Core network system and base station parameter setting method

Abstract

Provided is technology that makes it possible to easily maintain the communication quality of the portable terminal of a user having a specific attribute. A core network system executes the following: a step in which portable terminal information and base station information are acquired; a step in which a movement pattern of a portable terminal is determined; (a) a step in which a movement route of the portable terminal in a future scheduled period is inferred, (b) a step in which one or more base stations estimated to communicate with the mobile terminal on the movement path are determined, and (c) a step in which a base station parameter is calculated, the steps (a), (b), and (c) being executed using a machine learning model generated by learning the movement pattern of the portable terminal; a step in which a setting time for setting the base station parameter in the base stations is determined; and a step in which the base station parameter is set in the one or more base stations at the setting time.

Description

Core network system and method for setting base station parameters

[0001] The present invention relates to a core network system and a method for setting base station parameters.

[0002] In recent years, various measures have been taken to improve communication quality in order to improve the satisfaction of mobile device users such as mobile phones. For example, by adjusting the antenna transmission power, adjusting the antenna angle, cell - to - cell cooperation such as SFN (Single Frequency Network), and adjusting the handover threshold, etc., the communication quality of multiple mobile terminals within a specific area can be maintained and adjusted. For example, Patent Document 1 discloses handover processing when a large number of mobile terminals move simultaneously.

[0003] Japanese Unexamined Patent Application Publication No. 2020 - 014112

[0004] According to the technology described in Patent Document 1, for example, when mobile terminals move en masse as a moving body such as a train moves, the signaling burden related to handover can be reduced. However, the technology described in Patent Document 1 is adjusted for the purpose of improving the perceived average communication quality within a certain range, rather than for a specific user. Therefore, the maintenance of the communication quality of the mobile terminals of users with specific attributes has not been considered, and there is room for improvement.

[0005] An object of the present invention is to provide a technology that can easily maintain the communication quality of mobile terminals of users with specific attributes.

[0006] One aspect of the present disclosure is a core network system for setting parameters for a base station that communicates wirelessly with a mobile terminal, comprising the steps of: acquiring mobile terminal information including communication status associated with the mobile terminal, and base station information including setting information for the base station associated with the base station; determining the mobile terminal's movement pattern based on the mobile terminal information; and performing the following steps (a) to (c) using a machine learning model generated by learning the mobile terminal's movement pattern: (a) inferring the mobile terminal's movement path in a future planned period based on the movement pattern; (b) determining one or more base stations that are presumed to communicate with the mobile terminal on the movement path in the planned period; and (c) calculating base station parameters to be set for one or more base stations so as to maintain the quality of communication with the mobile terminal, determining a setting time for setting the base station parameters to the base station, and setting the base station parameters to one or more base stations at the setting time.

[0007] Another aspect of the present disclosure is a method for setting parameters for a base station that communicates wirelessly with a mobile terminal, comprising the steps of: obtaining mobile terminal information including communication status associated with the mobile terminal and base station information including setting information for the base station associated with the base station; determining the movement pattern of the mobile terminal based on the mobile terminal information; and performing the following steps (a) to (c) using a machine learning model generated by learning the movement pattern of the mobile terminal: (a) inferring the movement path of the mobile terminal in a future planned period based on the movement pattern; (b) determining one or more base stations that are presumed to communicate with the mobile terminal on the movement path in the planned period; and (c) calculating base station parameters to be set for one or more base stations so as to maintain the quality of communication with the mobile terminal; determining a setting time for setting the base station parameters to the base station; and setting the base station parameters to one or more base stations at the setting time.

[0008] According to the present invention, it is possible to provide a technology that makes it possible to easily maintain the communication quality of a mobile terminal of a user having specific attributes.

[0009] Figure 1 is a diagram showing an example of the system configuration of the communication system 1 according to the present disclosure. Figure 2 is a diagram showing the functional block configuration of the core network system 100 according to the present disclosure. Figure 3 is a diagram showing an example of the hardware configuration of the core network system 100 according to the present disclosure. Figure 4 is a diagram showing an overview of the base station parameter setting process performed by the communication system 1 according to the present disclosure. Figure 5A schematically shows a cell formed by communication base stations 200_1, 200_2, 200_3, and 200_4. Figure 5B schematically shows a cell formed by communication base stations 200_1, 200_2, 200_3, and 200_4. Figure 6 is a flowchart of the base station parameter setting method according to the present disclosure.

[0010] Embodiments of the present invention will be described with reference to the attached drawings. In each drawing, components denoted by the same reference numerals have the same or similar configurations.

[0011] <System Configuration> Figure 1 is a diagram showing an example of the system configuration of a communication system 1 according to the embodiment of this disclosure. The communication system 1 according to this embodiment comprises a core network system 100, a plurality of communication base stations 200, and a plurality of mobile terminals 300.

[0012] As described later, the core network system 100 is configured to set base station parameters for the communication base station 200 (base station 200) that communicates wirelessly with the mobile terminal 300. Specifically, the core network system 100 is configured to infer the movement path of the user's mobile terminal 300 and to change and set base station parameters, which are parameters related to the settings of the communication base station 200, according to the inference result.

[0013] More specifically, the core network system 100 is configured to perform the following steps: acquire mobile terminal information including communication status associated with the mobile terminal 300, and base station information including configuration information for the base station 200 associated with the base station 200; determine the movement pattern of the mobile terminal 300 based on the mobile terminal information; use a machine learning model generated by learning the movement pattern of the mobile terminal 300 to perform (a) inference of the movement path of the mobile terminal 300 in a future planned period based on the movement pattern; (b) determine one or more base stations 200 that are presumed to communicate with the mobile terminal 300 on the movement path in the planned period; and (c) calculate base station parameters to be set for one or more base stations 200 so as to maintain the quality of communication with the mobile terminal 300; and further perform the following steps: determine the setting time for setting the base station parameters to the base station 200; and set the base station parameters to one or more base stations 200 at the setting time.

[0014] The core network system 100 is configured to manage a core network that enables authentication processing, location management, policy control, packet forwarding control, communication path establishment, and internet connectivity for mobile terminals 300, for example, via a communication base station 200. The core network managed by the core network system 100 may be, for example, a 5G core network (5GC (5th Generation Core Network)), and may include various functions such as a UPF (User Plane Function), which is a network function (NF) that enables communication with the internet (data network (DN) side) in response to requests from the user's mobile terminal 300; an SMF (Session Management Function), which is a network function that manages communication sessions; and an AMF (Access and Mobility Management Function), which is a network function that queries subscriber information for communication services from a UDM (Unified Data Management) or UDR (Unified Data Repository), etc., and manages access by contracted mobile terminals 300 and the movement of mobile terminals 300.

[0015] The multiple communication base stations 200_1, 200_2, ..., 200_n shown in Figure 1 constitute a radio access network (RAN) that communicates with multiple mobile terminals 300_1, 300_2, ..., 300_n. Furthermore, the communication base stations 200_1, 200_2, ..., 200_n function as relays that relay communications between the multiple mobile terminals 300_1, 300_2, ..., 300_n and the core network system 100. The multiple communication base stations 200_1, 200_2, ..., 200_n are sometimes collectively referred to as communication base station 200.

[0016] The communication base station 200 may be configured to transmit information related to communication quality to the core network system 100, for example, in response to a request from the core network system 100, such as the received signal strength RSSI for the entire bandwidth received by the antenna of the communication base station 200, the reference signal received power RSRP indicating the radio wave strength from the communication base station 200, the radio wave reception quality RSRQ which serves as an indicator of line congestion, and the signal-to-interference noise ratio RSSNR which represents signal quality.

[0017] The multiple mobile terminals 300_1, 300_2, ..., 300_n shown in Figure 1 are devices used by users, such as mobile phones including smartphones and tablet devices, and are also called UE (User Equipment). In the following, mobile terminals 300_1, 300_2, ..., 300_n may be collectively referred to as mobile terminal 300.

[0018] In the communication system 1 according to this embodiment, the mobile terminal 300 used by the user is connected to a communication base station 200 (eNodeB, gNB, etc.) in an LTE (Long Term Evolution) connection environment. The mobile terminal 300 performs a handover as the user moves. For example, when the mobile terminal 300 moves from within the cell of the communication base station 200 with which it has established a communication path (the communication range of communication base station 200_1) to within the cell of another base station 200 (the communication range of another communication base station 200_2) as the user moves, it establishes a communication path with the other communication base station 200_2. In other words, the mobile terminal 300 repeatedly switches the communication base station 200 with which it has established a communication path as the user moves.

[0019] As shown in Figure 1, the communication system 1 may further include a base station management device 400. The base station management device 400 may, for example, have the function of an SMO (Service and Management Orchestration) and may be configured to monitor, manage, and control communications realized by a plurality of communication base stations 200. Furthermore, the communication base stations 200 may be configured to relay communications between the mobile terminal 300 and the core network system 100 via the base station management device 400.

[0020] <Functional Block Configuration> The core network system 100 according to this embodiment will be described with reference to Figure 2. Figure 2 is an example of a functional block diagram of the core network system 100 according to this embodiment. The core network system 100 includes an acquisition unit 110, a movement pattern analysis unit 120, an input unit 130, a trained model 140, a set time determination unit 150, a simulation execution unit 160, a simulation result evaluation unit 170, and a base station parameter transmission unit 180.

[0021] The acquisition unit 110 is configured to acquire, for example, mobile terminal information, which is information about the mobile terminal 300, from the UE database 500A located outside the core network system 100. The acquisition unit 110 is also configured to acquire, for example, base station information, which is information about the communication base station 200, from the base station database 500B.

[0022] The movement pattern analysis unit 120 determines the movement pattern of the mobile terminal 300 based on the mobile terminal information. The movement pattern analysis unit 120 may be configured to determine the movement pattern of the mobile terminal 300 by analyzing information such as the location information of the mobile terminal 300 and time information such as the time spent at each location and the time spent passing through each location.

[0023] The movement pattern analysis unit 120 may, for example, analyze and determine the movement pattern of the mobile terminal 300 using a known behavior pattern analysis method for analyzing the behavior patterns of users using the mobile terminal 300 based on the movement information of the mobile terminal 300. For example, it may be configured to calculate information such as places that the target mobile terminal 300 uses relatively frequently or places that it passes through during specific times on specific days of the week. The movement pattern analysis unit 120 may determine the movement pattern of the mobile terminal 300 based, for example, on point cloud information such as location information of the mobile terminal 300 at predetermined time intervals (for example, every minute or every 10 minutes).

[0024] The input unit 130 inputs the mobile terminal information and base station information acquired by the acquisition unit 110 into the trained model 140. The input unit 130 also inputs the information regarding the mobile terminal 300's movement pattern, which is the result of the movement pattern analysis unit 120, into the trained model 140.

[0025] The trained model 140 performs machine learning using, for example, the movement patterns analyzed by the movement pattern analysis unit 120 as training data. The trained model 140 is also configured to perform the following based on the movement patterns of the mobile terminal 300: inference of the movement path of the mobile terminal 300 over a planned period in the future; determination of one or more communication base stations 200 that are presumed to communicate with the mobile terminal 300 along the movement path over the planned period; and calculation of base station parameters that should be set for the one or more communication base stations 200 so as to maintain communication quality with the mobile terminal 300.

[0026] The setting time determination unit 150 is configured to determine the time to set base station parameters for the determined communication base station 200. The setting time determination unit 150 may be configured to determine, for example, the time to set base station parameters for the communication base station 200 on the travel path where the target user's mobile terminal 300 is expected to travel, either at the time the user is expected to travel or a predetermined time before the time the user is expected to travel.

[0027] The simulation execution unit 160 may be configured to simulate the communication status when base station parameters are set for one or more communication base stations 200 prior to a scheduled period, which is the period during which movement of mobile terminals 300 is predicted. The simulation execution unit 160 may be configured to perform an area simulation based on base station parameters calculated by the trained model 140. For example, the simulation execution unit 160 may be configured to perform a simulation of the communication status between a communication base station 200 for which base station parameters are set and a mobile terminal 300 within the cell of the communication base station 200 for which base station parameters are set.

[0028] The simulation result evaluation unit 170 may be configured to evaluate the simulation results performed by the simulation execution unit 160. The simulation result evaluation unit 170 may be configured to determine, for example, whether the simulation results satisfy a predetermined expected value regarding the throughput of communication quality. The simulation result evaluation unit 170 may be configured to determine, for example, whether the throughput of communication quality in the simulation results exceeds a predetermined expected value.

[0029] In the core network system 100 of the communication system 1 according to this embodiment, if the simulation result evaluation unit 170 determines, for example, that the simulation result does not meet a predetermined expected value regarding the throughput of communication quality, the inference of the mobile terminal 300's movement path using the trained model 140, the determination of the communication base station 200 where communication by the mobile terminal 300 is expected on the movement path, and the calculation of base station parameters may be performed again. Alternatively, if the simulation result evaluation unit 170 determines, for example, that the simulation result meets a predetermined expected value regarding the throughput of communication quality, the base station parameter transmission unit 180 may transmit the base station parameters to the base station management device 400. The base station parameter transmission unit 180 may be configured to transmit the base station parameters directly to the communication base station 200 instead of to the base station management device 400.

[0030] The base station parameter transmission unit 180 may be configured to transmit base station parameters to the base station management device 400 or the communication base station 200 a predetermined time before the set time determined by the set time determination unit 150 (for example, 10 minutes before).

[0031] The core network system 100 may further include a storage unit (not shown) for storing programs executed by the core network system 100. The storage unit may store, for example, information relating to the movement pattern of the mobile terminal 300, information relating to the movement path of the mobile terminal 300, information relating to the communication base station 200 with which the mobile terminal 300 is presumed to communicate, and information relating to the results of simulations performed by the simulation execution unit 160.

[0032] Figures 1 and 2 show an example in which the communication system 1 has a UE database 500A that stores mobile terminal information including communication status, associated with the mobile terminal 300, and a base station database 500B that stores base station information including setting information for the communication base station 200, associated with the communication base station 200. Therefore, although Figures 1 and 2 describe the case in which the UE database 500A and the base station database 500B are configured as physically separate databases, the explanation is not limited to this. The UE database 500A and the base station database 500B may both be provided within the same database. Furthermore, at least one of the mobile terminal information stored in the UE database 500A and the base station information stored in the base station database 500B, and / or at least a part thereof, may be stored in the storage unit of the core network system 100.

[0033] Furthermore, while Figure 2 illustrates a case where the core network system 100 includes a simulation execution unit 160, it is not limited to this configuration. For example, the simulation may be performed outside the core network system 100.

[0034] For example, a digital twin system may be configured outside the core network system 100, and the simulation may be performed in the digital twin system. The digital twin system configured outside the core network system 100 may be configured, for example, to generate a three-dimensional map of the communication base station 200, as described later. In this case, for example, in the digital twin system, base station information, which is information such as the current and past communication status of the communication base station 200, may be updated in real time, and a virtual world synchronized with the real world may be reproduced on the computer that constitutes the digital twin system. In this embodiment, such a digital twin system may also be used in the simulation of the communication status of the communication base station 200 by setting base station parameters calculated by the trained model 140 of the core network system 100.

[0035] <Hardware Configuration> Figure 3 shows an example of the hardware configuration of the core network system 100.

[0036] The core network system 100 includes a processor 11 such as a CPU (Central Processing Unit) and a GPU (Graphical Processing Unit), a storage device 12 such as memory, an HDD (Hard Disk Drive) and / or an SSD (Solid State Drive), a communication interface 13 for wired or wireless communication, an input device 14 for receiving input operations, and an output device 15 for outputting information. The input device 14 is, for example, a keyboard, a touch panel, a mouse and / or a microphone. The output device 15 is, for example, a display, a touch panel and / or a speaker.

[0037] In this embodiment, the mobile terminal 300 may also have a hardware configuration similar to that of the core network system 100 described with reference to Figure 3. Furthermore, the core network system 100 may consist of one or more physical computers or servers as needed, or it may be configured using virtual servers operating on a hypervisor.

[0038] The entire program or a part thereof, which is executed by the core network system 100 according to this embodiment, for setting base station parameters, may be stored and provided on a computer-readable storage medium such as the storage device 12. Alternatively, the entire program or a part thereof may be provided from outside the core network system 100 via a communication network to which the core network system 100 is connected. In the core network system 100, for example, the processor 11 executes the base station parameter setting program according to this embodiment, thereby realizing various operations described later with reference to Figure 4, etc.

[0039] For example, the memory unit of the core network system 100 described above can be implemented using the storage device 12 provided by the core network system 100. Furthermore, the acquisition unit 110, the movement pattern analysis unit 120, the input unit 130, the trained model 140, the setting time determination unit 150, the simulation execution unit 160, the simulation result evaluation unit 170, and the base station parameter transmission unit 180 can be implemented by the processor 11 of the core network system 100 executing a program stored in the storage device 12. This program can be stored in a storage medium as described above, and the storage medium storing the program may be a non-transitory computer-readable medium. The non-transitory storage medium is not particularly limited, but for example, it may be a USB memory or a CD-ROM.

[0040] These physical configurations are illustrative and do not necessarily have to be independent of each other. For example, the core network system 100 according to this embodiment may include an LSI (Large-Scale Integration) in which the processor 11 and the storage device 12 are integrated. Also, as described above, the core network system 100 may include a GPU as the processor 11, in which case the GPU executes the above program, thereby realizing various operations described later with reference to Figure 4, etc.

[0041] The core network system 100 is not limited to the configuration described above. For example, some functions of the core network system 100 may be performed by other information processing devices or servers. Furthermore, the core network system 100 may be configured using a cloud server.

[0042] Furthermore, with respect to each database (UE database 500A and base station database 500B), for example, some or all of the information and data stored in these databases may also be stored in a storage unit provided in the core network system 100.

[0043] <Processing Procedure> Referring to Figure 4, an overview of the base station parameter setting process according to this embodiment will be explained. Figure 4 is a diagram showing an overview of the base station parameter setting process performed by the communication system 1 according to this embodiment.

[0044] First, mobile terminal information is transmitted from mobile terminal 300 to UE database 500A (S402), and the UE database 500A accumulates the mobile terminal information as UE information (S404). The mobile terminal information may be, for example, information such as a phone number related to the mobile terminal 300 or information about applications executed on the mobile terminal 300. The mobile terminal information may include, for example, position information (GPS (Global Positioning System) information), CID (Cell ID), ECGI (E-UTRAN Cell Global Id), RSRP (Reference Signal Received Power), frequency band (Frequency Band), throughput information (Throughput info), etc. of the mobile terminal 300. Further, the mobile terminal information may include, for example, attribute information related to the user who uses the mobile terminal 300. The attribute information related to the user may be associated with, for example, the phone number. In the present embodiment, the attribute information related to the user may include, for example, user attribute information indicating that the user of the mobile terminal 300 satisfies preferential conditions. The user attribute information indicating that the user of the mobile terminal 300 satisfies preferential conditions may be, for example, information indicating that the user is a VIP user.

[0045] Also, the mobile terminal information may include, for example, information related to the network to which the mobile terminal 300 is connected. For example, the subscriber number (International Mobile Subscription Identity (IMSI)) in the user's mobile network may be included in the mobile terminal information. Further, the mobile terminal information may include, for example, information related to handover (Hand Over (HO)) generated in the mobile terminal 300, traffic information related to the communication status, access information, call drop (Call Drop) information, etc.

[0046] Furthermore, base station information is transmitted from the communication base station 200 to the base station database 500B (S406), and the base station information is stored in the base station database 500B (S408). In this embodiment, the base station information may include, for example, data relating to the configuration of the Radio Access Network (RAN) (RAN Config Data). The data relating to the configuration of the Radio Access Network may include, for example, information about the cells formed by the communication base station 200, transmission power information relating to the power transmitted by the communication base station 200, tilt information relating to the inclination of the antenna, information relating to handover (HO information), information relating to cell reselection in the mobile terminal 300 (CellReselectionInfo), and information relating to the priority of information communicated by the user (Quality of Service Class Indicator (QCI)). In addition, the base station information may include, for example, location information of the communication base station 200, such as the latitude and longitude of the communication base station 200, and 3D map information of the vicinity of the cells formed by the communication base station 200. Furthermore, the base station information may include, for example, information about the cells formed by the communication base station 200, which has been recreated using a digital twin.

[0047] The core network system 100 executes a step of acquiring mobile terminal information including communication status obtained from the mobile terminal 300 associated with the mobile terminal 300 and base station information including setting information for the communication base station 200 associated with the communication base station 200. In the present embodiment, for example, the acquisition unit 110 of the core network system 100 acquires mobile terminal information from the UE database 500A (S410). Further, the acquisition unit 110 of the core network system 100 acquires base station information from the base station database 500B (S412). Note that the transmission of mobile terminal information from the mobile terminal 300 to the UE database 500A (S402), the accumulation of mobile terminal information in the UE database 500A (S404), the base station data transmission from the communication base station 200 (S406), the accumulation of base station data by the base station database 500B (S408), the acquisition of mobile terminal information by the core network system 100 (S410), and the acquisition of base station data (S412) do not necessarily have to be executed in this order. For example, all or some of these may be executed simultaneously.

[0048] Next, the core network system 100 analyzes and determines the movement pattern of the mobile terminal 300 (S414). For example, the movement pattern analysis unit 120 of the core network system 100 determines the movement pattern of the mobile terminal 300 based on the mobile terminal information. The movement pattern analysis unit 120 analyzes and determines the movement pattern of the mobile terminal 300 based on information such as the position information of the mobile terminal 300 and time information such as the stay time and passing time at each position.

[0049] Subsequently, the core network system 100 executes learning and inference using the learned model 140. The learned model 140 performs machine learning using, for example, the determined movement pattern, which is the analysis result by the movement pattern analysis unit 120, as teacher data.

[0050] Furthermore, the trained model 140 performs inference of the mobile terminal 300's movement path in a future planned period based on the determined movement pattern of the mobile terminal 300 (S416_a). For example, based on the movement pattern determined as a result of the analysis, the facilities used and the routes taken by the mobile terminal 300 of a target user at specific times on specific days of the week may be predicted. For example, if the analysis of the movement pattern determines that a certain user's mobile terminal 300_k has a pattern of moving from point A to point B between 8:00 a.m. and 9:00 a.m. every Monday, then the inference may predict that the user's mobile terminal 300_k will also move from point A to point B between 8:00 a.m. and 9:00 a.m. every Monday in future periods such as next week.

[0051] Furthermore, the trained model 140 determines one or more communication base stations 200 that are presumed to communicate with the mobile terminal 300 along a travel route during a planned period in the future (S416_b). For example, in the above example, if a travel route is inferred in which the user of mobile terminal 300_k moves from point A to point B between 8:00 a.m. and 9:00 a.m. on Monday, then the communication base stations 200 to which the mobile terminal 300_k will connect along that travel route from point A to point B between 8:00 a.m. and 9:00 a.m. on Monday are determined. For example, the communication base stations 200 near the travel route from point A to point B are determined to be communication base station 200_k1, communication base station 200_k2, and communication base station 200_k3.

[0052] Furthermore, the trained model 140 calculates base station parameters to be set for one or more communication base stations 200 determined to maintain communication quality with the mobile terminal 300 (S416_c). The base station parameters may be, for example, parameters that change the settings of the communication base station 200. Examples of base station parameters may include parameters that correspond to changes in the output power of the communication base station 200, changes in the tilt of the antenna of the communication base station 200, adjustments to parameters related to handover (HO), and changes in the configuration of the single frequency network (SFN). By changing the output power of the communication base station 200, for example, the size of the cell formed by the communication base station 200 can be changed. Also, by changing the tilt of the antenna, the directivity and position of the cell formed by the communication base station 200 can be changed. Also, for example, by adjusting the handover threshold, the frequency of handovers between cells can be adjusted. Also, by adjusting the single frequency network, for example, it is possible to set the same frequency for multiple communication base stations 200 and virtually form a large cell. For example, if the mobile terminal 300 is virtually located in a large cell, it becomes possible to suppress the occurrence of handovers that occurred between cells before the merger.

[0053] An example of changing base station parameters will be explained with reference to Figures 5A and 5B. Figures 5A and 5B schematically show a cell formed by multiple communication base stations 200 (communication base stations 200_1, 200_2, 200_3, and 200_4). Figure 5A schematically shows each cell before changing the base station parameters, and Figure 5B schematically shows each cell after changing the base station parameters.

[0054] As shown in Figure 5A, base stations 200_1, 200_2, 200_3, and 200_4 form cells C1, C2, C3, and C4, respectively. When a user using mobile terminal 300_1 travels along the travel path MR1, the mobile terminal 300_1 passes through cells C2, C3, C1, and C4 in that order. Therefore, since a handover occurs when passing through the boundary between different cells, at least three handovers may occur in the mobile terminal 300_1.

[0055] Therefore, for example, if the mobile terminal information includes user attribute information indicating that the user of mobile terminal 300_v meets preferential conditions, the base station parameters of communication base stations 200_1, 200_2, 200_3, and 200_4 are changed so that a cell configuration as shown in Figure 5B is formed by communication base stations 200_1, 200_2, 200_3, and 200_4, with the aim of reducing the number of handovers. For example, the output power of communication base stations 200_2 and 200_4 is reduced, and the output power of communication base stations 200_2 and 200_4 is changed, and the single-frequency network configuration of communication base stations 200_1 and 200_3 is changed so that a single cell C13 is formed by virtually combining cell C1 formed by communication base station 200_1 and cell C3 formed by communication base station 200_3.

[0056] As a result, as shown in Figure 5B, in the mobile terminal 300_v's travel path MRv, the mobile terminal 300_v passes only through the virtually connected cell C13, thus suppressing the occurrence of handovers on the travel path MRv. Therefore, it becomes possible to improve the communication quality used by the user of the mobile terminal 300_v.

[0057] Returning to Figure 4, in the base station parameter setting process according to this embodiment, the setting time determination unit 150 determines the setting time for setting the base station parameters to the communication base station 200 (S418). For example, in the above example, if the target user's mobile terminal 300_k moves from point A to point B between 8:00 AM and 9:00 AM on Monday, the setting time may be set so that the base station parameters of communication base stations 200_k1, 200_k2, and 200_k3 are changed at 8:00 AM. Alternatively, the base station parameters of base stations 200_k1, 200_k2, and 200_k3 may be set to be changed at a predetermined time before the expected time when the mobile terminal 300_k of the target user is expected to move, such as at 7:50 a.m., 10 minutes before 8:00 a.m., or the base station parameters of base stations 200_k1, 200_k2, and 200_k3 may be set to be changed sequentially at 7:50 a.m., 8:10 a.m., and 8:30 a.m., respectively, in accordance with the movement speed of the mobile terminal 300_k.

[0058] Next, the simulation execution unit 160 of the core network system 100 performs a simulation using the base station parameters calculated by the trained model 140 (S420). For example, the simulation execution unit 160 simulates the communication situation when the base station parameters are set to one or more communication base stations 200 at a set time determined by the set time determination unit 150, prior to the expected period during which the movement of the mobile terminal 300 user is predicted.

[0059] In the simulation execution unit 160, for example, prior to a future scheduled period in which the movement of the mobile terminal 300 is predicted, a simulation of the communication status is performed when the base station parameters are set for the communication base station 200 determined in S416_b above. The simulation execution unit 160 may be configured to output, for example, numerical values ​​related to the communication quality provided by the communication base station 200 with the changed base station parameters as a simulation result of the communication status simulation. The simulation execution unit 150 may output, for example, information related to communication quality as a simulation result, such as the received signal strength RSSI for the entire bandwidth received by the antenna of the communication base station 200, the reference signal received power RSRP indicating the radio wave strength from the communication base station 200, the radio wave reception quality RSRQ which serves as an indicator of line congestion, and the signal-to-interference noise ratio RSSNR which represents signal quality. The simulation execution unit 160 may, as described above, perform the simulation using, for example, a digital twin system.

[0060] Next, the simulation result evaluation unit 170 of the core network system 100 evaluates the simulation results executed by the simulation execution unit 160. The simulation result evaluation unit 170 determines, for example, whether the simulation results satisfy predetermined expected values ​​regarding the throughput of communication quality. In the example shown in Figure 4, two expected values ​​are set as predetermined expected values ​​regarding the throughput of communication quality, and the simulation results determine whether the communication quality satisfies the two thresholds.

[0061] In this embodiment, the predetermined expected value may include, for example, a first expected value (Thp1) set for maintaining the communication quality of a mobile terminal 300 of a user who meets the preferential conditions, and a second expected value (Thp2) set for maintaining the communication quality of a mobile terminal 300 of a user who does not meet the preferential conditions. The simulation result evaluation unit 170 determines, for example, whether the simulation result for a mobile terminal 300 of a user who meets the preferential conditions satisfies the first expected value Thp1 (S422). Subsequently, the simulation result evaluation unit 170 determines, for example, whether the simulation result for a mobile terminal 300 of a user who does not meet the preferential conditions satisfies the second expected value Thp2 (S424).

[0062] If the simulation results for the mobile terminal 300 of a user who meets the preferential conditions satisfy the first expected value Thp1 (Yes in S422) and the second expected value Thp2 for the mobile terminal 300 of a user who does not meet the preferential conditions (Yes in S424), then base station parameters may be set for the one or more communication base stations 200 determined above. At this time, for example, language conversion of the command including the base station parameters may be performed (S426). For example, the machine language of the command that sets the base station parameters may be converted into the machine language of a command that can be executed at the communication base stations 200_k1, 200_k2, and 200_k3 that are the targets of the base station parameter change setting. For example, if the manufacturers of the communication base stations 200 are different, the machine language of the executable commands may be different. Therefore, the language of the command may be converted before sending the command to the communication base stations 200.

[0063] The base station parameters included in the command, which has been converted into machine language executable by the communication base station 200, may be transmitted from the core network system 100 to the base station management device 400 (S428). The command including the base station parameters may be transmitted to the communication base station 200 at the above-mentioned set time, or it may be transmitted in advance prior to the set time.

[0064] The base station management device 400 acquires the base station parameters included in the command (S430) and sets the base station parameters on the communication base station 200 (S432). The base station parameters are set on the communication base station 200 at the determined setting time.

[0065] At the communication base station 200, the settings are changed according to the configured base station parameters (S434). A cell is then formed by the communication base stations whose settings have been changed.

[0066] Subsequently, for example, the mobile terminal 300_k of the target user is located within a cell formed by communication base stations 200_k1, 200_k2, and 200_k3 along the travel path, and makes a connection request to the communication base stations 200_k1, 200_k2, or 200_k3 that form the cell (S436). The communication base stations 200_k1, 200_k2, or 200_k3 that received the connection request establish a connection in response to the request (S438).

[0067] In the embodiment described above, the simulation results for the mobile terminal 300 of a user who satisfies the preferential conditions satisfy a first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not satisfy the preferential conditions satisfy a second expected value Thp2. In this case, for example, reinforcement learning of the machine learning model (trained model 140) may be performed using a reward function that gives a reward when the simulation results satisfy a predetermined expected value (first expected value Thp1 and / or second expected value Thp2). In this embodiment, for example, a reward function may be used in which the reward for the simulation of the mobile terminal 300 of a user who satisfies the preferential conditions is set to be different from the reward for the simulation of the mobile terminal 300 of a user who does not satisfy the preferential conditions. By performing such reinforcement learning, the trained model 140 can be further trained, and the accuracy of inference by the trained model 140 in the inference phase can be improved.

[0068] In this embodiment, if the simulation results for the mobile terminal 300 of a user who meets the preferential conditions satisfy the first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not meet the preferential conditions satisfy the second expected value Thp2, then, for example, when the mobile terminal 300_k of the target user moves along a predicted travel path, the mobile terminal 300_l of another user (a user who does not meet the preferential conditions) also moves along a similar travel path, or is located within a cell formed by the same communication base station 200 (communication base station 200_k1, communication base station 200_k2, and communication base station 200_k3), then both the mobile terminals 300_k and 300_l satisfy the first expected value Thp1 and the second expected value Thp2. Therefore, if the simulation results for the mobile terminal 300 of a user who meets the preferential conditions satisfy the first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not meet the preferential conditions satisfy the second expected value Thp2, then by changing the base station parameters through the above process, the communication quality can be improved for both the mobile terminal 300 of the user who meets the preferential conditions and the mobile terminal 300 of the user who does not meet the preferential conditions.

[0069] The base station parameter setting process according to this embodiment can be applied not only to maintaining communication quality for users who meet preferential conditions, but also to maintaining communication quality for both users who meet and do not meet preferential conditions. For example, even for a mobile terminal 300 of a user riding in a vehicle (such as a train or bus) that moves from point A to point B at a specific time, it is possible to maintain communication quality by executing the base station parameter setting process according to this embodiment. For example, even if both users who meet and do not meet preferential conditions are riding in the vehicle, it is possible to maintain communication quality for the mobile terminal 300 of any user by applying the base station parameter setting process according to this embodiment.

[0070] In this embodiment, on the other hand, if the simulation results do not satisfy the first expected value Thp1 and / or the second expected value Thp2 (i.e., if the simulation results for the mobile terminal 300 of a user who satisfies the preferential conditions satisfy the first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not satisfy the preferential conditions do not satisfy the second expected value Thp2, or if the simulation results for the mobile terminal 300 of a user who satisfies the preferential conditions do not satisfy the first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not satisfy the preferential conditions satisfy the second expected value Thp2, or if the simulation results for the mobile terminal 300 of a user who satisfies the preferential conditions do not satisfy the first expected value Thp1, and the simulation results for the mobile terminal 300 of a user who does not satisfy the preferential conditions do not satisfy the second expected value Thp2), then, as shown in Figure 4, training / inference (S416) using the trained model 140 may be performed again. For example, if the simulation results do not satisfy the first expected value Thp1 and / or the second expected value Thp2, the following may be further performed: inference of the user's travel path (S416_a) and calculation of base station parameters (S416_c), or inference of the user's travel path (S416_a), determination of the communication base station 200 that communicates with the mobile terminal 300 along the inferred travel path (S416_b) and calculation of base station parameters (S416_c).

[0071] In this embodiment, however, the base station parameters may also be set if the simulation results described above do not satisfy the first expected value Thp1 and / or the second expected value Thp2. For example, if the simulation results for a mobile terminal 300 of a user who meets the preferential conditions satisfy the first expected value Thp1, and the simulation results for a mobile terminal 300 of a user who does not meet the preferential conditions do not satisfy the second expected value Thp2, the settings of the communication base station 200 may be changed based on the base station parameters set in this simulation. In this case, although the communication quality of the mobile terminal 300 of a user who does not meet the preferential conditions cannot be maintained in the simulation, the communication quality of the mobile terminal 300 of a VIP user who meets the preferential conditions can be maintained, so the settings of the communication base station 200 may be changed based on the base station parameters set in this case.

[0072] As described above, by executing the base station parameter setting process according to this embodiment, the movement pattern of the target user's mobile terminal 300 is determined by pattern analysis, and based on the determined movement pattern, the movement path of the mobile terminal 300 over a planned period is inferred, one or more communication base stations 200 that are presumed to communicate with the mobile terminal on the movement path over the planned period are determined, and base station parameters that maintain communication quality with the mobile terminal 300 are calculated. The setting time for setting the base station parameters to the communication base stations 200 is determined, and the base station parameters are set to the communication base stations 200 at the determined setting time. Therefore, for example, for the target user's mobile terminal 300, by inferring the movement path over the planned period and setting the base station parameters to the communication base stations 200 on the movement path, it is possible to maintain communication quality while the mobile terminal 300 moves along the movement path.

[0073] For example, if it is possible to deduce the behavioral patterns of VIP users who meet preferential conditions, such as users who pay high usage fees, important visitors, or corporate executives, and who move or stop at predetermined times, such as during commuting hours, then by changing the date, time, and base station parameters of the communication base station 200 along the travel route in advance, it becomes possible to improve the performance of the target user's mobile terminal 300 along the travel route. In this way, the base station parameter setting process according to this embodiment makes it possible to easily maintain the communication quality of mobile terminals of users with specific attributes.

[0074] Referring to Figure 6, a method for setting base station parameters according to the embodiment of this disclosure will be described. Figure 6 is a flowchart of the method for setting base station parameters according to the embodiment of this disclosure. Note that the method for setting base station parameters according to this embodiment may be performed, for example, by the core network system 100 (Figures 1, 2, etc.).

[0075] First, data acquisition is performed (S602). Specifically, mobile terminal information, including communication status, associated with the mobile terminal 300, and base station information, including configuration information for the base station 200, associated with the base station 200 are acquired.

[0076] Next, the movement pattern is determined (S604). That is, the movement pattern of the mobile terminal 300 is determined based on the acquired mobile terminal information.

[0077] Next, learning and inference are performed. Specifically, using a machine learning model 140 generated by learning the movement patterns of the mobile terminal 300, the following are performed: inference of the movement path of the mobile terminal 300 in a future planned period based on the movement patterns (S606); determination of one or more communication base stations 200 (base stations 200) that are presumed to communicate with the mobile terminal 300 on the movement path in the planned period (S608); and calculation of base station parameters to be set for the determined one or more communication base stations 200 so as to maintain the quality of communication with the mobile terminal 300 (S610).

[0078] Next, the setting time is determined (S612). That is, the setting time for setting the base station parameters to base station 200 is determined.

[0079] Next, the base station parameters are set (S614). That is, the base station parameters are set to the one or more communication base stations 200 determined above at the determined time.

[0080] <Summary> According to the embodiment described above, in the core network system 100 of the communication system 1, the movement pattern of the target user's mobile terminal 300 is determined by pattern analysis, and based on the determined movement pattern, the movement path of the mobile terminal 300 over a planned future period is inferred, one or more communication base stations 200 that are presumed to communicate with the mobile terminal on the movement path over the planned period are determined, and base station parameters that maintain communication quality with the mobile terminal 300 are calculated, and a setting time for setting the base station parameters in the communication base station 200 is determined, and the base station parameters are set in the communication base station 200 at the determined setting time. This makes it possible to provide a technology that can easily maintain the communication quality of a user's mobile terminal having specific attributes. Furthermore, the technology according to this embodiment can contribute to achieving Sustainable Development Goal (SDG) 9, "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation."

[0081] The embodiments described above are for the purpose of facilitating understanding of the present invention and are not intended to limit its interpretation. The flowcharts, sequences, elements, and their arrangement, materials, conditions, shapes, and sizes described in the embodiments are not limited to those exemplified and can be modified as appropriate. Furthermore, the calculation methods described in the embodiments described above are not limited to those exemplified. It is also possible to partially substitute or combine the configurations shown in different embodiments.

[0082] 1...Communication system, 100...Core network system, 110...Acquisition unit, 120...Movement pattern analysis unit, 130...Input unit, 140...Machine learning model, 150...Setting time determination unit, 160...Simulation execution unit, 170...Simulation result evaluation unit, 180...Base station parameter transmission unit, 200...Communication base station (base station), 300...Mobile terminal, 400...Base station management device, 500A...UE database, 500B...Base station database

Claims

1. A core network system for setting parameters for a base station that communicates wirelessly with a mobile terminal, comprising the steps of: acquiring mobile terminal information including communication status associated with the mobile terminal, and base station information including setting information for the base station associated with the base station; determining the movement pattern of the mobile terminal based on the mobile terminal information; and performing the following steps (a) to (c) using a machine learning model generated by learning the movement pattern of the mobile terminal: (a) inferring the movement path of the mobile terminal in a future planned period based on the movement pattern; (b) determining one or more base stations that are presumed to communicate with the mobile terminal on the movement path in the planned period; and (c) calculating base station parameters to be set for the one or more base stations so as to maintain the quality of communication with the mobile terminal; determining a setting time for setting the base station parameters to the base station; and setting the base station parameters to the one or more base stations at the setting time.

2. The core network system according to claim 1, further comprising:

1. The step of simulating the communication status when the base station parameters are set to the one or more base stations prior to the scheduled period; and 2. The step of determining whether the results of the simulation satisfy a predetermined expected value for the throughput of the communication quality, wherein the base station parameters are set to the one or more base stations based on the result of the determination.

3. The core network system according to claim 2, wherein the information relating to the mobile terminal includes user attribute information indicating that the user of the mobile terminal meets preferential conditions.

4. The core network system according to claim 3, wherein the predetermined expected value includes a first expected value set for maintaining the communication quality of the mobile terminal of the user who satisfies the preferential conditions, and a second expected value set for maintaining the communication quality of the mobile terminal of the user who does not satisfy the preferential conditions, and the system performs the step of setting the base station parameters for one or more base stations if the result of the simulation satisfies both the first and second expected values.

5. The core network system according to claim 2, wherein the step of performing reinforcement learning of the machine learning model is performed using a reward function that gives a reward when the result of the simulation satisfies the predetermined expected value.

6. The core network system according to claim 2, further comprising the steps of: inferring the travel path of the mobile terminal; and calculating the base station parameters if the results of the simulation do not satisfy the predetermined expected value.

7. The core network system according to claim 4, further comprising the steps of: inferring the travel path of the mobile terminal; and calculating the base station parameters if the result of the simulation does not satisfy the first expected value; or if the result of the simulation does not satisfy the second expected value.

8. A method for setting parameters for a base station that communicates wirelessly with a mobile terminal, comprising: a step of acquiring mobile terminal information including communication status associated with a mobile terminal, and base station information including setting information for the base station associated with a base station; a step of determining the movement pattern of the mobile terminal based on the mobile terminal information; a step of performing the following (a) to (c) using a machine learning model generated by learning the movement pattern of the mobile terminal: (a) a step of inferring the movement path of the mobile terminal in a future planned period based on the movement pattern; (b) a step of determining one or more base stations that are presumed to communicate with the mobile terminal on the movement path in the planned period; and (c) a step of calculating base station parameters to be set for the one or more base stations so as to maintain the quality of communication with the mobile terminal; a step of determining a setting time for setting the base station parameters to the base station; and a step of setting the base station parameters to the one or more base stations at the setting time.

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