radio wave by the UE 30, and therefore it is not possible to stop the radio waves of the radio base station.

[0031] In contrast, the distributed infrastructure 200 according to this embodiment may operate only at frequencies that can ensure the necessary capacity when communication traffic is low throughout the target area, and may put the radio equipment of the radio base station to sleep by forcibly handing over UEs 30 that are located on other frequencies. For example, as shown in Fig. 6, the distributed infrastructure 200 hands over UEs 30 that are located in cell 314 in the 1700 MHz band, cells 332 and 342 in the 2540 MHz band, and cells 334, 344, and 354 in the 3500 MHz band to either cells 312 and 322 in the 900 MHz band or cells 316 and 324 in the 2100 MHz band. As a result, as shown in FIG. 6 , for example, radio base station 310 can be made to stop transmitting cell 314, radio base station 330 can be made to stop transmitting cells 332 and 334, radio base station 340 can be made to stop transmitting cells 342 and 344, and radio base station 350 can be made to stop transmitting cells 352 and 354, thereby appropriately reducing overall power consumption.

[0032] The distributed infrastructure 200 may predict which of the multiple cells will be congested and execute control to alleviate the congestion in the cell. For example, the distributed infrastructure 200 instructs the UE 30 present in the cell predicted to be congested to hand over from the cell to a cell using a frequency different from that of the cell before the cell becomes congested.

[0033] Specific examples are shown in Figures 7 and 8. In the examples shown in Figures 7 and 8, a train 400 passes through a regional area covered by radio base station 310, radio base station 320, radio base station 330, radio base station 340, and radio base station 350. Here, it is assumed that the UEs 30 of many passengers on the train 400 are traveling while being within the range of both a 1700 MHz cell and a 2100 MHz cell.

[0034] Since the train 400 carries many passengers with UEs 30, communication traffic increases in the area through which the train 400 passes each time the train 400 passes, which may cause the connection of the UEs 30 that were originally within the service area to become unstable. Furthermore, the UEs 30 of the passengers on the train 400 may also experience unstable connections, such as handovers taking a long time due to the congestion of communication traffic. In the example shown in FIG. 7 , the passage of the train 400 may cause the connections of the UEs 30 that are within the service area of ​​the cells 314, 316, and 324 to become unstable. Furthermore, the UEs 30 of the passengers on the train 400 may also experience unstable connections.

[0035] 7 , for example, the distributed infrastructure 200 obtains from the radio base station 360 that covers the area where the train 400 is located information on the number of UEs 30 present in the cells generated by the radio base station 360 and information on the frequencies of the cells in which the UEs 30 are present, and predicts which cells will become congested. In this example, the distributed infrastructure 200 predicts that many UEs 30 present in the 1700 MHz cell and the 2100 MHz cell will move in, and therefore predicts that cells 314, 316, and 324 will become congested.

[0036] The distributed infrastructure 200 instructs the UEs 30 present in the range of the cells 314, 316, and 324 that are predicted to become congested to hand over to cells of other frequencies before the cells 314, 316, and 324 become congested. This makes it possible to vacate the cells 314, 316, and 324 before the train 400 passes, as shown in Fig. 8, and enables the UEs 30 of the passengers on the train 400 to smoothly hand over to the cells 314, 316, or 324. The UEs 30 that were originally present in the range of the cells 314, 316, and 324 are also no longer affected by the handover, and therefore communication instability can be prevented.

[0037] The distribution infrastructure 200 may predict that the area coverage status of a cell among the multiple cells, in which a railway line is installed in a covered area, will be congested based on train schedule data indicating the schedule of trains 400 running on the railway line. The distribution infrastructure 200 may determine the timing at which train 400 will pass through the cell based on the train schedule data, and predict that the cell will be congested when train 400 passes through. The train schedule data may be train schedule data indicating the schedule of train 400. The distribution infrastructure 200 may acquire train schedule data provided by a server of a railway management company that manages the train 400. The distribution infrastructure 200 may acquire train schedule data from any server that provides information about railways. The train schedule data may be operation status data indicating the operation status of train 400. The distribution infrastructure 200 may continuously acquire operation status information provided by a server of a railway management company that manages the train 400. The distribution infrastructure 200 may continuously acquire operation status information from a server that provides information about railways, such as transfer guides.

[0038] 9 shows an example of the functional configuration of the distributed infrastructure 200. The distributed infrastructure 200 includes a storage unit 202, a RAN control unit 204, an AI management unit 206, a data acquisition unit 208, a management unit 210, an instruction unit 212, and a prediction unit 214.

[0039] The RAN control unit 204 executes a RAN control function that controls a RAN 302 configured by a plurality of radio base stations 300. The RAN control unit 204 may execute a function of a so-called vRAN (Virtual RAN). The RAN control unit 204 may control communications in the RAN 302 by controlling the plurality of radio base stations 300 that configure the RAN 302 or by coordinating with other distributed infrastructures 200. The RAN control unit 204 manages, for each of the plurality of radio base stations 300, information on the frequency of the generated cell, communication traffic conditions, the number of user terminals located within the range, and UE capability including available frequency data indicating frequencies available for the located user terminals.

[0040] The AI ​​management unit 206 manages the AI ​​processing. For example, the AI ​​management unit 206 manages the execution of RAN control AI processing. For example, the AI ​​management unit 206 manages the execution of non-RAN control AI processing. The AI ​​management unit 206 causes the data acquisition unit 208, the management unit 210, the instruction unit 212, and the prediction unit 214 to perform various processes so as to control inter-frequency handover of UE 30 in multiple radio base stations 300.

[0041] The data acquisition unit 208 acquires various data and stores the acquired data in the storage unit 202.

[0042] For example, the data acquisition unit 208 acquires location status data that indicates the location status of user terminals in each of a plurality of cells, including cells using different frequencies, generated by a plurality of radio base stations 300 that are under the control of the RAN control unit 204. The data acquisition unit 208 may acquire the location status data from the RAN control unit 204.

[0043] For example, the data acquisition unit 208 acquires available frequency data that indicates frequencies that are available to each of a plurality of user terminals that are located in a plurality of cells, including cells with different frequencies, and that is generated by a plurality of radio base stations 300 that are under the control of the RAN control unit 204. The data acquisition unit 208 may acquire the available frequency data from the RAN control unit 204.

[0044] For example, the data acquisition unit 208 acquires data for predicting whether each of a plurality of cells will be congested. For example, for a cell where a railroad is installed in a covered area, the data acquisition unit 208 acquires train schedule data indicating when the train 400 is scheduled to run on the railroad. For example, for a cell where an event venue is located in a covered area, the data acquisition unit 208 acquires event information data indicating information about an event at the event venue.

[0045] The management unit 210 uses the data acquired by the data acquisition unit 208 to manage the status of the multiple radio base stations 300. The management unit 210 may manage the status of each of the multiple cells generated by the multiple radio base stations 300.

[0046] For example, the management unit 210 may manage the status of multiple cells covering each of multiple regional areas. The management unit 210 may manage the frequency bands of multiple cells covering each of multiple regional areas. The management unit 210 may manage the presence status of user terminals in each of multiple cells covering each of multiple regional areas.

[0047] The instruction unit 212 instructs the user terminal to perform a handover in order to adjust the location status of the user terminal among the plurality of cells covering the regional area for each of the plurality of regional areas. The instruction unit 212 may instruct the user terminal to perform an inter-frequency handover among the plurality of cells covering the regional area.

[0048] For example, based on the presence status data and available frequency data acquired by the data acquisition unit 208, the instruction unit 212 determines, from among user terminals present in one of the multiple cells, a user terminal to be handed over from the one cell to another cell having a different frequency from the one cell, and instructs the user terminal to hand over from the one cell to the other cell.

[0049] The instruction unit 212 may determine whether the coverage status of each of the multiple cells is congested, normal, or uncongested, and may hand over the user terminal based on the determination result.

[0050] The instruction unit 212 may determine whether the presence status of each of the plurality of cells is a congested status, a normal status, or an uncongested status based on the number of users present in each of the plurality of cells. As a specific example, the instruction unit 212 determines a cell in which the number of users present in each of the plurality of cells is greater than a predetermined first threshold to be a congested status, a cell in which the number of users present in each of the plurality of cells is less than a second threshold that is smaller than the first threshold to be an uncongested status, and a cell in which the number of users present in each of the plurality of cells is between the first threshold and the second threshold to be an uncongested status.

[0051] The instruction unit 212 may determine whether the presence status of each of the plurality of cells is congested, normal, or quiet, based on the communication traffic of each of the plurality of cells. As a specific example, the instruction unit 212 determines a cell whose communication traffic in a predetermined period is more than a first threshold to be congested, a cell whose communication traffic is less than a second threshold that is smaller than the first threshold to be quiet, and a cell whose communication traffic is between the first threshold and the second threshold to be quiet.

[0052] The instruction unit 212 may determine whether the coverage status of each of the multiple cells is congested, normal, or uncongested, based on parameters other than these.

[0053] The instruction unit 212 may hand over user terminals to distribute overall communication traffic. For example, when it determines that there is a bias in the presence status of multiple user terminals in multiple cells, the instruction unit 212 hands over some of the multiple user terminals to reduce the bias. For example, the instruction unit 212 decides to hand over a user terminal from a congested cell whose presence status is determined to be congested among the multiple cells to a sparse cell whose presence status is determined to be sparse, and instructs one or more user terminals that can be present in the sparse cell, among the multiple user terminals present in the congested cell, to hand over from the congested cell to the sparse cell.

[0054] The instruction unit 212 may perform handover of the user terminal in order to optimize the overall power consumption. For example, the instruction unit 212 may instruct a user terminal located in an sparse cell determined to have a sparse coverage area among the multiple cells to handover to a cell using a frequency different from that of the sparse cell in which the user terminal is located, and may cause the radio base station that generates the sparse cell to stop generating the sparse cell upon completion of handover of the user terminal located in the sparse cell from the sparse cell.

[0055] When there are multiple quiet cells, the instruction unit 212 may instruct a user terminal located in the quiet cell with the highest frequency among the multiple quiet cells to hand over to a cell with a frequency different from that of the quiet cell in which the user terminal is located, and may cause the radio base station that is generating the quiet cell to stop generating the quiet cell upon completion of handover from the quiet cell of the user terminal located in the quiet cell.

[0056] The prediction unit 214 predicts a cell among the plurality of cells whose coverage area will be congested. The prediction unit 214 predicts a cell that will be congested, for example, based on the data acquired by the data acquisition unit 208.

[0057] As a specific example, the prediction unit 214 predicts a cell whose presence status will be congested based on presence status data indicating the past presence status of user terminals in each of the multiple cells. For example, the prediction unit 214 identifies dates and times when each of the multiple cells tends to be congested by analyzing the presence status of each of the multiple cells for each date and time period in the past, and predicts a cell that will be congested based on the identification results. For example, the prediction unit 214 predicts that a cell that tends to be congested during weekday morning hours will also be congested during future weekday morning hours. The prediction unit 214 may perform machine learning using data indicating the congestion status of the multiple cells for each date and time as learning data, thereby generating a learning model that estimates the congestion status from the date and time, and then use the learning model to predict a cell that will be congested.

[0058] As a specific example, the prediction unit 214 predicts whether the presence status of each of a plurality of cells will be congested based on presence status data indicating the presence status of user terminals in cells located within a predetermined range based on the cell. For example, if there is a tendency for one cell to become congested immediately after another cell within the predetermined range, the prediction unit 214 predicts that the other cell will become congested if the one cell becomes congested at a certain point in time. The prediction unit 214 may also predict which cell will become congested for each of a plurality of cells based on the relationship between the presence status of the cell and the presence status of an adjacent cell. For example, if there is a tendency for one of two adjacent cells to become congested immediately after the other cell becomes congested, the prediction unit 214 predicts that the other cell will become congested if one cell becomes congested at a certain point in time. For example, this tendency may occur in two adjacent cells that cover a railroad line. The prediction unit 214 may perform machine learning using data indicating the presence status of multiple cells over time as learning data, to generate a learning model that can estimate the presence status of multiple cells of multiple radio base stations at a certain timing from multiple cells of multiple radio base stations at a next timing, and may use the learning model to predict which cells will become congested.

[0059] For example, the prediction unit 214 may predict, for each of a plurality of cells, whether the presence status will be congested based on presence status data indicating the presence status of user terminals in cells located within a predetermined range based on the cell, and utilization frequency data indicating frequencies used by user terminals located in cells located within a predetermined range based on the cell. For example, the prediction unit 214 performs machine learning using data indicating the presence status data and utilization frequency data of a plurality of cells in time series as learning data, thereby generating a learning model capable of estimating the presence status of a plurality of cells at the next timing using the presence status of user terminals in a plurality of cells and available frequencies for the user terminals at a certain timing as input, and predicts which cells will be congested using the learning model.

[0060] The prediction unit 214 may predict which cell will have a congested coverage area based on the data for predicting whether a cell will be congested, which data is acquired by the data acquisition unit 208. For example, the prediction unit 214 may predict whether a cell, among the multiple cells, that a railroad line is installed in a covered area will have a congested coverage area based on the train schedule data. The prediction unit 214 may determine the timing when the train 400 will pass through the cell based on the train schedule data, and predict that the cell will be congested when the train 400 passes through.

[0061] For example, the prediction unit 214 predicts that the coverage status of a cell in which an event venue is located in a coverage area among multiple cells will become congested based on the event information data. The prediction unit 214 predicts that the cell will become congested from the start time of the event indicated by the event information data or a predetermined time before the start time. The prediction unit 214 predicts that adjacent cells will become congested from a predetermined time after the end time of the event indicated by the event information data.

[0062] The instruction unit 212 may instruct a user terminal located in a cell predicted by the instruction unit 212 to become congested, to hand over from the cell to a cell using a different frequency from the cell before the cell becomes congested. For example, when the train 400 passes through a certain cell, the instruction unit 212 instructs a user terminal located in the cell predicted by the prediction unit 214 to hand over from the cell to a cell using a different frequency from the cell. This makes it possible, for example, when many user terminals using a certain frequency band are located on the train 400, to hand over user terminals located in a cell using that frequency band that is located ahead of the train 400 to a cell using another frequency band. This enables user terminals on the train 400 to smoothly hand over when the train 400 passes through the cell, and prevents user terminals originally located in the cell from being affected by the handover, thereby contributing to an improvement of the overall communication environment.

[0063] For example, when an event is held at a certain event venue, the instruction unit 212 instructs user terminals present in a cell that is predicted to be congested by the prediction unit 214 to hand over from that cell to a cell using a frequency different from that of the cell. As a result, for example, when it is predicted that many user terminals using a certain frequency band will move to the event venue based on the presence status of cells adjacent to the cell in which the event venue is located, it is possible to hand over user terminals present in a cell using that frequency band of the cell in which the event venue is located to a cell using another frequency band, thereby enabling smooth handover when many user terminals move to the event venue and preventing user terminals that were originally present from being affected by the handover, thereby contributing to an improvement of the overall communication environment.

[0064] 10 schematically illustrates an example of the hardware configuration of a computer 1200 that functions as the management infrastructure 100 or the distribution infrastructure 200. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of an apparatus according to the present embodiment, or can cause the computer 1200 to perform operations associated with the apparatus according to the present embodiment or one or more "parts," and / or can cause the computer 1200 to perform a process according to the present embodiment or steps of the process. Such a program can be executed by the CPU 1212 to cause the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0065] The computer 1200 according to this embodiment includes a CPU 1212, a GPU 1213, a RAM 1214, and a graphics controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communications interface 1222, a storage device 1224, a DVD drive 1226, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive 1226 may be a DVD-ROM drive, a DVD-RAM drive, or the like. The storage device 1224 may be a hard disk drive, a solid-state drive, or the like. The computer 1200 also includes a ROM 1230 and legacy input / output units such as a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0066] The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into the graphics controller 1216 itself, and causes the image data to be displayed on the display device 1218.

[0067] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive 1226 reads programs or data from a DVD-ROM 1227 or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0068] The ROM 1230 stores therein a boot program or the like that is executed by the computer 1200 upon activation, and / or programs that depend on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0069] The programs are provided by a computer-readable storage medium such as a DVD-ROM 1227 or an IC card. The programs are read from the computer-readable storage medium, installed in the storage device 1224, RAM 1214, or ROM 1230, which are also examples of computer-readable storage media, and executed by the CPU 1212. Information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or a method may be configured by implementing operations or processing of information in accordance with the use of the computer 1200.

[0070] For example, when communication is performed between computer 1200 and an external device, CPU 1212 may execute a communication program loaded into RAM 1214 and instruct communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of CPU 1212, communication interface 1222 reads transmission data stored in a transmission buffer area provided in RAM 1214, storage device 1224, DVD-ROM 1227, or a recording medium such as an IC card, and transmits the read transmission data to a network, or writes received data received from the network to a reception buffer area or the like provided on the recording medium.

[0071] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, the DVD drive 1226 (DVD-ROM 1227), an IC card, etc. to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0072] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and may undergo information processing. The CPU 1212 may perform various types of processing on data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries, each having an attribute value of a first attribute associated with an attribute value of a second attribute, are stored on the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0073] The above-described programs or software modules may be stored in a computer-readable storage medium on or near the computer 1200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0074] The blocks in the flowcharts and block diagrams in the present embodiments may represent stages of a process in which an operation is performed or "parts" of a device responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and / or a processor provided with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuitry may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits, such as field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements.

[0075] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture, including instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable storage media may include electronic, magnetic, optical, electromagnetic, and semiconductor storage media. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disc read-only memories (CD-ROMs), digital versatile discs (DVDs), Blu-ray discs, memory sticks, integrated circuit cards, and the like.

[0076] The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0077] The computer-readable instructions may be provided to a general-purpose computer, a special-purpose computer, or another programmable data processing device processor or programmable circuit, either locally or via a local area network (LAN), a wide area network (WAN) such as the Internet, so that the processor or programmable circuit of the programmable data processing device, such as a computer, executes the computer-readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Here, the computer may be a personal computer (PC), a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, a special-purpose computer, or the like, or may be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system, and is a broad definition of computer. In a distributed computing system, multiple computers collectively execute a program by each executing a portion of the program and passing data between the computers as needed during program execution.

[0078] Examples of processors include computer processors, central processing units (CPUs), processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc. A computer may have one processor or multiple processors. In a multiprocessor system with multiple processors, each processor executes a portion of a program and passes data between processors as needed during program execution, allowing the multiple processors to collectively execute the program. For example, in multitasking, each of the multiple processors may execute a portion of each task in small chunks by switching tasks at each time slice. In this case, which portion of a program each processor executes changes dynamically. Which portion of a program each of the multiple processors executes may also be statically determined by multiprocessor-aware programming.

[0079] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0080] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order.

[0081] 10 Communication system, 30 UE, 100 Management infrastructure, 200 Distribution infrastructure, 202 Memory unit, 204 RAN control unit, 206 AI management unit, 208 Data acquisition unit, 210 Management unit, 212 Instruction unit, 214 Prediction unit, 300 Radio base station, 302 RAN, 310 Radio base station, 312 Cell, 314 Cell, 316 Cell, 320 Radio base station, 322 Cell, 324 Cell, 330 Radio base station, 332 Cell, 334 Cell, 340 Radio base station, 342 Cell, 344 Cell, 350 Radio base station, 352 Cell, 354 Cell, 360 Radio base station, 400 Train, 1200 Computer, 1210 Host controller, 1212 CPU, 1213 GPU, 1214 RAM, 1216 graphic controller, 1218 display device, 1220 input / output controller, 1222 communication interface, 1224 storage device, 1226 DVD drive, 1227 DVD-ROM, 1230 ROM, 1240 input / output chip

Claims

1. A communication system comprising: a data acquisition unit that acquires presence status data indicating the presence status of user terminals in each of a plurality of cells including cells with different frequencies, and available frequency data indicating frequencies available to each of a plurality of user terminals that are present in the plurality of cells; and an instruction unit that, based on the presence status data and the available frequency data, determines a user terminal that is present in one of the plurality of cells to be handed over from the one cell to another cell with a different frequency from the one cell, and instructs the user terminal to hand over from the one cell to the other cell.

2. The communication system of claim 1, wherein the instruction unit instructs a user terminal located in a sparse cell among the plurality of cells whose coverage status is determined to be a sparse state to hand over to a cell using a different frequency from the sparse cell in which the user terminal is located, and causes the radio base station generating the sparse cell to stop generating the sparse cell upon completion of handover from the sparse cell of the user terminal located in the sparse cell.

3. The communication system of claim 2, wherein, when there are multiple quiet cells, the instruction unit instructs a user terminal located in the quiet cell having the highest frequency among the multiple quiet cells to hand over to a cell having a different frequency from the quiet cell in which the user terminal is located, and causes the radio base station that generates the quiet cell to stop generating the quiet cell upon completion of handover from the quiet cell of the user terminal located in the quiet cell.

4. The communication system of claim 1, wherein the instruction unit instructs a user terminal located in a congested cell among the plurality of cells, the location status of which is determined to be congested, to hand over to an unpopulated cell the location status of which is determined to be unpopulated.

5. A communication system according to any one of claims 1 to 4, further comprising: a prediction unit that predicts which of the plurality of cells will become congested; and wherein the instruction unit instructs a user terminal that is present in a cell that has been predicted by the prediction unit to become congested to hand over from that cell to a cell using a different frequency than that of the cell before the cell becomes congested.

6. The communication system according to claim 5, wherein the prediction unit predicts a cell whose presence status will become congested based on presence status data indicating the past presence status of user terminals in each of the plurality of cells.

7. A communication system as described in claim 5, wherein the prediction unit predicts whether the presence status of each of the plurality of cells will be congested based on presence status data indicating the presence status of user terminals in cells located within a predetermined range based on the cell.

8. The communication system described in claim 7, wherein the prediction unit predicts whether the presence status of each of the plurality of cells will be congested based on the presence status data indicating the presence status of user terminals in cells located within a predetermined range based on the cell, and the frequency usage data indicating the frequencies used by user terminals located in cells located within a predetermined range based on the cell.

9. The communication system of claim 5, wherein the prediction unit predicts that the coverage area of ​​a cell among the plurality of cells that has a railway line installed in the area to be covered will be congested based on train schedule data indicating when trains are scheduled to run on the railway line.

10. A data processing method executed by a computer, comprising: a data acquisition step of acquiring presence status data indicating the presence status of user terminals in each of a plurality of cells including cells with different frequencies, and available frequency data indicating frequencies available to each of a plurality of user terminals present in the plurality of cells; and an instruction step of determining, based on the presence status data and the available frequency data, a user terminal present in one of the plurality of cells to be handed over from the one cell to another cell with a different frequency from the one cell, and instructing the user terminal to hand over from the one cell to the other cell.

11. A program for causing a computer to execute the data processing method according to claim 10.

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