Information processing device, information processing method, and program

Abstract

Detailed information about the user's terminal is obtained through sensing. [Solution] An information processing device comprising a wireless communication network, having a processor that performs the steps of: acquiring a sensing request including a terminal ID of a user terminal; transmitting a sensing instruction to the user terminal; receiving sensing data from the user terminal; estimating attribute information of the user terminal based on the sensing data; and transmitting the attribute information to the source of the sensing request.

Description

Technical Field

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

Background Art

[0002] In a 3rd generation partnership project (3GPP) communication system, technologies for sensing the surrounding environment of a terminal have been studied (Non-Patent Document 1).

Prior Art Documents

Non-Patent Documents

[0003]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] One aspect of the present disclosure aims to obtain detailed information about a user terminal by sensing.

Means for Solving the Problems

[0005] One aspect of the present disclosure is an information processing apparatus constituting a wireless communication network, comprising a step of obtaining a sensing request including a terminal ID of a user terminal; a step of transmitting a sensing instruction to the user terminal; a step of receiving sensing data from the user terminal; a step of estimating attribute information of the user terminal based on the sensing data; The steps include transmitting the attribute information to the source of the sensing request, This is an information processing device having a processor that performs [some action].

[0006] Another aspect of this disclosure is, An information processing method performed by an information processing device that constitutes a wireless communication network, The steps include obtaining a sensing request that includes the device ID and location information of the user terminal, The steps include sending a sensing instruction to the user terminal, The steps include receiving sensing data from the user terminal, The steps include: estimating attribute information of the user terminal based on the sensing data; The steps include transmitting the attribute information to the source of the sensing request, This is an information processing method that includes [the following]. [Effects of the Invention]

[0007] According to the aspects of this disclosure, attribute information about the user terminal can be obtained by sensing. [Brief explanation of the drawing]

[0008] [Figure 1] A diagram illustrating the components of a wireless communication system. [Figure 2] A diagram showing an example configuration of an information processing device that can operate as an NF, OAM terminal, and external server. [Figure 3] A diagram showing an example configuration of a communication device that can operate as a user terminal and a base station. [Figure 4] A diagram illustrating the overall flow of the sensing process. [Figure 5] A block diagram showing the functional configuration of the Science Firmware (SF). [Figure 6] A flowchart illustrating the flow of sensing processing in science fiction. [Modes for carrying out the invention]

[0009] In fifth-generation communication systems (5G systems), the use of 5G sensing, which uses the wireless signals of the 5G network to detect and understand the surrounding environment and the position and movement of objects, is being considered. By utilizing the characteristics of high frequency bands and high-speed communication, 5G sensing can accurately measure position and capture the movement of objects in real time.

[0010] 5G sensing can detect what objects exist around the user terminal (UE) performing the sensing. However, if it can estimate more detailed information about the user terminal's location, rather than just knowing what objects are around it, more advanced processing can be performed based on that information.

[0011] One aspect of the present disclosure is an information processing device that constitutes a wireless communication network, and has a processor that performs the steps of: acquiring a sensing request including a terminal ID of a user terminal; transmitting a sensing instruction to the user terminal; receiving sensing data from the user terminal; estimating attribute information of the user terminal based on the sensing data; and transmitting the attribute information to the source of the sensing request.

[0012] In one embodiment, the attribute information is the type of environment surrounding the user terminal, and may include categories such as indoor and outdoor. In another embodiment, the attribute information is the type of user terminal, and may include at least one of the categories such as automobile, pedestrian, bicycle, ship, aircraft, drone, and motorcycle.

[0013] Thus, according to this embodiment, sensing is performed on a user terminal (target UE) having a terminal ID included in the sensing request, and the surrounding environment and type category of the target UE can be determined based on the results of the target UE's observations of its surroundings.

[0014] In one aspect, the attribute information can be estimated based on at least any one of the moving speed obtained from the sensing data, the type of surrounding objects, the relative speed with the surrounding objects, and the relative distance with the surrounding objects. Also, in one aspect, the sensing request includes the location information of the target UE, and the attribute information may be estimated based on this location information.

[0015] In one aspect, it further includes the step of discovering a peripheral device which is a device located around the user terminal, the step of sending a sensing instruction to the peripheral device, and the step of receiving sensing data from the peripheral device. The attribute information of the user terminal may be estimated based on the sensing data by the user terminal and the sensing data by the peripheral device.

[0016] By further using the results sensed not only by the target UE itself but also by the devices around the target UE to estimate the attribute information of the target UE, more qualified estimation can be performed.

[0017] In one aspect, the peripheral device may be determined as a device having a moving speed or moving direction similar to that of the target UE, or as a device connected to the same base station as the target UE or capturing the same base station. Also, the peripheral device may be determined as a device with known location information and being stationary. The peripheral device may be a user terminal (UE) or a base station.

[0018] According to such a configuration, detailed information about the target UE can be detected.

[0019] Examples of wireless communication networks include systems utilizing 5G, 4G, LTE, LTE-A, SUPER 3G, IMT-Advanced, NR, and others, as well as next-generation systems extended based on these. Other examples of wireless communication networks include IEEE 802.11 (Wi-Fi®), IEEE 802.16 (WiMAX®), IEEE 802.20, UWB, Bluetooth®, and other systems, as well as next-generation systems extended based on these. A wireless communication network may be a system combining multiple systems. Furthermore, communication equipment may be a base station or a user terminal.

[0020] (Embodiment 1) Embodiments of the present disclosure will be described below with reference to the drawings. The following embodiments are merely illustrative for illustrative purposes, and the present disclosure is not limited to the configuration of these embodiments. For example, the following describes an example of applying the present disclosure to a fifth-generation mobile communication system, but the present disclosure may also be applied to fourth-generation or later generations of mobile communication systems. The present disclosure may also be applied to mobile communication systems defined by entities other than 3GPP, or to any wireless communication system or wired communication system other than a mobile communication system. Furthermore, it is assumed that the data provided and used by the user terminal is sensing data measured by the user terminal. However, the data provided and used may be sensing data measured by an entity other than the user terminal, or any data other than sensing data.

[0021] <Configuration of the information processing system> Figure 1 shows the components that make up the fifth-generation mobile communication system (5G network). In Figure 1, UE (User Equipment) 2 is the user's (subscriber's) terminal. RAN (Radio Access Network) 3 is the access network to the 5G core network (5GC). RAN3 is composed of base stations (gNB). The 5G network has a 5G core network (5GC) and an access network ((R)AN), and UE2, DN5, and AF12 are connected to the 5G network. Each of NF11a to NF11n is a function realized by one or more computers (information processing devices) executing a program. However, a single computer may realize two or more of NF11a to NF11n. Each of NF11a to NF11n can also be called a network node or network component.

[0022] 5GC is composed of a set of components that have predetermined functions called NFs (Network Functions). Figure 1 illustrates the following as NF11 that make up 5GC. In Figure 1, they are shown as thick rectangles.

[0023] UPF (User Plane Function) 11a AMF (Access and Mobility Management Function)11b SMF (Session Management Function)11c PCF(Policy Control Function)11d NEF(Network Exposure Function)11e NRF(Network Repository Function)11g NSSF(Network Slice Selection Function)11h AUSF(Authentication Server Function)11i UDM(Unified Data Management)11j NWDAF(Network Data Analytics Function)11k LMF(Location Management Function)11m SF (Sensing Function) 11n

[0024] UPF11a handles routing and forwarding of user packets (user plane packets sent and received by UE2), packet inspection, and QoS processing.

[0025] AMF11b is the UE location accommodation device in 5GC. AMF11b accommodates RAN3 and performs subscriber authentication control, UE2 location (mobility) management, etc.

[0026] SMF11c manages PDU (Protocol Data Unit) sessions and controls UPF11a for QoS (Quality of Service) control and policy control. A PDU session is a virtual communication channel for data exchange between UE2 and DN (Data Network) 5. DN5 is an external data network (such as the Internet) outside of 5GC.

[0027] PCF11d performs QoS control, policy control, and billing control under the control of SMF11c. QoS control involves controlling the quality of communication, such as prioritizing packet forwarding. Policy control involves communication control, such as QoS, packet forwarding eligibility, and billing, based on network or subscriber information.

[0028] The NEF11e acts as an intermediary for communication between external nodes and nodes within the control plane.

[0029] NRF11g stores and manages information on NFs (e.g., AMF, SMF, UPF, etc.) within 5GC. In response to an inquiry regarding an NF that the user wishes to use, NRF11g can return multiple candidate NFs to the inquirer.

[0030] NSSF11h has the function of selecting the network slice to be used by the subscriber from among the network slices generated by network slicing. A network slice is a virtual network with specifications tailored to its intended use.

[0031] AUSF11i is a subscriber authentication server that performs subscriber authentication under the control of AMF11b.

[0032] UDM11j maintains subscriber-related information and provides subscriber information, as well as retrieves, registers, deletes, and modifies the status of UE2.

[0033] The NWDAF11k has the function of collecting and analyzing data from each NF11, OAM terminal 8 (Figure 2), and external servers. It is an NF that provides network analysis information.

[0034] LMF11m has the ability to estimate the location of UEs that are registered with or accessing 5GC. LMF11m may also estimate the movement speed of UEs in addition to their location.

[0035] The SF11n performs sensing services, including collecting sensing information from UE2, RAN3 (base station (gNB)), or other nodes, and providing the collected sensing information to UE2 or other external systems (AF12, DN5, etc.). Details of the SF11n will be described later.

[0036] AF12 is an NF that provides application services via NRF11g as part of 5GC, or it is outside of 5GC and provides application services via NEF11e. AF12 is a NF that provides sensing results. For example, AF12 performs processing using sensing results. As an example, AF12 generates dynamic map information based on sensing results obtained from SF11n. Alternatively, UE2 or an application program executed on UE2 may operate as AF12.

[0037] In 5GC, multiple NFs of the same type may be provided. For example, NF11 may be provided for each data center (station). Also, one NF11 may be shared among multiple data centers. Furthermore, multiple NF11s of the same type may be configured within a single data center. The number of data centers, the number of NF11s, and the correspondence between NF11s and data centers can be set as appropriate.

[0038] <Configuration of information processing equipment and terminal> Figure 2 shows an example configuration of an information processing device that can operate as an NF11a-11k, an OAM terminal, and an external server, respectively. In Figure 3A, the information processing device 20 can be configured using a dedicated or general-purpose information processing device (computer) such as a personal computer (PC), workstation (WS), or server machine. However, the information processing device 20 may also be a collection of one or more computers (cloud).

[0039] The information processing device 20 includes a processor 21 acting as a processing unit or control unit (controller), a storage device 22, a communication interface 23 (communication IF 23), an input device 24, and a display 25, all interconnected via a bus 26.

[0040] The storage device 22 includes main memory and auxiliary storage. The main memory is used as at least one of the following: a program and data storage area, a program deployment area, a program work area, and a communication data buffer area. The main memory consists of RAM (Random Access Memory), or a combination of RAM and ROM (Read Only Memory). The auxiliary storage is used as a data and program storage area. Non-volatile storage media are used for the auxiliary storage. Non-volatile storage media include, for example, hard disks, solid state drives (SSDs), flash memory, or EEPROM (Electrically Erasable Programmable Read-Only Memory). The storage device 22 may also include a drive device for a disk recording medium.

[0041] Communication IF23 is a circuit that performs communication processing. For example, communication IF23 is a network interface card (NIC). Alternatively, communication IF23 may be a wireless communication circuit that performs wireless communication (such as 5G, wireless LAN (Wi-Fi®), BLE, etc.). Furthermore, the communication IF23 may be a combination of a circuit that processes wired communication and a wireless communication circuit.

[0042] The input device 24 includes keys, buttons, pointing devices, and touch panels, and is used for inputting information. The display 25 is, for example, a liquid crystal display and displays information and data.

[0043] The processor 21 performs various processes by executing various programs stored in the storage device 22. By the processor 21 executing the programs stored in the storage device 22, the information processing device 20 can operate as NF11a~11k, OAM terminal 8, and external servers 12a and 12b, respectively.

[0044] Figure 3 shows an example configuration of a communication device 30 that can operate as UE2, RAN3, or base station. The communication device 30 consists of a processor 31, a storage device 32, a communication interface 33 (communication IF33), an input device 34, and a data This includes a display 35. The processor 31, storage device 32, communication IF 33, input device 34, and display 35 can be the same as those used for the processor 21, storage device 22, communication IF 23, input device 24, and display 25. Therefore, their descriptions are omitted.

[0045] Processors 21 and 31 are, for example, Central Processing Units (CPUs). PU is also called Microprocessor Unit (MPU). Processors 21 and 31 are single The processor configuration may be single-processor or multi-processor. Furthermore, a single physical CPU connected via a single socket may have a multi-core configuration. Processors 21 and 31 may include various circuit configurations of arithmetic units, such as Digital Signal Processors (DSPs) or Graphics Processing Units (GPUs). Also, processors 21 and 31 may have configurations that interact with at least one of the following: integrated circuits (ICs), other digital circuits, and analog circuits. Integrated circuits include LSIs, Application Specific Integrated Circuits (ASICs), and Programmable Logic Devices (PLDs). This includes. PLDs include, for example, Field-Programmable Gate Arrays (FPGAs). The processors 21 and 31 also include, for example, what are called microcontrollers (MCUs), SoCs (System-on-a-chip), system LSIs, or chipsets.

[0046] <Overall sensing processing> Figure 4 shows the overall flow of sensing processing in a 5G system.

[0047] In step S0, UE2 and base station 3 register their sensing capabilities with SF11n or NRF11g. Sensing capabilities include information indicating what sensing can be performed by UE2 and base station 3.

[0048] In step S1, AF12 or LMF11m sends a sensing request to SF11n requesting sensing. The sensing request in this embodiment specifies a UE2 and requests the acquisition of attribute information including the type of the UE2 and / or the surrounding environment. Therefore, the sensing request includes at least identification information to identify the UE2. An example of identification information is the terminal ID (UE ID). Hereinafter, the UE2 having the terminal ID specified in the sensing request will also be referred to as the target UE. The sensing request may further include location information of the target UE. Note that here, an example is given where the source of the sensing request is AF12 or LMF11m, but the source of the sensing request may be any NF.

[0049] In step S2, the SF11n determines which UE2 or base station 3 will perform the requested sensing. The UE2 or base station 3 that performs the sensing process is referred to here as the sensing participant. Details of the sensing participant determination and discovery process will be described later.

[0050] In step S3, the SF11n sends a sensing instruction corresponding to the sensing request acquired in step S1 to the sensing participant determined in step S2. The generation and transmission of the sensing instruction will be explained in detail later.

[0051] In step S4, the sensing participant performs sensing according to the received sensing instruction. Specifically, they transmit radio waves used for 5G communication and receive the reflected, diffracted, or scattered radio waves. In addition to using radio waves for 5G communication, the sensing process may also be performed using other sensors such as cameras, ultrasonic sensors, millimeter-wave radar, or LiDAR.

[0052] In step S5, the sensing participant sends sensing data to the SF11n. In step S6, SF11n performs data processing on the acquired sensing data to estimate attribute information including the type of target UE and / or the surrounding environment. Details of the attribute information and the method of estimation will be described later. In step S11n, the attribute information of the target UE is transmitted as a sensing result to AF12 or LMF11m, the source of the sensing request.

[0053] <SF(Sensing Function)> Figure 5 is a block diagram showing the functional configuration of SF50(11n). SF50 includes, as its functional units, a sensing request acquisition unit 51, a sensing participant discovery unit 52, a sensing instruction transmission unit 55, a sensing data reception unit 56, a data processing unit 57, and a sensing result transmission unit 58. These functional units are implemented by the processor of the information processing device 20.

[0054] The sensing request acquisition unit 51 acquires sensing requests from AF12, LMF11m, or other NFs. The sensing participant discovery unit 52 determines and discovers the sensing participants to perform sensing. The sensing instruction transmission unit 55 generates sensing instructions according to the sensing task and transmits them to the sensing participants. The sensing data reception unit 56 receives sensing data from the sensing participants. The data processing unit 57 estimates the attribute information of the target UE based on the received sensing data and generates sensing results. The sensing result transmission unit 58 transmits the generated sensing results to AF12 or other NFs that sent the sensing request.

[0055] Figure 6 is a flowchart showing the sensing process performed by the SF50.

[0056] In step S61, the sensing request acquisition unit 51 acquires a sensing request from AF12, LMF11m, or another NF. The processing in step S61 corresponds to the processing in step S1 in Figure 2. The sensing request includes the identification information of the target UE (e.g., UE ID) and its location information.

[0057] In step S62, the sensing participant discovery unit 52 determines and discovers sensing participants to perform the requested sensing. The process in step S62 corresponds to the process in step S2 in Figure 2. The sensing participant discovery unit 52 determines the target UE and UEs or base stations located around the target UE (hereinafter also referred to as peripheral devices) as sensing participants. Sensing by the target UE is performed to detect the surrounding environment of the target UE from the viewpoint of the target UE. Sensing by peripheral devices is performed to detect the target UE or its surrounding environment from viewpoints around the target UE.

[0058] The discovery of the target UE includes a process of identifying the base station 3 to which the target UE is connected, based on the identification information of the target UE included in the sensing request.

[0059] The detection of peripheral devices involves identifying UEs or base stations whose distance from the target UE is within a distance threshold, based on the location information of the target UE included in the sensing request. Alternatively, peripheral devices may be determined as UEs connected to or detecting the same base station as the target UE. Furthermore, peripheral devices may be determined if they satisfy the following conditions: their moving speed is within a speed threshold, and / or their moving direction is within a direction threshold, compared to the target UE's moving direction. Such determination is useful when the target UE is moving quickly, and by selecting UEs with similar moving speeds and / or directions as sensing participants, continuous sensing from a close distance is possible. There may be one or more peripheral devices. At least one of the peripheral devices may be a stationary device with a known location. For example, base stations and roadside units (RSUs) fall into this category. By selecting a stationary device as a sensing participant in this way, the absolute position of the target UE can be determined from the relative distance and direction to the stationary device. The position is determined, and the absolute velocity of the target UE can be determined from its relative velocity with respect to the stationary device.

[0060] In step S63, the sensing instruction transmission unit 55 generates sensing instruction data based on the sensing request and transmits it to the sensing participant. The processing in step S63 corresponds to the processing in step S3 in Figure 2.

[0061] In step S64, the sensing data receiving unit 56 receives sensing data from the sensing participant. The processing in step S64 corresponds to the processing in step S5 in Figure 2.

[0062] In step S65, the data processing unit 57 estimates attribute information, including the type of target UE and / or the surrounding environment, from the obtained sensing data and the location information of the target UE included in the sensing request. The attribute information can be estimated based on at least one of the following: the movement speed of the target UE obtained from the sensing data, the type of surrounding objects of the target UE, the relative distance between the surrounding objects and the target UE, and the location information of the target UE included in the sensing request. In this embodiment, the attribute information is assumed to be obtained as category information. The attribute information and its estimation method will be described below.

[0063] One example of attribute information is the type of the target UE. Possible UE types include the types of objects on which the target UE is mounted or possessed, such as automobiles, pedestrians, bicycles, ships, aircraft, and drones. The object types listed here are merely examples, and other object types may be used. For example, a movement speed of approximately 5 km / h can be identified as a pedestrian, approximately 10 km / h as a bicycle, and 30 km / h or more as an automobile. Similarly, identification can be based on the relative velocity between the target UE and surrounding objects, or on location information or movement speed change patterns. Such object types can also be determined by considering the types of objects present around the target UE, which are obtained from sensing data. Furthermore, such identification can also be performed using machine learning models. A machine learning model, for example, is a neural network, which is trained to identify the type of the target UE from sensing data, using sensing data of known UEs or surrounding UEs as training data. Additionally, UE types may include ships, aircraft, drones, and motorcycles. These types can also be determined in the same way as above, based on the movement speed of the target UE, the type of objects surrounding the target UE, and their relative velocities. Furthermore, if the target UE may fall into multiple types, the UE type may include multiple types. In this case, a confidence level may be included for each type. In addition, if the UE type cannot be determined with a confidence level above a certain level, the UE type may be set to "undeterminable".

[0064] Another example of attribute information is the type of surrounding environment of the target UE. Examples of surrounding environment types include indoor and outdoor. For example, whether an environment is indoors or outdoors can be determined based on the type of surrounding objects and their relative distance. Alternatively, the location of the target UE can be determined based on whether the base station it is tracking is installed indoors or outdoors. Specific examples of surrounding environments are not limited to indoors and outdoors; they could include categories such as urban pedestrian areas, highways, commercial facilities, or parks. The surrounding environment can be estimated by considering either or both of the sensing data and the location information included in the sensing request. Furthermore, if the surrounding environment cannot be determined with a certain level of confidence or higher, the type of surrounding environment may be set to "undeterminable."

[0065] Another example of attribute information is a combination of the target UE type and the surrounding environment type. Examples of such attribute information include, for example, moving indoors, stationary indoors, or moving in a vehicle.

[0066] In step S66, the sensing result transmission unit 58 transmits the estimated attribute information of the target UE as the sensing result to the requester of the sensing request. The processing in step S66 corresponds to the processing in step S7 in Figure 2. The sensing result may consist only of the attribute information of the target UE, or it may include other information about the target UE, or information about objects in the vicinity of the target UE.

[0067] <Advantageous effects of this embodiment> According to this embodiment, by combining the sensing results of the target UE's surroundings by the target UE itself with the sensing results of the target UE's peripheral devices, attribute information such as the type of target UE and its surrounding environment can be estimated in more detail and with greater accuracy. When the attribute information of the target UE can be estimated, it becomes possible to provide more appropriate services according to the status of the target UE.

[0068] <Other variations> The embodiments described above are merely examples, and this disclosure may be modified as appropriate without departing from its essence.

[0069] In the above explanation, both the target UE and its surrounding devices are selected as sensing participants, but the sensing participants may be the target UE alone or the surrounding devices alone. Combining the sensing by the target UE with the sensing of the target UE by the surrounding devices allows for a more accurate estimation of the target UE's attributes, but it is also possible to estimate the target UE's attributes from the sensing results of only one of them.

[0070] Furthermore, while the SF11n obtains attribute information for the target UE, the SF11n may also send sensing data obtained from sensing participants, or data partially processed from said sensing data, to the AF12 or LMF11m, which is the source of the sensing request, to obtain attribute information for the target UE at the source of the sensing request. Alternatively, an NF different from the SF11n and the source of the sensing request, such as NWDAF11k, may obtain attribute information for the target UE based on data from the SF11n and notify the source of the sensing request of the determination result via the SF11n or directly.

[0071] The present disclosure can also be realized by supplying a computer program implementing the functions described in the embodiments above to a computer, and having one or more processors in the computer read and execute the program. Such a computer program may be provided to the computer by a non-temporary computer-readable storage medium that can be connected to the computer's system bus, or it may be provided to the computer via a network. Non-temporary computer-readable storage mediums include, for example, any type of disk such as magnetic disks (floppy disks, hard disk drives (HDDs), etc.), optical disks (CD-ROMs, DVDs, Blu-ray discs, etc.), read-only memory (ROM), random access memory (RAM), EPROM, EEPROM, magnetic cards, flash memory, optical cards, and any type of medium suitable for storing electronic instructions. [Explanation of Symbols]

[0072] 2: User Terminal (UE), 3: RAN 11n: SF (Sensing Function)

Claims

1. An information processing device that constitutes a wireless communication network, The steps include sending sensing instructions to the user terminal, The steps include receiving sensing data from the user terminal, The steps include: estimating attribute information of the user terminal based on the sensing data; An information processing device having a processor that performs the following.

2. The processor performs the step of obtaining a sensing request that includes the identification information of the user terminal. In response to receiving the sensing request, the sensing instruction is transmitted to the user terminal. The information processing apparatus according to feature 1.

3. The processor further performs the step of transmitting the attribute information to the requester of the sensing request. The information processing apparatus according to feature 2.

4. The attribute information is the type of the surrounding environment of the user terminal. The information processing apparatus according to feature 1.

5. The aforementioned types of surrounding environments include indoors and outdoors. The information processing apparatus according to feature 4.

6. The attribute information is the type of the user terminal, The information processing apparatus according to feature 1.

7. The type of user terminal includes at least one of the following: automobile, pedestrian, bicycle, ship, aircraft, drone, and motorcycle. The information processing apparatus according to feature 6.

8. The attribute information is estimated based on at least one of the following: the moving speed, the type of surrounding object, the relative speed to the surrounding object, and the relative distance to the surrounding object, which are obtained from the sensing data. The information processing apparatus according to feature 1.

9. The sensing instruction is generated based on a sensing request that includes the user terminal's identification information and location information. The aforementioned attribute information is further estimated based on the aforementioned location information. The information processing apparatus according to feature 8.

10. A step of discovering a peripheral device which is a device located around the user terminal, The steps include transmitting a sensing instruction to the peripheral device, The steps include receiving sensing data from the aforementioned peripheral device, It further includes, The attribute information of the user terminal is estimated based on sensing data from the user terminal and sensing data from the peripheral device. The information processing apparatus according to feature 1.

11. The peripheral device is located around the user terminal's location information and the user terminal's movement speed It is a device having a moving speed such that the difference from the degree is within a speed threshold. The information processing apparatus according to feature 10.

12. The peripheral device is located around the user terminal's location information and has a movement direction in which the difference from the user terminal's movement direction is within a direction threshold. The information processing apparatus according to feature 10.

13. The peripheral device is a device that is connected to or has acquired the same base station as the user terminal. The information processing apparatus according to feature 10.

14. The aforementioned peripheral device is a stationary device whose location information is known. The information processing apparatus according to feature 10.

15. The aforementioned peripheral device is a user terminal or a base station. The information processing apparatus according to feature 10.

16. A user terminal, The steps include receiving a sensing instruction from an information processing device constituting a wireless network to identify attribute information of the user terminal, The steps include: performing sensing based on the sensing instruction; The steps include transmitting the sensing data acquired by the sensing to the information processing device, A user terminal having a processor that executes [the specified program / function].

17. An information processing method performed by an information processing device that constitutes a wireless communication network, The steps include obtaining a sensing request that includes user terminal identification information, The steps include sending a sensing instruction to the user terminal, The steps include receiving sensing data from the user terminal, The steps include: estimating attribute information of the user terminal based on the sensing data; The steps include transmitting the attribute information to the source of the sensing request, Information processing methods, including those mentioned above.

18. A method performed by the user terminal, The steps include receiving a sensing instruction from an information processing device constituting a wireless network to identify attribute information of the user terminal, The steps include: performing sensing based on the sensing instruction; The steps include transmitting the sensing data acquired by the sensing to the information processing device, Methods that include...

19. A computer program for causing a computer to perform each step of the method according to claim 17 or 18.

20. A computer-readable medium storing a computer program for causing a computer to perform each step of the method according to claim 17 or 18.

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