Information processing device, information processing method, and program

Abstract

An information processing device according to the present disclosure comprises a control unit. The control unit generates an inference model by using data related to communication characteristics in a first area and a captured image of the first area. The inference model is used for inferring communication characteristics in a second area different from the first area.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] In wireless communication, there is known a technique for realizing more suitable communication by appropriately controlling radio resources and communication parameters. For example, suitable communication can be realized by adaptively controlling communication parameters according to the state of the propagation path between a base station and a terminal device.

[0003] For example, a base station transmits a known signal and a terminal device receives the known signal, thereby enabling the terminal device to estimate the state of the propagation path. Furthermore, the terminal device feeds back the estimated state of the propagation path to the base station, allowing the base station to set suitable communication parameters for the terminal device.

[0004] In addition, if there is no feedback from the terminal device regarding the propagation path conditions, the base station can recognize the average propagation path conditions by using a statistical propagation model (e.g., a path loss model, an interference model, etc.) that corresponds to the distance from the terminal device.

[0005] Japanese Patent Application Laid-Open No. 2021-108459

[0006] However, radio wave propagation in wireless communication varies greatly depending on, for example, the presence or absence of obstacles between a base station (transmitting point) and a terminal device (receiving point). In addition, when considering interference with neighboring cells and surrounding base stations, the base station determines communication parameters based on statistical information such as a propagation model to minimize the interference.

[0007] Therefore, when communication is performed using communication parameters determined by a base station, there is a risk that suitable wireless communication will not be possible depending on obstacles that exist in the space where the base station and the terminal device actually perform wireless communication (hereinafter also referred to as real space). For example, when a base station determines the minimum transmission power to minimize interference, if an obstacle exists between the base station and the terminal device, there is a risk that the signal transmitted by the base station will not reach the terminal device due to this obstacle.

[0008] Therefore, it is desirable that the base station and the terminal device communicate with more appropriate communication parameters. In order to set these communication parameters appropriately, it is desirable to estimate the propagation path conditions between the base station and the terminal device, such as communication characteristics, with high accuracy.

[0009] Therefore, the present disclosure provides a mechanism that can estimate the propagation path conditions between a base station and a terminal device with higher accuracy.

[0010] It should be noted that the above problem or object is merely one of multiple problems or objects that can be solved or achieved by multiple embodiments disclosed in this specification.

[0011] The information processing device of the present disclosure includes a control unit that generates an estimation model using data related to communication characteristics in a first area and a captured image of the first area, and the estimation model is used to estimate the communication characteristics in a second area different from the first area.

[0012] 1 is a diagram illustrating an example of radio wave propagation according to a proposed technique of the present disclosure. FIG. 2 is a diagram illustrating an example of a communication process according to an embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of a configuration of a wireless communication system according to a first embodiment of the present disclosure. FIG. 4 is a diagram illustrating another example of a configuration of a wireless communication system according to the first embodiment of the present disclosure. FIG. 5 is a block diagram illustrating an example of a configuration of a base station according to the first embodiment of the present disclosure. FIG. 6 is a block diagram illustrating an example of a configuration of a terminal device according to the first embodiment of the present disclosure. FIG. 7 is a diagram illustrating an example of a configuration of a control station according to the first embodiment of the present disclosure. FIG. 8 is a block diagram illustrating an example of a configuration of a generation process and a determination process according to an embodiment of the present disclosure. FIG. 9 is a block diagram illustrating an example of a configuration of a generation unit according to an embodiment of the present disclosure. FIG. 10 is a diagram illustrating an example of a first captured image according to an embodiment of the present disclosure. FIG. 11 is a diagram illustrating an example of a result of segmentation according to an embodiment of the present disclosure. FIG. 12 is a scatter plot illustrating a relationship between a blocking ratio and a shadowing value according to an embodiment of the present disclosure. FIG. 13 is a scatter plot illustrating a relationship between an average RSRP and a transmission-reception distance according to an embodiment of the present disclosure. FIG. 14 is a sequence diagram illustrating an example of a flow of a generation process according to an embodiment of the present disclosure. FIG. 15 is a sequence diagram illustrating an example of a flow of a determination process according to an embodiment of the present disclosure. FIG. 16 is a flowchart illustrating an example of a flow of an information generation process according to an embodiment of the present disclosure. FIG. 17 is a diagram illustrating an example of a user interface of a terminal device according to a first application example of the present disclosure. FIG. 18 is a diagram illustrating an example of a user interface of a terminal device according to a second application example of the present disclosure. FIG. 19 is a block diagram

[0013] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0014] Furthermore, in this specification and drawings, similar components of the embodiments may be distinguished by adding at least one different alphabet and / or number after the same reference numeral. However, if there is no need to particularly distinguish between similar components, only the same reference numeral is used. For example, multiple components having substantially the same functional configuration may be distinguished as necessary, such as terminal device 400_1 and terminal device 400_2. For example, if there is no need to particularly distinguish between terminal device 400_1 and terminal device 400_2, they will simply be referred to as terminal device 400.

[0015] One or more embodiments (including examples, modifications, and application examples) described below can be implemented independently. However, at least a portion of the embodiments described below may be implemented in appropriate combination with at least a portion of another embodiment. These embodiments may include novel features that are different from each other. Therefore, these embodiments may contribute to solving different purposes or problems and may produce different effects from each other.

[0016] <<1. Introduction>> <1-1. Background> As described above, in wireless communication, suitable communication is realized by adaptively controlling communication parameters in accordance with the state of a propagation path between a base station and a terminal device. For example, a terminal device estimates the state of a propagation path between the base station and the terminal device using a known signal transmitted from the base station. The base station sets appropriate communication parameters for the terminal device based on the state of the propagation path fed back from the terminal device.

[0017] Furthermore, if there is no feedback on the propagation path conditions from the terminal device, the base station recognizes the average propagation path conditions using a statistical propagation model (e.g., a path loss model or an interference model) according to the distance from the terminal device. Even if there is no feedback on the propagation path conditions, the base station sets communication parameters for the terminal device based on the average propagation path conditions.

[0018] <1-2. Issues> However, radio wave propagation in wireless communication varies greatly depending on the presence or absence of obstacles between the base station (transmission point) and the terminal device (reception point). This point will be explained using FIG.

[0019] 1A and 1B are diagrams illustrating an example of radio wave propagation according to the proposed technique of the present disclosure, in which Fig. 1A is a diagram illustrating an example of radio wave propagation when there is no obstacle 600, and Fig. 1B is a diagram illustrating an example of radio wave propagation when there is an obstacle 600.

[0020] For example, when the base station 300 transmits a transmission power P ｔｘ When there is no obstacle 600 (see FIG. 1(a)), the radio wave can reach a longer distance than when there is an obstacle 600 (see FIG. 1(b)).

[0021] When determining communication parameters using the above-mentioned statistical propagation model, the base station must determine the communication parameters to minimize interference with neighboring cells and surrounding base stations, because the statistical propagation model differs from the actual propagation path conditions.

[0022] Here, the statistical propagation model is generated by limiting the communication environment to typical propagation environments such as free space, urban areas, etc. Therefore, if the statistical propagation model is used to estimate radio wave strength in a specific environment, the estimation accuracy may be degraded.

[0023] Therefore, in conventional interference design, base stations take into account fluctuations in radio wave strength due to obstacles and add a large margin to the interference power to avoid interference with adjacent cells and surrounding base stations.

[0024] In this way, if communication parameters are determined with a large margin added in order to minimize interference, the utilization efficiency of radio resources may be limited, which may cause a significant degradation of communication performance.

[0025] Furthermore, when the terminal device estimates the propagation path conditions and provides feedback, the base station 300 can determine more accurate communication parameters according to the actual transmission path conditions. However, the base station 300 can only grasp the propagation path conditions at the location of the terminal device that provided the feedback.

[0026] Therefore, when a terminal device moves, it is not possible to grasp the propagation path conditions at the destination more accurately, and it is also not possible to grasp the propagation path conditions at a location where no terminal device is present more accurately.

[0027] Furthermore, when a large number of terminal devices each feed back information on the propagation path conditions, the communication resources required for the feedback become overhead, which becomes a factor in reducing the efficiency of radio resource utilization in the entire communication system.

[0028] Furthermore, depending on the use case, there is a risk that the base station may not receive sufficient feedback on the propagation path conditions from the terminal device. For example, there may be cases where the base station receives no feedback at all or only a small amount of feedback from the terminal device.

[0029] In such a situation (environment, location, area), the communication system is required to estimate propagation path conditions of the terminal device and / or the base station with high accuracy. The propagation path conditions may include, for example, communication characteristics and the wireless communication environment.

[0030] <1-3. Overview of Proposed Technology> Fig. 2 is a diagram illustrating an example of communication processing according to an embodiment of the present disclosure. The communication processing illustrated in Fig. 2 is executed in a communication system (not shown). The communication processing is executed by a control station (not shown) of the communication system.

[0031] The control station acquires first data and first captured images in a first area.

[0032] The first data is, for example, data (measured data) obtained by actually measuring a signal from a base station in the first area by a terminal device. Alternatively, the first data is, for example, data (measured data) obtained by actually measuring a signal from a terminal device in the first area by a base station. The first data is, for example, data related to communication characteristics in the first area.

[0033] Although the first data is assumed to be actual measurement data here, the first data may be simulation data, or the first data may include actual measurement data and simulation data.

[0034] The first captured image is, for example, an image of the surroundings of the terminal device captured under predetermined conditions, such as the direction of a base station.

[0035] The terminal device that transmits the first data and the terminal device that transmits the first captured image may be the same device or different devices.

[0036] Furthermore, the timing of transmitting the first data and the timing of transmitting the first captured image may be the same or different. For example, the terminal device may transmit the first captured image at the same time as transmitting the first data.

[0037] Furthermore, the location where the terminal device measures the first data (hereinafter referred to as the measurement location) and the location where the first photographed image is captured (hereinafter referred to as the photographing location) may be different. A terminal device at one location may measure the first data, and a terminal device at another location may capture the first photographed image. Alternatively, one terminal device may measure the first data at one location and capture the first photographed image at another location.

[0038] Furthermore, a device not included in the communication system may capture and / or transmit the first captured image. For example, the first captured image may be captured by a device (e.g., a camera) of a system different from the communication system to which the control station that executes the communication processing belongs. In this case, the control station acquires the first captured image from, for example, the communication system different from the system to which the control station belongs.

[0039] The control station generates an estimation model using the acquired first data and the first captured image, and the estimation model is used to estimate communication characteristics in a second area different from the first area.

[0040] The estimation models include, for example, a first estimation model and a second estimation model. The control station generates the second estimation model based on, for example, the first data. The control station also generates the first estimation model using the first captured image. The control station estimates communication characteristics in the second area by correcting the output of the second estimation model using the first estimation model.

[0041] For example, the control station acquires second data and second captured images in a second area.

[0042] The second data may include, for example, information related to the terminal device and / or the base station. The second data may be, for example, location information of the terminal device and the base station. Alternatively, the second data may be data (measured data) obtained by actually measuring a signal from a base station in the second area by the terminal device. Alternatively, the second data may be, for example, data (measured data) obtained by actually measuring a signal from a terminal device in the second area by the base station. The second data may include, for example, data related to communication characteristics in the second area.

[0043] Here, the second data includes actual measurement data, but the second data may also include simulation data.

[0044] The second captured image is, for example, an image of the surroundings of the terminal device captured under predetermined conditions, such as the direction of a base station.

[0045] The terminal device that transmits the second data and the terminal device that transmits the second captured image may be the same device or different devices.

[0046] Furthermore, the timing of transmitting the second data and the timing of transmitting the second captured image may be the same or different. For example, the terminal device may transmit the second captured image at the same time as transmitting the second data.

[0047] It is desirable that the measurement point of the second data and the photographing point of the second photographed image are the same or close to each other (within a predetermined range). When the measurement point of the second data and the photographing point of the second photographed image are within a predetermined range, the estimation accuracy of the communication characteristics of the second area by the estimation model can be further improved.

[0048] Furthermore, a device not included in the communication system may capture and / or transmit the second captured image. For example, the second captured image may be captured by a device (e.g., a camera) of a system different from the communication system to which the control station that executes the communication processing belongs. In this case, the control station acquires the second captured image from, for example, the communication system different from the system to which the control station belongs.

[0049] The control station estimates communication characteristics in the second area using an estimation model based on the second data and the second captured image, and generates estimated data relating to communication characteristics in the second area.

[0050] For example, when the estimation model includes a first estimation model and a second estimation model, the control station generates first estimation data (pre-correction estimation data) using the second estimation model and the second data. The control station generates correction data using the second captured image and the first estimation model. The control station corrects the first estimation data with the correction data to generate estimation data (corrected estimation data).

[0051] For example, the second estimation model is a model for calculating global communication characteristics, and the first estimation model is a model for calculating location-dependent communication characteristics (e.g., shadowing). The control station generates first estimation data indicating global communication characteristics at the shooting location of the second photographed image, for example, using the second estimation model.

[0052] The control station calculates shadowing (shadowing estimation value) at the shooting location of the second captured image using the second captured image and the first estimation model. The control station generates estimation data indicating local communication characteristics at the shooting location by adding the shadowing estimation value to the first estimation data indicating global communication characteristics.

[0053] In this way, the control station calculates estimated data for the second area using an estimation model generated using the first data and the first captured image for the first area, thereby enabling the control station to estimate propagation path conditions (e.g., communication characteristics) of the terminal device and / or base station in the second area with high accuracy.

[0054] <<2. Configuration Example of Communication System>> <2.1. Overall Configuration Example of Communication System> Fig. 3 is a diagram illustrating a configuration example of a wireless communication system according to the first embodiment of the present disclosure. The wireless communication system illustrated in Fig. 3 includes a control station 100, core networks 200A and 200B, and a base station 300A. １ , 300A ２ , 300B １ , 300B ２ and the terminal device 400A １ , 400A ２ , 400B １ , 400B ２ And, it is equipped with.

[0055] The control station 100 connects to a core network 200A in a local network N1_A through the network N1_P. The control station 100 connects to a core network 200B in a local network N1_B through the network N1_P.

[0056] The network N1_P is, for example, a communication network such as a local area network (LAN), a wide area network (WAN), a cellular network, a fixed telephone network, a regional Internet Protocol (IP) network, or the Internet. The network N1_P may include a wired network or a wireless network. The network N1_P may also be a data network connected to a core network. The data network may be a service network of a telecommunications carrier, for example, an IP Multimedia Subsystem (IMS) network. The data network may also be a private network such as an in-house network. Note that, although only one network N1_P is shown in the example of FIG. 3, the number of networks N1_P is not limited to one.

[0057] 3 shows two local networks N1_A and N1_B, the number of local networks is not limited to two. The number of local networks may be one, or three or more.

[0058] In the local network N1_A, the core network 200A includes a base station 300A. １ , 300A ２ The number of base stations 300A connected to the core network 200A is not limited to two. The number of base stations 300A may be one, or three or more.

[0059] Base station 300A １ terminal device 400A １ The base station 300A is connected to the base station 300A by wireless communication. ２ terminal device 400A ２ The number of terminal devices 400A connected to the base station 300A is not limited to one, but may be two or more. １ Terminal device 400A connected to １ and the number of base stations 300A ２ Terminal device 400A connected to ２ The number of may be different from.

[0060] The configuration of the local network N1_B is the same as that of the local network N1_A, and therefore a description thereof will be omitted.

[0061] For example, the control station 100 is an information processing device that controls a dynamic spectrum access (DSA) system. The control station 100 can control radio resources and communication parameters for at least one of the local networks N1_A and N1_B, the core networks 200A and 200B, and the base stations 300A and 300B connected to the DSA. Here, the radio resources refer to resources in at least one of the time, frequency, MIMO layer, and spatial domain used for wireless communication.

[0062] The core networks 200A and 200B do not necessarily have to be installed. In this case, the control station 100 is directly connected to the base stations 300A and 300B.

[0063] The core network 200 may be located in either the control station 100 or the base station 300. The core network 200 may also be located in both the control station 100 and the base station 300 in a distributed manner.

[0064] The local networks N1_A and N1_B are also called private networks, and are networks whose communication coverage (an example of a communication zone) is, for example, within a predetermined area or within a premises. In the local networks N1_A and N1_B, only pre-registered terminal devices 400 can connect to at least one of the base station 300, the control station 100, and the core network 200.

[0065] Furthermore, examples of radio access technologies (RATs) used for wireless communication between the base station 300 and the terminal device 400 include cellular communication systems such as a 4G system, a 5G system, a 6G system, LTE (Long Term Evolution), and NR (New Radio). Furthermore, this radio access technology is not limited to cellular communication systems. For example, examples of this radio access technology include various wireless communication systems such as wireless LAN, Bluetooth (registered trademark), and LPWA (Low Power Wide Area) systems.

[0066] In the example of FIG. 3, the control station 100 is connected to the local networks N1_A and N1_B, but the network to which the control station 100 is connected may be a public network to which subscribers can connect.

[0067] 4 is a diagram illustrating another exemplary configuration of the wireless communication system according to the first embodiment of the present disclosure. As described above, the core network 200 may be omitted or may be located in the control station 100 and / or the base station 300.

[0068] Therefore, in the following, for the sake of simplicity, the wireless communication system is assumed to be a system in which the core network 200 is omitted, as shown in Fig. 4. That is, the wireless communication system of this embodiment is assumed to include a control station 100, a base station 300, and a terminal device 400.

[0069] <2-2. Configuration Example of Base Station> Next, the base station 300 will be described. The base station 300 is a communication device that operates a cell and provides wireless communication services to one or more terminal devices 400 located within the coverage of the cell. The cell is operated according to any wireless communication method, such as LTE or NR. The base station 300 is connected to a core network 200. The core network 200 is connected to a packet data network (not shown) via a gateway device (not shown). Furthermore, the base station 300 operates beams that can be identified by SSB (Synchronization Signal / PBCH Block), and can transmit and receive data to and from one or more terminal devices 400 via one or more beams.

[0070] Note that the base station 300 may be configured as a collection of multiple physical or logical devices. For example, in this embodiment, the base station 300 may be divided into multiple devices, a baseband unit (BBU) and an RU, and interpreted as a collection of these multiple devices. Additionally or alternatively, in this embodiment, the base station 300 may be either or both of a BBU and an RU. The BBU and the RU may be connected via a predetermined interface (e.g., eCPRI). Additionally or alternatively, the RU may be referred to as a remote radio unit (RRU) or a radio DoT (RD). Additionally or alternatively, the RU may correspond to a gNB-DU (gNB-CU) (described later). Additionally or alternatively, the BBU may correspond to a gNB-CU (gNB-CU) (described later). Alternatively, the RU may be connected to a gNB-DU (gNB-DU) (described later). Furthermore, the BBU may correspond to a combination of a gNB-CU and a gNB-DU (gNB-DU) (described later). Additionally or alternatively, the RU may be a device integrally formed with an antenna. The antennas of the base station 300 (e.g., antennas integrally formed with the RU) may employ an Advanced Antenna System and support MIMO (e.g., FD-MIMO) and beamforming. In the Advanced Antenna System, the antennas of the base station 300 (e.g., antennas integrally formed with the RU) may have, for example, 64 transmitting antenna ports and 64 receiving antenna ports.

[0071] Furthermore, multiple base stations 300 may be connected to each other. One or more base stations 300 may be included in a Radio Access Network (RAN). That is, the base station 300 may simply be referred to as a RAN, a RAN node, an Access Network (AN), or an AN node. The RAN in LTE is called an Enhanced Universal Terrestrial RAN (EUTRAN). The RAN in NR is called an NGRAN. The RAN in W-CDMA (UMTS) is called a UTRAN. The base station 300 in LTE is called an Evolved Node B (eNodeB) or eNB. That is, the EUTRAN includes one or more eNodeBs (eNBs). The base station 300 in NR is called a gNodeB or gNB. That is, the NGRAN includes one or more gNBs. Furthermore, the EUTRAN may include a gNB (en-gNB) connected to a core network (EPC) in an LTE communication system (EPS). Similarly, the NGRAN may include an ng-eNB connected to a core network (5GC) in a 5G communication system (5GS). Additionally or alternatively, if the base station 300 is an eNB, gNB, or the like, it may be referred to as a 3GPP (registered trademark) access. Additionally or alternatively, if the base station 300 is a wireless access point (e.g., a Wi-Fi (registered trademark) access point), it may be referred to as a non-3GPP access. Additionally or alternatively, the base station 300 may be an optical extension device called an RRH (Remote Radio Head). Additionally or alternatively, if the base station 300 is a gNB, it may be referred to as a combination of the gNB CU (Central Unit) and gNB DU (Distributed Unit) described above, or as either one of them. The gNB CU hosts multiple upper layers (e.g., RRC, SDAP, PDCP) of the Access Stratum for communication with the UE.On the other hand, the gNB-DU hosts multiple lower layers (e.g., RLC, MAC, PHY) of the Access Stratum. That is, among the messages and information described below, RRC signaling (e.g., various SIBs including MIB and SIB1, RRC Setup message, RRC Reconfiguration message) may be generated by the gNB CU, while DCI and various physical channels (e.g., PDCCH and PBCH) described below may be generated by the gNB-DU. Alternatively, among the RRC signaling, some configuration (setting information), such as IE: cellGroupConfig, may be generated by the gNB-DU, and the remaining configuration may be generated by the gNB-CU. These configurations (setting information) may be transmitted and received via the F1 interface described below. The base station 300 may be configured to be able to communicate with other base stations 300. For example, when multiple base stations 300 are eNBs or a combination of an eNB and an en-gNB, the base stations 300 may be connected to each other via the X2 interface. Additionally or alternatively, when multiple base stations 300 are gNBs or a combination of gn-eNBs and gNBs, the devices may be connected via an Xn interface. Additionally or alternatively, when multiple base stations 300 are a combination of gNB CUs and gNB DUs, the devices may be connected via the above-mentioned F1 interface. Messages and information (RRC signaling or DCI information, physical channel) described below may be communicated between multiple base stations 300 (e.g., via the X2, Xn, or F1 interfaces).

[0072] Furthermore, as described above, the base station 300 may be configured to manage multiple cells. A cell provided by the base station 300 is called a serving cell. The serving cell includes a PCell (Primary Cell) and an SCell (Secondary Cell). When dual connectivity (e.g., EUTRA-EUTRA Dual Connectivity, EUTRA-NR Dual Connectivity (ENDC), EUTRA-NR Dual Connectivity with 5GC, NR-EUTRA Dual Connectivity (NEDC), or NR-NR Dual Connectivity) is provided to a UE (e.g., the terminal device 400), the PCell and zero or one or more SCell(s) provided by the MN (Master Node) are called a Master Cell Group. Furthermore, the serving cell may include a PSCell (Primary Secondary Cell or Primary SCG Cell). That is, when dual connectivity is provided to a UE, the PSCell and zero or one or more SCell(s) provided by the SN (Secondary Node) are called a Secondary Cell Group (SCG). Unless special configuration (e.g., PUCCH on SCell) is performed, the physical uplink control channel (PUCCH) is transmitted on the PCell and PSCell, but not on the SCell. Furthermore, radio link failure is detected on the PCell and PSCell, but not on the SCell (it does not need to be detected). Because the PCell and PSCell thus play special roles within the serving cell(s), they are also called special cells (SpCells). One cell may be associated with one downlink component carrier and one uplink component carrier. Furthermore, the system bandwidth corresponding to one cell may be divided into multiple bandwidth parts.In this case, one or more Bandwidth Parts (BWPs) may be configured in the UE, and one Bandwidth Part may be used by the UE as an Active BWP. Also, radio resources (e.g., frequency band, numerology (subcarrier spacing), slot format (Slot configuration)) that the terminal device 400 can use may differ for each cell, each component carrier, or each BWP.

[0073] 5 is a block diagram showing a configuration example of a base station 300 according to the first embodiment of the present disclosure. The base station 300 is a wireless communication device that wirelessly communicates with a terminal device 400. The base station 300 is a type of communication device. The base station 300 is also a type of information processing device.

[0074] The base station 300 shown in Figure 5 includes a communication unit 310, a storage unit 320, a network communication unit 330, and a control unit 340. Note that the configuration shown in Figure 5 is a functional configuration, and the hardware configuration may be different. Furthermore, the functions of the base station 300 may be distributed and implemented in multiple physically separated configurations. For example, as described above, the functions of the base station 300 may be distributed to the CU and DU, or to the CU, DU, and RU.

[0075] The communication unit 310 is a signal processing unit for wireless communication with other wireless communication devices (e.g., terminal device 400 and other base stations 300). The communication unit 310 operates under the control of the control unit 340. When the other wireless communication device is a terminal device 400, the communication unit 310 may be a wireless transceiver compatible with one or more wireless access methods. For example, the communication unit 310 supports both NR and LTE. The communication unit 310 may also support W-CDMA and cdma2000 in addition to NR and LTE. The communication unit 310 may also support communication using NOMA. When the other wireless communication device is another base station 300, the communication unit 310 may be an X2 interface, an Xn interface, or an F1 interface.

[0076] The communication unit 310 includes a reception processing unit 311, a transmission processing unit 312, and an antenna 313. The communication unit 310 may include a plurality of reception processing units 311, a plurality of transmission processing units 312, and a plurality of antennas 313. Note that when the communication unit 310 supports a plurality of radio access methods, each unit of the communication unit 310 may be configured separately for each radio access method. For example, the reception processing unit 311 and the transmission processing unit 312 may be configured separately for LTE and NR.

[0077] The reception processing unit 311 processes uplink signals received via the antenna 313. The reception processing unit 311 operates as a receiver that receives received signals. The reception processing unit 311 includes a radio reception unit 311a, a demultiplexing unit 311b, a demodulation unit 311c, and a decoding unit 311d.

[0078] The radio receiving unit 311a performs down-conversion, removal of unnecessary frequency components, control of amplification level, orthogonal demodulation, conversion to a digital signal, removal of guard intervals (cyclic prefixes), extraction of frequency domain signals by fast Fourier transform, etc. on the uplink signals. The demultiplexing unit 311b separates uplink channels such as a PUSCH (Physical Uplink Shared Channel) and a PUCCH (Physical Uplink Control Channel) and an uplink reference signal from the signals output from the radio receiving unit 311a.

[0079] The demodulator 311c demodulates the received signal using a modulation method such as binary phase shift keying (BPSK) or quadrature phase shift keying (QPSK) for the modulation symbols of the uplink channel. The modulation method used by the demodulator 311c may be 16QAM (quadrature amplitude modulation), 64QAM, or 256QAM. In this case, the signal points on the constellation do not necessarily need to be equidistant. The constellation may be a non-uniform constellation (NUC).

[0080] The decoder 311d performs a decoding process on the coded bits of the demodulated uplink channel. The decoded uplink data and uplink control information are output to the controller 340.

[0081] The transmission processing unit 312 performs transmission processing of the downlink control information and downlink data. In this manner, the transmission processing unit 312 is an acquisition unit that acquires, for example, bit sequences of the downlink control information, downlink data, etc. from the control unit 340. The transmission processing unit 312 includes an encoding unit 312a, a modulation unit 312b, a multiplexing unit 312c, and a radio transmission unit 312d.

[0082] The encoder 312a encodes the downlink control information and downlink data input from the controller 340 using a coding method such as block coding, convolutional coding, or turbo coding. Note that the encoder 312a may also encode using a polar code or a low density parity check code (LDPC code).

[0083] The modulation unit 312b modulates the coded bits output from the coding unit 312a using a predetermined modulation method such as BPSK, QPSK, 16QAM, 64QAM, or 256QAM. In this case, the signal points on the constellation do not necessarily have to be equidistant. The constellation may be a non-uniform constellation.

[0084] The multiplexing unit 312c multiplexes the modulation symbols of each channel and the downlink reference signal and allocates the multiplexed symbols to predetermined resource elements. The radio transmitting unit 312d performs various signal processing on the signal from the multiplexing unit 312c. For example, the radio transmitting unit 312d performs processing such as conversion from the time domain to the frequency domain using a fast Fourier transform, addition of a guard interval (cyclic prefix), generation of a baseband digital signal, conversion to an analog signal, quadrature modulation, up-conversion, removal of unnecessary frequency components, and power amplification. The signal generated by the transmission processing unit 312 is transmitted from the antenna 313.

[0085] The storage unit 320 is a data readable / writable storage device such as a dynamic random access memory (DRAM), a static random access memory (SRAM), a flash memory, a hard disk, etc. The storage unit 320 functions as a storage means of the base station 300.

[0086] The network communication unit 330 is a communication interface for communicating with a node located higher on the network (e.g., the core network 200). For example, the network communication unit 330 may be a LAN (Local Area Network) interface such as a NIC (Network Interface Card). Additionally or alternatively, the network communication unit 330 may be an S1 interface or an NG interface for connecting to a core network node. The network communication unit 330 may be a wired interface or a wireless interface. The network communication unit 330 functions as a network communication means of the base station 300.

[0087] The control unit 340 is a controller that controls each unit of the base station 300. The control unit 340 is realized by a processor (hardware processor) such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). For example, the control unit 340 is realized by a processor executing various programs stored in a storage device inside the base station 300 using a RAM (Random Access Memory) or the like as a working area. The control unit 340 may also be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The CPU, MPU, ASIC, and FPGA can all be considered as controllers.

[0088] <2-3. Configuration Example of Terminal Device> Next, a configuration example of the terminal device 400 according to the first embodiment of the present disclosure will be described with reference to Fig. 6. Fig. 6 is a block diagram showing a configuration example of the terminal device 400 according to the first embodiment of the present disclosure.

[0089] The terminal device 400 is a wireless communication device that wirelessly communicates with the base station 300. The terminal device 400 is, for example, a mobile phone, a smart device (smartphone or tablet), a PDA (Personal Digital Assistant), or a personal computer. The terminal device 400 may also be a device such as a commercial camera equipped with a communication function, an M2M (Machine to Machine) device, or an IoT (Internet of Things) device.

[0090] The terminal device 400 may also be capable of sidelink communication with other terminal devices 400. The terminal device 400 may be able to use an automatic retransmission technique such as hybrid automatic repeat reQuest (HARQ) when performing sidelink communication. The terminal device 400 may be capable of non-orthogonal multiple access (NOMA) communication with the base station 300. The terminal device 400 may also be capable of NOMA communication in communication (sidelink) with other terminal devices 400. The terminal device 400 may also be capable of low-power wide area (LPWA) communication with other communication devices (e.g., base station 300 and other terminal devices 400). Alternatively, the wireless communication used by the terminal device 400 may be wireless communication using millimeter waves. The wireless communication (including sidelink communication) used by the terminal device 400 may be wireless communication using radio waves or wireless communication using infrared or visible light (optical wireless).

[0091] The terminal device 400 may simultaneously connect to multiple base stations 300 or multiple cells to perform communication. For example, if one base station 300 can provide multiple cells, the terminal device 400 can perform carrier aggregation by using one cell as a pCell and another cell as an sCell. Furthermore, if multiple base stations 300 can each provide one or multiple cells, the terminal device 400 can use one or multiple cells managed by one base station 300 (MN (e.g., MeNB or MgNB)) as a pCell, or a pCell and sCell(s), and use one or multiple cells managed by the other base station 300 (SN (e.g., SeNB or SgNB)) as a pCell (PSCell), or a pCell (PSCell) and sCell(s), thereby realizing dual connectivity (DC). DC may also be referred to as multi-connectivity (MC).

[0092] When a communication area is supported via cells of different base stations 300 (multiple cells having different cell identifiers or the same cell identifier), the multiple cells can be bundled together using carrier aggregation (CA), dual connectivity (DC), or multi-connectivity (MC) technology to enable communication between the base station 300 and the terminal device 400. Alternatively, the terminal device 400 can communicate with the multiple base stations 300 via the cells of the different base stations 300 using coordinated multi-point transmission and reception (CoMP) technology.

[0093] The terminal device 400 includes a communication unit 410, a storage unit 420, a network communication unit 430, an input / output unit 440, and a control unit 450. Note that the configuration shown in Fig. 6 is a functional configuration, and the hardware configuration may be different from this. Furthermore, the functions of the terminal device 400 may be distributed and implemented in multiple physically separated components.

[0094] The communication unit 410 is a signal processing unit for wireless communication with other wireless communication devices (e.g., the base station 300 and other terminal devices 400). The communication unit 410 operates under the control of the control unit 450. The communication unit 410 may be a wireless transceiver compatible with one or more wireless access methods. For example, the communication unit 410 is compatible with both NR and LTE. The communication unit 410 may be compatible with W-CDMA and cdma2000 in addition to NR and LTE. The communication unit 410 may also be compatible with communication using NOMA.

[0095] The communication unit 410 includes a reception processing unit 411, a transmission processing unit 412, and an antenna 413. The communication unit 410 may include a plurality of reception processing units 411, a plurality of transmission processing units 412, and a plurality of antennas 413.

[0096] The reception processing unit 411 includes, for example, a radio reception unit 411a, a demultiplexing unit 411b, a demodulation unit 411c, and a decoding unit 411d. The transmission processing unit 412 includes an encoding unit 412a, a modulation unit 412b, a multiplexing unit 412c, and a radio transmission unit 412d.

[0097] The configurations of the communication unit 410 , the reception processing unit 411 , the transmission processing unit 412 , and the antenna 413 are similar to those of the communication unit 310 , the reception processing unit 311 , the transmission processing unit 312 , and the antenna 313 of the base station 300 .

[0098] The storage unit 420 is a data readable / writable storage device such as a DRAM, an SRAM, a flash memory, a hard disk, etc. The storage unit 420 functions as a storage means of the terminal device 400.

[0099] The network communication unit 430 is a communication interface for communicating with other devices connected via a network. For example, the network communication unit 430 is a LAN interface such as a NIC. The network communication unit 430 may be a wired interface or a wireless interface. The network communication unit 430 functions as a network communication means of the terminal device 400. The network communication unit 430 communicates with other devices under the control of the control unit 450.

[0100] The input / output unit 440 is a user interface for exchanging information with the user. For example, the input / output unit 440 is an operation device such as a keyboard, a mouse, operation keys, or a touch panel that allows the user to perform various operations. Alternatively, the input / output unit 440 is a display device such as a liquid crystal display (LCD) or an organic electroluminescence display (OLED). The input / output unit 440 may be an audio device such as a speaker or a buzzer. The input / output unit 440 may also be a lighting device such as an LED (Light Emitting Diode) lamp. The input / output unit 440 functions as input / output means (input means, output means, operation means, or notification means) of the terminal device 400.

[0101] The control unit 450 is a controller that controls each unit of the terminal device 400. The control unit 450 is realized by a processor such as a CPU, an MPU, or a GPU. For example, the control unit 450 is realized by the processor executing various programs stored in a storage device inside the terminal device 400 using RAM or the like as a work area. The control unit 450 may also be realized by an integrated circuit such as an ASIC or an FPGA. The CPU, MPU, GPU, ASIC, and FPGA can all be considered as controllers.

[0102] 7 is a diagram illustrating a configuration example of the control station 100 according to the first embodiment of the present disclosure. As described above, the control station 100 is an information processing device that controls, for example, a dynamic spectrum access (DSA) system. As shown in FIG. 7, the control station 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

[0103] (Communication Unit 110) The communication unit 110 is a communication interface for communicating with other devices (e.g., the base station 300). The communication unit 110 may be a network interface or a device connection interface. For example, the communication unit 110 may be a LAN interface such as a NIC, or a Universal Serial Bus (USB) interface configured by a USB host controller, a USB port, etc. The communication unit 110 may be a wired interface or a wireless interface. The communication unit 110 functions as communication means of the control station 100. The communication unit 110 communicates with the base station 300 under the control of the control unit 130.

[0104] (Storage Unit 120) The storage unit 120 is a data readable / writable storage device such as a DRAM, an SRAM, a flash memory, a hard disk, etc. The storage unit 120 functions as a storage unit of the control station 100.

[0105] The storage unit 120 stores information (data) used by the generation unit 132 and the determination unit 133, which will be described later.

[0106] (Control Unit 130) The control unit 130 is a controller that controls each unit of the control station 100. The control unit 130 is realized by a processor such as a CPU, an MPU, or a GPU.

[0107] For example, the control unit 130 is realized by a processor executing various programs stored in a storage device inside the control station 100 using RAM or the like as a work area. The control unit 130 may also be realized by an integrated circuit such as an ASIC or FPGA. A CPU, MPU, GPU, ASIC, and FPGA can all be considered as controllers.

[0108] The control unit 130 includes an acquisition unit 131, a generation unit 132, a determination unit 133, and a notification unit 134. Each block (acquisition unit 131 to notification unit 134) constituting the control unit 130 is a functional block indicating a function of the control unit 130.

[0109] These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be a software module implemented by software (including a microprogram), or may be a circuit block on a semiconductor chip (die). Of course, each functional block may be a processor or an integrated circuit. The functional blocks may be configured in any manner.

[0110] The control unit 130 may be configured with functional units different from the above-described functional blocks.

[0111] (Acquisition unit 131) The acquisition unit 131 acquires information used by the generation unit 132 via the communication unit 110. For example, the acquisition unit 131 acquires actual measurement data of the above-described first area from the base station 300 and / or the terminal device 400 via the communication unit 110. The acquisition unit 131 acquires captured images of the above-described first area from the base station 300 and / or the terminal device 400 via the communication unit 110.

[0112] The acquisition unit 131 receives, via the communication unit 110, information that may be transmitted from at least one of the local network, the core network 200, the base station 300, the terminal device 400, and other communication nodes.

[0113] The acquisition unit 131 outputs the acquired information to the generation unit 132 .

[0114] (Generation unit 132) Fig. 8 is a diagram illustrating an example of a generation process and an execution process according to an embodiment of the present disclosure. As shown in Fig. 8, the generation unit 132 generates a communication characteristics model (estimation model) using first data and first captured images at each location A1, A2, A3, ... in the first area. The first area (estimation area) is location A1 (e.g., around Osaki Station), location A2 (e.g., around Shinagawa Station), and location A3 (e.g., around Shinjuku Station). Note that the number of locations A included in the first area may be one or more.

[0115] Here, the first area is a model generation area (learning area) for generating an estimation model. The first area is different from the second area in which the determination unit 133 estimates communication characteristics. The first area may be replaced with location A. That is, as a generation process, the generation unit 132 generates an estimation model using first data and first captured images in one or more first areas (location A).

[0116] 8 , the estimation model generated by the generation process is used to generate estimated data related to communication characteristics in the second area. The determination unit 133, which will be described later, generates the estimated data related to communication characteristics in the second area using the second data related to communication characteristics in the second area, the second captured image, and the estimation model. The determination unit 133 uses the generated estimated data to determine, for example, communication parameters (control information) between the terminal device 400 and the base station 300.

[0117] Here, the second area is an area (estimated area) for generating estimated data, and is different from the first area. The second area includes, for example, a location X1 (e.g., around Tokyo Station). Note that the second area may be replaced with a location X. Also, although the second area includes one location X1 here, the second area may include multiple locations (e.g., locations X1, X2, ...).

[0118] 7, the generation unit 132 generates an estimation model used by the determination unit 133. The generation unit 132 will be described in detail below with reference to FIG.

[0119] Fig. 9 is a block diagram showing an example configuration of the generation unit 132 according to an embodiment of the present disclosure. The generation unit 132 shown in Fig. 9 includes a first generation unit 1321 and a second generation unit 1322. The generation unit 132 generates an estimation model using the first data and the first captured image. The estimation models include a first estimation model and a second estimation model.

[0120] (First Generator 1321) The first generator 1321 generates a first estimation model using a first captured image.

[0121] The first generation unit 1321 acquires a first captured image via the acquisition unit 131. The first captured image is, for example, an image of a landscape captured at an arbitrary point (capture point) in the first area. The first captured image includes, for example, an image that satisfies predetermined conditions (hereinafter also referred to as capture conditions). Details of the capture conditions will be described later.

[0122] 10 is a diagram illustrating an example of a first captured image according to an embodiment of the present disclosure. In the example of Fig. 10, the first captured image includes high-rise buildings, a passageway, trees, and the like as objects.

[0123] For example, the first captured image is a transmission / reception propagation path image. In other words, the first captured image is an image of a scene on a propagation path connecting a transmission point and a reception point. One of the transmission point and the reception point is the base station 300, and the other is the capturing location.

[0124] 10, for example, it is assumed that the base station 300 is located in the center of the first photographed image, but is hidden by a high-rise building, and therefore the base station 300 is not visible in the first photographed image. In other words, in the first photographed image in FIG. 10, the transmission and reception propagation paths are blocked by the high-rise building.

[0125] The first generation unit 1321 first analyzes the first captured image and estimates the shielding ratio of the transmission and reception propagation paths. The first generation unit 1321 analyzes the first captured image using a technique called segmentation, for example.

[0126] Segmentation is a technique that has been actively researched in the field of computer vision in AI (artificial intelligence) in recent years. Segmentation is a technique for dividing an image into multiple objects (regions). There are three segmentation methods:

[0127] - Semantic Segmentation - Instance Segmentation - Panoptic Segmentation

[0128] (Semantic Segmentation) Semantic segmentation is a method for classifying objects by labeling each pixel in an image. Objects of the same type are assigned the same label. Therefore, objects of the same type are classified as the same class.

[0129] (Instance Segmentation) Instance segmentation is a method for classifying objects after identifying object regions in an image. Instance segmentation differs from semantic segmentation in that each object of the same type is assigned a different label, and objects that do not have a fixed shape, such as the sky or roads, are not classified.

[0130] (Panoptic Segmentation) Panoptic segmentation is a technique that combines semantic segmentation and instance segmentation.

[0131] In this embodiment, since the shielding ratio of the transmission and reception propagation paths is estimated, it is desirable to use a method of classifying the sky as an object.

[0132] The first generation unit 1321 performs segmentation on the first captured image to classify it into one or more objects.

[0133] Fig. 11 is a diagram illustrating an example of a segmentation result according to an embodiment of the present disclosure. Fig. 11 illustrates a result of performing segmentation on the first captured image shown in Fig. 10. In Fig. 11, identical objects are hatched identically.

[0134] 11, the same label is assigned to the sky area (hereinafter simply referred to as "sky") on both sides of the skyscraper. The first generation unit 1321 has successfully segmented the sky in the first captured image. The first generation unit 1321 has also successfully segmented the skyscraper, its pillars, and the passageway connecting to the left side of the skyscraper.

[0135] The first generation unit 1321 calculates the shading rate of the transmission and reception propagation paths in the first captured image (in other words, the capturing location) according to the segmentation result. The first generation unit 1321 performs segmentation and assigns labels to objects, thereby dividing the first captured image into one or more regions according to one or more objects included in the first captured image. The first generation unit 1321 calculates the shading rate according to the proportion of the object that is covered by the first captured image.

[0136] For example, the first generating unit 1321 calculates the occlusion rate according to at least one of the following: - the proportion of sky in the first captured image - the proportion of obstacles in the first captured image - the proportion of sky and obstacles

[0137] As the shielding ratio of the transmission and reception propagation paths increases, the line of sight of the transmission and reception propagation paths narrows. This is thought to result in a decrease in the proportion of sky in the first captured image. The first generator 1321 indirectly estimates the shielding ratio R of the transmission and reception propagation paths, for example, by calculating the proportion of sky in the first captured image.

[0138] For example, the first generation unit 1321 calculates the shading ratio according to the proportion of sky in the first captured image. The first generation unit 1321 calculates the shading ratio R (R=1-P1 / P0) according to the proportion of the size of the object labeled as sky (for example, the number of pixels P1) to the size of the first captured image (for example, the number of pixels P0).

[0139] Specifically, suppose that the number of pixels assigned the sky label in the first captured image shown in Fig. 11 is 400 (P1 = 400). Also, suppose that the number of pixels assigned the label in the first captured image, i.e., the total number of pixels in the first captured image, is 1000 (P0 = 1000).

[0140] In this case, the proportion of sky in the entire first captured image is 0.4. The first generating unit 1321 sets 1-0.4=0.6 as the shielding rate R of the transmission and reception transmission paths at the capturing point.

[0141] The first generating unit 1321 may also directly calculate the shielding ratio of the transmission and reception propagation paths by calculating the ratio of the labels assigned to the obstacles.

[0142] For example, the first generation unit 1321 calculates the occlusion ratio R (R=P2 / P0) according to the ratio of the size of the object labeled as the obstacle (e.g., the number of pixels P2) to the size of the first captured image (e.g., the number of pixels P0).

[0143] For example, obstacles may include structures and natural objects. Structures may include man-made objects such as buildings, elevated walkways, and pillars. Natural objects may include non-man-made objects such as trees and cliffs. In the captured image of FIG. 11 , objects labeled as skyscrapers, walkways, pillars, trees, etc. may correspond to objects labeled as obstacles.

[0144] Alternatively, for example, the first generation unit 1321 may calculate the occlusion rate according to the ratio of the sky to the obstacles. The first generation unit 1321 calculates the occlusion rate R (R=P2 / P1+P2) according to the ratio between the size of the object labeled as the sky (e.g., the number of pixels P1) and the size of the object labeled as the obstacle (e.g., the number of pixels P2).

[0145] Although the first generating unit 1321 calculates the blocking ratio for the entire first captured image in this embodiment, the first generating unit 1321 may calculate the blocking ratio for a part of the first captured image. For example, the first generating unit 1321 may calculate the blocking ratio for a region in the first captured image according to the Fresnel zone.

[0146] Here, the Fresnel zone refers to a space that indicates "line of sight" in wireless communication. When this Fresnel zone is secured, the wireless communication environment between the base station 300 and the terminal device 400 is considered to be a line-of-sight environment.

[0147] Specifically, for example, if X (%) (e.g., 60%) of the Fresnel zone radius (Fresnel radius) is secured, the wireless communication environment between the base station 300 and the terminal device 400 is considered to be a line-of-sight environment.

[0148] This Fresnel zone is determined by the distance between the base station 300 and the terminal device 400 and the frequency used for communication. For example, depending on the shooting direction of the first photographed image and the direction (position) of the base station 300 from the shooting point as the starting point, the Fresnel zone may include the entire space captured in the first photographed image, or only a part of the space captured in the first photographed image may be included in the Fresnel zone.

[0149] In other words, the entire angle of view of the first captured image may be included in the Fresnel zone, or only a part of the angle of view of the first captured image may be included in the Fresnel zone.

[0150] Therefore, the first generation unit 1321 identifies an area (hereinafter also referred to as a Fresnel area) of the Fresnel zone (more specifically, the Fresnel zone within X (%) of the Fresnel radius) in the first captured image according to the position of the base station 300, the position of the capturing point, the frequency used for communication, etc.

[0151] The first generator 1321 calculates the shading ratio in the Fresnel region using at least one of the proportion of sky and the proportion of obstacles included in the identified Fresnel region. The specific calculation method is the same as the method for calculating the shading ratio in the first captured image described above (the same as when the first captured image is replaced with a Fresnel region), so a detailed description will be omitted.

[0152] In this way, the first generation unit 1321 can calculate the shading rate according to the shooting conditions of the first captured image (e.g., the relationship between the shooting direction and the direction of the base station 300, the proportion of the Fresnel region included in the first captured image, etc.).

[0153] The first generation unit 1321 also calculates data related to shadowing at the imaging point of the first area (for example, a shadowing value). The shadowing value is calculated based on formula (2) in the reference document (K. Katagiri, K. Sato, K. Inage, and T. Fujii, "Experimental Verification of Shadowing Classification for Radio Map," 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), Victoria, BC, Canada, 2020, pp. 1-7).

[0154] The first generating unit 1321, for example, associates the shadowing value with the coverage rate R at the shooting point and stores the associated shadowing value in the storage unit 12.

[0155] The first generating unit 1321 calculates the shadowing value and the blocking ratio R at the shooting point of the first photographed image based on the first photographed images.

[0156] 12 is a scatter plot showing the relationship between the shielding ratio R and the shadowing value according to an embodiment of the present disclosure, where the horizontal axis represents the shielding ratio R and the vertical axis represents the shadowing value S (dB).

[0157] The first generating unit 1321 calculates the blocking ratio R and the shadowing value at the shooting point of the first photographed image based on the plurality of first photographed images, thereby obtaining a scatter diagram as shown in FIG. 12 .

[0158] The first generation unit 1321 performs linear regression analysis on the shading ratio R and the shadowing value at multiple shooting points, and estimates the relationship between the shadowing value and the shading ratio (first estimation model) using, for example, a linear function expressed by the following equation (1).

[0159]

[0160] For example, the first generating unit 1321 estimates the relationship between the shadowing value and the shielding rate using a linear function indicated by a straight line in Fig. 12. This estimated linear function corresponds to the above-mentioned first estimation model.

[0161] Here, S is the shadowing value (estimated shadowing value), and R is the shadowing ratio at an arbitrary point. a is the slope of the regression line, which represents the degree of shadowing attenuation with respect to changes in the shadowing ratio R. The greater this slope a, the greater the increase in shadowing loss due to an increase in the shadowing ratio R. Furthermore, b (dB) is the intercept of the regression line.

[0162] Here, the first generation unit 1321 is assumed to perform linear regression (simple linear regression) analysis, but the first generation unit 1321 may also use statistical analysis to generate the first estimation model, and the statistical analysis is not limited to linear regression analysis.

[0163] For example, the first generator 1321 may generate the first estimation model using at least one of the following statistical analyses: In this case, the first generator 1321 may perform the statistical analysis using information other than the actual measurement data (e.g., simulation data, data related to the base station 300 and / or the terminal device 400, etc.).

[0164] - Multiple regression analysis - Multi-slope - AI / ML (Machine Learning) method

[0165] In the multiple regression analysis, for example, explanatory variables other than the shielding rate R are utilized. In the multi-slope analysis, the slope of the regression line is calculated for each interval of the shielding rate R. In the AI / ML (Machine Learning) method, for example, a neural network or the like is utilized.

[0166] The first generation unit 1321 estimates a relational expression (first estimation model) between the shadowing value and the shielding rate using a first captured image of a first area. The first generation unit 1321 may use first data to estimate the first estimation model.

[0167] Note that if the antenna of the base station 300 is installed on the roof of a structure, the structure is likely to appear in the first photographed image at a receiving point near the base station 300. In this way, the first generating unit 1321 may segment the first photographed image that includes the antenna of the base station 300 (or the structure on which the antenna is installed).

[0168] In this case, the first generating unit 1321 may overestimate the shielding ratio R even though the transmission and reception propagation paths are not actually shielded. That is, even though the environment is actually a line-of-sight environment, the first generating unit 1321 may estimate that the environment is a non-line-of-sight environment.

[0169] Therefore, the first generating unit 1321 may perform pre-processing for segmentation. For example, the first generating unit 1321 performs processing according to map information including the shooting location as the pre-processing.

[0170] For example, as preprocessing, the first generation unit 1321 determines whether each shooting location is in a line-of-sight (LOS) environment or a non-line-of-sight (NLOS) environment by utilizing map information, etc. Here, the map information includes information such as map data, topographical data, and structure data.

[0171] The first generation unit 1321 calculates the obscuration rate R at the shooting point from the first captured image at the shooting point determined to be a non-line-of-sight environment as a result of preprocessing. In other words, the first generation unit 1321 uses the first captured image captured in a non-line-of-sight environment to generate the first estimation model.

[0172] Alternatively, as preprocessing, the first generation unit 1321 may exclude first captured images captured within a predetermined range including the base station 300 from the calculation target of the coverage ratio R. The first generation unit 1321 selects first captured images to be excluded from the calculation target of the coverage ratio R, in other words, captured within the predetermined range, according to the map information. That is, the first generation unit 1321 selects first captured images to be used in the calculation of the coverage ratio R, in other words, captured outside the predetermined range.

[0173] As described above, the first generation unit 1321 calculates at least one of the shadowing value S and the shielding ratio R. The first generation unit 1321 generates a first estimation model based on at least one of the estimated shadowing value S and the shielding ratio R.

[0174] The first generation unit 1321 outputs the generated first estimation model to the determination unit 133 .

[0175] (Photographing Conditions) Here, the photographing conditions for the first photographed image will be described. The control station 100 acquires the first photographed image that satisfies at least one of the following conditions. For example, when the terminal device 400 photographs the first photographed image, the control station 100 may request that at least one of the following conditions be satisfied:

[0176] - Angle of view and size of the first captured image - Shooting point (shooting position) - Shooting direction (azimuth angle, elevation angle) of the first captured image - Zoom amount

[0177] For example, the photographing condition may be the angle of view or size of the first photographed image. For example, the control station 100 acquires the first photographed image photographed at a predetermined angle of view or within a predetermined range. Alternatively, the control station 100 acquires the first photographed image at a predetermined size or within a predetermined range. In other words, the photographing condition in this case is that "the angle of view and / or the size is predetermined or within a predetermined range."

[0178] For example, the photographing condition may be a photographing location. For example, the control station 100 acquires a first photographed image photographed within a first area. Alternatively, the control station 100 may acquire the first photographed image by specifying a photographing location. The photographing location may be specified by, for example, latitude and longitude. In this case, the photographing condition is that the image is "photographed in a specified area or a specified photographing location."

[0179] For example, the photographing conditions include the photographing direction (azimuth angle (heading) and elevation angle (pitch)). For example, the control station 100 acquires a first photographed image photographed at a predetermined azimuth angle and / or elevation angle within a predetermined range.

[0180] It is desirable that the control station 100 acquires a first captured image taken while facing the base station 300. Therefore, the predetermined azimuth angle and / or elevation angle within a predetermined range are determined according to the position of the base station 300 and the position of the image capturing point. Here, the position of the base station 300 and the position of the image capturing point are two-dimensional position information such as latitude and longitude, or three-dimensional position information including latitude, longitude, altitude, etc.

[0181] For example, the condition for the azimuth angle is that "the angle (azimuth) in the horizontal plane of the line connecting the base station 300 and the imaging point is predetermined or within a predetermined range." Also, the condition for the elevation angle is that "the angle that the line connecting the base station 300 and the imaging point makes with respect to the horizontal plane is predetermined or within a predetermined range." For example, if the altitude of the imaging point is higher than the altitude of the base station 300, the control station 100 acquires an image captured looking down toward the base station 300 as the first captured image that satisfies the imaging condition.

[0182] Another example of the shooting condition is the zoom amount (fov). For example, if the angle of view or size of the first captured image does not satisfy the above-mentioned shooting condition, the control station 100 acquires a first captured image captured with a predetermined zoom amount or a predetermined range of zoom amounts. The predetermined zoom amount or a predetermined range of zoom amounts may be determined according to the angle of view or size of the first captured image. In this case, the shooting condition is "captured with a predetermined zoom amount or a predetermined range of zoom amounts."

[0183] The above-described photographing conditions are merely examples. The photographing conditions are not limited to the above-described examples, and may be any conditions under which the control station 100 generates the first estimation model, in other words, calculates the shading ratio R, for a plurality of first photographed images. For example, if the photographing conditions are the same, the shading ratio R calculated from the first photographed images photographed at the same photographing point will be the same or fall within a certain range.

[0184] The first captured image may be an image captured by the terminal device 400 or may be an image captured by another device.

[0185] For example, the control station 100 may acquire a street view (street image) provided by a map application or the like as the first captured image.

[0186] In this case, the control station 100, for example, specifies the shooting conditions and acquires the first captured image from a map application. Alternatively, the control station 100 may acquire the first captured image that satisfies the shooting conditions by performing image processing such as enlarging, reducing, or cropping the image acquired from the map application. In this way, the control station 100 generates the first estimation model using the first captured image according to the shooting conditions.

[0187] The control station 100 acquires the first captured image, for example, by using an API (Application Programming Interface) provided by a map application or by capturing a screen.

[0188] 8 , the second generator 1322 generates a second estimation model using the first data. The second estimation model (e.g., data estimated by the second estimation model) is corrected using the first estimation model.

[0189] The first estimation model is used to estimate location-dependent communication characteristics, and the second estimation model is used to estimate global (less location-dependent) communication characteristics, which are estimated using, for example, first data in a first area.

[0190] Here, a case where the first data is actual measurement data will be described as an example, but the first data may be actual measurement data or simulation data, or may include both actual measurement data and simulation data.

[0191] Global communication characteristics include path loss, etc. Global communication characteristics are basically factors that do not involve random fluctuations.

[0192] The second generator 1322 estimates the path loss using, for example, actual measurement data (first data) as the second estimation model. The path loss can be estimated using various methods, but when actual measurement data is used, it is conventionally estimated using linear regression.

[0193] The second generation unit 1322 estimates the path loss and generates a second estimation model by executing the following steps.

[0194] (Step 1) The second generating unit 1322 acquires actual measurement data (here, RSRP (Reference Signals Received Power)) at each location A1, A2, A3, . . . in the first area.

[0195] (Step 2) The second generation unit 1322 divides each location A1, A2, A3, ... in the first area into, for example, rectangular grids and averages the acquired measured data for each grid. In this way, the second generation unit 1322 calculates an average RSRP from the acquired measured data.

[0196] Here, the length of one side of the grid (grid size) is usually determined within the range of 1 to 10 (m). Note that this range is just an example, and the grid size may be outside this range.

[0197] (Step 3) The second generating unit 1322 performs linear regression analysis on the calculated average RSRP and the transmission-reception distance d (m) to generate a second estimation model.

[0198] 13 is a scatter plot showing the relationship between the average RSRP and the distance d (m) according to an embodiment of the present disclosure, where the horizontal axis represents the logarithm of the distance d (m) and the vertical axis represents the average RSRP calculated in step 2.

[0199] The second generation unit 1322 performs linear regression analysis on the average RSRP represented by the scatter diagram shown in FIG. 13 and the distance between the transmitter and receiver d (m), for example, to generate a received power prediction model P Ｌ (dBm). This reception power prediction model P Ｌ corresponds to the second estimation model. In the following, the received power prediction model PＬ The received power estimated using Ｌ Also written as:

[0200] Received power prediction model P Ｌ (dBm) is expressed by the following equation (2). In equation (2), α represents the path loss coefficient. The larger the value of α, the larger the path loss. It is known that the path loss coefficient is 3 to 5 in urban environments. Also, β (dBm) is a parameter that depends on the transmission power and antenna characteristics at the transmission point.

[0201]

[0202] Here, the second generation unit 1322 is assumed to perform linear regression (simple linear regression) analysis, but the second generation unit 1322 may generate the second estimation model using statistical analysis, and the statistical analysis is not limited to linear regression analysis.

[0203] For example, the second generator 1322 may generate the second estimation model using at least one of the following statistical analyses: In this case, the second generator 1322 may perform the statistical analysis using information other than the actual measurement data (e.g., simulation data, data related to the base station 300 and / or the terminal device 400, etc.).

[0204] - Multiple regression analysis - Multi-slope - AI / ML (Machine Learning) method

[0205] The second generation unit 1322 outputs the generated second estimation model to the determination unit 133 .

[0206] 7 , the determination unit 133 generates estimated data regarding communication characteristics in the second area using the second data, the second captured image, the first estimation model, and the second estimation model. The determination unit 133 determines communication parameters between the base station 300 and the terminal device 400 in the second area using the estimated data, for example.

[0207] Here, the second data includes, for example, information on the location of the terminal device 400 and / or the location of the base station 300 for which communication characteristics are to be estimated. The determination unit 133 calculates the distance (transmission and reception distance) between the terminal device 400 and the base station 300 from the location of the terminal device 400 and / or the location of the base station 300. Alternatively, the second data may include, for example, the distance (transmission and reception distance) between the terminal device 400 and the base station 300.

[0208] The determination unit 133 determines the received power P Ｌ (corresponding to the estimated data before correction) is estimated. Ｌ is a path loss-based global communication characteristic.

[0209] The determination unit 133 determines the received power P Ｌ The correction data used for correcting the above is calculated.

[0210] For example, the determination unit 133 calculates the shielding ratio R of the transmission and reception propagation paths from the second captured image. The method of calculating the shielding ratio R is the same as that for the first captured image, and therefore the explanation will be omitted. Note that it is desirable that the second captured image be captured under the same capturing conditions as those for the first captured image.

[0211] The determination unit 133 calculates correction data (here, the shadowing estimated value S) at the shooting location of the second captured image, in other words, at the position of the terminal device 400, based on the calculated shading rate R in the second captured image and the first estimation model.

[0212] The determination unit 133 determines the received power P Ｌ By adding the correction data to ｆｉｎａｌ For example, the determination unit 133 calculates the final received power P ｆｉｎａｌ is calculated based on the following formula (3).

[0213]

[0214] Here, P ＬAs described above, σ is the global communication characteristic (received power) at the terminal device 400. S is the shadowing estimate at the position of the terminal device 400.

[0215] As a result, the determination unit 133 determines estimated data (final received power P ｆｉｎａｌ ) is calculated.

[0216] The determination unit 133 determines, for example, based on the estimated data, communication parameters between the base station 300 and the terminal device 400. The determination unit 133 notifies the notification unit 134 of the determined communication parameters.

[0217] The determination unit 133 may acquire the second captured image from the terminal device 400 or from a device other than the terminal device 400. For example, the determination unit 133 may acquire the second captured image from a street view provided by a map app or the like.

[0218] In this case, the determination unit 133 acquires, for example, a street image captured from the position of the terminal device 400 as the second captured image based on the position information of the terminal device 400 included in the second data. The determination unit 133 can acquire the second captured image by specifying the capturing conditions.

[0219] Furthermore, the determination unit 133 may generate the estimated data by taking into consideration not only the geographical fluctuation component (shadowing) of the communication characteristics but also the instantaneous fluctuation component (fading).

[0220] For example, the determination unit 133 determines the estimated data (final received power P ｆｉｎａｌ ) is calculated.

[0221] Specifically, the determination unit 133 calculates a fading margin from the actual measurement data included in the second data. The determination unit 133 calculates estimated data by adding the calculated fading margin to equation (3).

[0222] In this way, the determination unit 133 generates estimated data for the second area using the second estimation model. The determination unit 133 corrects this estimated data using the first estimation model. For example, the determination unit 133 generates corrected data using the first estimation model and the first captured image. The determination unit 133 corrects the estimated data generated using the second estimation model using the correction data to generate corrected estimated data.

[0223] The determination unit 133 determines communication parameters using the corrected estimated data and outputs the determined communication parameters to the notification unit 134.

[0224] (Notification Unit 134) The notification unit 134 notifies the base station 300 and / or the terminal device 400 of the communication parameters determined by the determination unit 133.

[0225] <<3. Example of Communication Processing>> In the communication system, communication processing is executed, which includes a generation processing for generating an estimation model and a determination processing for determining communication parameters.

[0226] <3-1. Example of Generation Process> Fig. 14 is a sequence diagram showing an example of the flow of the generation process according to an embodiment of the present disclosure. The generation process shown in Fig. 14 is executed in a communication system. The terminal device 400 and the base station 300 shown in Fig. 14 are the terminal device 400 and the base station 300 in a first area.

[0227] 14, the base station 300 transmits a signal (step S101). This signal is, for example, a measurement signal that the terminal device 400 uses to measure actual measurement data.

[0228] The terminal device 400 measures the signal, generates first data including actual measurement data that is the measurement result, and transmits this first data to the control station 100 (step S102).

[0229] The terminal device 400 may transmit the first data to the control station 100 via the base station 300, or may transmit the first data to the control station 100 without passing through the base station 300. That is, the terminal device 400 may transmit the first data to the control station 100 via the cellular network.

[0230] Alternatively, the terminal device 400 may transmit the first data to the control station 100 via Wi-Fi, the Internet, etc. Alternatively, the terminal device 400 may transmit the first data to the control station 100 by being directly connected to the control station 100 via a cable.

[0231] The terminal device 400 transmits the first captured image to the control station 100 (step S103). The terminal device 400 may transmit the first captured image to the control station 100 via the base station 300, or may transmit the first captured image to the control station 100 without passing through the base station 300.

[0232] That is, the terminal device 400 may transmit the first captured image to the control station 100 via a cellular network. Alternatively, the terminal device 400 may transmit the first captured image to the control station 100 via Wi-Fi, the Internet, or the like. Alternatively, the terminal device 400 may transmit the first captured image to the control station 100 by being directly connected to the control station 100 via a cable.

[0233] In this example, the terminal device 400 that transmits the first data transmits the first captured image to the control station 100, but the terminal device 400 that transmits the first data and the terminal device 400 that transmits the first captured image may be different. Alternatively, the control station 100 may obtain the first captured image from a device other than the terminal device 400.

[0234] The control station 100 generates a first estimation model based on the acquired first captured image (step S104). For example, the control station 100 performs a segmentation process on the first captured image to divide the first captured image into objects.

[0235] The control station 100 calculates the shielding ratio R of the transmission and reception propagation paths at the shooting point from the area (number of pixels) of the objects that have been assigned a sky label and / or the area (number of pixels) of the objects that have been assigned an obstacle-related label. Examples of obstacle-related labels include labels for structures (buildings, etc.).

[0236] The control station 100 also calculates the shadowing value at the imaging point and stores it in association with the shielding ratio R. The control station 100 generates a first estimation model from the shadowing values ​​and shielding ratio R at a plurality of points.

[0237] Next, the control station 100 generates a second estimation model based on the acquired first data (step S105). For example, the control station 100 calculates an average RSRP by averaging the RSRPs included in the first data for each grid obtained by dividing the first area.

[0238] The control station 100 generates a second estimation model based on the average RSRP and the distance between the transmitter and the receiver.

[0239] <3-2. Example of Determination Process> Fig. 15 is a sequence diagram showing an example of the flow of the determination process according to an embodiment of the present disclosure. The generation process shown in Fig. 15 is executed in a communication system. The terminal device 400 and the base station 300 shown in Fig. 15 are the terminal device 400 and the base station 300 in the second area.

[0240] 15, the terminal device 400 transmits second data to the control station 100 (step S201). The second data includes, for example, location information of the terminal device 400.

[0241] The terminal device 400 may transmit the second data to the control station 100 via the base station 300, or may transmit the second data to the control station 100 without passing through the base station 300. That is, the terminal device 400 may transmit the second data to the control station 100 via the cellular network.

[0242] Alternatively, the terminal device 400 may transmit the second data to the control station 100 via Wi-Fi (registered trademark), the Internet, etc. Alternatively, the terminal device 400 may transmit the second data to the control station 100 by being directly connected to the control station 100 via a cable.

[0243] The terminal device 400 transmits the second captured image to the control station 100 (step S202). The terminal device 400 may transmit the second captured image to the control station 100 via the base station 300, or may transmit the second captured image to the control station 100 without passing through the base station 300.

[0244] That is, the terminal device 400 may transmit the second captured image to the control station 100 via a cellular network. Alternatively, the terminal device 400 may transmit the second captured image to the control station 100 via Wi-Fi, the Internet, or the like. Alternatively, the terminal device 400 may transmit the second captured image to the control station 100 by being directly connected to the control station 100 via a cable.

[0245] In this example, the terminal device 400 that transmits the second data transmits the second captured image to the control station 100, but the terminal device 400 that transmits the second data and the terminal device 400 that transmits the second captured image may be different. Alternatively, the control station 100 may obtain the second captured image from a device other than the terminal device 400.

[0246] The control station 100 determines communication parameters (here, control information) using the second data and the second captured image (step S203).

[0247] For example, the control station 100 uses the second data and the second estimation model to generate first estimated data (e.g., received power P Ｌ For example, the control station 100 calculates the distance (transmission and reception distance) between the base station 300 and the terminal device 400 from the location information of the terminal device 400 included in the second data. The control station 100 inputs the calculated transmission and reception distance into a second estimation model. The control station 100 uses the output of the second estimation model as first estimation data.

[0248] The control station 100 generates correction data using the second captured image and the first estimation model. For example, the control station 100 performs a segmentation process on the second captured image to divide the second captured image into objects.

[0249] The control station 100 calculates the shielding ratio R of the transmission and reception propagation paths at the position of the terminal device 400 from the area (number of pixels) of the object to which the sky label is assigned and / or the area (number of pixels) of the object to which the obstacle-related label is assigned. An example of the obstacle-related label is a label of a structure (such as a building).

[0250] The control station 100 inputs the calculated shadowing ratio R into the first estimation model. The control station 100 uses the shadowing value, which is the output of the first estimation model, as correction data.

[0251] The control station 100 generates estimated data (corrected estimated data) by correcting the first estimated data using the correction data. The control station 100 determines control information based on the estimated data.

[0252] The control station 100 transmits the determined control information to the base station 300 and the terminal device 400 (step S204).

[0253] As described above, the control station 100 according to this embodiment generates an estimation model using the first data and the first captured image in the first area. The estimation model includes, for example, a first estimation model and a second estimation model.

[0254] The control station 100 generates estimated data related to communication characteristics of the second area using the second data, the second captured image, and the estimation model for the second area. For example, the control station 100 corrects the second estimation model using the first estimation model to generate the estimated data. More specifically, the control station 100 corrects the output of the second estimation model with the output of the first estimation model.

[0255] The control station 100 corrects the output of the second estimation model when information based on the second data is input, with the output of the first estimation model when the second captured image is input.

[0256] In this way, the control station 100 can estimate the propagation path conditions (communication characteristics) between the base station 300 and the terminal device 400 with higher accuracy by estimating the communication characteristics using the captured image.

[0257] <<4. Other>> Here, definitions (explanations) of terms used in the above-described embodiment will be described.

[0258] <4-1. Terminology> <4-1-1. Communication Characteristics> For example, the communication characteristics are any of the following, or a combination thereof: - Characteristics based on radio wave propagation from a transmission point to a reception point (downlink, uplink, and sidelink) - Communication parameters at the transmission point, reception point, base station 300, terminal device 400, and / or communication node

[0259] The characteristics based on radio wave propagation from a transmitting point to a receiving point include at least one of a characteristic related to received power, a characteristic related to communication speed (throughput), and a characteristic related to delay.

[0260] The characteristics related to the received power include information on at least one of the received power, interference power, RSRP, RSRQ (Reference Signal Received Quality), RSSI (Received Signal Strength Indicator), SNR (Signal-to-noise ratio), and SINR (Signal and interference-to-noise ratio).

[0261] The characteristics related to communication speed include information on at least one of downlink throughput, uplink throughput, and sidelink throughput.

[0262] The delay-related characteristics include information about at least one of latency, jitter, and ping value.

[0263] The communication parameters at the transmission point, reception point, base station 300, terminal device 400 and / or communication node include dynamically determined parameters and / or semi-statically determined parameters.

[0264] The dynamically determined parameters include at least one of the following information: - Information about MCS (Modulation and Coding Scheme) - Information about transmission power - Information about beam control - Information about the number of MIMO (Multi-Input Multi-Output) multiplexings

[0265] The semi-statically determined parameters include at least one of a range, a maximum value, a minimum value, an average value, and a median value of a parameter that can be selected (allowed for the base station 300 or the terminal device 400) by the base station 300 or the terminal device 400. An example of a semi-statically determined parameter is the maximum transmission power.

[0266] <4-1-2. Area> The area (location, base) in this embodiment can be given by any one of the following, or a combination thereof. This area corresponds to the first area and / or second area described above. - Coverage area (communication area) of a predetermined base station 300, terminal device 400, or communication node - Site or building owned or managed by a predetermined business operator - Area set in advance by a predetermined business operator or government - Area divided in a predetermined manner

[0267] A communication area includes, for example, coverage that can be connected to one communication node (such as a base station 300 or a terminal device 400). Also, for example, when multiple base stations 300 are installed in one base station, these base stations 300 are connected to one core network. In other words, a base station can be defined as a coverage area covered by at least one base station 300 connected to one core network.

[0268] For example, a base station 300 of a private network or an access point name (APN) of a core network can be set as a communication area for each base station. In other words, the same access point name is set for the same base station (communication area), and bases (communication areas) with different access point names are recognized as different base stations (communication areas).

[0269] An example of a predetermined method for dividing areas is a method based on location information, in which areas are divided into predetermined distances based on location information such as latitude and longitude.

[0270] <4-1-3. Regarding Communication Environment Information> The communication environment information is information that can be included in the first data and / or the second data. The communication environment information can be used to generate an estimation model (the first estimation model and / or the second estimation model). The communication environment information can be used to generate estimation data using the estimation model. In other words, the communication environment information can be an explanatory variable of the estimation model.

[0271] The communication environment information includes at least one of static or quasi-static information and dynamic information. Static or quasi-static information is fixed information or information that is updated infrequently. Note that the static or quasi-static information may be information in a higher communication layer (e.g., an application layer, an RRC (Radio Resource Control) layer, etc.). The dynamic information is information that is updated frequently. Note that the dynamic information may be information in a lower communication layer (e.g., a physical layer, etc.).

[0272] The communication environment information includes, for example, at least one of the following information: - Map information - Structure information - Device information related to the base station 300 or the terminal device 400 - Sensing information acquired through a sensing device - Wireless communication information related to wireless communication

[0273] (Map Information) The map information here is information that allows the positions and sizes of structures, the base station 300, the terminal device 400, etc. to be recognized. The positions may be absolute position information such as latitude and longitude, or may be relative position information within an area.

[0274] The map information includes, for example, topographical information, an office layout diagram, and a premises diagram.

[0275] (Structure Information) The structure information here includes information that affects radio wave propagation, such as reflection, diffraction, and transmission.

[0276] Examples of structures include buildings, walls, plantations, roads, signs, traffic lights, road signs, pillars, buildings, the ground, glass, windows, desks, and cabinets.

[0277] The structure information includes, for example, the position, shape, size, and material of the structure, as well as parameters related to radio wave propagation in the structure (dielectric constant, conductivity, etc.).

[0278] The structure information is generated and constructed based on, for example, the map information described above. In addition, the structure information may be generated and constructed based on information acquired from a sensing device, which will be described later.

[0279] (Device Information Regarding the Base Station 300 or the Terminal Device 400) The device information regarding the base station 300 or the terminal device 400 here includes, for example, at least one of the following pieces of information: - Antenna information regarding the antenna - Capability information regarding the functions and capabilities supported in wireless communication - Shape information regarding the shape and weight of the base station 300 and / or the terminal device 400 - Location information of the fixed base station 300 and / or the fixed terminal device 400

[0280] The antenna information here includes, for example, at least one of the antenna configuration, beam pattern, number of antenna elements, and configuration of the antenna elements of the base station 300 and / or the terminal device 400 .

[0281] (Sensing information acquired through the sensing device) The sensing information acquired through the sensing device here includes object information regarding an object detected through the sensing device, and / or impact information regarding fluctuations and / or impacts on wireless communication caused by the detected object.

[0282] Here, the sensing device includes a camera, a sensor, etc. The sensor includes a photoelectric sensor, a fiber sensor, a laser sensor, a color sensor, a proximity sensor, an eddy current type displacement sensor, a contact type displacement sensor, an ultrasonic sensor, an image discrimination sensor, a pressure sensor, a vibration sensor, an inertial measurement sensor, etc.

[0283] Three-dimensional spatial information (e.g., the above-described structure information) is generated from sensing information acquired through a sensing device. For example, when the sensing information is an image or video acquired in real time by a camera, the three-dimensional spatial information is generated in real time using, for example, photogrammetry technology or volumetric capture technology.

[0284] The objects detected by the sensing device include various devices such as the sensing device itself, devices other than the sensing device, and the terminal device 400 that transmits information acquired by the sensing device. The objects detected by the sensing device also include the above-mentioned structures and objects other than structures.

[0285] The terminal device 400 that transmits the sensing information acquired by the sensing device may or may not be equipped with the sensing device. If the terminal device 400 and the sensing device are separate devices, it is preferable that the terminal device 400 acquires the sensing information from the sensing device, for example, by wired or wireless communication.

[0286] Note that sensing information acquired by sensing (sensing information acquired through a sensing device) may include various sensing information in addition to object detection information. For example, the sensing information acquired by sensing may include beam information (e.g., information on a beam pattern, a beam angle, etc.) related to a beam transmitted from the base station 300 and / or the terminal device 400.

[0287] The sensing device described above can detect moving objects such as people and robots in addition to stationary objects such as structures. The sensing device transmits, for example, information about the detected moving objects as sensing information via the terminal device 400.

[0288] The sensing device may transmit the sensing information when it detects a moving object and / or when it no longer detects a moving object. Alternatively, the sensing device may transmit the sensing information at regular intervals.

[0289] (Wireless communication information related to wireless communication) Here, the wireless communication information related to wireless communication includes, for example, at least one of the following information: - Communication information related to RAT (Radio access technology) and frequency - Information related to the transmission power of the base station 300 or the terminal device 400 - Scenario information related to the communication environment scenario - Constraint information related to the conditions and constraints related to wireless communication available in the local network - Quality information related to the communication quality in wireless communication

[0290] The communication information related to the RAT includes, for example, information related to LTE, NR, wireless LAN, Bluetooth (registered trademark), etc. The communication information related to the frequency includes information related to at least one of a frequency band, a center frequency, and a frequency bandwidth.

[0291] The information relating to the transmission power of the base station 300 or the terminal device 400 includes, for example, information (ss-PBCH-BlockPower) indicating the transmission power of an SS / PBCH (Synchronization Signal and Physical Broadcast CHannel) block included in an SS / PBCH (System information block type 1) included in SIB1 (System information block type 1), which is control information broadcast from the base station 300.

[0292] Scenario information relating to communication environment scenarios includes, for example, information relating to urban areas, suburban areas, depopulated areas (rural areas), indoor offices, indoor factories, and the like.

[0293] The scenario information may further include information on a radio wave propagation model (e.g., a path loss model) corresponding to the communication environment scenario. The radio wave propagation model may correspond to each of a LOS environment and a NLOS environment.

[0294] The restriction information here includes information about conditions and restrictions regarding wireless communication permitted in the local network.

[0295] These conditions and constraints may include, for example, information about available RATs, areas where wireless communication is possible (geographical information (such as two-dimensional planar information and / or spatial information including three-dimensional height)), an upper limit on the amount of interference power outside the area, maximum transmit power that can be transmitted, transmittable frequency information, transmittable time information, and the installation location of base station 300.

[0296] These conditions and constraints may be set or defined in advance, and may be determined and / or changed based on information sent from a predetermined server or storage device (e.g., a Spectrum Access System (SAS) server).

[0297] The quality information regarding the communication quality in wireless communication includes, for example, at least one of the following information measured or estimated by the terminal device 400 in wireless communication: - Received power - Interference power - RSRP - RSRQ - RSSI - SNR - Downlink throughput - Uplink throughput - Latency - Jitter - Ping value

[0298] <4-1-4. Location Information> The information relating to location is location information of the base station 300 and / or the terminal device 400. For example, the location information may be included in the second data.

[0299] The information about the location includes absolute location information such as latitude, longitude, and / or altitude obtained from, for example, a global positioning system (GPS) or a global navigation satellite system (GNSS).

[0300] Alternatively, the information relating to the location includes relative location information obtained by a beacon, UWB (Ultra-Wide Band), or the like.

[0301] The absolute location information or relative location information may be an area divided by a predetermined distance or method.

[0302] Note that the information according to this embodiment (first and second data, first and second captured images, etc.) can be information linked to location information.

[0303] 4-2. Virtual Space Estimation Information The virtual space estimation information includes, for example, information about radio wave propagation of at least one of the base station 300 and the terminal device 400. The virtual space estimation information is, for example, data (information) obtained by a simulation.

[0304] The virtual space estimation information may be used as needed when generating the estimation model (the first estimation model and / or the second estimation model). For example, the virtual space estimation information may be included in the first data and / or the second data.

[0305] The virtual space estimation information may be used as an explanatory variable of an estimation model (the first estimation model and / or the second estimation model). Alternatively, the virtual space estimation information may be used as a response variable of an estimation model (the first estimation model and / or the second estimation model). For example, the virtual space estimation information included in the first data may be used as student data and teacher data of the estimation model.

[0306] The virtual space estimation information includes, for example, at least one of the following information: - LOS / NLOS information - Simulation information - Calculation information calculated based on the LOS / NLOS information, simulation information, etc.

[0307] (LOS / NLOS Information) LOS / NLOS information is information indicating whether the environment between the base station 300 and the terminal device 400 is an LOS environment or an NLOS environment.

[0308] The LOS environment is also called a line-of-sight environment. The LOS environment indicates a situation in which there are no obstacles 600, such as structures or people, on the line between the base station 300 and the terminal device 400, and the base station 300 and the terminal device 400 can transmit and receive direct waves between them. In this case, wireless communication between the base station 300 and the terminal device 400 is performed through reflected waves, diffracted waves, and the like in addition to direct waves.

[0309] The NLOS environment is also called a non-line-of-sight environment. The NLOS environment indicates a situation in which an obstacle 600, such as a structure or a person, is present on the line between the base station 300 and the terminal device 400, preventing the base station 300 and the terminal device 400 from transmitting and receiving direct waves therebetween. In this case, wireless communication between the base station 300 and the terminal device 400 is performed via reflected waves, diffracted waves, and the like, other than direct waves.

[0310] (Simulation Information) The simulation information includes information related to the simulation results of radio wave propagation in wireless communication between the base station 300 and the terminal device 400. The simulation information includes, for example, path information related to one or more paths (transmitted waves, arriving waves, rays) acquired by ray tracing simulation.

[0311] This path includes direct waves, reflected waves, diffracted waves, transmitted waves, etc. between the base station 300 and the terminal device 400. Generally, there are various structures between the base station 300 and the terminal device 400, so a signal (radio wave) transmitted from a transmitting point (e.g., the base station 300) travels through various routes, becomes multiple paths, and arrives at a receiving point (e.g., the terminal device 400).

[0312] The path information regarding the path may include, for example, at least one of the following information: - Received power at the receiving point - Transmitted power at the transmitting point - Path loss - Propagation distance - Number of reflections - Number of diffractions - Number of transmissions - Phase fluctuation - Emission angle at the transmitting point - Arrival angle at the receiving point - Arrival order of the path (the order of arrival in time among multiple paths) - Number of paths

[0313] (Calculation Information) The calculation information is information that is generated and calculated based on the above-mentioned LOS / NLOS information, simulation information, etc. The calculation information may include, for example, at least one of the following information: - Path loss at the reception point - Received power - Interference power - RSRP - RSRQ - RSSI - SNR - Downlink throughput - Uplink throughput - Latency - Jitter - Ping value

[0314] Here, an example of a process for generating virtual space estimation information (information generation process) according to this embodiment will be described with reference to Fig. 16. Fig. 16 is a flowchart showing an example of the flow of the information generation process according to an embodiment of the present disclosure.

[0315] The information generation process shown in FIG. 16 can be executed by, for example, the control station 100 when virtual space estimation information (simulation data) is used to generate an estimation model and / or generate estimation data.

[0316] First, the control station 100 constructs a virtual communication environment for an area (first area and / or second area) (step S301).

[0317] For example, the virtual communication environment is a three-dimensional virtual space of the area. For example, the virtual communication environment is generated based on communication environment information of the area. For example, the virtual communication environment includes structures (such as buildings and the ground) within the area.

[0318] Next, the control station 100 performs a radio wave propagation simulation between the base station 300 and the terminal device 400 in a virtual communication environment (step S302). The radio wave propagation simulation can use various methods, such as determining whether the environment is a LOS environment or a NLOS environment in a virtual space, or a ray tracing simulation.

[0319] The control station 100 generates virtual space estimation information based on the simulation results (step S303).

[0320] The information generation process may be executed by a device other than the control station 100. In this case, the control station 100 acquires virtual space estimation information (simulation data) from the device that executes the information generation process. Furthermore, the timing of performing the information generation process is not limited to when an estimation model and / or estimation data is generated. The control station 100 may execute the information generation process at any timing.

[0321] <4-3. Regarding Estimation Accuracy> For example, when the control station 100 estimates actual communication characteristics using an estimation model (first estimation model and / or second estimation model), an estimation accuracy may be provided. Alternatively, an estimation accuracy may be provided for the estimation model (first estimation model and / or second estimation model). This estimation accuracy may be further used when using (utilizing) data estimated using the estimation model of communication characteristics.

[0322] The estimation accuracy of the communication characteristics and / or estimation model in the communication area (second area) can be given by any one of the following or a combination thereof: - Number of first areas (number of locations A included in the first area) - Number of actually measured data at each location A in the first area - Estimation accuracy of the shielding factor R of the transmission and reception propagation path in the first area and / or second area - Resolution of the first photographed image and / or second photographed image - Obtainable range of the first photographed image and / or second photographed image - Generation accuracy of the estimation model - Similarity of the communication environment in the first area and the second area - Accuracy of the simulation data in the first area and / or second area - Observation accuracy of the actually measured data in the first area and / or second area

[0323] Examples of similarities in communication environments include the average height of structures in each area, the density of structures, and the height of base station 300 (including installation location (altitude), building height, antenna height, etc.).

[0324] For example, the accuracy of the simulation data can be determined based on the accuracy (precision, accuracy) of the communication environment information in the simulation for generating the simulation data.

[0325] The observation accuracy of the measured data may include at least one of the accuracy of the communication characteristics and the accuracy of the location information. For example, the error of the measured data may include the measurement error of the RSRP and / or the error of the location information obtained by the GPS.

[0326] Furthermore, if an observation error specific to the terminal device 400 occurs, information indicating that terminal device 400 can be included in the observation accuracy of the actual measurement data.

[0327] <4-4. Normalization of Measured Data> In this embodiment, when there are multiple first areas (more specifically, multiple locations A that are first areas), the simulation data and / or the measured data in the first areas are normalized (offsets are provided) by, for example, a predetermined method.

[0328] The predetermined method can be performed based on communication environment information (for example, information on the transmission power from base station 300) in each first area (location A).

[0329] Here, the communication environment information is the information described above, and includes, for example, information on the transmission power of the base station 300, information on the frequency used for communication (carrier frequency, frequency bandwidth, etc.), information on the first area (coverage size, indoor / outdoor information, etc.), etc.

[0330] For example, normalization is performed so that the communication environment information in each first area (location A) is the same as each other.

[0331] Simulation data of communication characteristics in a specified area (one of multiple first areas) is normalized so that the communication environment information in the specified area is the same as the communication environment information in each of the first areas (the remaining first areas other than the specified area).

[0332] Data on communication characteristics in a predetermined area (one of the plurality of first areas) is estimated taking into account the normalization described above.

[0333] The actual measurement data of the communication characteristics in a specified area (one of a plurality of first areas) is normalized so that the communication environment information in the specified area is the same as the communication environment information in each of the first areas (the remaining first areas other than the specified area).

[0334] The above-mentioned normalization is performed so that the communication environment information in each first area becomes the communication environment information in the above-mentioned predetermined area (one of the plurality of first areas).

[0335] The normalization is performed, for example, by a device that generates the estimation model (in this embodiment, the control station 100). Note that the device that performs the normalization and the device that generates the estimation model may be different devices.

[0336] A specific example of normalization will be described below.

[0337] For example, consider a case where the communication characteristics of the simulation data and / or the actual measurement data in the first area are downlink RSRP.

[0338] Consider a case where the transmission power of the base station 300 at location A1 is B1 (dBm), the transmission power of the base station 300 at location A2 is B2 (dBm), and the transmission power of the base station 300 at location A3 is B3 (dBm).

[0339] When normalizing these transmission powers to S (dBm), the control station 100 assigns an offset of S-B1 (dBm) to the RSRP at location A1. The control station 100 assigns an offset of S-B2 (dBm) to the RSRP at location A2. The control station 100 assigns an offset of S-B3 (dBm) to the RSRP at location A3. In this way, the control station 100 performs normalization by assigning an offset to each RSRP (each data).

[0340] Here, S (dBm) may be the transmission power of the base station 300 in the second area (location X1) where estimation is performed.

[0341] <<5. Application Examples>> <5-1. First Application Example> As described above, the determination of communication parameters is executed by the control station 100. At this time, the control station 100 may determine the communication parameters (communication environment) in accordance with, for example, an instruction from a user who carries the terminal device 400. The control station 100 may estimate communication conditions (e.g., estimated received power, estimated interference power, etc.) at a predetermined location (e.g., the user's current location) in accordance with, for example, an instruction from the user.

[0342] In this case, the user first requests the control station 100 to perform estimation by transmitting information to the control station 100 that will be used (or will be useful) for estimation by the control station 100. The user may transmit this information using the terminal device 400 that the user owns.

[0343] FIG. 17 is a diagram showing an example of a user interface of the terminal device 400 according to the first application example of the present disclosure.

[0344] 17 , the terminal device 400 transmits information about at least one of a surrounding image of the location to be estimated, a questionnaire about the communication environment, the estimated location, and a map as information used for estimation in the control station 100. This surrounding image may correspond to the second captured image described above.

[0345] The information about the image of the surroundings of the estimated location may be a still image or a moving image. The terminal device 400 may also transmit a previously captured image of the surroundings to the control station 100. Alternatively, as shown in FIG. 17 , when requesting estimation from the control station 100, the user may take a picture of the surroundings (photograph) using a camera (not shown) mounted on the terminal device 400. The terminal device 400 transmits the image of the surroundings captured by the user to the control station 100.

[0346] The questionnaire information regarding the communication environment is information generated based on information input by the user, for example. The user answers the questionnaire displayed on the display device, and the terminal device 400 generates the questionnaire information. The questionnaire to which the user answers may be in a multiple-choice format, in which the user selects a yes or no answer, or in a descriptive format, in which the user answers in free text.

[0347] The questionnaire may include, for example, questions about whether the base station 300 is visible, questions about the surrounding environment, questions about the maximum transmission power of the assumed base station 300, etc. Questions about the surrounding environment may include, for example, questions about whether the estimated location is outdoors or indoors, and if outdoors, whether it is a depopulated area, a suburban area, or an urban area. Furthermore, questions about the surrounding environment may include, for example, questions about whether the location is indoors, whether it is a residence or an office.

[0348] The information about the estimated location includes information about the location where the control station 100 estimates the received power, interference power, etc. This estimated location may be the current location of the terminal device 400, or may be a location different from the current location (for example, a planned installation location of the terminal device 400).

[0349] The terminal device 400 may transmit absolute position information such as latitude, longitude, and altitude as information about the estimated location to the control station 100. Alternatively, the terminal device 400 may transmit relative position information such as a relative positional relationship with the base station 300 as information about the estimated location.

[0350] Alternatively, the terminal device 400 may transmit the location where the peripheral image was captured as an estimated location to the control station 100. For example, when a camera mounted on the terminal device 400 captures a peripheral image including information about the location where the image was captured, the terminal device 400 transmits the information about the location where the image was captured to the control station 100 as information about the estimated location.

[0351] Furthermore, the terminal device 400 may include information about the estimated location in the information about the map.

[0352] The information about the map includes, for example, information about a map of the area around the estimated location. At this time, the terminal device 400 may transmit map information indicating the installation position of the base station 300 to the control station 100. At this time, the terminal device 400 may transmit information about its own location or the estimated location to the control station 100 by including it in the map information.

[0353] The control station 100 executes the above-described determination process based on the information acquired from the terminal device 400, thereby generating estimated data and determining communication parameters. The control station 100 notifies the terminal device 400 of the communication parameters (or control information generated based on the communication parameters). Based on the notification, the terminal device 400 presents the communication parameters to the user by displaying them on a display device provided in the terminal device 400.

[0354] <5-2. Second Application Example> As a second application example, a case will be described in which a user who owns a terminal device 400 has the control station 100 estimate coverage (communication availability) based on the actual space when the base station 300 is installed at a predetermined location.

[0355] First, the user requests the control station 100 to perform estimation by transmitting information to be used (or useful) for estimation by the control station 100. The user may transmit this information using a terminal device 400 that the user possesses.

[0356] The terminal device 400 transmits at least one of information related to the maximum transmission power assumed by the base station 300 and map information as information used for estimation by the control station 100. The map information includes, for example, information related to the location of the base station 300 (corresponding to the predetermined location described above). The location of the base station 300 is the location for which the control station 100 is to estimate coverage based on real space. This location may be the actual location of the base station 300, or may be a location specified by the user.

[0357] The control station 100 executes the above-described determination process based on the information acquired from the terminal device 400, generates estimated data, and determines communication parameters.

[0358] For example, the control station 100 acquires an image of the area around the designated base station 300 as a second captured image and generates estimated data for the location where the second captured image was captured. The control station 100 generates estimated data for multiple capture locations and determines communication parameters. The control station 100 may acquire the second captured image from a terminal device 400 located in the vicinity of the base station 300, or may acquire a street image from a map app or the like.

[0359] In other words, the control station 100 estimates an area where the interference power of the base station 300 (or the received power of the terminal device 400) is equal to or greater than a predetermined value. In this way, the control station 100 estimates the coverage of the base station 300 when the base station 300 is placed at a predetermined location.

[0360] The control station 100 notifies the terminal device 400 of information about the estimated coverage as an estimation result. The terminal device 400 displays the acquired estimation result on a display device to present it to the user.

[0361] 18 is a diagram illustrating an example of a user interface of the terminal device 400 according to the second application example of the present disclosure. In FIG. 18, the terminal device 400 presents an estimation result acquired from the control station 100 to a user.

[0362] As shown in FIG. 18, the terminal device 400 displays information indicating the coverage estimated by the control station 100 together with the base station 300 on the display device, superimposed on map information.

[0363] At this time, the terminal device 400 may present the user with the estimated maximum transmission power used in the coverage estimation ("estimated transmission power" in the figure). The terminal device 400 may also accept a change in this estimated transmission power from the user.

[0364] For example, as shown in Fig. 18, the user may be allowed to freely change the number indicating the estimated transmission power. After the user inputs the estimated transmission power, the user presses the "transmit" button, and the terminal device 400 requests the control station 100 to re-estimate the coverage using the estimated transmission power input by the user.

[0365] In this way, the terminal device 400 presents the estimated coverage of the base station 300 to the user together with map information, so that the user can more easily recognize the estimated coverage of the base station 300 .

[0366] <<6. Hardware Configuration Example>> Next, a description will be given of a hardware configuration example of the control station 100, base station 300, and terminal device 400 according to each embodiment. The information devices of the control station 100, base station 300, and terminal device 400 described above are realized by, for example, a computer 1000 having a configuration as shown in FIG.

[0367] 19 is a block diagram showing an example hardware configuration of a computer 1000 according to the present disclosure. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM 1300, a hard disk drive (HDD) 1400, a communication interface 1500, and an input / output interface 1600. The components of the computer 1000 are connected via a bus 1050.

[0368] The CPU 1100 operates and controls each component based on programs stored in the ROM 1300 or the HDD 1400. For example, the CPU 1100 loads the programs stored in the ROM 1300 or the HDD 1400 into the RAM 1200 and executes processing corresponding to the various programs.

[0369] The ROM 1300 stores boot programs such as a Basic Input Output System (BIOS) that is executed by the CPU 1100 when the computer 1000 is started, and programs that depend on the hardware of the computer 1000 .

[0370] HDD 1400 is a computer-readable recording medium that non-temporarily records programs executed by CPU 1100 and data used by such programs. Specifically, HDD 1400 is a recording medium that records the proposed program according to the present disclosure, which is an example of program data 1450.

[0371] The communication interface 1500 is an interface for connecting the computer 1000 to an external network 1550 (e.g., the Internet). For example, the CPU 1100 receives data from other devices and transmits data generated by the CPU 1100 to other devices via the communication interface 1500.

[0372] The input / output interface 1600 is an interface for connecting the input / output device 1650 and the computer 1000. For example, the CPU 1100 receives data from an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 also transmits data to an output device such as a display, a speaker, or a printer via the input / output interface 1600. The input / output interface 1600 may also function as a media interface for reading programs recorded on a predetermined recording medium. Examples of media include optical recording media such as a DVD (registered trademark) (Digital Versatile Disc) or a PD (Phase Change Rewritable Disk), magneto-optical recording media such as an MO (Magneto-Optical disk), tape media, magnetic recording media, or semiconductor memory.

[0373] CPU 1100 executes programs loaded onto RAM 1200 to realize functions of control units 130, 340, 450, etc. Furthermore, HDD 1400 stores proposed programs according to the present disclosure and data in storage units 120, 320, 420. Note that CPU 1100 reads and executes program data 1450 from HDD 1400, but as another example, these programs may be acquired from other devices via external network 1550.

[0374] <<7. Other Embodiments>> The processing according to each of the above-described embodiments may be implemented in various different forms other than the above-described embodiments.

[0375] For example, in the above-described embodiment, the control station 100 executes the determination process by acquiring the second data and the second captured image from the terminal device 400. However, the control station 100 may execute the determination process without acquiring at least one of the second data and the second captured image from the terminal device 400.

[0376] In this case, the control station 100 determines a position in the second area where the estimated data is calculated. The control station 100 acquires a second captured image at the determined position. The control station 100 may acquire the second captured image from the terminal device 400, or from a device other than the terminal device 400.

[0377] Furthermore, if the second photographed image includes information about the photographing location, the control station 100 may omit acquiring the second data. Alternatively, the control station 100 may acquire information about the photographing location included in the second photographed image as the second data.

[0378] For example, in each of the above-described embodiments, the control station 100 performs the generation process and the determination process, but the device that performs these processes is not limited to the control station 100. For example, the base station 300 may perform these processes. In this case, the base station 300 acquires information used to perform the generation process and the determination process from the control station 100 and / or the terminal device 400.

[0379] Alternatively, these processes may be executed by the terminal device 400. In this case, the terminal device 400 acquires information used to execute the generation process and the determination process from the control station 100 and / or the base station 300.

[0380] Furthermore, in each of the above-described embodiments, the same device (for example, the control station 100) executes both the generation process and the determination process, but these processes may be executed by different devices.

[0381] For example, the control station 100 may perform the generation process, and the base station 300 may perform the determination process. In this case, the control station 100 acquires information used in the generation process from the base station 300 and / or the terminal device 400. The base station 300 acquires information used in the determination process from the control station 100 and / or the terminal device 400.

[0382] Alternatively, for example, the control station 100 may perform the generation process, and the terminal device 400 may perform the determination process. In this case, the control station 100 acquires information used in the generation process from the base station 300 and / or the terminal device 400. The terminal device 400 acquires information used in the determination process from the control station 100 and / or the base station 300.

[0383] Alternatively, for example, the base station 300 may perform the generation process, and the terminal device 400 may perform the determination process. In this case, the base station 300 acquires information used in the generation process from the control station 100 and / or the terminal device 400. The terminal device 400 acquires information used in the determination process from the control station 100 and / or the base station 300. Note that the terminal device 400 may perform the generation process, and the base station 300 may perform the determination process.

[0384] Furthermore, the generation process may be distributed among multiple devices. For example, the device that generates the first estimation model and the device that generates the second estimation model may be different. For example, the control station 100 may generate the first estimation model, and the base station 300 may generate the second estimation model.

[0385] In this case, the control station 100 acquires information used to generate the first estimation model from the terminal device 400 or a device other than the terminal device 400. Furthermore, the base station 300 acquires information used to generate the second estimation model from the control station 100 and / or the terminal device 400.

[0386] In this case, the control station 100 may be appropriately replaced with the base station 300 or the terminal device 400. The base station 300 may be appropriately replaced with the control station 100 or the terminal device 400. The terminal device 400 may be appropriately replaced with the control station 100 or the base station 300.

[0387] In the above-described embodiment, the control station 100 generates an estimation model including a first estimation model and a second estimation model. That is, although the control station 100 generates a plurality of estimation models, the control station 100 may generate only one estimation model.

[0388] For example, the control station 100 may generate an estimation model by machine learning or the like using the first data and the shielding rate R calculated from the first captured image. For example, the control station 100 may generate an estimation model using the first data and the shielding rate R as explanatory variables and information on the communication characteristics to be estimated from the first data as a target variable. Alternatively, the control station 100 may generate an estimation model using the first captured image instead of the shielding rate R as an explanatory variable.

[0389] In this way, the control station 100 according to this embodiment only needs to generate an estimation model based on the first captured image and the first data, and the number of estimation models, the method of generating the estimation models, etc. are not limited to those of the above-described embodiment.

[0390] For example, the control station 100, the base station 300, and the control device that controls the terminal device 400 in each of the above-described embodiments may be realized by a dedicated computer system or a general-purpose computer system.

[0391] For example, a communication program for executing the above-described operations is stored on a computer-readable recording medium such as an optical disk, a semiconductor memory, a magnetic tape, or a flexible disk and distributed. Then, for example, the program is installed on a computer and the above-described processing is executed to configure a control device. In this case, the control device may be a device (e.g., a personal computer) external to the control station 100, the base station 300, and the terminal device 400. Alternatively, the control device may be a device (e.g., a control unit 130, 340, 450) internal to the control station 100, the base station 300, and the terminal device 400.

[0392] The communication program may also be stored in a disk device provided in a server device on a network such as the Internet, and may be downloaded to a computer. The above-described functions may also be realized by cooperation between an operating system (OS) and application software. In this case, the components other than the OS may be stored on a medium and distributed, or the components other than the OS may be stored in a server device and may be downloaded to a computer.

[0393] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. Furthermore, the information, including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings, can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0394] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0395] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0396] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0397] Furthermore, for example, each embodiment can be implemented as any configuration that constitutes an apparatus or system, such as a processor as a system LSI (Large Scale Integration), a module using multiple processors, a unit using multiple modules, a set in which other functions are added to a unit, or the like (i.e., a configuration of a part of an apparatus).

[0398] In each embodiment, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all of the components are in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0399] Furthermore, for example, each embodiment may have a cloud computing configuration in which one function is shared and processed jointly by a plurality of devices via a network.

[0400] In the above-described embodiments, the control station 100 determines the communication parameters of the base station 300 and / or the terminal device 400. However, the present invention is not limited to this. The above-described embodiments can be used to determine and design the number of base stations 300 and / or the terminal device 400 to be installed (maximum number of installations), installation locations, and / or installation directions (horizontal direction, tilt angle, etc.).

[0401] <<8. Conclusion>> Although the embodiments of the present disclosure have been described above, the technical scope of the present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure. Furthermore, components of different embodiments and modifications may be combined as appropriate.

[0402] Furthermore, the effects of each embodiment described in this specification are merely examples and are not intended to be limiting, and other effects may also be obtained.

[0403] The present technology may also be configured as follows. (1) An information processing device including a control unit that generates an estimation model using data related to communication characteristics in a first area and a captured image of the first area, wherein the estimation model is used to estimate the communication characteristics in a second area different from the first area. (2) The information processing device according to (1), wherein the control unit estimates a shadowing value at a shooting point of the captured image from the captured image, and generates the estimation model using the estimated shadowing value. (3) The information processing device according to (1) or (2), wherein the control unit estimates an occlusion ratio in a transmission path between the shooting point of the captured image and a transmitting point or a receiving point from the captured image, and generates the estimation model using the estimated occlusion ratio. (4) The information processing device according to any one of (1) to (3), wherein the control unit divides the captured image into one or more segments according to one or more objects included in the captured image, and generates the estimation model according to a proportion of the object occupying the captured image. (5) The information processing device according to (4), wherein the object includes at least one of the sky and an obstacle. (6) The information processing device according to (5), wherein the obstacle includes at least one of a structure and a tree. (7) The information processing device according to any one of (1) to (6), wherein the control unit generates the estimation model based on imaging information regarding the captured image. (8) The information processing device according to (7), wherein the control unit generates the estimation model using the captured image having predetermined imaging information. (9) The information processing device according to (7) or (8), wherein the control unit corrects the captured image based on the imaging information. (10) The information processing device according to any one of (7) to (9), wherein the imaging information includes information regarding at least one of an angle of view of the captured image, a size of the captured image, a capturing position, a capturing direction, and a zoom amount. (11) The information processing device according to any one of (1) to (10), wherein the captured image is an image captured in the first area under predetermined conditions.(12) The information processing device according to any one of (1) to (11), wherein the estimation model includes a first estimation model and a second estimation model, and the control unit generates the first estimation model using the captured image, and generates the second estimation model using the data. (13) The information processing device according to (12), wherein the control unit generates estimated data related to communication characteristics in the second area using the second estimation model, and corrects the estimated data using the first estimation model. (14) The information processing device according to (13), wherein the control unit generates corrected data using the first estimation model based on the captured image in the second area, and generates corrected estimated data from the estimated data and the corrected data. (15) An information processing method comprising generating an estimation model using data related to communication characteristics in a first area and a captured image of the first area, and the estimation model is used to estimate the communication characteristics in a second area different from the first area. (16) The information processing method according to (15), including generating the estimation model based on imaging information related to the captured image. (17) The information processing method according to (15) or (16), wherein the estimation models include a first estimation model and a second estimation model, and including: generating the first estimation model using the captured image; and generating the second estimation model using the data. (18) The information processing method according to (17), including: generating estimated data related to communication characteristics in the second area using the second estimation model; and correcting the estimated data using the first estimation model. (19) The information processing method according to (18), including: generating correction data using the first estimation model based on the captured image in the second area; and generating corrected estimation data from the estimation data and the correction data.(20) A program that causes a computer to function as a control unit that generates an estimation model using data on communication characteristics in a first area and a captured image of the first area, and the estimation model is used to estimate the communication characteristics in a second area different from the first area.

[0404] 100 Control station 110, 310, 410 Communication unit 120, 320, 420 Storage unit 130, 340, 450 Control unit 131 Acquisition unit 132 Generation unit 133 Determination unit 134 Notification unit 300 Base station 313, 413 Antenna 330, 430 Network communication unit 400 Terminal device 440 Input / output unit

Claims

1. An information processing device comprising: a control unit that generates an estimation model using data regarding communication characteristics in a first area and captured images of the first area, and the estimation model is used to estimate the communication characteristics in a second area different from the first area.

2. The information processing device according to claim 1, wherein the control unit estimates a shadowing value at the shooting point of the captured image from the captured image, and generates the estimation model using the estimated shadowing value.

3. The information processing device according to claim 1, wherein the control unit estimates the shading rate in the transmission path between the shooting point of the captured image and the transmitting point or the receiving point from the captured image, and generates the estimation model using the estimated shading rate.

4. The information processing device according to claim 1, wherein the control unit divides the captured image into one or more parts according to one or more objects contained in the captured image, and generates the estimation model according to the proportion of the object occupying the captured image.

5. The information processing device according to claim 4, wherein the object includes at least one of the sky and an obstacle.

6. The information processing device according to claim 5, wherein the obstacle includes at least one of a structure and a tree.

7. The information processing device according to claim 1, wherein the control unit generates the estimation model based on imaging information relating to the captured image.

8. The information processing device according to claim 7, wherein the control unit generates the estimation model using the captured image having predetermined imaging information.

9. The information processing device according to claim 7, wherein the control unit corrects the captured image based on the imaging information.

10. The information processing device according to claim 7, wherein the imaging information includes information relating to at least one of the angle of view of the captured image, the size of the captured image, the shooting position, the shooting direction, and the zoom amount.

11. The information processing device according to claim 1, wherein the captured image is an image captured in the first area under predetermined conditions.

12. The information processing device of claim 1, wherein the estimation model includes a first estimation model and a second estimation model, and the control unit generates the first estimation model using the captured image and generates the second estimation model using the data.

13. The information processing device according to claim 12, wherein the control unit generates estimated data relating to communication characteristics in the second area using the second estimation model, and corrects the estimated data using the first estimation model.

14. The information processing device according to claim 13, wherein the control unit generates correction data using the first estimation model based on the captured image in the second area, and generates corrected estimation data from the estimation data and the correction data.

15. An information processing method comprising: generating an estimation model using data on communication characteristics in a first area and a captured image of the first area; and the estimation model is used to estimate the communication characteristics in a second area different from the first area.

16. The information processing method according to claim 15, further comprising generating the estimation model based on imaging information relating to the captured image.

17. The information processing method according to claim 15, wherein the estimation model includes a first estimation model and a second estimation model, and further comprising: generating the first estimation model using the captured image; and generating the second estimation model using the data.

18. An information processing method according to claim 17, comprising: generating estimated data relating to communication characteristics in the second area using the second estimation model; and correcting the estimated data using the first estimation model.

19. An information processing method as described in claim 18, comprising: generating correction data using the first estimation model based on an image captured in the second area; and generating corrected estimation data from the estimation data and the correction data.

20. A program that causes a computer to function as a control unit that generates an estimation model using data on communication characteristics in a first area and captured images of the first area, and the estimation model is used to estimate the communication characteristics in a second area different from the first area.

Images