Information processing device, communication device, information processing method, communication method, and communication system

Abstract

An information processing device according to the present invention can perform processing related to first communication that transmits source data as information that can be restored to the same form on a reception side and second communication that transmits all or a portion of information that has been extracted from the source data using an artificial intelligence (AI) / machine learning (ML) model to the reception side. The information processing device comprises a determination unit that determines a format for a protocol stack for the second communication and a transmission unit that transmits information about the determined format to one or a plurality of communication devices that support the first communication and the second communication.

Description

Information processing device, communication device, information processing method, communication method, and communication system

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

[0002] Various communication technologies (communication methods / communication formats) related to mobile communication systems (e.g., cellular communication systems such as 5G) have emerged. For example, in recent years, a new communication technology called semantic communication has emerged. Semantic communication is a communication method that transmits only the meaning of source data. The introduction of semantic communication makes it possible to provide high-quality communication services.

[0003] Qiao Lan; Dingzhu Wen; Zezhong Zhang; Qunsong Zeng;

[0004] However, the emergence of a new communication technology (communication method / communication format) does not necessarily mean that users or communication devices will be able to enjoy high-quality communication services. For example, even if semantic communication becomes applicable to a mobile communication system (e.g., a cellular communication system), unless semantic communication is introduced into the mobile communication system in a form suitable for the user or the communication device, the user or the communication device will not be able to enjoy high-quality communication services.

[0005] Therefore, the present disclosure proposes an information processing device, a communication device, an information processing method, a communication method, and a communication system that can provide high-quality communication services.

[0006] 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.

[0007] In order to solve the above problems, one form of information processing device according to the present disclosure is an information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form at the receiving side, and a second communication that propagates some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving side, and is equipped with a determination unit that determines the form of a protocol stack for the second communication, and a transmission unit that transmits information regarding the determined form to one or more communication devices that support the first communication and the second communication.

[0008] 1 is a diagram for explaining first communication. FIG. 1 is a diagram for explaining second communication. FIG. 2 is a diagram for explaining an example of a protocol stack configuration for the first communication. FIG. 3 is a diagram for explaining an example of a protocol stack configuration for the second communication. FIG. 4 is a diagram for explaining an example of a protocol stack configuration for the second communication. FIG. 5 is a diagram for explaining a configuration of a communication system according to the present embodiment. FIG. 6 is a diagram for explaining a configuration example of a server according to an embodiment of the present disclosure. FIG. 7 is a diagram for explaining a management device according to the present embodiment. FIG. 8 is a diagram for explaining a configuration of a base station according to the present embodiment. FIG. 9 is a diagram for explaining a terminal device according to the present embodiment. FIG. 10 is a diagram for explaining a configuration example of a 5GS architecture. FIG. 11 is a diagram for explaining a neural network model. FIG. 12 is a diagram for explaining a protocol stack of a conventional user plane in radio access. FIG. 13 is a diagram for explaining a neural network model. FIG. 14 is a diagram for explaining a neural network model. FIG. 15 is a diagram for explaining a neural network model. FIG. 16 is a diagram for explaining a neural network model. FIG. 17 is a diagram for explaining a neural network model. FIG. 18 is a diagram for explaining a neural network model. FIG. 19 is a diagram for explaining a neural network model. FIG. 20 is a diagram for explaining a neural network model. FIG. 10 is a flowchart illustrating an example of a decision process according to a second embodiment. FIG. 11 is a sequence diagram illustrating an example of a handover process according to a third embodiment. FIG. 12 is a sequence diagram illustrating an example of a handover process according to the third embodiment. FIG. 13 is a diagram illustrating an example of a configuration of a deep neural network model to be divided. FIG. 14 is a diagram illustrating an example of a propagation channel and a conversion process for a divided model. FIG. 15 is a diagram illustrating another example of a propagation channel and a conversion process for a divided model. FIG. 16 is a diagram illustrating an example of a mapping process of nodes and antenna ports. FIG. 17 is a diagram illustrating an example of information on propagation channels for frequencies.

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the following embodiments, the same components are designated by the same reference numerals, and redundant description will be omitted.

[0010] Additionally, in this description / specification, the phrase "at least one of" following a list of elements is understood to mean that the listed elements are optional. For example, "at least one of A, B, and C" means "(A), (B), (C), (A and B), (A and C), (B and C), or (A, B, and C)." "At least one of A, B, or C" and "at least one of A, B, and / or C" are similar to "at least one of A, B, and C." Here, A, B, and C are all arbitrary expressions (e.g., words, phrases, clauses, terms, or items).

[0011] In addition, in this specification and drawings, multiple components having substantially the same functional configuration may be distinguished by adding different numbers to the same reference numeral. For example, multiple components having substantially the same functional configuration may be distinguished by adding different numbers to the same reference numerals to the terminal device 40 as needed. １ , 40 ２ , and 40 ３ However, when there is no need to particularly distinguish between multiple components having substantially the same functional configuration, only the same reference numerals are used. For example, the terminal device 40 １ , 40 ２ , and 40 ３ When there is no need to particularly distinguish between them, they will be simply referred to as terminal devices 40.

[0012] One or more embodiments (including examples and variations) 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 one another. Therefore, these embodiments may contribute to solving different purposes or problems and may produce different effects.

[0013] The present disclosure will be described in the following order: 1. Overview 2. Configuration of a communication system 2-1. Server configuration 2-2. Management device configuration 2-3. Base station configuration 2-4. Terminal device configuration 3. Technologies applied to a communication system 3-1. 5GS network architecture 3-2. Network slice 3-3. Session establishment process 3-4. Flow-based QoS control 3-5. AI / ML model 3-6. Semantic communication 4. Operational examples of a communication system 4-1. First example 4-2. Second example 4-3. Third example 4-4. Fourth example 5. Modification 6. Conclusion

[0014] <<1. Overview>> The first standard for the fifth-generation mobile communications system (so-called 5G) was formulated as Rel-15 in 2018. 5G is a wireless access technology that can support a variety of use cases, including eMBB (Enhanced Mobile Broadband), mMTC (Massive Machine Type Communications), and URLLC (Ultra-Reliable and Low Latency Communications).

[0015] The fifth generation mobile communication system enables wireless communication with high communication performance (e.g., connection stability, low latency, high reliability, high throughput, power saving, or low processing load). Wireless communication with high communication performance allows users or communication devices (e.g., terminal devices) to enjoy high-quality communication services. For example, a terminal device can receive large amounts of data at high speed from a transmitting communication device. Alternatively, a terminal device can perform real-time communication (e.g., real-time communication in VR games, the metaverse, or video conferencing) with low latency.

[0016] However, with conventional technologies, it may be difficult to provide high-quality communication services to communication devices in some cases. For example, with conventional communication methods used in conventional mobile communication systems such as 5G, communication devices in low SNR environments can only enjoy lower-quality communication services (e.g., slower communication services or communication services with longer delays) than communication devices in high SNR environments. Here, SNR refers to the signal-to-noise ratio.

[0017] A conventional communication technique is, for example, a communication method that propagates data so that source data (hereinafter simply referred to as source data) can be restored in the same form on the receiving side. In the following description, this communication may be referred to as conventional communication. The source data is, for example, data that is the source of data that is actually transmitted using a communication path. The source data may be, for example, data generated by an application (for example, data before input into an AI / ML model described below). The source data may also be referred to as original data.

[0018] Various communication technologies (communication methods / communication formats) related to mobile communication systems (e.g., cellular communication systems such as 5G) have emerged. For example, in recent years, a new communication technology called semantic communication has emerged. Semantic communication is communication that transmits only the meaning of source data. The introduction of semantic communication makes it possible to provide high-quality communication services to users or communication devices. For example, the introduction of semantic communication makes it possible to provide communication services with better communication quality at the application level than communication services using conventional communication, even in a low SNR environment.

[0019] However, the emergence of a new communication technology (communication method / communication format) does not necessarily mean that users or communication devices will be able to enjoy high-quality communication services. For example, even if semantic communication becomes applicable to a mobile communication system (e.g., a cellular communication system), unless semantic communication is introduced into the mobile communication system in a form suitable for the user or the communication device, the user or the communication device will not be able to enjoy high-quality communication services.

[0020] For example, Non-Patent Document 1 ("What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence") discloses that possible forms of semantic communication include a form that utilizes a wireless layer of a conventional communication system (e.g., a mobile communication system before 5G) and a form using joint source-channel coding / decoding that integrates source coding / decoding and channel coding / decoding. For example, in mobile communication systems of generations after 6G (or B5G) in which 5G is expected to be mixed, the issue is how to introduce a new communication technology such as semantic communication so that users or communication devices can enjoy high-quality communication services.

[0021] Therefore, in this embodiment, the above problem is solved as follows.

[0022] 1 to 5 are diagrams for explaining an overview of the present embodiment. The communication system of the present embodiment is, for example, a mobile communication system. For example, the communication system of the present embodiment is a cellular communication system such as 5G.

[0023] The communication system of this embodiment includes multiple information processing devices (multiple communication devices). For example, the communication system of this embodiment includes a device belonging to a core network, a base station, and a terminal device. The device belonging to the core network is, for example, a device (e.g., a management device 20 described below) that implements network functions that constitute the core network. Note that the devices that belong to the core network may also include base stations. In the following description, the device that implements network functions that constitute the core network may simply be referred to as the core network.

[0024] The communication system of this embodiment supports at least a communication (hereinafter referred to as a first communication) that propagates information (data) so that source data can be restored in the same form at the receiving end, and a communication (hereinafter referred to as a second communication) that propagates part or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving end. For example, at least one of a plurality of information processing devices included in the communication system (in the examples of FIGS. 1 and 2, at least one of a terminal device, a base station, and a core network) is capable of processing the first communication and the second communication.

[0025] Here, the first communication is, for example, conventional communication provided by a conventional mobile communication system (e.g., a mobile communication system prior to fifth generation). The second communication is, for example, semantic communication. The first communication can be rephrased as a first communication form, a first communication means, or a first communication method. Similarly, the second communication can be rephrased as a second communication form, a second communication means, or a second communication method.

[0026] 1 is a diagram illustrating the first communication. For example, when using the first communication, a terminal device transmits data to a receiving communication device (a base station in the example of FIG. 1) so that the receiving communication device can restore the source data in the same form. Note that in the example of FIG. 1, the terminal device is the transmitting communication device and the base station is the receiving communication device, but the base station may also be the transmitting communication device and the terminal device may also be the receiving communication device.

[0027] FIG. 2 is a diagram for explaining the second communication. When using the second communication, the terminal device and the base station acquire information related to the settings for the second communication, for example, from a core network. Then, the terminal device and the base station perform settings to set the communication they use as the second communication. Here, the information related to the settings for the second communication may include information related to an AI / ML model for the second communication (the first AI / ML model shown in FIG. 2). Then, the terminal device performs settings for the first AI / ML model based on the information related to the AI / ML model. Furthermore, the base station performs settings for the second AI / ML model based on the information related to the AI / ML model.

[0028] The first AI / ML model may be an AI / ML model for extracting data for second communication (semantic data in the example of FIG. 2) from source data. The second AI / ML model may be an AI / ML model for generating data to be used in predetermined processing from data transmitted by the second communication. For example, the second AI / ML model may be an AI / ML model for generating data to be passed to an application from data transmitted by semantic communication.

[0029] The terminal device then uses the first AI / ML model to calculate data for the second communication (semantic data in the example of FIG. 2 ) from the source data. For example, the terminal device inputs the source data into the input layer of the first AI / ML model, thereby acquiring the semantic data from the output layer of the first AI / ML model. The terminal device then transmits the data for the second communication to a receiving communication device (e.g., a base station). The receiving communication device uses the second AI / ML model to calculate data to be used in a predetermined process from the data for the second communication. The predetermined process may be transfer to another communication device or processing in its own application.

[0030] In the example of FIG. 2 , the terminal device is the transmitting communication device and the base station is the receiving communication device. However, the base station may be the transmitting communication device and the terminal device may be the receiving communication device. In this case, the terminal device may configure a second AI / ML model based on information related to the AI / ML model. Also, the base station may configure a first AI / ML model based on information related to the AI / ML model. Then, the base station calculates data for the second communication (semantic data in the example of FIG. 2 ) from the source data using the first AI / ML model. Then, the base station transmits the data for the second communication to the terminal device. The base station calculates data to be used in predetermined processing from the data for the second communication using the second AI / ML model.

[0031] In the communication system of this embodiment, the protocol stack configuration for the second communication is determined by, for example, at least one of a plurality of information processing devices included in the communication system (in the example of FIGS. 1 and 2, at least one of the terminal device, the base station, and the core network).

[0032] Below, we will explain the form of the protocol stack for the first communication and the form of the protocol stack for the second communication. In the following explanation, the communication device on the sending side will be referred to as the transmitting device, and the communication device on the receiving side will be referred to as the receiving device. The transmitting device may be a base station or a terminal device. Also, the receiving device may be a base station or a terminal device.

[0033] Fig. 3 is a diagram showing an example of a protocol stack configuration for the first communication. Fig. 3 shows the configuration of a protocol stack of a conventional communication system (e.g., a pre-5G mobile communication system). In the example of Fig. 3, the transmitting device includes an application layer and a first encoding unit. Also, in the example of Fig. 3, the receiving device includes an application layer and a first decoding unit. The first encoding unit and the first decoding unit are each a radio access layer of the conventional communication system (e.g., a pre-5G mobile communication system).

[0034] FIG. 4 is a diagram showing an example of a protocol stack configuration for the second communication. FIG. 4 shows a configuration utilizing a radio layer of a conventional communication system (e.g., a pre-5G mobile communication system). More specifically, FIG. 4 shows a configuration utilizing encoding or decoding processing for the first communication (hereinafter referred to as the first configuration). In the example of FIG. 4, the transmitting device includes an application layer, a pre-encoding unit, and a first encoding unit. Also, in the example of FIG. 4, the receiving device includes a first decoding unit, a post-decoding unit, and an application layer. The first encoding unit and the first decoding unit are each the radio access layer of a conventional communication system (e.g., a pre-5G mobile communication system).

[0035] In the first embodiment, to enable second communication using a conventional communication system, data output from the application layer is subjected to processing related to semantic communication (hereinafter also referred to as pre-encoding or pre-encoding processing) in a pre-encoding unit before being input to the first encoding unit. The pre-encoding processing may be performed within the application layer. Here, the pre-encoding processing may be, for example, processing to extract meaning from transmission data generated by an application. The pre-encoding processing may be performed using an AI / ML model. Here, the pre-encoding processing may be processing similar to processing performed using the first AI / ML model described above.

[0036] Furthermore, in the first embodiment, to enable the second communication, data received from the transmitting device (semantic data shown in FIG. 4 ) undergoes processing related to semantic communication (hereinafter also referred to as post-decoding or post-decoding processing) in a post-decoding unit before being input to the application layer. The post-decoding processing may be performed within the application layer. Here, the post-decoding processing may be, for example, processing to convert received data (semantic level data) into data in a format usable by an application. The post-decoding processing may be performed using an AI / ML model. Here, the post-decoding processing may be processing similar to processing performed using the second AI / ML model described above.

[0037] FIG. 5 is a diagram illustrating an example of a protocol stack configuration for the second communication. FIG. 5 illustrates a configuration (hereinafter referred to as a second configuration) that utilizes integrated source channel encoding and / or integrated source channel decoding for the second communication as an example of a protocol stack configuration for the second communication. In the example of FIG. 5, the transmitting device includes an application layer and a second encoding unit. Also, in the example of FIG. 5, the receiving device includes an application layer and a second decoding unit. In the second configuration, at least one AI / ML model may be configured between the second encoding unit of the transmitting device and the second decoding unit of the receiving device. Here, the second encoding unit may be the first AI / ML model described above, and the second decoding unit may be the second AI / ML model described above.

[0038] The information processing device determines a configuration selected from a plurality of configurations for the second communication as a configuration of the protocol stack for the second communication. For example, the information processing device determines one configuration selected from a plurality of configurations including at least a first configuration and a second configuration as a configuration of the protocol stack for the second communication. The information processing device transmits information regarding the setting of the determined configuration to one or more communication devices that support the first communication and the second communication. The communication devices may be base stations or terminal devices.

[0039] The communication device sets the configuration of the protocol stack for the second communication based on the information regarding the configuration setting.

[0040] For example, if the information on the mode indicates a first mode, the communication device selects a first encoding unit / first decoding unit as a communication processing unit for the second communication, and configures a pre-encoding unit that performs pre-encoding for transmission or a post-decoding unit that performs post-decoding for reception. On the other hand, if the information on the mode indicates a second mode, the communication device selects a second encoding unit / second decoding unit as a communication processing unit for the second communication.

[0041] As a result, the communication system of the present embodiment can selectively use different forms of semantic communication depending on the situation. For example, the communication system of the present embodiment can selectively use a first form that realizes the second communication using a wireless layer of a conventional communication system and a second form that uses a newly prepared layer for the second communication depending on the capability of the communication device. As a result, the communication system can provide semantic communication in a form suitable for a user or a communication device, thereby providing a high-quality communication service (e.g., communication with little delay) to the user or the communication device.

[0042] The outline of this embodiment has been described above, and the communication system 1 of this embodiment will now be described in detail.

[0043] <<2. Configuration of the Communication System>> First, the configuration of the communication system 1 will be described. Fig. 6 is a diagram showing the configuration of the communication system 1 according to this embodiment. The communication system 1 includes a server 10, a management device 20, a base station 30, and a terminal device 40. The communication system 1 provides users with a wireless network (mobile network) that enables mobile communication by having the wireless communication devices that make up the communication system 1 operate in cooperation with each other.

[0044] The wireless network of this embodiment may be, for example, a cellular network configured of a radio access network RAN ​​and a core network CN. The mobile network may include a terminal device 40. In this embodiment, a wireless communication device is a device having a wireless communication function, and in the example of Fig. 6, this corresponds to the base station 30 and the terminal device 40.

[0045] The communication system 1 may include a plurality of servers 10, a plurality of management devices 20, a plurality of base stations 30, and a plurality of terminal devices 40. In the example of FIG. 6, the communication system 1 includes a plurality of servers 10. １ and server 10 ２ The management device 20 includes the management device 20 １ and management device 20 ２ The communication system 1 also includes a base station 30. １, base station 30 ２ , and base station 30 ３ The terminal device 40 is provided with the terminal device 40 １ , terminal device 40 ２ , and terminal device 40 ３ In the following description, the devices included in the communication system 1 may be referred to as network devices.

[0046] The terminal device 40 may be configured to connect to a network using radio access technologies (RATs) such as LTE (Long Term Evolution), NR (New Radio), B5G (Beyond 5G), 6G, Wi-Fi, Bluetooth (registered trademark), etc. In this case, the terminal device 40 may be configured to be able to use different radio access technologies (wireless communication methods). For example, the terminal device 40 may be configured to be able to use NR and Wi-Fi. Furthermore, the terminal device 40 may be configured to be able to use different cellular communication technologies (e.g., LTE, NR, B5G, or 6G). In the following description, the terminal device 40 may be referred to as UE (User Equipment) 40.

[0047] LTE and NR are types of cellular communication technologies that enable mobile communication for terminal devices by arranging multiple areas covered by base stations in the form of cells. 6G, also a type of cellular communication technology, has the potential to become a technology that enables mobile communication for terminal devices by arranging multiple areas covered by base stations in the form of cells.

[0048] In the following description, "LTE" includes LTE-A (LTE-Advanced), LTE-A Pro (LTE-Advanced Pro), and EUTRA (Evolved Universal Terrestrial Radio Access). NR includes NRAT (New Radio Access Technology) and FEUTRA (Further EUTRA). A single base station 30 may manage multiple cells. In the following description, a cell corresponding to LTE is referred to as an LTE cell, and a cell corresponding to NR is referred to as an NR cell.

[0049] NR is the next generation (5th generation) radio access technology after LTE (4th generation communications including LTE-Advanced and LTE-Advanced Pro). NR is a radio access technology that can support various use cases, including eMBB (Enhanced Mobile Broadband), mMTC (Massive Machine Type Communications), and URLLC (Ultra-Reliable and Low Latency Communications). NR was standardized in 3GPP (registered trademark) Rel-15 as a technical framework that corresponds to the usage scenarios, requirements, and deployment scenarios of these use cases. Furthermore, B5G and 6G require the simultaneous realization of multiple axes of high speed, large capacity, low latency, high reliability, and multiple simultaneous connections.

[0050] 6G is the next generation of cellular communications technology, following NR and 5GS (5G system), which are fifth-generation mobile communications. 6G includes radio access technology and network technologies between base stations, core networks, and data networks. 6G also includes technologies for the enhancement of eMBB, mMTC, and URLLC (extreme connectivity), which were the main use cases or requirements of NR. 6G also includes new technologies in new areas. For example, 6G may include technologies related to AI (cognitive network, AI native air interface), sensing (including radar / RF sensing and network as a sensor), and terahertz communications.

[0051] The wireless network described above or below may correspond to at least one of radio access technologies (RATs) such as LTE, NR, B5G, and 6G. LTE, NR, and 6G are types of cellular communication technologies that enable mobile communication for terminal devices by arranging multiple areas covered by base stations in the form of cells. The wireless access method used by the communication system 1 is not limited to LTE, NR, B5G, and 6G, and may be other wireless access methods such as W-CDMA (Wideband Code Division Multiple Access) and cdma2000 (Code Division Multiple Access 2000).

[0052] Furthermore, the base station 30 may be a terrestrial station or a non-terrestrial station. The non-terrestrial station may be a satellite station or an aircraft station. If the non-terrestrial station is a satellite station, the wireless network may be a bent-pipe (transparent) type mobile satellite communication system.

[0053] In this embodiment, terrestrial stations and terrestrial base stations refer to base stations and relay stations installed on the ground. Here, "terrestrial" refers to terrestrial in a broad sense, including not only land but also underground, on water, and underwater. In the following description, the term "terrestrial station" may be replaced with "gateway."

[0054] Note that an LTE base station may be referred to as an eNodeB (Evolved Node B) or eNB. An NR base station may be referred to as a gNodeB or gNB. A 6G base station may be referred to as a 6G NodeB (6GNB). In LTE, NR, and 6G, a terminal device (also referred to as a mobile station or terminal) may be referred to as a UE (User Equipment). Note that a terminal device is a type of communication device and is also referred to as a mobile station or terminal.

[0055] The terminal device 40 may be able to connect to a network using a wireless access technology (wireless communication method) other than LTE, NR, B5G, 6G, Wi-Fi, or Bluetooth. For example, the terminal device 40 may be able to connect to a network using low power wide area (LPWA) communication. The terminal device 40 may also be able to connect to a network using proprietary wireless communication.

[0056] Here, LPWA communication refers to wireless communication that enables low-power, wide-area communication. For example, LPWA wireless refers to IoT (Internet of Things) wireless communication using a specific low-power radio (e.g., the 920 MHz band) or the ISM (Industry-Science-Medical) band. LPWA wireless may include LTE-M, which operates in the cellular frequency band, and / or C-IoT (Cellular IoT), represented by NB-IoT. The LPWA communication used by the terminal device 40 may conform to the LPWA standard. The LPWA standard may be, for example, at least one of ELTRES, ZETA, SIGFOX, LoRaWAN, LTE-M, and NB-IoT. Of course, the LPWA standard is not limited to these and may be another LPWA standard.

[0057] Each wireless communication device shown in Fig. 6 may be considered as a device in a logical sense, i.e., a part of each wireless communication device may be realized by a virtual machine (VM), a container such as Docker, or the like, and these may be physically implemented on the same hardware.

[0058] In this embodiment, the concept of a wireless communication device includes not only portable mobile devices (terminal devices) such as mobile terminals, but also devices installed in structures or mobile bodies. The structures or mobile bodies themselves may be considered wireless communication devices. Furthermore, the concept of a wireless communication device includes not only terminal devices 40 but also base stations 30. A wireless communication device is a type of processing device or information processing device. A wireless communication device can also be referred to as a transmitting device or a receiving device.

[0059] Below, we will explain in detail the configuration of each wireless communication device that makes up the communication system 1. Note that the configuration of each wireless communication device shown below is merely an example. The configuration of each wireless communication device may be different from the configuration shown below.

[0060] <2-1. Server Configuration> First, the configuration of the server 10 will be described.

[0061] The server 10 is an information processing device (computer) that provides various services to the terminal device 40. For example, the server 10 is an XR server that distributes XR content (XR media) such as XR video content to the terminal device 40. The server 10 is, for example, an application server (AS). In the following description, the server 10 may be referred to as the application server 10 or the AS 10.

[0062] The server 10 may be a web server, a PC server, a midrange server, or a mainframe server. The server 10 may also be an information processing device that performs data processing (edge ​​processing) near a user or a terminal. For example, the server 10 may be an information processing device (computer) attached to or built into a base station. The server 10 may also have a core network function. For example, the server 10 may be a device that functions as the management device 20. Of course, the server 10 may also be an information processing device that performs cloud computing, such as a cloud server. The server 10 of this embodiment can function as an application function.

[0063] The server 10 is connected to the management device 20 via a network N. Although only one network N is shown in the example of FIG. 6, multiple networks N may exist. Here, the network N is, for example, a public network such as the Internet. Note that the network N is not limited to the Internet, and may be, for example, a local area network (LAN), a wide area network (WAN), a cellular network, a fixed telephone network, or a regional Internet Protocol (IP) network. The network N may include a wired network or a wireless network.

[0064] 7 is a diagram illustrating an example configuration of a server 10 according to an embodiment of the present disclosure. The server 10 includes a communication unit 11, a storage unit 12, and a control unit 13. The configuration illustrated in FIG. 7 is a functional configuration, and the hardware configuration may be different from this. Furthermore, the functions of the server 10 may be distributed and implemented in multiple physically separated configurations. For example, the server 10 may be configured by multiple information processing devices.

[0065] The communication unit 11 is a communication interface for communicating with other devices. For example, the communication unit 11 is a network interface. For example, the communication unit 11 is a LAN (Local Area Network) interface such as a NIC (Network Interface Card). The communication unit 11 may be a wired interface or a wireless interface. The communication unit 11 communicates with the management device 20, the base station 30, the terminal device 40, and other servers 10 under the control of the control unit 13.

[0066] The storage unit 12 is a storage device that can read and write data, such as a dynamic random access memory (DRAM), a static random access memory (SRAM), a flash memory, or a hard disk.

[0067] The control unit 13 is a controller that controls each component of the server 10. The control unit 13 may be implemented by a processor such as a central processing unit (CPU) or a microprocessing unit (MPU). Specifically, the control unit 13 may be implemented by a processor executing various programs stored in a storage device within the management device 20 using a random access memory (RAM) or the like as a work area. The control unit 13 may be implemented by an integrated circuit such as an application-specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The control unit 13 may also be implemented by a graphics processing unit (GPU). A CPU, an MPU, an ASIC, an FPGA, and a GPU can all be considered controllers. The control unit 13 may be configured by multiple physically separated entities. For example, the control unit 13 may be configured by multiple semiconductor chips.

[0068] <2-2. Configuration of Management Device> Next, the configuration of the management device 20 will be described.

[0069] The management device 20 is an information processing device (computer) that manages the wireless network. For example, the management device 20 is an information processing device that manages communication of the base station 30.

[0070] The management device 20 may be a device constituting a core network CN. For example, the management device 20 may be a device having a function as an MME (Mobility Management Entity). The management device 20 may also be a device having a function as an AMF (Access and Mobility Management Function) and / or an SMF (Session Management Function). The MME, AMF, and SMF are control plane network function nodes in the core network CN. The management device 20 may be a device having a function as a control plane network function (6G CPNF) in 6G. The 6G CPNF may be composed of one or more logical nodes.

[0071] Of course, the functions of the management device 20 are not limited to MME, AMF, SMF, and 6G CPNF. The management device 20 may be a device having functions as a Network Slice Selection Function (NSSF), an Authentication Server Function (AUSF), a Policy Control Function (PCF), and a Unified Data Management (UDM). The management device 20 may also be a device having functions as a Home Subscriber Server (HSS). The management device 20 may also be a device having functions as an OAM (Operations, Administration, and Maintenance) that operates, manages, and maintains a network. Furthermore, the management device 20 may be a device having a function as a Non-Real Time RIC that controls a CU (Central Unit) and a DU (Distributed Unit) that constitute the base station 30 via a Near-Real Time RIC (Near-Real Time RAN Intelligent Controller), and a function as an SMO (Service Management and Orchestration) that has a function of managing policies, settings, performance, etc.

[0072] The management device 20 may have a gateway function. For example, the management device 20 may have a function as an S-GW (Serving Gateway) or a P-GW (Packet Data Network Gateway). The management device 20 may also have a function as a UPF (User Plane Function). In this case, the management device 20 may have multiple UPFs. The management device 20 may also be a device that has a function as a 6G User Plane Network Function (6G UPNF).

[0073] The core network CN is composed of multiple network functions, and each network function may be consolidated into one physical device or distributed across multiple physical devices. In other words, the management device 20 may be distributed across multiple devices. Furthermore, this distributed distribution may be controlled so that it is executed dynamically. The base station 30 and the management device 20 form a single network, providing wireless communication services to terminal devices 40. The management device 20 is connected to the Internet, and the terminal devices 40 can use various services provided via the Internet via the base station 30.

[0074] The management device 20 does not necessarily have to be a device that constitutes the core network CN. For example, assume that the core network CN is a core network of W-CDMA (Wideband Code Division Multiple Access) or cdma2000 (Code Division Multiple Access 2000). In this case, the management device 20 may be a device that functions as an RNC (Radio Network Controller).

[0075] FIG. 8 is a diagram showing the configuration of the management device 20 according to this embodiment. The management device 20 includes a communication unit 21, a storage unit 22, and a control unit 23. The configuration shown in FIG. 8 is a functional configuration, and the hardware configuration may be different from this. Furthermore, the functions of the management device 20 may be statically or dynamically distributed and implemented in multiple physically separated configurations. The management device 20 may also be configured by multiple server devices.

[0076] The communication unit 21 is a communication interface for communicating with a wireless communication device (e.g., base station 30). The communication unit 21 may be a network interface or a device connection interface. The communication unit 21 may be a LAN (Local Area Network) interface such as a NIC (Network Interface Card), or a Universal Serial Bus (USB) interface configured by a USB host controller or a USB port. The communication unit 21 may be a wired interface or a wireless interface. The communication unit 21 is controlled by the control unit 23.

[0077] The storage unit 22 is a readable and writable storage device such as a DRAM, an SRAM, a flash memory, or a hard disk. The storage unit 22 stores, for example, the connection state of the terminal device 40. The storage unit 22 stores the state of the RRC (Radio Resource Control) of the terminal device 40 and the state of the ECM (EPS Connection Management) or the 5G System CM (Connection Management). The storage unit 22 may function as a home memory that stores location information of the terminal device 40.

[0078] The control unit 23 is a controller that controls each unit of the management device 20. The control unit 23 may be realized by a processor such as a CPU or MPU. In particular, the control unit 23 may be realized by a processor executing various programs stored in a storage device inside the management device 20 using RAM or the like as a work area. The control unit 23 may be realized by an integrated circuit such as an ASIC or FPGA. The control unit 23 may also be realized by a GPU. A CPU, MPU, ASIC, FPGA, and GPU can all be considered controllers. The control unit 23 may be composed of multiple physically separated objects. For example, the control unit 23 may be composed of multiple semiconductor chips.

[0079] The control unit 23 includes at least one block of an acquisition unit 231, a determination unit 232, a transmission unit 233, and a setting unit 234. Each block (acquisition unit 231 to setting unit 234) constituting the control unit 23 is a functional block that indicates the function of the control unit 23. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be a software module realized 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 control unit 23 may be configured as a functional unit different from the above-mentioned functional blocks. The method of configuring the functional blocks is arbitrary.

[0080] <2-3. Configuration of Base Station> Next, the configuration of the base station 30 will be described.

[0081] The base station 30 is a wireless communication device (for example, a base station (BS)) that performs wireless communication with other wireless communication devices (for example, a terminal device 40 or another base station 30). The base station 30 may perform wireless communication with the terminal device 40 via a relay station, or may perform wireless communication directly with the terminal device 40. In the following description, the base station 30 may be referred to as a BS 30.

[0082] The base station 30 is a device equivalent to a radio base station (such as a base station, Node B, eNB, gNB, or 6GNB) or a radio access point. The base station 30 may be a radio relay station. The base station 30 may be an optical device called a remote radio head (RRH). The base station 30 may be a receiving station such as a field pickup unit (FPU). The base station 30 may be an integrated access and backhaul (IAB) donor node or an IAB relay node that provides radio access lines and radio backhaul lines using time division multiplexing, frequency division multiplexing, or space division multiplexing.

[0083] The wireless access technology used by the base station 30 may be cellular communication technology. The wireless access technology used by the base station 30 may be wireless LAN technology. The wireless access technology used by the base station 30 may be low-power wide-area (LPWA) communication technology. However, the wireless access technology used by the base station 30 is not limited to these and may be other wireless access technologies. The wireless communication used by the base station 30 may be wireless communication using millimeter waves or wireless communication using terahertz waves. The wireless communication used by the base station 30 may be wireless communication using radio waves or wireless communication using infrared or visible light (optical wireless). Furthermore, the base station 30 may be capable of NOMA (Non-Orthogonal Multiple Access) communication with the terminal device 40. Here, NOMA communication refers to communication (transmission, reception, or both) using non-orthogonal resources. Note that the base station 30 may be capable of NOMA communication with other base stations 30.

[0084] The base station 30 may be able to communicate with the core network via a base station-core network interface (e.g., NG Interface, S1 Interface, etc.). This interface may be either wired or wireless. The base station may also be able to communicate with other base stations via an inter-base station interface (e.g., Xn Interface, X2 Interface, F1 Interface, etc.). This interface may be either wired or wireless.

[0085] The concept of a base station (also called a "base station device") includes not only a donor base station but also a relay base station (also called a "relay station"). A relay base station may be any one of an RF Repeater, a Smart Repeater, and an Intelligent Surface. The concept of a base station includes not only a structure with base station functions but also equipment installed in the structure.

[0086] Examples of structures include high-rise buildings, houses, steel towers, station facilities, airport facilities, port facilities, office buildings, school buildings, hospitals, factories, commercial facilities, stadiums, and other buildings. The concept of a structure includes not only buildings, but also non-building structures such as tunnels, bridges, dams, fences, and steel pillars, as well as equipment such as cranes, gates, and wind turbines. The concept of a structure includes not only land (ground in the narrow sense) or underground structures, but also water-based structures such as piers or megafloats, and underwater structures such as ocean observation facilities. A base station can also be referred to as an information processing device.

[0087] The base station 30 may be a donor station or a relay station (relay station). The base station 30 may also be a fixed station or a mobile station. A mobile station is a wireless communication device (e.g., a base station) configured to be mobile. In this case, the base station 30 may be a device installed in a mobile body, or may be the mobile body itself. For example, a relay station with mobility can be considered a base station 30 as a mobile station. Furthermore, devices that are inherently mobile and have base station functionality (at least part of the base station functionality), such as vehicles, UAVs (Unmanned Aerial Vehicles) represented by drones, and smartphones, also fall under the category of a base station 30 as a mobile station.

[0088] Here, the mobile body may be a mobile terminal such as a smartphone or a mobile phone. The mobile body may be a mobile body that moves on land (ground in the narrow sense) (e.g., a vehicle such as an automobile, bicycle, bus, truck, motorcycle, train, or linear motor car), or a mobile body that moves underground (e.g., in a tunnel) (e.g., a subway). The mobile body may also be a mobile body that moves on water (e.g., a ship such as a passenger ship, cargo ship, or hovercraft), or a mobile body that moves underwater (e.g., a submersible vessel such as a submersible boat, submarine, or unmanned submersible). The mobile body may also be a mobile body that moves in the atmosphere (e.g., an aircraft such as an airplane, airship, or drone).

[0089] The base station 30 may be a terrestrial base station (ground station) installed on the ground. The base station 30 may be a base station located on a structure on the ground, or a base station installed on a mobile object moving on the ground. The base station 30 may be an antenna installed on a structure such as a building and a signal processing device connected to that antenna. The base station 30 may be the structure or the mobile object itself. "Ground" refers not only to land (ground in the narrow sense) but also to ground, on water, and underwater in a broad sense. The base station 30 is not limited to a terrestrial base station. If the communication system 1 is a satellite communication system, the base station 30 may be an aircraft station. From the perspective of a satellite station, an aircraft station located on Earth is a ground station.

[0090] The base station 30 is not limited to a ground station. The base station 30 may be a non-terrestrial base station (non-ground station) that can float in the air or space. The base station 30 may be an aircraft station or a satellite station.

[0091] A satellite station is a wireless communication device capable of floating outside the atmosphere. The satellite station may be a device mounted on a space vehicle such as an artificial satellite, or may be the space vehicle itself. A space vehicle is a vehicle that moves outside the atmosphere. The space vehicle may be at least one of an artificial satellite, a spacecraft, a space station, and a probe. Of course, the space vehicle may also be an artificial celestial body other than these. Note that a satellite that serves as a satellite station may be any of a low Earth orbiting (LEO) satellite, a medium Earth orbiting (MEO) satellite, a geostationary Earth orbiting (GEO) satellite, or a highly elliptical orbiting (HEO) satellite. The satellite station may be a device mounted on a low Earth orbiting (LEO), a medium Earth orbiting (MEO), a geostationary Earth orbiting (GEO), or a highly elliptical orbiting (HEO) satellite.

[0092] An aircraft station is a wireless communication device capable of floating in the atmosphere of an aircraft or the like. The aircraft station may be a device mounted on the aircraft or the like, or may be the aircraft itself. The concept of aircraft includes not only heavier-than-air vehicles such as airplanes and gliders, but also lighter-than-air vehicles such as balloons and airships. The concept of aircraft includes not only heavier-than-air vehicles or lighter-than-air vehicles, but also rotorcraft such as helicopters and autogyros. The aircraft station, or an aircraft equipped with an aircraft station, may be an unmanned aerial vehicle such as a drone.

[0093] The concept of unmanned aerial vehicles also includes unmanned aerial systems (UAS) and tethered unmanned aerial systems (UAS). The concept of unmanned aerial vehicles also includes lighter than air UAS (LTA) and heavier than air UAS (HTA). The concept of unmanned aerial vehicles also includes high altitude unmanned aerial system platforms (HAPs).

[0094] The coverage size of the base station 30 may be relatively large, such as a macrocell, or relatively small, such as a picocell. The coverage size of the base station 30 may be extremely small, such as a femtocell. The base station 30 may have a beamforming function. The base station 30 may form a cell or service area for each beam. Additionally or alternatively, in addition to beamforming, which imparts directionality to the beam, the base station 30 may have a function for pinpointing a desired wave to a specific point by further considering distance information from the antenna of the base station 30. This function may be called beam focusing or point forming. The base station 30 may also be configured to acquire detection data by performing sensing using the beam.

[0095] Fig. 9 is a diagram showing the configuration of a base station 30 according to this embodiment. The base station 30 includes a wireless communication unit 31, a storage unit 32, and a control unit 33. However, the configuration shown in Fig. 9 is a functional configuration, and the hardware configuration may be different. Furthermore, the functions of the base station 30 may be distributed and implemented in multiple physically separated units.

[0096] It should be noted that the base station 30 does not necessarily have to include all of the components described above or below, and may also include components other than the components described above or below.

[0097] The wireless communication unit 31 is a signal processing unit for wireless communication with other wireless communication devices (e.g., at least one of the terminal device 40 and another base station 30). The wireless communication unit 31 may be referred to as a wireless transceiver or simply as a transceiver. In this case, the wireless communication unit 31 may be a transceiver (hereinafter referred to as a 3GPP transceiver) conforming to the specifications defined in the Technical Specification of the 3rd Generation Partnership Project (3GPP). The 3GPP transceiver may be a 3G transceiver, a 4G (LTE) transceiver, a 5G (NR) transceiver, or a transceiver of a generation after 5G. The wireless communication unit 31 is controlled by the control unit 33. The wireless communication unit 31 supports one or more wireless access methods. The wireless communication unit 31 may support at least one of NR, LTE, B5G, and 6G. The wireless communication unit 31 may support W-CDMA, cdma2000, etc. in addition to NR, LTE, B5G, and 6G. The wireless communication unit 31 may support automatic retransmission techniques such as HARQ (Hybrid Automatic Repeat reQuest). Some or all of the processing performed by the wireless communication unit 31 may be performed by the control unit 33.

[0098] The wireless communication unit 31 includes a transmission processing unit 311, a reception processing unit 312, and an antenna 313. Alternatively, at least one of the transmission processing unit 311, the reception processing unit 312, and the antenna 313 may be considered as the wireless communication unit 31. The wireless communication unit 31 may include a plurality of transmission processing units 311, a plurality of reception processing units 312, and a plurality of antennas 313. When the wireless communication unit 31 supports a plurality of wireless access methods, each unit of the wireless communication unit 31 may be configured individually for each wireless access method. The transmission processing unit 311 and the reception processing unit 312 may be configured individually for LTE, NR, B5G, and 6G. The antenna 313 may be configured with a plurality of antenna elements, for example, a plurality of patch antennas. The wireless communication unit 31 may have a beamforming function. For example, the wireless communication unit 31 may have a polarization beamforming function using vertical polarization (V polarization) and horizontal polarization (H polarization) (or a polarization beamforming function using dual polarization in polarization directions of 45 degrees and -45 degrees from the vertical direction).

[0099] The transmission processing unit 311 performs transmission processing of the downlink control information and downlink data. For example, the transmission processing unit 311 encodes the downlink control information and downlink data input from the control unit 33 using a coding method such as block coding, convolutional coding, or turbo coding. Here, the encoding may be performed using polar codes or low density parity check codes (LDPC codes). The transmission processing unit 311 then modulates the coded bits using a predetermined modulation method (e.g., BPSK, QPSK, 16QAM, 64QAM, 256QAM, or a higher-order multi-level modulation method). In this case, the signal points on the constellation do not necessarily need to be equidistant. The constellation may also be a non-uniform constellation (NUC). The transmission processing unit 311 then multiplexes the modulation symbols of each channel and the downlink reference signal and allocates them to predetermined resource elements. The transmission processing unit 311 then performs various signal processing on the multiplexed signal. For example, the transmission processing unit 311 performs processes such as conversion to the frequency domain by 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, power amplification, etc. The signal generated by the transmission processing unit 311 is transmitted from an antenna 313.

[0100] The reception processing unit 312 processes the uplink signal received via the antenna 313. For example, the reception processing unit 312 performs downconversion, removal of unnecessary frequency components, control of amplification level, quadrature demodulation, conversion to a digital signal, removal of guard intervals (cyclic prefixes), extraction of frequency domain signals by fast Fourier transform, and the like on the uplink signal. The reception processing unit 312 then 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 signal that has undergone these processes. The reception processing unit 312 also 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 for demodulation may be 16QAM (Quadrature Amplitude Modulation), 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 (NUC). The reception processing unit 312 then performs decoding processing on the coded bits of the demodulated uplink channel. The decoded uplink data and uplink control information are output to the control unit 33.

[0101] The antenna 313 is an antenna device that converts electric current and radio waves into each other. The antenna 313 may be composed of a single antenna element, for example, a single patch antenna. The antenna 313 may be composed of multiple antenna elements, for example, multiple patch antennas. When the antenna 313 is composed of multiple antenna elements, the wireless communication unit 31 may have a beamforming function. The wireless communication unit 31 may be configured to generate a directional beam by controlling the directivity of a wireless signal using the multiple antenna elements. The antenna 313 may be a dual-polarized antenna. When the antenna 313 is a dual-polarized antenna, the wireless communication unit 31 may use vertical polarization (V polarization) and horizontal polarization (H polarization) (or dual polarization with polarization directions at 45 degrees and -45 degrees from the vertical direction) when transmitting a wireless signal. The wireless communication unit 31 may control the directivity of a wireless signal transmitted using vertical polarization and horizontal polarization (or dual polarization with polarization directions at 45 degrees and -45 degrees from the vertical direction). Furthermore, the wireless communication unit 31 may transmit and receive spatially multiplexed signals via multiple layers each consisting of multiple antenna elements.

[0102] The storage unit 32 is a readable and writable storage device such as a DRAM, an SRAM, a flash memory, or a hard disk.

[0103] The control unit 33 is a controller that controls each unit of the base station 30. The control unit 33 controls the wireless communication unit to perform wireless communication with other wireless communication devices (e.g., terminal devices 40 or other base stations 30). The control unit 33 may be implemented by a processor such as a CPU or MPU. Specifically, the control unit 33 may be implemented by a processor executing various programs stored in a storage device inside the base station 30 using RAM or the like as a work area. The control unit 33 may be implemented by an integrated circuit such as an ASIC or FPGA. The control unit 33 may also be implemented by a GPU. A CPU, MPU, ASIC, FPGA, and GPU can all be considered controllers. The control unit 33 may be composed of multiple physically separated objects. For example, the control unit 33 may be composed of multiple semiconductor chips.

[0104] The control unit 33 includes at least one block of an acquisition unit 331, a determination unit 332, a transmission unit 333, and a setting unit 334. Each block (acquisition unit 331 to setting unit 334) constituting the control unit 33 is a functional block that indicates the function of the control unit 33. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be a software module realized 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 control unit 33 may be configured with functional units different from the above-mentioned functional blocks. The method of configuring the functional blocks is arbitrary.

[0105] The control unit 33 may have a function of Near-Real Time RIC. Near-Real Time RIC is compatible with conventional RRM (Radio Resource Management) and can provide RRM functions that utilize AI (Artificial Intelligence) (for example, QoS (Quality of Service) management that utilizes AI (Artificial Intelligence), connection management that utilizes AI (Artificial Intelligence), and seamless handover that utilizes AI (Artificial Intelligence).

[0106] In some embodiments, the base station 30 may be configured as a collection of multiple physical or logical devices. As an example, the base station 30 of this embodiment may be divided into multiple devices such as a baseband unit (BBU) and a radio unit (RU). The base station 30 may be interpreted as a collection of these multiple devices. Furthermore, the base station may be either a BBU or an RU, or may be both. The BBU and the RU may be connected by a predetermined interface such as an enhanced Common Public Radio Interface (eCPRI).

[0107] The RU may be referred to as an RRU (Remote Radio Unit) or an RD (Radio DoT). The RU may correspond to a gNB-DU (gNB Distributed Unit) described later. The BBU may correspond to a gNB-CU (gNB Central Unit) described later. The RU may be a device integrally formed with an antenna. The antenna of the base station 30, for example, an antenna integrally formed with the RU, may employ an Advanced Antenna System and support MIMO such as FD-MIMO or beamforming. The antenna of the base station 30 may have, for example, 64 transmitting antenna ports and 64 receiving antenna ports.

[0108] The antenna mounted on the RU may be an antenna panel consisting of one or more antenna elements, and the RU may be equipped with one or more antenna panels. The RU may be equipped with two types of antenna panels, a horizontally polarized antenna panel and a vertically polarized antenna panel. The RU may be equipped with two types of antenna panels, a right-handed circularly polarized antenna panel and a left-handed circularly polarized antenna panel, or an antenna panel with a polarization direction at 45 degrees from the vertical direction and an antenna panel with a polarization direction at -45 degrees from the vertical direction. Multiple antennas with these multiple polarization directions may be mounted on a single antenna panel. The RU may form and control an independent beam for each antenna panel.

[0109] A plurality of base stations 30 may be connected to each other. One or more base stations 30 may be included in a radio access network (RAN). In this case, the base station 30 may be simply referred to as a RAN, a RAN node, an AN (Access Network), an AN node, or the like. The RAN in LTE may be called an Enhanced Universal Terrestrial RAN (EUTRAN). The RAN in NR may be called an NGRAN. Furthermore, the RAN in 6G may be called a 6GRAN. The RAN in W-CDMA (UMTS) may be called a UTRAN.

[0110] An LTE base station 30 may be referred to as an eNodeB (Evolved Node B) or eNB. In this case, the EUTRAN includes one or more eNodeBs (eNBs). An NR base station 30 may be referred to as a gNodeB or gNB. In this case, the NGRAN includes one or more gNBs. A 6G base station may be referred to as a 6GNodeB, 6gNodeB, 6GNB, or 6gNB. In this case, the 6GRAN includes one or more 6GNBs. The EUTRAN may include a gNB (en-gNB) connected to a core network (EPC) in an LTE communication system (EPS). The NGRAN may include an ng-eNB connected to a core network 5GC in a 5G communication system (5GS).

[0111] When the base station 30 is an eNB, gNB, 6GNB, or the like, the base station 30 may be referred to as a 3GPP access. When the base station 30 is a wireless access point, the base station 30 may be referred to as a non-3GPP access. The base station 30 may be a radio device called an RRH (Remote Radio Head). When the base station 30 is a gNB, the base station 30 may be a combination of the gNB-CU and gNB-DU described above, or may be either a gNB-CU or a gNB-DU.

[0112] Here, the gNB-CU hosts multiple upper layers (e.g., RRC (Radio Resource Control), SDAP (Service Data Adaptation Protocol), PDCP (Packet Data Convergence Protocol)) of the access stratum for communication with the UE. On the other hand, the gNB-DU hosts multiple lower layers (e.g., RLC (Radio Link Control), MAC (Medium Access Control), PHY (Physical layer)) of the access stratum. That is, among the messages / information described below, RRC signaling (semi-static notification) is generated by the gNB-CU, while MAC The CE and DCI (dynamic notification) may be generated by the gNB-DU. Alternatively, some of the RRC configuration (semi-static notification), such as IE:cellGroupConfig, may be generated by the gNB-DU, and the remaining configuration may be generated by the gNB-CU. These configurations may be transmitted and received via the F1 interface described below. The gNB-CU and gNB-DU are connected to the Near-Real Time RIC via the E2 interface.

[0113] The base station 30 may be configured to be able to communicate with other base stations. When multiple base stations 30 are eNBs or a combination of eNBs and en-gNBs, these base stations 30 may be connected via an X2 interface. When multiple base stations 30 are gNBs or a combination of gn-eNBs and gNBs, these base stations 30 may be connected via an Xn interface. When multiple base stations 30 are a combination of gNB-CUs and gNB-DUs, these base stations 30 may be connected via the F1 interface described above. Messages / information (e.g., RRC signaling, MAC Control Element (CE), or Downlink Control Information (DCI)) described below may be transmitted between multiple base stations 30 via, for example, the X2 interface, the Xn interface, or the F1 interface.

[0114] A cell provided by the base station 30 may be referred to as a serving cell. The concept of a serving cell includes a PCell (Primary Cell) and an SCell (Secondary Cell). When dual connectivity is provided to the terminal device 40, the PCell and zero or more SCells provided by a Master Node (MN) may be referred to as a Master Cell Group. The dual connectivity may be at least one of EUTRA-EUTRA Dual Connectivity, EUTRA-NR Dual Connectivity (ENDC), EUTRA-NR Dual Connectivity with 5GC, NR-EUTRA Dual Connectivity (NEDC), NR-NR Dual Connectivity, NR-6G Dual Connectivity, and 6G-NR Dual Connectivity. Of course, dual connectivity is not limited to these.

[0115] The serving cell may include a PSCell (Primary Secondary Cell or Primary SCG Cell). When dual connectivity is provided to the terminal device 40, the PSCell provided by a Secondary Node (SN) and zero or more SCells may be referred to as a Secondary Cell Group (SCG). Unless special configuration (e.g., PUCCH on SCell) is performed, the Physical Uplink Control Channel (PUCCH) is transmitted by the PCell and PSCell but not by the SCell. Radio link failure is detected by the PCell and PSCell but not (does not need to be detected by) the SCell. As such, the PCell and PSCell play special roles among serving cells and are therefore also referred to as Special Cells (SpCells).

[0116] One cell may be associated with one downlink component carrier and one uplink component carrier. The system bandwidth corresponding to one cell may be divided into multiple BWPs (Bandwidth Parts). In this case, one or multiple BWPs may be configured in the terminal device 40, and one BWP may be used by the terminal device 40 as an active BWP. Radio resources available to the terminal device 40, such as a frequency band, numerology (subcarrier spacing), or slot format (Slot configuration), may differ for each cell, each component carrier, or each BWP.

[0117] 2-4. Configuration of Terminal Device Next, the configuration of the terminal device 40 will be described.

[0118] The terminal device 40 is a wireless communication device (e.g., User Equipment (UE)) that performs wireless communication with another wireless communication device (e.g., a base station 30 or another terminal device 40). In the following description, the terminal device 40 may be referred to as the UE 40.

[0119] The terminal device 40 may be any type of information processing device (computer). For example, the terminal device 40 may be a mobile terminal such as a mobile phone, a smart device (smartphone or tablet), a personal digital assistant (PDA), a notebook PC, or a portable game console. The terminal device 40 may also be an imaging device (e.g., a camcorder) equipped with a communication function. The terminal device 40 may also be a motorcycle or a mobile broadcasting vehicle equipped with a communication device such as a field pickup unit (FPU). The terminal device 40 may also be a machine-to-machine (M2M) device or an Internet of Things (IoT) device. The terminal device 40 may also be a wearable device such as a smartwatch.

[0120] Furthermore, the terminal device 40 may be an XR device such as an AR (Augmented Reality) device, a VR (Virtual Reality) device, or an MR (Mixed Reality) device. In this case, the XR device may be a glasses-type device such as AR glasses or MR glasses, or a head-mounted device such as a VR head-mounted display. When the terminal device 40 is an XR device, the terminal device 40 may be a standalone device consisting only of a part worn by a user (e.g., a glasses part). Furthermore, the terminal device 40 may be a terminal-linked device consisting of a part worn by a user (e.g., a glasses part) and a terminal part (e.g., a smart device) linked to the part worn by a user.

[0121] The terminal device 40 may be capable of NOMA communication with the base station 30. The terminal device 40 may be able to use an automatic repeat technique such as HARQ when communicating with the base station 30. The terminal device 40 may be capable of sidelink communication with another terminal device 40. The terminal device 40 may be able to use an automatic repeat technique such as HARQ when performing sidelink communication. The terminal device 40 may be capable of NOMA communication when performing sidelink communication with another terminal device 40. The terminal device 40 may be capable of LPWA communication with other wireless communication devices such as the base station 30. The wireless communication used by the terminal device 40 may be wireless communication using millimeter waves. The wireless communication used by the terminal device 40, including sidelink communication, may be wireless communication using radio waves, or wireless communication using infrared or visible light, i.e., optical wireless.

[0122] The terminal device 40 may be a mobile wireless communication device, i.e., a mobile device. The terminal device 40 may be a wireless communication device installed in a mobile device, or may be the mobile device itself. The terminal device 40 may be a vehicle that moves on a road, such as an automobile, bus, truck, or motorcycle, or a train that runs on a track, or may be a wireless communication device mounted on the vehicle. The mobile device may be a mobile terminal, or a mobile device that moves on land (in the narrow sense of the word), underground, on water, or underwater. The mobile device may also be a mobile device that moves within the atmosphere, such as an airplane, airship, balloon, or helicopter, or a mobile device that moves outside the atmosphere, such as an artificial satellite. The mobile device may also be a UAV (Unmanned Aerial Vehicle) such as a drone. The terminal device 40 may also be a wireless communication device mounted on the mobile device.

[0123] The terminal device 40 may be capable of simultaneously connecting to and communicating with a plurality of base stations 30 or a plurality of cells. When one base station 30 supports a communication area via a plurality of cells (e.g., pCell or sCell), the plurality of cells can be bundled together to enable communication between the base station 30 and the terminal device 40 by using carrier aggregation (CA) technology, dual connectivity (DC) technology, multi-connectivity (MC) technology, or the like. Alternatively, communication between the terminal device 40 and the plurality of base stations 30 can also be achieved via cells of different base stations 30 by coordinated multi-point transmission and reception (CoMP) technology.

[0124] The terminal device 40 may be a relay terminal that relays communications to a remote terminal.

[0125] Fig. 10 is a diagram showing the configuration of a terminal device 40 according to this embodiment. The terminal device 40 includes a wireless communication unit 41, a storage unit 42, and a control unit 43. The configuration shown in Fig. 10 is a functional configuration, and the hardware configuration may be different from this. Furthermore, the functions of the terminal device 40 may be distributed and implemented in multiple physically separated units.

[0126] It should be noted that the terminal device 40 does not necessarily have to have all of the configurations described above or below. Furthermore, the terminal device 40 may have a configuration other than the configurations described above or below. The terminal device 40 may have a beamforming function. Furthermore, the terminal device 40 may be configured to acquire detection data by performing sensing using beams.

[0127] The wireless communication unit 41 is a signal processing unit for wireless communication with other wireless communication devices (e.g., a base station 30 or another terminal device 40). The wireless communication unit 41 may be referred to as a wireless transceiver or simply as a transceiver. In this case, the wireless communication unit 41 may be a transceiver of a standard defined in the 3GPP technical specifications (hereinafter referred to as a 3GPP transceiver). The 3GPP transceiver may be a 3G transceiver, a 4G (LTE) transceiver, a 5G (NR) transceiver, or a transceiver of a generation after 5G. The wireless communication unit 41 is controlled, for example, by the control unit 43. The wireless communication unit 41 supports one or more wireless access methods. The wireless communication unit 41 may support at least one of NR, LTE, B5G, and 6G. In addition to NR, LTE, B5G, and 6G, the wireless communication unit 41 may also support W-CDMA, cdma2000, and the like. The wireless communication unit 41 may support an automatic repeat technique such as HARQ. A part or all of the processing performed by the wireless communication unit 41 may be performed by the control unit 43.

[0128] The wireless communication unit 41 includes a transmission processing unit 411, a reception processing unit 412, and an antenna 413. At least one of the transmission processing unit 411, the reception processing unit 412, and the antenna 413 may be considered as the wireless communication unit 41. The wireless communication unit 41 may include a plurality of transmission processing units 411, a plurality of reception processing units 412, and a plurality of antennas 413. When the wireless communication unit 41 supports a plurality of wireless access methods, each unit of the wireless communication unit 41 may be configured individually for each wireless access method. The transmission processing unit 411 and the reception processing unit 412 may be configured individually for LTE, NR, B5G, and 6G. The antenna 413 may be configured with a plurality of antenna elements, for example, a plurality of patch antennas. The wireless communication unit 41 may have a beamforming function. For example, the wireless communication unit 41 may have a polarization beamforming function using vertical polarization (V polarization) and horizontal polarization (H polarization) (or a polarization beamforming function using dual polarization in polarization directions of 45 degrees and -45 degrees from the vertical direction).

[0129] The storage unit 42 is a readable and writable storage device such as a DRAM, an SRAM, a flash memory, or a hard disk.

[0130] The control unit 43 is a controller that controls each unit of the terminal device 40. The control unit 43 controls the wireless communication unit to perform wireless communication with other wireless communication devices (e.g., a base station 30 or another terminal device 40). The control unit 43 may be implemented by a processor such as a CPU or MPU. In particular, the control unit 23 may be implemented by a processor executing various programs stored in a storage device internal to the terminal device 40 using RAM or the like as a work area. The control unit 43 may be implemented by an integrated circuit such as an ASIC or FPGA. The CPU, MPU, ASIC, and FPGA can all be considered controllers. The control unit 43 may be implemented by a GPU. The CPU, MPU, ASIC, FPGA, and GPU can all be considered controllers. The control unit 43 may be composed of multiple physically separated objects. For example, the control unit 43 may be composed of multiple semiconductor chips.

[0131] The control unit 43 includes at least one block of an acquisition unit 431, a determination unit 432, a transmission unit 433, and a setting unit 434. Each block (acquisition unit 431 to setting unit 434) constituting the control unit 43 is a functional block that indicates the function of the control unit 43. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be a software module realized 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 control unit 43 may be configured as a functional unit different from the above-mentioned functional blocks. The method of configuring the functional blocks is arbitrary.

[0132] <<3. Technologies Applied to the Communication System>> The configuration of the communication system 1 has been described above. Next, technologies applied to the communication system 1 will be described.

[0133] In the following description, the communication system 1 is assumed to be a fifth-generation mobile communication system (5G) as an example, but the communication system 1 is not limited to a fifth-generation mobile communication system. The communication system 1 may be a fourth-generation mobile communication system (4G) or a sixth-generation mobile communication system (6G). Of course, the communication system 1 may be any other wireless communication system.

[0134] <3-1. 5GS Network Architecture> Next, a network architecture that can be applied to the communication system 1 of the present embodiment will be described. Here, as an example of the architecture of the communication system 1, the architecture of a 5GS (5G System) will be described.

[0135] FIG. 11 is a diagram illustrating an example of the configuration of a 5GS architecture. The 5G core network CN is also referred to as 5G Core (5GC) / Next Generation Core (NGC). The core network CN of this embodiment is configured, for example, by one or more management devices 20. Hereinafter, the 5G core network CN is also referred to as 5GC / NGC. The core network CN is connected to a UE (User Equipment) 40 via a Radio Access Network (RAN) / Access Network (AN) 910. The UE 40 is, for example, a terminal device 40 in the communication system 1. The RAN / AN 910 includes, for example, a base station 30 in the communication system 1. Note that in the example of FIG. 15, the RAN / AN 910 is not included in the core network CN, but can be considered as a device belonging to the core network CN.

[0136] An application server (AS) 10 that performs processing related to applications is connected to 5GS via the Internet. The server 10 is, for example, an application server (AS). The application server 10 shown in FIG. 9 corresponds to, for example, the server 10 in the communication system 1. This enables the UE 40 to use applications via the 5G service.

[0137] If the entity providing the application has a contract such as a service level agreement (SLA) with a public land mobile network (PLMN) operator that provides 5G services, the server 10 can be arranged as the DN 930 or in the core network CN as the DN 930. The server 10 may be provided in the form of an edge server.

[0138] The 5GS control plane function group 940 is configured by a plurality of NFs (Network Functions). The plurality of NFs included in the control plane function group 940 include, for example, an Access and Mobility Management Function (AMF) 941, a Network Exposure Function (NEF) 942, a Network Repository Function (NRF) 943, a Network Slice Selection Function (NSSF) 944, a Policy Control Function (PCF) 945, a Session Management Function (SMF) 946, a Unified Data Management (UDM) 947, an Application Function (AF) 948, an Authentication Server Function (AUSF) 949, a UE radio Capability Management Function (UCMF) 950, and a Network Data Analytics Function (NWDAF) 951.

[0139] The UDM 947 includes a UDR (Unified Data Repository) that stores and manages subscriber information, and an FE (Front End) that processes the subscriber information. The AMF 941 performs mobility management. The SMF 946 performs session management.

[0140] The UCMF 950 holds UE Radio Capability Information corresponding to all UE Radio Capability IDs in a PLMN (Public Land Mobile Network), and is responsible for assigning each PLMN-assigned UE Radio Capability ID.

[0141] The NWDAF 951 processes network analysis information (e.g., statistical information) for network automation. The NWDAF 951 defines an analytics logical function (AnLF) (not shown), which is a logical function that executes inference using an AI (artificial intelligence) / ML (machine learning) model, acquires analytical information, and discloses the analytical information, and an MTLF (model training logical function) (not shown). The AnLF is a logical function that executes inference using an AI (artificial intelligence) / ML (machine learning) model, acquires analytical information, and discloses the analytical information. The MTLF is a logical function that learns the AI / ML model and discloses the learning service.

[0142] Namf is a service-based interface provided by the AMF 941. Nsmf is a service-based interface provided by the SMF 946. Nnef is a service-based interface provided by the NEF 942. Npcf is a service-based interface provided by the PCF 945. Nudm is a service-based interface provided by the UDM 947. Naf is a service-based interface provided by the AF 948. Nnrf is a service-based interface provided by the NRF 943. Nnssf is a service-based interface provided by the NSSF 944. Nausf is a service-based interface provided by the AUSF 949. Nucmf is a service-based interface provided by the UCMF 950. Nnwdaf is a service-based interface provided by the NWDAF 951. Each NF exchanges information with other NFs via its respective service-based interface.

[0143] Each NF can request or subscribe to a service provided by another network function and receive a response or notification from the service. That is, each NF exchanges information with other NFs by means of a request / response or a subscribe / notification via each service-based interface.

[0144] The UPF (User Plane Function) 920 has a function of processing the user plane. The DN (Data Network) 930 has a function of enabling connection to MNO (Mobile Network Operator) proprietary services, the Internet, and third-party services. The UPF 920 functions as a forwarding processor for user plane data processed by the server 10. The UPF 920 also functions as a gateway connected to the RAN / AN 910.

[0145] Here, each NF of the core network CN can be configured using virtualization or a container. Each NF can be implemented on a cloud server. In 5GS, each NF can be dynamically and reconfigurably configured using SDN (Software Defined Network).

[0146] In a 5G core network CN configured according to a service-based architecture, new NFs can be introduced by defining new services and service-based interfaces for those services. Furthermore, in next-generation (i.e., 6G) and later core networks CN, it is expected that the above-mentioned NFs will be aggregated, subdivided, or specific services will be transferred to other NFs depending on the services provided by each NF. For this reason, the NFs supported by the core network CN are not limited to the types of NFs in the 5G core network CN illustrated above.

[0147] The RAN / AN 910 has a function that enables connection with the RAN and connection with an AN other than the RAN. The RAN / AN 910 includes a base station called a gNB or ng-eNB. The RAN is sometimes called an NG (Next Generation)-RAN.

[0148] The functions of the RAN / AN 910 are divided into a CU (Central Unit) that processes L2 / L3 functions above the PDCP (Packet Data Convergence Protocol) sublayer, and a DU (Distributed Unit) that processes L2 / L1 functions below the RLC (Radio Link Control) sublayer. The functions of the RAN / AN 910 can be distributed and arranged via an F1 interface.

[0149] Furthermore, the functions of the DU are divided into an RU (Radio Unit) that processes the LOW PHY sublayer and the radio unit (Radio), and a DU that processes the RLC, MAC (Medium Access Control), and HIGH PHY sublayers. The functions of the RU can be distributed and arranged, for example, via a fronthaul that complies with eCPRI (evolved Common Public Radio Interface).

[0150] The functions of the CU and / or DU can be configured using virtualization or containers. The functions of the CU and / or DU can be implemented on a cloud server. In 5GS, the functions of the CU and / or DU can be dynamically and reconfigurably configured using SDN.

[0151] Between the UE 40 and the AMF 941, information is exchanged via a reference point N1. Between the RAN / AN 910 and the AMF 941, information is exchanged via a reference point N2. Between the SMF 946 and the UPF 920, information is exchanged via a reference point N4.

[0152] The SMF 946 performs QoS (Quality of Service) control for each service data flow. The QoS control of the SMF 946 can be applied to both IP and Ethernet type service data flows. By performing QoS control for each service data flow, the SMF 946 provides authorized QoS for each specific service.

[0153] The SMF 946 can utilize indicators such as QoS subscriber information in conjunction with service-based, subscription-based, or predefined PCF internal policy rules.

[0154] The SMF 946 uses the Policy and Charging Control (PCC) rules associated with the QoS flow, i.e., the QoS-controlled data flow, to determine the QoS to authorize for the QoS flow.

[0155] When a QoS flow is deleted, the SMF 946 can notify the PCF 945 that the QoS flow has been deleted. Furthermore, when the SMF 946 cannot guarantee the bit rate guaranteed by the QoS flow, i.e., the Guaranteed Flow Bit Rate (GFBR), it can notify the PCF 945 that the GFBR cannot be guaranteed.

[0156] The QoS reservation procedure for a QoS flow can be to establish a UE-initiated QoS flow, and the QoS can be downgraded or upgraded as part of the QoS flow modification procedure.

[0157] In mobile communication systems of the next generation (i.e., 6G) and beyond, it is expected that not only the control plane functions but also the user plane functions (e.g., UPF 920) and RAN / AN 910 will support the service-based architecture. Therefore, each node constituting the mobile communication system can be dynamically and re-configurably implemented in an information processing device including a cloud server and / or configured / reconfigured by utilizing technologies such as virtualization, containers, and / or SDN (Software Defined Network).

[0158] <3-2. Network Slice> Next, the network slice will be described.

[0159] A network slice is a unit of service that divides communication services provided by 5G according to the communication characteristics of each service (e.g., data rate, delay, etc.).

[0160] Each network slice is assigned Single Network Slice Selection Assistance Information (S-NSSAI) as Network Slice Selection Assistance Information (NSSAI). The network slice selection assistance information is information for assisting in the selection of a network slice.

[0161] The S-NSSAI consists of a mandatory 8-bit SST (Slice / Service Type) that identifies the slice type, and an optional 24-bit SD (Slice Differentiator) that distinguishes different slices within the same SST.

[0162] The S-NSSAI can use either a standardized SST or a non-standardized proprietary SST. When a standardized S-NSSAI value is used, it contains only the standardized SST without the SD. On the other hand, when a non-standardized S-NSSAI value is used, it contains the standardized SST and SD, or the non-standardized SST and SD, or the non-standardized SST only. A non-standardized S-NSSAI value can only be used within the PLMN, i.e., the telecom operator, that uses it.

[0163] FIG. 12 is a diagram showing standardized SST values. The table shown in FIG. 12 is based on the table shown in 3GPP TS23.501. The above-mentioned "case where standardized S-NSSAI values ​​are used" corresponds to the case where S-NSSAI values ​​including only these SST values ​​(eMBB: 1, URLLC: 2, MIoT: 3, V2X: 4, HMTC: 5, HDLC: 6) are used. In other words, for other network slices, for example, for network slices subdivided by SD, non-standardized S-NSSAI values ​​are used.

[0164] The network slice configuration information includes one or more Configured NSSAI(s). A serving PLMN (Serving Public Land Mobile Network) can configure a Configured NSSAI that applies to each PLMN in the UE 40. Alternatively, a Home PLMN (HPLMN) can configure a Default Configured NSSAI in the UE 40. Only when a Configured NSSAI for the serving PLMN is configured in the UE 40, the UE 40 under the serving PLMN can use the Default Configured NSSAI.

[0165] Note that a Default Configured NSSAI may be set in advance in UE 40. Also, UDM 947 of the HPLMN may provide or update the Default Configured NSSAI using a UE Parameters Update procedure via UDM Control Plane processing.

[0166] A Configured NSSAI consists of one or more S-NSSAI(s).

[0167] The Requested NSSAI is the NSSAI provided by the UE 40 to the serving PLMN during the registration process. The Requested NSSAI must be one of the following: Default Configured NSSAI Configured NSSAI Allowed NSSAI or a part of it NSSAI that is the Allowed NSSAI or a part of it plus one or more S-NSSAIs included in the Configured NSSAI

[0168] The Allowed NSSAI is, for example, the NSSAI that the serving PLMN provides to the UE 40 during the registration process. The Allowed NSSAI indicates one or more S-NSSAI(s) values ​​that can be used within the current registration area of ​​the current serving PLMN.

[0169] The Rejected S-NSSAI indicates the value of one or more S-NSSAIs included in the Requested NSSAI that is not authorized for use in at least one tracking area within the current registration area of ​​the current serving PLMN.

[0170] Here, a tracking area is an area used for mobility management and is identified by a Tracking Area Identity (TAI). The network (PLMN) manages the location of the UE 40 within a set of tracking areas in which the UE 40 is camped so that messages or data can be transmitted to the UE 40 in the RRC_IDLE state. When the UE 40 is registered in the network, the AMF 941 assigns a set of tracking areas included in the TAI list as an area in which the UE 40 is registered (a registration area). In other words, the network manages that the registered UE 40 is located within any of the tracking areas in the TAI list.

[0171] If UE 40 detects a more optimal cell according to the cell reselection criteria, it reselects the cell and camps on it. At this time, if the selected cell does not belong to any tracking area in the TAI list in which UE 40 is registered, a location registration process, i.e., a process of updating the TAI list, is performed.

[0172] The Subscribed S-NSSAI is an S-NSSAI that UE 40 can use within the PLMN according to the subscription information. The subscription information must include one or more Subscribed S-NSSAIs and at least one default S-NSSAI.

[0173] The UDM 947 transmits a maximum of 16 Subscribed S-NSSAIs to the AMF 941. Therefore, the number of S-NSSAIs that can be included in the Configured NSSAI is 16. The contract information that the UDM 947 transmits to the AMF 941 must include at least one default S-NSSAI. The NSSF 944 determines the Allowed NSSAI and the Configured NSSAI, and determines an AMF Set, which is a list of candidates for the AMF 941. For example, an AMF 941 may be selected from the list of candidates according to the network slice used by the UE 40 or other criteria, and the UE 40 may be assigned to the selected AMF 941.

[0174] One or more S-NSSAI(s) included in the Allowed NSSAI(s) provided to the UE 40 may contain values ​​that are not part of the UE 40's current network slice configuration information for the serving PLMN. In this case, the network provides a mapping between each S-NSSAI in the Allowed NSSAI and a corresponding S-NSSAI in the HPLMN for the Allowed NSSAI. This mapping information allows the UE 40 to associate applications with the S-NSSAI in the HPLMN and the corresponding S-NSSAI in the Allowed NSSAI per Network Slice Selection Policy (NSSP) in a UE Route Selection Policy (URSP) rule or per the UE 40's local configuration.

[0175] For example, if the HPLMN and / or VPLMN (Visitor PLMN) uses a non-standardized S-NSSAI value, UE 40 needs to provide information regarding the mapping between the S-NSSAI value included in the Requested NSSAI and the corresponding S-NSSAI value used in the HPLMN when roaming. UE 40 may obtain this mapping information in advance from the serving PLMN as a mapping between the S-NSSAI value included in the Configured NSSAI for the serving PLMN and the corresponding S-NSSAI value used in the HPLMN. Alternatively, UE 40 may obtain this mapping information in advance from the serving PLMN as a mapping between the S-NSSAI value included in the Allowed NSSAI for the serving PLMN and the corresponding S-NSSAI value used in the HPLMN.

[0176] Furthermore, the UE 40 can support a contract-based restriction function regarding network slices that can be simultaneously registered. If the UE 40 supports this function, the UE 40 includes, as part of the UE 5GMM Core Network Capability, information indicating that the function is supported in a registration request message at the time of initial registration and mobility registration update.

[0177] The AMF 941 provides a Configured NSSAI to the UE 40 that has notified that it supports the contract-based restriction function regarding simultaneously registered network slices. At this time, the AMF 941 provides information regarding the Network Slice Simultaneous Registration Group (NSSRG) associated with the network slice (S-NSSAI(s)) of the HPLMN.

[0178] The contract information including the NSRRG information must include at least one default S-NSSAI. If multiple default S-NSSAIs are configured, the default S-NSSAIs are associated with the same NSRRG. In other words, the UE 40 is allowed to register all the default S-NSSAIs simultaneously.

[0179] The HPLMN can transmit, as subscription information, other Subscribed S-NSSAIs that share at least all NSSRGs defined for the default S-NSSAI, in addition to the default S-NSSAI, to the VPLMN. In this case, the HPLMN does not need to transmit NSRRG information to the VPLMN.

[0180] A UE 40 that receives an NSSRG must include only network slices (S-NSSAIs) assigned to the same common NSSRG in the Requested NSSAI.

[0181] Furthermore, when the boundary of the service area of ​​the network slice does not coincide with the boundary of the tracking area, the communication device can define additional constraints on the use of the network slice within the tracking area using network slice availability location information (S-NSSAI location availability information). For example, consider a case where the S-NSSAI of the Configured NSSAI is not available in some cells within the tracking area of ​​the Registration Area. In this case, the network slice availability location information including location information (e.g., cell ID) of a cell in which the S-NSSAI is available among multiple cells within the tracking area is provided to the UE 40.

[0182] The AMF 941 may determine the Target NSSAI by itself or in cooperation with the NSSF 944. The Target NSSAI is information used by the RAN / AN 910 (e.g., NG-RAN) to redirect the UE 40 to cells / tracking areas of other frequency bands and other tracking areas that support the S-NSSAI of the Target NSSAI. The RAN / AN 910 uses this information in addition to information such as the Allowed NSSAI and the RFSP (RAT / Frequency Selection Priority) for the Allowed NSSAI to redirect the UE 40.

[0183] The Target NSSAI includes at least one S-NSSAI in the Requested NSSAI. For example, the Target NSSAI includes at least one S-NSSAI that is not available in the current tracking area but is available in another tracking area in another frequency band or in an area in another frequency band that overlaps with the current tracking area. Furthermore, at least one S-NSSAI in the Requested NSSAI may be optionally added to the Target NSSAI. For example, the S-NSSAI added as an option is an S-NSSAI that is not available in the current tracking area but is available in the same tracking area as the tracking area in which the S-NSSAI included in the Target NSSAI is available.

[0184] The AMF 941 obtains an RFSP index (RAT / Frequency Selection Priority Index) suitable for the Target NSSAI from the PCF 945. Then, the AMF 941 includes the RFSP index in information to be sent to the RAN / AN 910 (e.g., NG-RAN). If the PCF 945 is not installed, the AMF 941 determines the RFSP index according to a locally configured rule. The RAN / AN 910 maps the RFSP index to a locally defined configuration to apply an individual radio resource management policy taking into account the available information. That is, the RAN / AN 910 can select a configuration for a radio resource management policy suitable for the Target NSSAI corresponding to the RFSP index.

[0185] If the RAN / AN 910 can redirect the UE 40 to a new tracking area that supports the Target NSSAI or an S-NSSAI of either the Target NSSAI, the RFSP index associated with the Target NSSAI is considered, otherwise the RFSP index of the Allowed NSSAI is considered.

[0186] In addition, a partial network slice can be provided within a registration area by configuring a Partially Allowed NSSAI and / or an S-NSSAI that is partially rejected within the registration area (S-NSSAIs rejected partially in the RA).

[0187] The S-NSSAI of an Allowed NSSAI can be used in all tracking areas within the registration area, whereas the S-NSSAI of a Partially Allowed NSSAI can only be used in tracking areas corresponding to the list of tracking areas associated with that S-NSSAI.

[0188] Assume that UE 40 supports partial network slicing within a registration area. In this case, AMF 941 configures a registration area for UE 40, taking into account the support status of the S-NSSAI of the Requested NSSAI in the current tracking area and surrounding tracking areas. AMF 941 provides the Partially Allowed NSSAI or the S-NSSAI that is partially rejected within the registration area to UE 40 using a Registration Accept message or a UE Configuration Update Command message.

[0189] For each S-NSSAI of the Partially Allowed NSSAI, AMF941 provides a list of tracking areas in which the S-NSSAI is supported. Alternatively, AMF941 may reject the S-NSSAI with a rejection reason indicating "partially in the RA". For each S-NSSAI of the partially rejected S-NSSAI in the registration area, AMF941 provides a list of tracking areas in which the S-NSSAI is supported or not supported.

[0190] If the S-NSSAI is unavailable or is overloaded, a Network Slice Replacement function may be used to replace the S-NSSAI with an Alternative S-NSSAI.

[0191] The AMF 941 can decide to replace the S-NSSAI with an Alternative S-NSSAI based on a notification from the NSSF 944, the PCF 945, or the OAM (Operations, Administration and Maintenance).

[0192] In the case of roaming, to activate the network slice alternative function of the HPLMN's S-NSSAI, the V-AMF 941-2 can receive notification of the network slice availability of the HPLMN's S-NSSAI from the HPLMN's H-NSSF 944-1 via the V-NSSF 944-2 of the VPLMN.

[0193] The AMF 941 determines an Alternative S-NSSAI for the UE 40 that has registered the S-NSSAI based on a notification from the NSSF 944 or PCF 945 (or based on a local configuration if the NSSF 944 or PCF 945 does not provide an Alternative S-NSSAI).

[0194] The Alternative S-NSSAI must be supported within the registration area of ​​the UE 40. For example, assume that the AMF 941 cannot determine the Alternative S-NSSAI for the S-NSSAI because the NSSF 944 or the PCF 945 does not provide the Alternative S-NSSAI. In this case, the AMF 941 may further negotiate with the PCF 945 to determine the Alternative S-NSSAI.

[0195] The UE 40 notifies the network of its support for the network slice alternative function during the registration process. The PDU session related to the S-NSSAI that needs to be exchanged supports the UE 40 in connected mode (CM-CONNECTED mode) existing in the UE context. To enable this, the AMF 941 provides the UE 40 with an Alternative S-NSSAI for this S-NSSAI, which is included in the Allowed NSSAI and the Configured NSSAI. The AMF 941 may also provide the UE 40 with mapping information between the S-NSSAI and the Alternative S-NSSAI using a UE Configuration Update message.

[0196] After sending the mapping information to the UE 40, the AMF 941 invokes the Update Session Management Context (Nsmf_PDUSession_UpdateSMContext) service for the current PDU session associated with the S-NSSAI exchanged for the Alternative S-NSSAI, and instructs the SMF 946 to update the PDU session required to transition the PDU session to the Alternative S-NSSAI.

[0197] The UE 40 establishes a Non-Access Stratum (NAS) signaling connection through a Service Request procedure or a UE registration procedure. At this time, it is assumed that the AMF 941 decides to exchange S-NSSAIs to support the UE 40 in the CM-IDLE state. At this time, if a PDU session related to the S-NSSAI exists in the UE context, the AMF 941 provides the UE 40 with mapping information between the S-NSSAI and the Alternative S-NSSAI using a UE Configuration Update message or a Registration Accept message.

[0198] Session Establishment Processing Next, the session establishment processing will be described. Fig. 13 is a diagram showing an example of a connection processing in 5GS.

[0199] After powering on, the UE 40 executes a registration procedure and is registered in the network. The UE 40 updates the registration area (i.e., tracking area) on a registration area basis. Here, the UE 40 can include a UE radio capability ID in a registration request message. The AMF 941 can hold the UE radio capability information of the UE 40 according to the UE radio capability ID notified from the UE 40. Furthermore, the RAN / AN 910 can acquire the UE radio capability information from the UE 40 or the AMF 941.

[0200] During communication, UE 40 transitions to the RRC_IDLE and CM-IDLE states (step S101). UE 40 in the RRC_IDLE and CM-IDLE states performs cell reselection (step S102) and camps on an appropriate cell that meets predetermined criteria.

[0201] UE 40 determines to use an S-NSSAI corresponding to the application to be used from among the Allowed NSSAIs (step S103). Subsequently, UE 40 transmits an RRC Setup Request message to RAN / AN 910 of the base station that manages the cell where UE 40 is camped (step S104).

[0202] Upon receiving this, the RAN / AN 910 transmits an RRC Setup message to the UE 40 (step S105). The UE 40 transitions to an RRC_CONNECTED and CM-IDLE state (step S106), and returns an RRC Setup Complete message to the RAN / AN 910 (step S107). This completes the RRC setup process.

[0203] Next, the UE 40 transmits a PDU SESSION ESTABLISHMENT REQUEST message, which is a NAS message, to the AMF 941 (step S108). As a result, a PDU session establishment process is executed between the UE 40 and the DN 930 via the RAN / AN 910 and the UPF 920 (step S109).

[0204] The UE 40 transitions to an RRC_CONNECTED and CM-CONNECTED state (step S110). Note that the PDU SESSION ESTABLISHMENT REQUEST message can include the S-NSSAI selected by the UE 40.

[0205] The AMF 941 sends an INITIAL CONTEXT SETUP REQUEST message to the RAN / AN 910 (step S111). The INITIAL CONTEXT SETUP REQUEST message may include at least one of a PDU session context, a security key, a UE radio capability, and a UE security capability. The INITIAL CONTEXT SETUP REQUEST message may also include an Allowed NSSAI. The INITIAL CONTEXT SETUP REQUEST message may also include an S-NSSAI for each PDU session.

[0206] The RAN / AN 910 sets a UE context for the UE 40 and transmits a SecurityModeCommand message to the UE 40 (step S112). The SecurityModeCommand message includes an integrity algorithm selected by the RAN / AN 910.

[0207] The UE 40 verifies the integrity of the received SecurityModeCommand message to confirm the validity of the message, and returns a SecurityModeComplete message to the RAN / AN 910 (step S113).

[0208] The RAN / AN 910 transmits an RRCReconfiguration message to the UE 40 in order to set up a Signaling Radio Bearer (SRB) 2 and a Data Radio Bearer (DRB) (step S114). The UE 40, having received this message, returns an RRCReconfigurationComplete message to the RAN / AN 910 (step S115). As a result, the SRB 2 and the DRB are established between the UE 40 and the RAN / AN 910.

[0209] The RAN / AN 910 sends an INITIAL CONTEXT SETUP REQUEST RESPONSE message to the AMF 941 to notify that the UE context setup process has been completed (step S116).

[0210] 14A and 14B are sequence diagrams showing an example of a PDU session establishment process. Specifically, FIG. 14A and FIG. 14B are sequence diagrams showing an example of a PDU session establishment process (step S109 shown in FIG. 13) started by a PDU SESSION ESTABLISHMENT REQUEST message.

[0211] When the AMF 941 receives a PDU session establishment request message from the UE 40 (step S108 shown in FIGS. 13 and 14A), it performs SMF selection (step S201 shown in FIG. 14A).

[0212] The AMF 941 sends an Nsmf_PDUSession_Create_SMContext Request message to the selected SMF 946 (step S202). The Nsmf_PDUSession_Create_SMContext Request message includes a Subscription Permanent Identifier (SUPI), an S-NSSAI, and a UE Requested Data Network Name (DNN) or a DNN.

[0213] The DNN (Data Network Name) corresponds to the APN (Access Point Name) used in systems prior to 4G. The S-NSSAI is information for assisting in the selection of a network slice (network slice selection support information).

[0214] If session management subscription data corresponding to the SUPI, S-NSSAI, and DNN (Data Network Name) is not available, the SMF 946 uses a Nudm_SDM_Get message to acquire the session management subscription data from the UDM 947. In addition, the SMF 946 registers the session management subscription data with the UDM 947 using a Nudm_SDM_Subscribe message so that it can be notified when the session management subscription data is updated.

[0215] Upon receiving the Nsmf_PDUSession_Create_SMContext Request message, the SMF 946 creates an SM context if it can process the message. The SMF 946 returns an Nsmf_PDUSession_Create_SMContext Response message including the SM context ID to the AMF 941 (step S203).

[0216] If it is necessary to perform a second authentication and authorization process by the DN-AAA server during the PDU session establishment process, the SMF 946 initiates PDU Session Authentication / Authorization (step S204).

[0217] The SMF 946 performs PCF selection if dynamic policy and charging control (PCC) is applied to the PDU session to be established (step S205). Alternatively, the SMF 946 may apply a local policy.

[0218] In addition, the SMF 946 may perform an SM Policy Association Establishment Procedure to establish an SM Policy Association with the PCF 945 and obtain a default PCC rule for the PDU session (step S206). This allows the PCC rule to be obtained before selecting the UPF 920.

[0219] The SMF 946 performs UPF selection (step S207) according to a preset rule or the PCC rule acquired in step S206. As a result, the SMF 946 selects one or more UPFs 920. The SMF 946 transmits an N4 Session Establishment Request message to the selected UPF 920 (step S208).

[0220] The N4 session establishment request message is used to set an N4 rule for controlling uplink and downlink traffic in the UPF 920. The N4 rule is information related to, for example, a packet detection rule (PDR), a forwarding action rule (FAR), a QoS enforcement rule (QER), a usage reporting rule (URR), and a buffering action rule (BAR).

[0221] The PDR contains information necessary for classifying packets in the UPF 920. The FAR contains information regarding how to handle a particular packet, such as forward, duplicate, drop, or buffer. The QER contains information regarding an indication of the QoS to be applied to the traffic. The URR contains information necessary for traffic metering and reporting. The BAR contains information regarding how long and how much data will be buffered and how to notify the control plane.

[0222] The UPF 920 that has received the N4 session establishment request returns an N4 session establishment response message to the SMF 946 (step S209). Note that, if multiple UPFs 920 are selected for the PDU session in step S207, the N4 session establishment process is initiated for each UPF 920.

[0223] The SMF 946 sends a Namf_Communication_N1N2MessageTransfer message to the AMF 941 (step S210). The Namf_Communication_N1N2MessageTransfer message may include at least one of a PDU session ID, N2SM information, CN tunnel information, S-NSSAI, and an N1SM container.

[0224] The N2SM information may include at least one of a PDU session ID, a QFI, and a QoS profile.

[0225] If multiple UPFs 920 are used for a PDU session, the CN tunnel information includes tunneling information related to these multiple UPFs 920 terminating at N3.

[0226] The N1SM container includes a PDU Session Establishment Accept and QoS rules that the AMF 941 must provide to the UE 40. The PDU Session Establishment Accept includes an S-NSSAI.

[0227] The Namf_Communication_N1N2MessageTransfer message includes a PDU session ID so that AMF941 knows which access to use for UE40.

[0228] 14B, the AMF 941 sends an N2 PDU Session Request message to the RAN / AN 910 (step S211). The N2 PDU Session Request message includes a NAS message including a PDU session ID and an N1SM container destined for the UE 40, and the N2SM information received from the SMF 946.

[0229] The RAN / AN 910 acquires the PDU session ID, QFI, QoS profile, etc. from the N2SM information included in the N2 PDU session request message. The RAN / AN 910 also transfers the NAS message included in the N2 PDU session request message to the UE 40 (step S212). As described above, the NAS message includes the PDU session ID and an N1SM container, and the N1SM container includes a PDU session establishment permission and a QoS rule.

[0230] The RAN / AN 910 also assigns AN tunnel information (AN Tunnel Info) to the PDU session. Here, the AN tunnel information includes the tunnel endpoints of each participating RAN / AN node and the QFIs assigned to each tunnel endpoint. The RAN / AN 910 updates N2SM information for notification to the SMF 946. Here, the N2SM information may include at least one of a PDU session ID, AN tunnel information, a list of allowed or denied QFI(s), and a User Plane Enforcement Policy Notification.

[0231] The RAN / AN 910 returns an N2 PDU Session Response message including the N2SM information to the AMF 941 (step S213).

[0232] The AMF 941 acquires the N2SM information through the N2 PDU session response received from the RAN / AN 910. Then, the AMF 941 forwards an Nsmf_PDUSession_UpdateSMContext Request message including the SM context ID and the acquired N2SM information to the SMF 946 (step S214).

[0233] The SMF 946 initiates an N4 session modification procedure between the SMF 946 and the UPF 920. Then, the SMF 946 sends an N4 session modification request message to the UPF 920 (step S215). The SMF 946 provides the UPF 920 with AN tunnel information in addition to the forwarding rule.

[0234] The UPF 920 returns an N4 Session Modification Response message to the SMF 946 (step S216). Note that, when multiple UPFs 920 are used in the PDU session, the above-mentioned session modification process is performed on all UPFs 920 that terminate N3.

[0235] The above processing completes the PDU session establishment processing shown in step S109 of FIG.

[0236] <3-4. Flow-Based QoS Control> Figure 15 shows an example of a 5GS QoS architecture. Figure 15 is based on 3GPP TS38.300. At the NAS (Non-Access Stratum) level, a QoS flow is the finest granularity for distinguishing different QoS within a PDU (Protocol Data Unit) session. Within a PDU session, a QoS flow is identified by a QFI (QoS Flow ID).

[0237] 5GS allows for finer granularity in identifying data by PDU sets within QoS flows, which are the finest granularity in terms of QoS control. 5GS can apply PDU set level QoS control in addition to QoS flow level QoS control.

[0238] The PCF 945 can associate information about the AF session with the PDU session. The AF 948 can request, via the AF session with the PCF 945, that a data session (e.g., a PDU session) for the UE 40 be established as a session with a specific QoS (e.g., low latency or low jitter).

[0239] The SMF 946 associates PCC rules with QoS flows based on the QoS and service requirements. The SMF 946 assigns a QFI to the new QoS flow and obtains the PCC rules and other information associated with the QoS flow from the PCF 945.

[0240] From this PCC rule, the SMF 946 obtains the QoS profile of the QoS flow, instructions regarding the corresponding UPF 920 (e.g., N4 rule), and QoS rule.

[0241] The base station (gNB) of the RAN / AN 910 can establish at least one DRB (Data Radio Bearer) together with a PDU session with each UE 40. The DRB is a logical path for transmitting data.

[0242] The 5G QoS model supports GBR (Guaranteed flow Bit Rate), which guarantees bandwidth, and Non-GBR (Non-Guaranteed flow Bit Rate), which does not guarantee bandwidth. Furthermore, Delay-critical GBR is supported for TSC (Time Sensitive Communication) QoS flows.

[0243] The RAN / AN 910 and the core network CN ensure quality of service by mapping each packet to the appropriate QoS flow and DRB, i.e., a two-stage mapping is performed: mapping between IP flows and QoS flows in the NAS, and mapping between QoS flows and DRBs in the AS.

[0244] At the NAS level, a QoS flow is characterized by a QoS profile provided from the core network CN to the RAN / AN 910 and a QoS rule provided from the core network CN to the UE 40 .

[0245] The QoS profile is used by the RAN / AN 910 to determine how to handle traffic over the air interface, and the QoS rules are used to instruct the UE 40 on the mapping between user plane traffic in the uplink and QoS flows.

[0246] Therefore, for a multicast MBS (Multicast / Broadcast Service) session, the QoS rules of the MBS QoS flow and the QoS parameters at the QoS flow level are not provided to the UE 40 .

[0247] The QoS profile is provided to the RAN / AN 910 from the SMF 946 via the AMF 941 and reference point N2, or is pre-configured in the RAN / AN 910.

[0248] The SMF 946 may also provide one or more QoS rules and, if necessary, QoS flow-level QoS parameters associated with the QoS rules to the UE 40 via the AMF 941 and reference point N1.

[0249] Additionally or alternatively, reflective QoS control may be applied to the UE 40. Reflective QoS control is QoS control that monitors the QFI of downlink packets and applies the same mapping to uplink packets.

[0250] A QoS flow can be a GBR QoS flow or a non-GBR QoS flow depending on its QoS profile, which includes QoS parameters such as 5QI (5G QoS Identifier) ​​and ARP (Allocation and Retention Priority).

[0251] The ARP includes information regarding priority level, preemption capability, and preemption vulnerability.

[0252] Priority defines the relative importance of a QoS flow, with the lowest Priority Level indicating the highest priority.

[0253] Preemption capability is a metric that defines whether a QoS flow can seize resources already allocated to other, lower priority QoS flows, while preemption vulnerability is a metric that defines whether a QoS flow can give up its allocated resources to other, higher priority QoS flows.

[0254] Preemption capability and preemption vulnerability can be set to either "enabled" or "disabled."

[0255] Additionally, the QoS profile of a QoS flow may include PDU Set QoS Parameters.

[0256] For a GBR QoS flow, the QoS profile may include, for example, at least one of the following information: GFBR for uplink and downlink; MFBR (Maximum Flow Bit Rate) for uplink and downlink; Maximum Packet Loss Rate for uplink and downlink; Delay Critical Resource Type; and Notification Control.

[0257] In a non-GBR QoS flow, the QoS profile may include at least one of a Reflective QoS Attribute (RQA) and Additional QoS Flow Information.

[0258] The notification control of the QoS parameters indicates whether a notification is required from the RAN / AN 910 when a QoS flow cannot meet the GFBR. If the notification control is "enabled" for a GBR QoS flow and it is determined that the GFBR cannot be met, the RAN / AN 910 sends a notification to the SMF 946.

[0259] In this case, the RAN / AN 910 must maintain the GBR QoS flow unless a special condition exists that requires the RAN / AN 910 to release RAN resources for the GBR QoS flow, such as at least one of a radio link failure and RAN internal congestion.

[0260] If it is determined that the GFBR is again satisfied for the QoS flow, the RAN / AN 910 sends a new notification to that effect to the SMF 946.

[0261] An alternative QoS profile can also be used to control the notification of QoS parameters. The alternative QoS profile consists of a set of packet delay budget (PDB), packet error rate (PER), averaging window, and GFBR. The alternative QoS profile for a delay-critical GBR QoS flow can further include information on maximum data burst volume (MDBV).

[0262] When the RAN / AN 910 sends a notification to the SMF 946 that the QoS profile cannot be satisfied, the RAN / AN 910 checks, based on the list of alternative QoS profiles, whether there is a higher-priority alternative QoS profile that can currently satisfy the QoS profile. If there is a corresponding alternative QoS profile, the RAN / AN 910 indicates to the SMF 946 that there is an alternative QoS profile that can currently satisfy the QoS profile. To do this, the RAN / AN 910 includes information referencing the alternative QoS profile in the notification sent to the SMF 946. This control allows the SMF 946 to determine that even the lowest-priority alternative QoS profile cannot satisfy the QoS profile.

[0263] The Aggregate Maximum Bit Rate (AMBR) is related to the Session-AMBR of each PDU session and the UE-AMBR of each UE 40 for each PDU session. The Session-AMBR limits the aggregate bit rate expected to be provided across all Non-GBR QoS flows for a particular PDU session. The Session-AMBR is managed by the UPF 920. The UE-AMBR also limits the aggregate bit rate expected to be provided across all Non-GBR QoS flows for a UE 40. The UE-AMBR is managed by the RAN / AN 910.

[0264] Furthermore, a Slice Maximum Bit Rate (S-MBR) related to the network slice (S-NSSAI) may be set for each UE 40. The S-MBR may be included in the subscriber information as a Subscribed UE-Slice-MBR.

[0265] The UE-Slice-MBR limits the aggregate bit rate expected to be provided across all GBR and non-GBR QoS flows belonging to all PDU sessions established by UE 40 for the same network slice (S-NSSAI).

[0266] The RAN / AN 910 receives a UE-Slice-MBR corresponding to the network slice (S-NSSAI) from the AMF 941. The RAN / AN 910 sets the Session-AMBR and MFBR for the UE 40 so that the sum of the Session-AMBR and MFBR of the GBR QoS flow of all PDU sessions belonging to this network slice (S-NSSAI) is the UE-Slice-MBR.

[0267] The 5QI is related to QoS features. It provides guidelines (policies) for setting node-specific parameters for each QoS flow. A communication device can learn standardized or pre-configured 5G QoS features from the 5QI. Standardized or pre-configured 5G QoS features are not explicitly signaled. Signaled QoS features can be part of a QoS profile.

[0268] The QoS characteristics may include information regarding at least one of a resource type, a priority, a packet delay tolerance, a packet error rate, an averaging window, and a maximum data burst volume.

[0269] The resource type is a GBR QoS flow, a non-GBR QoS flow, or a delay-critical GBR QoS flow. The packet delay tolerance may include a packet delay tolerance in the core network CN.

[0270] At the AS level, DRB defines how packets are handled on the radio interface (Uu interface). DRB provides uniform packet forwarding treatment for any packet.

[0271] The RAN / AN 910 maps QoS flows to DRBs based on the QFI and the QoS profile configured for that QFI. The RAN / AN 910 can establish different DRBs for packets requiring different packet forwarding treatments (see FIG. 15).

[0272] The RAN / AN 910 can also multiplex multiple QoS flows belonging to the same PDU session into the same DRB (see FIG. 15).

[0273] In the uplink, the mapping of QoS flows to DRBs is controlled by mapping rules, which are signaled in two different ways:

[0274] One method is called Reflective Mapping, in which UE 40 monitors the QFI of downlink packets for each DRB and applies the same mapping to uplink packets.

[0275] The other method is called explicit configuration, in which the mapping rule of QoS flows to DRBs is explicitly signaled by RRC (Radio Resource Control).

[0276] In the downlink, the QFI is signaled by the RAN / AN 910 over the Uu interface for Reflective Quality of Service (RQoS). However, neither the RAN / AN 910 nor the NAS signals the QFI for a DRB over the Uu interface unless they use reflective mapping for the QoS flows carried on that DRB.

[0277] In the uplink, the RAN / AN 910 can configure signaling of QFI to the UE 40 on the Uu interface. The RAN / AN 910 can also configure a default DRB for each PDU session. If an uplink packet does not fit either the explicit configuration or the reflective mapping, the UE 40 maps the packet to the default DRB of the PDU session.

[0278] For Non-GBR QoS flows, the core network CN may send additional QoS flow information parameters associated with any QoS flow to the RAN / AN 910 to indicate an increased frequency of certain traffic compared to other Non-GBR QoS flows within the same PDU session.

[0279] How multiple QoS flows within a PDU session are mapped to one DRB is up to the RAN / AN 910. For example, the RAN / AN 910 may map a GBR QoS flow and a non-GBR QoS flow to the same DRB or to separate DRBs. The RAN / AN 910 may also map multiple GBR QoS flows to the same DRB or to separate DRBs.

[0280] In 5G NR, a new SDAP (Service Data Adaptation Protocol) sublayer is introduced for QoS control via QoS flows. The SDAP sublayer maps QoS flow traffic to an appropriate DRB. The SDAP sublayer can have multiple SDAP entities. The SDAP sublayer has an SDAP entity for each PDU session on the Uu interface. The establishment or release of an SDAP entity is performed by RRC.

[0281] QoS flows are identified by a QFI in the PDU session container contained in the GPRS Tunneling Protocol (GTP)-U header. PDU sessions are identified by a GTP-UTEID (GTP-U Tunnel Endpoint ID). The SDAP sublayer maps each QoS flow to a specific DRB.

[0282] When the PCF 945 receives a QoS monitoring request from the AF 948, it generates an authorized QoS monitoring policy and provides it to the SMF 946. At this time, the PCF 945 may include the QoS monitoring policy in a PCC rule. Note that the AF 948 may include the QoS monitoring request in an AF request (described later).

[0283] Here, the AF 948 can request monitoring of packet delay, monitoring of congestion information, monitoring of data rate, monitoring of QoS notification, and the like as QoS monitoring.

[0284] The monitoring of packet delay is the measurement of UL (Uplink) packet delay, DL (Downlink) packet delay, or RT (Round Trip) packet delay between the UE 40 and the PSA-UPF 920 .

[0285] The congestion information monitoring is monitoring of congestion information related to UL and / or DL ​​QoS flows provided by the RAN / AN 910.

[0286] Data rate monitoring is the measurement of UL and / or DL ​​data rates for each QoS flow.

[0287] QoS notification monitoring is monitoring of notification control information of QoS parameters provided by the RAN / AN 910.

[0288] The PCF 945 may include in the PCC rule an indication to perform traffic parameter measurements to detect jitter occurring at N6 and measurements of UL period and / or DL ​​period according to local policy, and may then send the PCC rule including this indication to the SMF 946. 5GS can also treat these measurements as QoS monitoring.

[0289] The SMF 946 can activate end-to-end UL / DL / RT packet delay measurements for QoS flows between the UE 40 and the PSA-UPF 920. The SMF 946 can perform this activation during the PDU session establishment procedure or during the PDU session modification procedure.

[0290] The SMF 946 sends a QoS monitoring request to the UPF 920 via reference point N4. The SMF 946 then sends N2 signaling to request QoS monitoring between the UPF 920 and the RAN / AN 910.

[0291] The SMF 946 requests QoS monitoring based on the QoS monitoring policy received from the PCF 945 or a pre-configured locally authorized QoS monitoring policy. The QoS monitoring request includes monitoring variables determined by the SMF 946.

[0292] The RAN / AN 910 measures the delay of UL / DL packets in the RAN / AN 910. The RAN / AN 910 provides the measurement results to the UPF 920 via reference point N3.

[0293] The UPF 920 calculates the delay of UL / DL packets at the reference point N3 or N9, and sends the QoS monitoring result to the SMF 946 based on a predetermined condition, such as one-time, periodic, or event-triggered.

[0294] Furthermore, the UPF 920 may transmit the QoS monitoring results to the AF 948 via the locally deployed NEF 942. Here, the QoS monitoring results are, for example, as follows: Measurement results of the bit rate (e.g., average bit rate, maximum bit rate) of each GBR QoS flow of the target PDU session Measurement results of the total bit rate of all Non-GBR QoS flows of the target PDU session Measurement results of the packet error rate of the target PDU session Measurement results of the total bit rate of all Non-GBR QoS flows of the target UE 40 Measurement results of the packet error rate of the target UE 40 Measurement results of the UL / DL packet delay

[0295] In addition, the AF 948 may transmit a request for monitoring and reporting packet delay variation together with the request for measuring packet delay to the PCF 945. Here, the packet delay variation is, for example, the variation in packet delay measured between the UE 40 and the PSA-UPF 920. The packet delay variation is one definition for evaluating jitter during packet transmission.

[0296] The packet delay variation request may include, for example, at least one of the following: - Packet delay variation parameter to be measured (UL, DL, or Round Trip (RT) packet delay variation) - Reporting frequency (event triggered or periodic)

[0297] In response to a packet delay variation monitoring request from the AF 948, the PCF 945 starts a QoS monitoring process. The PCF 945 obtains the UL, DL, or RT (Round Trip) QoS monitoring results from the SMF 946. The PCF 945 derives 5GS packet delay variation based on the QoS monitoring results and reports it to the AF 948.

[0298] The delay of the UL / DL packet is a delay including the delay of the UL / DL packet in the RAN / AN 910 portion obtained from the RAN / AN 910 and the delay of the UL / DL packet at the reference point N3 or N9.

[0299] 3-5. AI / ML Model The information processing device of this embodiment (for example, at least one of the server 10, the management device 20, the base station 30, and the terminal device 40) can analyze and / or synthesize data using an AI (Artificial Intelligence) / ML (Machine Learning) model. In the following description, the AI / ML model may be referred to as a learning model, a trained model, or simply a model.

[0300] A learning model is a machine learning model generated by a learning process using machine learning. Machine learning is, for example, one of the artificial intelligence techniques that allows a computer to perform recognition, judgment, or estimation similar to humans. The processes performed by machine learning include two processes: a learning process and a determination process for recognition, judgment, or estimation.

[0301] In the learning process, processing is performed to learn a learning model (e.g., training using learning data). In the learning process, an information processing device that performs the learning (hereinafter referred to as a learning device) uses the learning data to learn a learning model (e.g., a neural network model). For example, in the case of a neural network model, the weight coefficient of each edge is optimized during the learning process. The model extracted as a result of the learning process is sometimes referred to as a trained model.

[0302] The learning device is, for example, at least one of the MTLF (Model Training logical function) of the NWDAF 951 mentioned above, the server 10, the management device 20, the base station 30, and the terminal device 40, or two or more devices that cooperate with each other.

[0303] The determination process is a process for recognition, judgment, or estimation. In the determination process, for example, an information processing device that performs the determination (hereinafter referred to as a determination device) inputs data related to unknown data into a learning model (trained model). The learning model outputs a result of recognition, judgment, or estimation for the unknown data as a result of calculation processing. The determination device may be the same device as the learning device, or may be a different device.

[0304] The learning model is, for example, a neural network model. FIG. 16 is a diagram for explaining a neural network model. The neural network model is composed of layers called an input layer, a hidden layer (or intermediate layer), and an output layer, each of which includes a plurality of nodes, and each node is connected via an edge. Each layer has a function called an activation function, and each edge is weighted. The learning model has one or more intermediate layers (or hidden layers). When the learning model is a neural network model, learning the learning model means, for example, setting the number of hidden layers (or intermediate layers), the number of nodes in each layer, or the weight of each edge.

[0305] Here, the neural network model may be a deep learning model. By using a trained deep learning model that has been trained using a huge amount of data, the accuracy of recognition, judgment, or estimation is improved. Typical algorithms used in deep learning include, for example, the following. The algorithm of the AI / ML model used in this embodiment may be at least one of the following:

[0306] ・Deep Neural Network (DNN) ・Convolution Neural Network (CNN) ・Recurrent Neural Network (RNN) ・Fully connected neural network ・Long Short-Term Memory (LSTM) ・Autoencoder

[0307] A deep neural network (DNN) has two or more hidden layers, which allows it to achieve higher accuracy in recognition, judgment, or estimation than a conventional neural network with one hidden layer.

[0308] In a CNN, the hidden layer is composed of layers called convolution layers and pooling layers. In the convolution layers, filtering is performed using convolution operations, and data called feature maps, for example, are extracted. In the pooling layers, the information in the feature maps output from the convolution layers is compressed and down-sampling is performed.

[0309] The RNN has a network structure in which values ​​of hidden layers are recursively input to hidden layers, and is used to process, for example, short-term time-series data.

[0310] In a fully connected neural network, all of the intermediate layers are fully connected layers. In other words, in a fully connected neural network, all nodes between the intermediate layers are connected to each other. Fully connected neural networks have been widely applied, mainly in the field of speech recognition.

[0311] In LSTM, parameters called memory cells that hold the state of the hidden layer are introduced into the output of the hidden layer of the RNN. This allows LSTM to retain the influence of outputs from the distant past. In other words, LSTM processes time-series data over a longer period than RNN.

[0312] Autoencoders extract low-dimensional features that can reproduce input data through unsupervised learning. Autoencoders are useful for noise removal and dimensionality reduction.

[0313] Furthermore, the learning model is not limited to a neural network model. For example, the learning model may be a model based on reinforcement learning. In reinforcement learning, behaviors (settings) that maximize value are learned through trial and error. Alternatively, the learning model may be a logistic regression model.

[0314] Furthermore, the learning model may be composed of a plurality of models. For example, the learning model may be composed of a plurality of neural network models. More specifically, the learning model may be composed of a plurality of neural network models selected from the above-mentioned plurality of neural network models (e.g., DNN, CNN, RNN, LSTM, etc.). When the learning model is composed of a plurality of neural network models, these plurality of neural network models may be in a subordinate relationship or in a parallel relationship.

[0315] The learning model can also be referred to as an AI model, an ML model, or a trained model. In the following description, the learning model may be simply referred to as a model.

[0316] Any learning algorithm may be used for the learning. For example, the information processing device may perform learning of the learning model using a learning algorithm such as a neural network, a support vector machine, clustering, reinforcement learning, a random forest, or a decision tree.

[0317] <3-6. Semantic Communication> Mobile communication systems up to 5G are designed based on information theory, i.e., Shannon's theory, which focuses on the maximum data rate that can be supported by a communication channel. Source data is transmitted so that it can be restored in its original form at the receiving end.

[0318] Meanwhile, in preparation for 6G, the concept of semantic communication, which transmits only the meaning of source data through communication systems, is gaining attention. Semantic communication is expected to be a communication method that utilizes machine intelligence (e.g., a communication method suitable for robotics applications) realized through the synergistic effects of IoT (Internet of Things) and AI (Artificial Intelligence).

[0319] In this embodiment, the concept of semantic communication also includes communication that propagates only the characteristic components of source data.

[0320] Traditionally, human-to-human (H2H) communication, such as phone calls, has been the norm. However, with the spread of IoT and AI, there is now a demand for human-to-machine (H2M) and machine-to-machine (M2M) communication.

[0321] For example, in H2M communication, it is necessary to transmit information that can be understood not only by humans but also by machines, so that humans and machines can communicate (interact) and converse. On the other hand, in M2M communication, it is not necessarily necessary for humans to understand the information, but rather the transmission of information necessary to efficiently execute specific computational processes between multiple machines. In other words, conventional wireless communication systems designed for human-to-human communication are not necessarily efficient for human-to-machine or machine-to-machine communication.

[0322] 5G introduces the aforementioned concept of network slicing to provide communication methods suited to different communication purposes. Furthermore, 5G also supports flow-level QoS control so that different QoS controls can be applied to each data flow. For example, a Service Data Adaptation Protocol (SDAP) sublayer has been newly introduced to the protocol stack that processes the user plane (U-plane) for data flow-level QoS control. Here, the SDAP sublayer provides QoS flows to 5G Core (5GC). The SDAP sublayer provides functions or services such as mapping QoS flows to data radio bearers (DRBs) and marking QoS flow identifiers (QFIs) for downlink (DL) and uplink (UL) packets.

[0323] On the other hand, the other sublayers of the protocol stack that processes the user plane follow the conventional sublayers of PDCP (Packet Data Convergence Protocol), RLC (Radio Link Control), MAC (Media Access Control), and PHY (PHYsical).

[0324] In other words, 5G provides a mechanism for distinguishing between H2H (Human-to-Human), H2M (Human-to-Machine), and M2M (Machine-to-Machine) communications, but it does not necessarily mean that a communication method suitable for each can be provided from a perspective other than QoS control (i.e., priority control).

[0325] For example, a layer connection approach and a partitioned neural network approach are known for designing an architecture for this semantic communication.

[0326] <3-6-1. Layer-coupling> Shannon proved that for P2P (Point-to-Point) links with asymptotically long code block lengths, separation of the source and channel in encoding / decoding is optimal.

[0327] For example, by encoding the source symbols together, the average code length per symbol can be reduced, and according to the source coding theorem known as Shannon's First Theorem, the average code length per symbol can be made closer to the lower bound of entropy (source encoding / source decoding).

[0328] Furthermore, according to the channel coding theorem, also known as Shannon's second theorem, when a codeword is transmitted at a coding rate R (bits / symbol) over a channel with a channel capacity C (bits / symbol), if R is smaller than C, then there exists a code that can reduce the decoding error rate to close to zero by making the code length sufficiently large (channel encoding / channel decoding).

[0329] Conventional wireless communication systems (i.e., pre-5G mobile wireless communication systems) are designed based on these theories, so the source encoder / decoder and the channel encoder / decoder can be optimized as separate modules.

[0330] The layer integration approach is a design method in which the semantic communication layer and the conventional wireless access layer cooperate to provide semantic communication, so that the conventional protocol stack can be reused as much as possible.

[0331] 17 is a diagram showing an example of a conventional user plane protocol stack in wireless access. In 5G, for example, the user plane protocol stack of the wireless access layer 44 of the UE 40 is composed of an SDAP sublayer 441, a PDCP sublayer 442, an RLC sublayer 443, a MAC sublayer 444, and a PHY sublayer 445.

[0332] Similarly, the user plane protocol stack of the radio access layer 34 of the BS 30 (e.g., gNB 30) is, for example, in 5G, composed of an SDAP sublayer 341, a PDCP sublayer 342, an RLC sublayer 343, a MAC sublayer 344, and a PHY sublayer 345. Here, the BS 30 is a node corresponding to the RAN / AN 910 in the 5GS network architecture.

[0333] 18 is a diagram showing an example of the configuration of a communication device for layer-bonding. Layer-bonding uses a conventional protocol stack. That is, the UE 40 uses the radio access layer 44, and the BS 30 uses the radio access layer 34.

[0334] The transmitting device 50 is composed of an application layer 510, a semantic process layer 520, and a radio access layer 530. Here, the radio access layer 530 corresponds to the radio access layer 44 in the UE 40, and corresponds to the radio access layer 34 in the BS 30.

[0335] The receiving device 60 is composed of an application layer 610, a semantic process layer 620, and a radio access layer 630. Here, the radio access layer 630 corresponds to the radio access layer 44 in the UE 40 and the radio access layer 34 in the BS 30.

[0336] The semantic process layer 520 and / or the semantic process layer 620 is a layer that provides support information for the second communication to, for example, one or more sublayers constituting a pre-5G protocol stack (for example, at least one of a plurality of sublayers constituting the radio access layer 44). Here, the semantic process layer 620 may be configured using an AI / ML model.

[0337] In the case of semantic communication, in the transmitting device 50, source data provided by the application layer 510 is processed by the semantic process layer 520 and further processed by the radio access layer 630, which includes channel encoding, before being transmitted to the receiving device 60 via a channel.

[0338] Data received from the transmitting device 50 is processed in the radio access layer 630 of the receiving device 60, including channel decoding, and further processed in the semantic process layer 620. The processed data is then output to the application layer 610.

[0339] It should be noted that the semantic process layer 520 may be implemented in the application layer 510. Similarly, the semantic process layer 620 may be implemented in the application layer 610.

[0340] In the uplink, the transmitting device 50 is the UE 40 (terminal device 40), and the receiving device 60 is the BS 30 (base station 30). In the downlink, the transmitting device 50 is the BS 30 (base station 30), and the receiving device 60 is the UE 40 (terminal device 40).

[0341] <3-6-2. Split Neural Network> In the region of code lengths that cannot be considered as asymptotically long code block lengths, source-channel separation is not necessarily optimal. For this reason, joint source-channel encoding / decoding using finite code lengths can be considered as one approach. Furthermore, joint source-channel encoding / decoding can utilize AI technology, which has been evolving rapidly in recent years.

[0342] 19 is a diagram showing an example of the configuration of a communication device for a split neural network. Here, the communication device may be a transmitting device 50 or a receiving device 60. The transmitting device 50 is, for example, a UE 40 (terminal device 40) or a BS 30 (base station 30). The receiving device 60 is, for example, a BS 30 (base station 30) or a UE 40 (terminal device 40).

[0343] The partitioned neural network approach is a semantic communication method that configures an end-to-end (E2E) deep neural network (DNN). This approach is not limited to conventional protocol stacks (i.e., the conventional user plane protocol stack shown in FIG. 17 ), but instead integrates the semantic processing layer and the physical layer according to a unified source-channel coding / decoding approach to configure an end-to-end (E2E) deep neural network (DNN).

[0344] The deep neural network is divided into an encoder 540 (transmit encoding unit) and a decoder 640 (receive decoding unit). The encoder 540 is a joint source-channel encoder on the transmit side, and the decoder 640 is a joint source-channel decoder on the receive side.

[0345] The transmitting device 50 includes an application layer 510 and an encoder 540 (integrated source-channel encoder). The encoder 540 includes a source encoder 541 and a channel encoder 542 equivalently.

[0346] The receiving device 60 comprises an application layer 610 and a decoder 640 (integrated source channel decoder). Here, the decoder 640 equivalently includes a source decoder 641 and a channel decoder 642.

[0347] A deep neural network including a propagation channel is divided into an encoder 540 (joint source-channel encoder) and a decoder 640 (joint source-channel decoder). That is, one of the divided deep neural networks (first deep neural network) is set as the encoder 540 (joint source-channel encoder), and the other (second deep neural network) is set as the decoder 640 (joint source-channel decoder).

[0348] A part of the first deep neural network acts as a source encoder 541, and the remaining part of the first deep neural network acts as a channel encoder 542. In this case, the encoder 540 does not need to specify the split points within the first deep neural network.

[0349] Similarly, part of the second deep neural network acts as a channel decoder 642, and the remaining part of the second deep neural network acts as a source decoder 641. In this case, it is not necessary to specify the split points in the second deep neural network in the decoder 640.

[0350] Source data provided from the application layer 510 of the transmitting device 50 is processed by an encoder 540 that constitutes a first deep neural network. The processed intermediate layer data is transmitted to the receiving device 60 via a channel.

[0351] The receiving device 60 receives the intermediate layer data from the transmitting device 50. The intermediate layer data is processed by a decoder 640 that constitutes a second deep neural network. The output layer data of the second deep neural network is output to the application layer 610.

[0352] In the uplink, the transmitting device 50 is the UE 40 (terminal device 40), and the receiving device 60 is the BS 30 (base station 30). In the downlink, the transmitting device 50 is the BS 30 (base station 30), and the receiving device 60 is the UE 40 (terminal device 40).

[0353] <<4. Example of Operation of Communication System>> Based on the above, an example of operation of the communication system 1 will be described.

[0354] In the following description, each information processing device (e.g., server 10, management device 20, base station 30, and terminal device 40) included in the communication system 1 is assumed to support multiple communication modes including a first communication and a second communication. That is, each information processing device included in the communication system 1 is capable of processing the first communication and the second communication. As described above, the first communication is a communication mode (e.g., a communication mode provided by mobile communication systems prior to the fifth generation) in which source data is propagated as information that can be restored to the same form by a receiving communication device. The second communication is, for example, a communication mode in which part or all of information extracted from source data using an AI / ML model is propagated to the receiving side. The second communication is, for example, semantic communication.

[0355] The first communication can be rephrased as a first communication form, a first communication means, or a first communication method, and the second communication can be rephrased as a second communication form, a second communication means, or a second communication method.

[0356] 4-1. First Example First, the operation of the communication system 1 according to the first example will be described.

[0357] <4-1-1. Example of functional configuration of communication device> Fig. 20 is a diagram showing an example of the functional configuration of a communication device of this embodiment. The communication device may be a terminal device 40 or a base station 30. The communication device of this embodiment supports the first communication and the second communication.

[0358] The communication device includes at least one of a transmitting unit 500 and a receiving unit 600. If the communication device is a terminal device 40, the transmitting unit 500 may be configured with a transmission processing unit 411 and / or a control unit 43, and the receiving unit 600 may be configured with a reception processing unit 412 and / or a control unit 43. If the communication device is a base station 30, the transmitting unit 500 may be configured with a transmission processing unit 311 and / or a control unit 33, and the receiving unit 600 may be configured with a reception processing unit 312 and / or a control unit 33.

[0359] The transmitting unit 500 may be referred to as a transmitting device, the receiving unit 600 may be referred to as a receiving device, and the communication device may be referred to as a transmitting device or a receiving device.

[0360] The transmitting unit 500 includes an application layer 510, a semantic process layer 520, a radio access layer 530, an encoder 540 (transmission encoding unit), and a mode selector 550. The application layer 510 includes the semantic process layer 520.

[0361] The semantic process layer 520 is a layer for the layer combination form (first form). The application layer 510 selectively uses the semantic process layer 520 in the case of semantic communication (second communication) in the layer combination form (first form), and does not use the semantic process layer 520 in the case of other communication (e.g., the first communication and / or the second form of the second communication).

[0362] When encoding data, the mode selector 550 selects the radio access layer 530 or the encoder 540 according to instructions from the application layer 510 or information included in the header of the data.

[0363] The radio access layer 530 is a radio access unit corresponding to a conventional protocol stack (i.e., the conventional user plane protocol stack shown in FIG. 17 ). The radio access layer 530 includes a channel encoding unit. In the following description, the radio access layer 530 or the channel encoding unit included in the radio access layer 530 may be referred to as a first encoding unit (first encoder).

[0364] The encoder 540 (transmission encoding unit) is a joint source-channel encoder. In this embodiment, the encoder 540 is an encoding unit for semantic communication. The encoder 540 corresponds to a form of a split neural network that performs joint encoding of the source and the channel. The encoder 540 (joint source-channel encoder) equivalently includes a source encoder 541 and a channel encoder 542. In the following description, the encoder 540 may be referred to as a second encoding unit (second encoder).

[0365] The receiving unit 600 includes an application layer 610, a semantic process layer 620, a radio access layer 630, a decoder 640 (receiving decoding unit), and a mode selector 650. The application layer 610 includes the semantic process layer 620.

[0366] The semantic process layer 620 is a layer for the layer combination form. The application layer 610 selectively uses the semantic process layer 620 in the case of semantic communication (second communication) in the layer combination form, and does not use the semantic process layer 620 in the case of other communication (e.g., other forms of the first communication and / or the second communication).

[0367] When decoding data, the mode selector 650 selects the radio access layer 630 or the decoder 640 according to instructions from the application layer 610 or information included in the header of the data.

[0368] The radio access layer 630 is a radio access unit corresponding to a conventional protocol stack (i.e., the conventional user plane protocol stack shown in FIG. 17 ). The radio access layer 630 includes a channel decoding unit. In the following description, the radio access layer 630 or the channel decoding unit included in the radio access layer 630 may be referred to as a first decoding unit (first decoder).

[0369] The decoder 640 (receiving decoding unit) is a joint source-channel decoder. The decoder 640 is a decoding unit for semantic communication. The decoder 640 corresponds to the form of a split neural network that jointly decodes the source and the channel (joint decoding). Therefore, the decoder 640 (joint source-channel decoder) equivalently includes a source decoder 641 and a channel decoder 642. In the following description, the decoder 640 may be referred to as a second decoding unit (second decoder).

[0370] In the above configuration, an example has been shown in which the communication device includes the radio access layer 530 and the encoder 540 (integrated source channel encoder), and the mode selector 550 selectively uses the radio access layer 530 or the encoder 540. However, the configuration of the communication device of this embodiment is not limited to this. For example, the mode selector 550 may configure the radio access layer 530 or the encoder 540 (integrated source channel encoder) in a programmable / software manner.

[0371] In the above configuration, an example has been shown in which the communication device includes the radio access layer 630 and the decoder 640 (integrated source channel decoder), and the mode selector 650 selectively uses the radio access layer 630 or the decoder 640. However, the configuration of the communication device of this embodiment is not limited to this. For example, the mode selector 650 may configure the radio access layer 630 or the decoder 640 (integrated source channel decoder) in a programmable / software manner.

[0372] In the following description, a processing unit that performs encoding or decoding for the first communication may be referred to as a first communication processing unit, and a processing unit that performs encoding or decoding for the second communication may be referred to as a second communication processing unit. In the example of Figure 20, the first communication processing unit is the radio access layer 530 (first encoder) or the radio access layer 630 (first decoder). Also, in the example of Figure 20, the second communication processing unit is the encoder 540 (second encoder) or the decoder 640 (second decoder).

[0373] The first encoder and the first decoder may each be considered as a first signal processing unit. Similarly, the second encoder and the second decoder may each be considered as a second signal processing unit. Furthermore, the first communication processing unit may include both the first encoder and the first decoder. Similarly, the second communication processing unit may include both the second encoder and the second decoder.

[0374] In the following description, a functional block that performs pre-encoding for the second communication using the first mode (e.g., layer-combined mode) may be referred to as a pre-encoding unit. In the example of FIG. 20 , the pre-encoding unit is the semantic process layer 520. In the following description, a functional block that performs post-encoding for the second communication using the first mode (e.g., layer-combined mode) may be referred to as a post-encoding unit. In the example of FIG. 20 , the post-encoding unit is the semantic process layer 620.

[0375] 21 is a flowchart showing an example of a setting process according to the first embodiment. A communication device performs setting for communication with another communication device according to the following flowchart. The following process is executed by, for example, the communication device shown in FIG. 20. For example, if the communication device is a base station 30, the following process is executed by the control unit 33 of the base station 30. Furthermore, if the communication device is a terminal device 40, the following process is executed by the control unit 43 of the terminal device 40. The setting process according to the first embodiment will be described below with reference to the flowchart in FIG. 21.

[0376] The communication device selects either first communication or second communication according to an application or service (step S301). Here, the first communication is communication that propagates source data as information that can be restored to the same form on the receiving side. The second communication is communication that propagates part or all of information (e.g., meaning or characteristics of data) extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving side. The second communication is, for example, semantic communication.

[0377] The communication device determines whether the selected communication is the second communication (step S302). If the selected communication is not the second communication, i.e., if the selected communication is the first communication (step S302: No), the communication device selects the first communication processing unit as the communication processing unit for the first communication (step S307). Once the selection is complete, the communication device ends the setting process.

[0378] On the other hand, if the selected communication is the second communication (step S302: Yes), the communication device acquires information regarding the protocol stack configuration for the second communication (hereinafter referred to as second communication configuration information) (step S303). At this time, the communication device may acquire the information from its own storage unit or from another communication device. For example, the communication device may acquire the information from a core network or from another communication device with which it communicates. If the communication device is a terminal device 40, the other communication device may be, for example, a base station 30 or another terminal device 40. If the communication device is a base station 30, the other communication device may be, for example, the terminal device 40. Note that the information regarding the protocol stack configuration for the second communication may be, for example, information regarding the protocol stack configuration for the second communication supported by the other communication device.

[0379] Furthermore, the information on the protocol stack topology of the second communication may include information on a network slice corresponding to the second communication. Here, different network slices may be prepared as the network slices corresponding to the second communication depending on the communication direction. Furthermore, different network slices may be prepared as the network slices corresponding to the second communication depending on the communication targets. For example, different network slices may be prepared as the network slices corresponding to the second communication depending on whether the communication is person-to-person (H2H), person-to-machine (H2M), or machine-to-machine (M2M). The communication device may acquire topology information including information on the network slice (e.g., information on one of the plurality of network slices). Then, the communication device may perform configuration related to the network slice based on the information on the network slice.

[0380] Here, the protocol stack configuration for the second communication includes at least a first configuration and a second configuration. The first configuration is a configuration that uses encoding or decoding processing for the first communication. For example, the first configuration is the layer-combined configuration described above. The second configuration is a configuration that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. For example, the second configuration is a configuration in which at least one AI / ML model is configured between a transmission encoding unit of the transmitting device and a reception decoding unit of the receiving device. For example, the second configuration is the partitioned neural network configuration described above. In the following description, the protocol stack configuration for the second communication may be referred to as the second communication configuration. Furthermore, information regarding the protocol stack configuration for the second communication may be referred to as configuration information.

[0381] Next, the communication device determines whether the second communication mode indicated in the mode information is the first communication mode. For example, the communication device determines whether the second communication mode supported by the other communication device with which it is to communicate is the first communication mode (step S304).

[0382] If the second communication mode indicated in the mode information is the second mode (step S304: No), the communication device selects a second communication processing unit as a communication processing unit for the second communication (step S305). That is, the communication device selects (sets) a second encoding unit and / or a second decoding unit as a communication processing unit for the second communication. In the example of FIG. 20, the second encoding unit is the encoder 540 (integrated source channel encoder). Also, in the example of FIG. 20, the second decoding unit is the decoder 640 (integrated source channel decoder). Here, the communication device may transmit information regarding the selected mode to another communication device (e.g., a communication device that will be the communication partner) as information regarding the mode of the protocol stack for the second communication. Once the selection is complete, the communication device terminates the setting process.

[0383] Note that, when the second communication mode indicated in the mode information is the second mode, the mode information may include information regarding an AI / ML model to be set in the second communication processing unit. Here, different AI / ML models may be prepared according to differences in communication targets. For example, different AI / ML models may be prepared according to differences between human-to-human (H2H), human-to-machine (H2M), and machine-to-machine (M2M). The communication device may acquire mode information including information regarding the AI / ML model (e.g., information regarding one of the above-mentioned multiple AI / ML models). Then, the AI / ML model may be set in the second communication processing unit based on the information regarding the AI / ML model.

[0384] On the other hand, if the second communication mode indicated in the mode information is the first mode (step S304: Yes), the communication device sets a pre-encoding unit and / or a post-decoding unit for the second communication (step S306). In the example of FIG. 20, the pre-encoding unit is the semantic process layer 520. Also, in the example of FIG. 20, the post-decoding unit is the semantic process layer 620. Here, the communication device may transmit information about the selected mode to another communication device (e.g., a communication device that is the communication partner) as information about the mode of the protocol stack for the second communication.

[0385] Next, the communication device selects the first communication processing unit as the communication processing unit for the second communication (step S307). Once the selection is complete, the communication device ends the setting process.

[0386] Through the above process, the communication device can perform settings suitable for the selected communication mode (first communication, first mode of second communication, or second mode of second communication).

[0387] 22A and 22B are sequence diagrams showing an example of a PDU session establishment process for second communication (e.g., semantic communication). Specifically, Fig. 22A and 22B are sequence diagrams showing an example of a PDU session establishment process (step S109 shown in Fig. 13) activated by a PDU SESSION ESTABLISHMENT REQUEST message. In the following description, UE 40 is the terminal device 40, and RAN / AN 910 is the base station 30 that serves as the serving cell.

[0388] In this embodiment, the UE 40 performs second communication different from the first communication for communication in the form of H2H (Human-to-Human), H2M (Human-to-Machine), or M2M (Machine-to-Machine). At this time, the UE 40 transmits a session establishment request to a core network CN (e.g., 5GC) via the RAN / AN 910 (step S108 shown in FIGS. 13 and 22A).

[0389] More specifically, in step S103 of FIG. 13, UE 40 selects a network slice corresponding to the second communication. For example, UE 40 selects S-NSSAI (Single Network Slice Selection Assistance Information), which is network slice selection assistance information. This process corresponds to step S301 of FIG. 21. Then, in step S108 of FIG. 13 and FIG. 22A, UE 40 transmits a PDU SESSION ESTABLISHMENT REQUEST message including the S-NSSAI selected in step S103 to AMF 941.

[0390] Note that the PDU session establishment process shown in Figures 22A and 22B includes processes common to the processes shown in Figures 14A and 14B. In the following description, the description of the common processes will be omitted.

[0391] When the session establishment request sent from the UE 40 is a session establishment request for a second communication, the SMF 946 determines the protocol stack type for the second communication in step S401 (step S401). For example, the SMF 946 determines the protocol stack type for the second communication in accordance with a local policy or the default PCC rule acquired from the PCF 945 in step S206. At this time, the SMF 946 may determine a type selected from multiple types for the second communication as the protocol stack type for the second communication. For example, the SMF 946 may select either the first type or the second type as the protocol stack type for the second communication.

[0392] As described above, the first form is a form that uses encoding or decoding processing for the first communication. For example, the first form is the layer-coupling form described above. The second form is a form that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. For example, the second form is a form in which at least one AI / ML model is configured between a transmission encoding unit of a transmitting device and a reception decoding unit of a receiving device. For example, the second form is the partitioned neural network form described above. In the following description, the protocol stack form for the second communication may be referred to as the second communication form.

[0393] The SMF 946 may determine the form of the second communication depending on a protocol stack supported by a communication device (e.g., the UE 40 and / or the RAN / AN 910). In this case, the SMF 946 may determine the form of the second communication depending on a protocol stack supported by the RAN / AN 910 (base station 30), or may determine the form of the second communication depending on a protocol stack supported by the UE 40 (terminal device 40).

[0394] In step S210, the SMF 946 transmits a Namf_Communication_N1N2MessageTransfer message to the AMF 941 (step S210). At this time, the Namf_Communication_N1N2MessageTransfer message includes information about the second communication mode determined in step S401. The information about the second communication mode may include information about the setting of the second communication. For example, the information about the second communication mode may include an instruction to set the first mode or an instruction to set the second mode. In the following description, the information about the second communication mode (information about the mode of the protocol stack of the second communication) may be referred to as mode information.

[0395] In step S401, the SMF 946 may determine only to set up the second communication, rather than the form of the second communication (step S401). For example, the SMF 946 may determine to set up the second communication according to a local policy or a default PCC rule. Then, in step S210, the SMF 946 may send a Namf_Communication_N1N2MessageTransfer message including an instruction to set up the second communication to the AMF 941 (step S210).

[0396] In this case, the AMF 941 that has received a message including an instruction to set up the second communication may determine the form of the second communication. At this time, the AMF 941 may determine the form of the second communication according to the UE radio capability information and information related to capabilities supported by the RAN / AN 910.

[0397] Alternatively, the AMF 941, which has received the message including the instruction to establish the second communication, may forward the instruction to establish the second communication to the RAN / AN 910. Then, the RAN / AN 910 may determine the mode of the second communication according to the UE radio capability information and information related to capabilities supported by the RAN / AN 910. In this case, information related to the mode of the second communication is provided to the UE 40 via RRC signaling.

[0398] (When the Second Communication Form is the First Form) When the determined second communication form is the first form, the information about the second communication form may include, for example, information about the settings of pre-encoding on the transmitting side and post-decoding on the receiving side in the aforementioned application. For example, the information about the second communication form may include information about the settings of the semantic process layer 520 on the transmitting side and the semantic process layer 620 on the receiving side. When the semantic process layer 520 and the semantic process layer 620 are configured using an AI / ML model, the information about the settings of the semantic process layer 520 on the transmitting side and the semantic process layer 620 on the receiving side may be information about the configuration of the AI / ML model. Here, the information about the configuration of the AI / ML model may include, for example, any of the number of hidden layers (or intermediate layers) of the deep neural network, the number of nodes in each layer, and the weight of each edge. Here, a deep neural network with one hidden layer (or intermediate layer) may be considered a neural network model.

[0399] Here, it is assumed that the communication device to which the information on the configuration is provided is UE 40. In this case, information on the configuration of the transmitting side semantic process layer 520 for the uplink and / or the receiving side semantic process layer 620 for the downlink may be provided to UE 40 via an N1SM container in step S212. Also, it is assumed that the communication device to which the information on the configuration is provided is RAN / AN 910 facing UE 40. In this case, information on the configuration of the transmitting side semantic process layer 520 for the downlink and / or the receiving side semantic process layer 620 for the uplink may be provided to RAN / AN 910 via N2SM information in step S211. Here, the second communication according to the first form may be configured for only the uplink, only the downlink, or both the uplink and the downlink.

[0400] The RAN / AN 910 configures the second communication according to information regarding the configuration of the transmitting side semantic process layer 520 for the downlink and the receiving side semantic process layer 620 for the uplink obtained from the SMF 946 (step S402).

[0401] UE40 configures the second communication according to information relating to the configuration of the transmitting side semantic process layer 520 for the uplink and / or the receiving side semantic process layer 620 for the downlink obtained from SMF946 (step S403).

[0402] (When the Second Communication Form is the Second Form) When the determined second communication form is the second form, the information about the second communication form may include, for example, information about the settings of the transmitting-side encoder 540 (integrated source channel encoder) and / or the receiving-side decoder 640 (integrated source channel decoder). For example, the information about the second communication form may include information about the settings of the transmitting-side encoder 540 and the receiving-side decoder 640. When the encoder 540 and / or the decoder 640 are configured using an AI / ML model, the information about the settings of the transmitting-side encoder 540 and / or the receiving-side decoder 640 may be information about the configuration of the AI / ML model. Here, the information about the configuration of the AI / ML model may include, for example, any of the number of hidden layers (or intermediate layers) of the deep neural network, the number of nodes in each layer, and the weight of each edge. Here, a deep neural network with one hidden layer (or intermediate layer) may be considered a neural network model.

[0403] Here, it is assumed that the communication device to which the information on the configuration is provided is UE 40. In this case, information on the configuration of the transmitting encoder 540 for the uplink and / or the receiving decoder 640 for the downlink may be provided to UE 40 via an N1SM container in step S212. Also, it is assumed that the communication device to which the information on the configuration is provided is RAN / AN 910 facing UE 40. In this case, information on the configuration of the transmitting encoder 540 for the downlink and / or the receiving decoder 640 for the uplink may be provided to RAN / AN 910 via N2SM information in step S211. Here, the second communication according to the first form may be configured for only the uplink, only the downlink, or both the uplink and the downlink.

[0404] The RAN / AN 910 configures the second communication according to information regarding the configuration of the transmitting encoder 540 (integrated source channel encoder) for the downlink and the receiving decoder 640 (integrated source channel decoder) for the uplink obtained from the SMF 946 (step S402).

[0405] The UE 40 configures the second communication according to information relating to the configuration of the transmitting side encoder 540 (integrated source channel encoder) for the uplink and / or the receiving side decoder 640 (integrated source channel decoder) for the downlink obtained from the SMF 946, the AMF 941, or the RAN / AN 910 (step S403).

[0406] Here, the SMF 946, the AMF 941, or the RAN / AN 910 acquires information about the configuration of the AI / ML model from the learning device. The learning device manages the life cycle of the trained AI / ML model and can set a validity period for the trained AI / ML model. Therefore, the information about the configuration of the AI / ML model can include the validity period of the AI / ML model.

[0407] The SMF 946 checks the validity period of the AI / ML model, and if it detects that the validity period has elapsed or that the remaining validity period is within a predetermined period, it acquires the latest AI / ML model from the learning device. The SMF 946 can update the configuration of the AI / ML model with N2SM information and / or an N1SM container containing information about the configuration of the latest AI / ML model via a Namf_Communication_N1N2MessageTransfer message.

[0408] The AMF 941 checks the validity period of the AI / ML model, and if it detects that the validity period has expired or that the remaining validity period is within a predetermined period, it acquires the latest AI / ML model from the learning device. The AMF 941 can update the configuration of the AI / ML model with an N1SM container containing information about the configuration of the latest AI / ML model via an N2 PDU session request message.

[0409] The RAN / AN 910 checks the validity period of the AI / ML model, and if it detects that the validity period has expired or that the remaining validity period is within a predetermined period, it acquires the latest AI / ML model from the learning device. The RAN / AN 910 can update the configuration of the AI / ML model with an RRC reconfiguration message that includes information about the configuration of the latest AI / ML model.

[0410] As described above, possible usage patterns include performing the second communication only via uplink, only via downlink, or both via uplink and downlink. The core network CN may provide, for example, three types of network slices as shown in (A1) to (A3) below. (A1) A first network slice that supports an uplink via the second communication and a downlink via the first communication using only a conventional (e.g., pre-5G) protocol stack. (A2) A second network slice that supports an uplink via the first communication using only a conventional protocol stack and a downlink via the second communication. (A3) A third network slice that supports an uplink and a downlink via the second communication.

[0411] Here, instead of classifying network slices by the first communication and the second communication, they may be classified by the protocol stack they use. For example, the core network CN may provide three types of network slices as shown in the following (B1) to (B3): (B1) A first network slice supporting an uplink using a protocol stack for the second communication in the second mode and a downlink using a conventional protocol stack; (B2) A second network slice supporting an uplink using only the conventional protocol stack and a downlink using a protocol stack for the second communication in the second mode; and (B3) A third network slice supporting an uplink and a downlink using a protocol stack for the second communication in the second mode.

[0412] Furthermore, the core network CN may classify network slices as either H2H, H2M, or M2M.

[0413] Similarly, the core network CN may configure separate AI / ML models for each of H2H, H2M or M2M.

[0414] In step S103, UE40 may select one network slice from multiple network slices corresponding to the second communication depending on the communication target (H2H, H2M, or M2M) and the application used.

[0415] Through the above process, the communication device can establish a session for second communication (e.g., semantic communication) suitable for another communication device as a communication partner and / or an application to be used, thereby reducing the amount of radio resources consumed.

[0416] 4-2. Second Example Next, the operation of the communication system 1 according to the second example will be described. In the second example, another example of the process of determining the protocol stack configuration for the second communication (step S401 shown in FIG. 22A) will be described.

[0417] FIG. 23 is a flowchart illustrating an example of a determination process according to the second embodiment. The information processing device determines (selects) the protocol stack configuration for the second communication according to the following flowchart. The following process is executed, for example, by the core network CN (or a device belonging to the core network CN). For example, the following process is executed by the control unit 23 of the management device 20. The determination process according to the second embodiment will be described below with reference to the flowchart of FIG. 23.

[0418] When the session establishment request from the UE 40 is a session establishment request for the second communication, the SMF 946 acquires information about the serving cell (step S501). The serving cell is, for example, the RAN / AN 910 in which the UE 40 has completed the RRC configuration in steps S105 to S107 of FIG. 13 .

[0419] The SMF 946 may determine the type of protocol stack for the second communication depending on the protocol stack supported by the serving cell (RAN / AN 910).

[0420] For example, the SMF 946 checks information about the protocol stack configuring the serving cell based on the acquired information about the serving cell (step S502). Then, the SMF 946 determines whether the serving cell is a cell configuring a conventional protocol stack (e.g., a protocol stack before 5G) (step S503).

[0421] If the serving cell is a cell that configures a conventional protocol stack (step S503: Yes), the SMF 946 selects a first configuration as the configuration of the protocol stack for the second communication (step S504). As described above, the first configuration is a configuration that utilizes encoding or decoding processing for the first communication. For example, the first configuration is the above-described layer-coupling configuration.

[0422] Then, the SMF 946 generates information about the first mode as information about the mode of the protocol stack for the second communication. Here, the information about the first mode may include an instruction to set the first mode. When the generation of the information about the first mode is completed, the SMF 946 ends the determination process.

[0423] On the other hand, if the serving cell is not a cell that configures a conventional protocol stack (step S503: No), the SMF 946 selects the second configuration as the configuration of the protocol stack for the second communication (step S505). As described above, the second configuration is a configuration that utilizes integrated source channel encoding processing or integrated source channel decoding processing for the second communication. For example, the second configuration is a configuration in which at least one AI / ML model is configured between a transmission encoding unit of the transmitting device and a reception decoding unit of the receiving device. For example, the second configuration is the above-mentioned split neural network configuration.

[0424] Then, the SMF 946 generates information about the second mode as information about the mode of the protocol stack for the second communication. Here, the information about the second mode may include an instruction to set the second mode. When the generation of the information about the second mode is completed, the SMF 946 ends the determination process.

[0425] In the early stages of introducing a new generation of mobile communication systems, cells of different generations may coexist. The above processing makes it possible to smoothly introduce new communication methods (e.g., semantic communication) made possible by the evolution of AI technology in an environment where cells of different generations coexist.

[0426] The determination process may be executed by an information processing device other than the management device 20. For example, the determination process may be executed by the server 10, or may be executed by a communication device (e.g., the base station 30 and / or the terminal device 40) that supports the second communication. In this case, the determination process may be executed within a process other than the PDU session establishment process (e.g., within a handover process).

[0427] <4-3. Third Example> Next, the operation of the communication system 1 according to the third example will be described. In the first example, the decision regarding the communication mode was made within the PDU session establishment process. In the third example, the decision regarding the communication mode is made within the handover process.

[0428] 24A and 24B are sequence diagrams showing an example of handover processing according to the third embodiment. In the following description, UE 40 is the terminal device 40, and RAN / AN 910 is the base station 30. In the following description, the handover source base station 30 (for example, Source gNB 30) is referred to as Source BS 30. １ The handover destination base station 30 (for example, Target gNB 30) is referred to as the target BS 30 ２ That's what they say.

[0429] UE 40 communicates with source BS 30, which is RAN / AN 910, according to the processes shown in FIGS. 22A and 22B. １ A PDU session for the second communication is established between the UE 40 and the UPF 920 via the PDU session. When the session is established, the UE 40 starts exchanging user data with the UPF 920 over the established PDU session.

[0430] Source BS30 １ The UE context held by the source BS 30 includes information related to mobility control (e.g., information related to roaming and / or access restriction) provided by the AMF 941 when the PDU session is established. １ acquires information related to this mobility control (step S601). This information related to mobility control is updated when a TA (Tracking Area) is updated.

[0431] Source BS30 １ sets a measurement procedure in the UE 40. Then, the UE 40 performs measurements according to the set measurement procedure, and the source BS 30 １ The measurement results are reported to (step S602).

[0432] Source BS30１ The UE 40 determines handover of the UE 40 based on the reported measurement result (Measurement Report) and RRM (Radio Resource Management) information (step S603). Here, the RRM information is, for example, information about the RRM configuration. For example, it is assumed that both types of measurements, SSB (SS / PBCH block) and CSI-RS (Channel State Information Reference Signal), are available. In this case, the RRM configuration may include information about beam measurements related to SSB and CSI-RS for the reporting cell. Furthermore, if carrier aggregation is configured, the RRM configuration may include a list of the best cells in each frequency for which measurement information is available. The RRM measurement information includes the target BS 30 included in the list. ２ It may also include information about beam measurements for cells belonging to

[0433] Source BS30 １ is target BS30 ２ The target BS 30 issues a handover request message to the target BS 30 (step S604). ２ contains the information necessary to prepare for handover. １ The source BS 30 may request a Dual Active Protocol Stack (DAPS) handover for one or more Data Radio Bearers (DRBs). Here, the DAPS handover is performed by the source BS 30 even after receiving a Radio Resource Control (RRC) message for handover. １ More specifically, the DAPS handover is a handover in which the target BS 30 maintains the connection with the target BS 30 even after receiving the RRC message for handover. ２ Successfully randomly accesses the source BS30 １ until the connection with the source BS 30 is released. １This is a handover that maintains connection with the

[0434] Target BS30 ２ For example, the target BS 30 can perform admission control (step S605). ２ When the established PDU session is provided to the target BS 30, network slice-aware admission control is performed. ２ If the PDU session is related to a network slice that is not supported by the target BS 30, ２ rejects the PDU session.

[0435] Target BS30 ２ If the established PDU session is a PDU session for the second communication, the target BS 30 determines the form of the protocol stack for the second communication (step S606). ２ determines the form of the protocol stack for the second communication based on the UE radio capability information of the UE 40. ２ may determine the form of the protocol stack for the second communication depending on the protocol stack supported by the UE 40. For example, the target BS 30 ２ may determine a form selected from a plurality of forms for the second communication as the form of the protocol stack for the second communication. ２ may select either the first form or the second form as the form of the protocol stack for the second communication.

[0436] As described above, the first form is a form that uses encoding or decoding processing for the first communication. For example, the first form is the above-described layer-coupling form. The second form is a form that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. For example, the second form is a form in which at least one AI / ML model is configured between a transmission encoding unit of a transmitting device and a reception decoding unit of a receiving device. For example, the second form is the above-described split neural network form. In the following description, the form of the protocol stack for the second communication may be referred to as the second communication form.

[0437] Target BS30 ２ prepares the handover and sends a HANDOVER REQUEST ACKNOWLEDGE message to the source BS 30. １ (Step S607). This message includes a transparent container to be transmitted to UE 40 as an RRC message for executing handover. Furthermore, if the established PDU session is a PDU session for the second communication, this container includes information about the second communication mode determined in step S606. The information about the second communication mode may include information about the configuration of the second communication. For example, the information about the second communication mode may include an instruction to set the first mode or an instruction to set the second mode. Furthermore, the information about the second communication mode may include information about the configuration of the AI / ML model. In the following description, information about the second communication mode (information about the mode of the protocol stack for the second communication) may be referred to as mode information.

[0438] Source BS30 １The UE 40 initiates the Uu handover by sending an RRC Reconfiguration message to the UE 40 (step S608). The RRC Reconfiguration message includes the target cell (i.e., the target BS 30 ２ The information required to access the RRC reconfiguration message includes at least the ID of the target cell, a new Cell Radio Network Temporary Identifier (C-RNTI), and information about the target BS security algorithm for the selected security algorithm. Furthermore, the RRC reconfiguration message may include a set of dedicated Random Access Channel (RACH) resources, information indicating the relationship between the RACH resources and SSB(s), information indicating the relationship between the RACH resources and the UE-specific CSI-RS configuration, information about common RACH resources, and system information of the target cell.

[0439] Source BS30 １ In step S615, the target BS 30 ２ The DAPS handover-configured DRB(s) continue to transmit downlink packets until a HANDOVER SUCCESS message is received from the DAPS handover-configured DRB(s) (step S609).

[0440] Source BS30 １ sends an EARLY STATUS TRANSFER message to the target BS 30 using the DRB(s) configured for DAPS handover. ２ (Step S610). Here, the DL COUNT value included in the early status transfer message is, for example, １ Target BS30 ２The PDCP SN (Packet Data Convergence Protocol Sequence Number) and HFN (Hyper Frame Number) of the first PDCP SDU (Packet Data Convergence Protocol Service Data Unit) to be transmitted to the source BS 30. １ In step S616, the SN STATUS TRANSFER message is sent to the target BS 30. ２ The PDCP SDUs in the downlink continue to be assigned SNs until they are transmitted to the PDCP SDUs in the downlink.

[0441] Also, Source BS30 １ sends an SN status transfer message to the target BS 30 using DRB(s) for which DAPS handover is not configured. ２ (Step S611). The SN status transfer message includes the uplink PDCP SN reception status and the downlink PDCP SN transmission status of the DRBs to which PDCP status maintenance is applied (i.e., RLC AM (Acknowledged Mode)). The uplink PDCP SN reception status includes at least the PDCP SN of the first missing UL PDCP SDU. When the UE 40 transfers the SN status to the target cell (target BS 30), ２ ), the uplink PDCP SN reception status may include a bitmap of the reception status. The downlink PDCP SN transmission status is information indicating the next PDCP SN that the target BS 302 must assign to a new PDCP SDU that does not yet have a PDCP SN assigned.

[0442] Source BS30 １ The user data transmitted to the target BS 30 ２ The target BS 30 ２ buffers the transferred user data (step S612).

[0443] The UE 40 is connected to the old cell (source BS 30 １ ) and detach from the new cell (target BS30 ２ However, in the case of DAPS handover, the UE 40 synchronizes with the source cell (source BS 30) until it receives the RRC setup message (step S613). １ ) and does not detach from the target cell (target BS 30 ２ Upon receiving an explicit release notification from the source cell, the UE 40 releases the resources and configuration for the source cell and stops receiving downlink data from the source cell and / or transmitting uplink data to the source cell.

[0444] In the case of DAPS handover and RLC AM, the source BS 30 １ may transmit the uplink PDCP SN reception status and the downlink PDCP SN transmission status of the DRB for which DAPS is not configured using the SN status transfer message of step S616 instead of the SN status transfer message of step S611.

[0445] Source BS30 １ The target BS 30 may additionally send an Early Status Transfer message between steps S611 and S616 using the DRBs with DAPS configured to indicate the discarding of the PDCP SDUs that have already been forwarded. ２ PDCP SDUs (target BS 30) whose COUNT is smaller than the transmitted DL COUNT value. ２ The target BS 30 does not transmit downlink PDCP SDUs (transmitted from the target BS 30) to the UE 40. ２ discards PDCP SDUs for which transmission is not being attempted.

[0446] Target BS30 ２ The UE 40 synchronized with the target BS 30 sends an RRCReconfigurationComplete message to the target BS 30. ２ , thereby completing the RRC handover procedure (step S614).

[0447] In the case of a DAPS handover, the target BS 30 ２ is the number of UEs 40 that are connected to the target cell (target BS 30 ２ ) and sends a HANDOVER SUCCESS message to the source BS 30 to notify the source BS 30 that it has successfully accessed the １ In response, the source BS 30 １ As described above, the SN status transfer message for the DRBs with DAPS configured is sent to the target BS 30. ２ (step S616).

[0448] If DAPS is set, the source BS 30 １ transmits the uplink PDCP SN reception status and the downlink PDCP SN transmission status of the DRBs in RLC UM (Unacknowledged Mode) using an SN status transfer message in step S616.

[0449] Source BS30 １ sends the SN status transfer message to the target BS 30 in step S616. ２ The target BS 30 continues transmitting uplink QoS flows to the UPF 920 using DRBs with DAPS configured until the target BS 30 transmits ２ The target BS 30 does not forward successfully received uplink PDCP SDUs to the UPF 920 until it receives an SN status transfer message. This SN status transfer message indicates the start of the uplink PDCP SDUs to be forwarded to the UPF 920. For example, the UL HFN and the first missing SN in the uplink PDCP SN reception status indicate the start of the uplink PDCP SDUs to be forwarded to the UPF 920. ２ does not transmit uplink PDCP SDUs with a UL COUNT lower than the provided UL COUNT.

[0450] If the established PDU session is a PDU session for the second communication, the target BS 30２ UE 40 sets the second communication mode to transmit and receive user data between UE 40 and the first communication mode (step S617). For example, UE 40 sets the first mode or the second mode according to the mode information (i.e., information on the mode of the protocol stack for the second communication) included in the transparent container transmitted to UE 40 as an RRC message.

[0451] Target BS30 ２ The BS 941 then sends a PATH SWITCH REQUEST message to the AMF 941 (step S618). This message indicates that the core network CN has assigned a downlink data path (DL data path) to the target BS 30. ２ and then switches to a route toward the target BS 30 ２ This message is a trigger for establishing an NG-C interface instance for the NG-C interface.

[0452] The core network CN routes the downlink data path to the target BS 30. ２ Here, the UPF 920 sends a packet indicating an "end marker" to the source BS 30 for each PDU session / tunnel on the old route (step S619). １ In this case, the UPF 920 transmits the １ All U-plane / TNL (Transport Network Layer) resources may be released.

[0453] The AMF 941 sends a PATH SWITCH REQUEST ACKNOWLEDGE message to the target BS 30 in response to the PATH SWITCH REQUEST message in step S618. ２ (step S620).

[0454] Target BS30 ２Upon receiving the path switch request response message from the AMF 941, the AMF 941 sends a UE context release message to the source BS 30 to notify the handover success. １ (Step S621). When the UE context release message is received, the source BS 30 １ releases resources associated with the UE context (e.g., radio resources and control plane (C-plane) related resources).

[0455] Through the above processing, it is possible to provide semantic communication in a form suitable for the protocol stack supported by the handover destination cell in an environment where cells of different generations coexist.

[0456] 4-4. Fourth Example Next, a fourth example will be described. The fourth example can be applied to any of the first to third examples described above.

[0457] As described above, in the second form of the second communication (split neural network form), the communication device configures a deep neural network that integrates a semantic communication layer and a physical layer in an E2E manner. The communication device then configures the split deep neural network in the transmitter (encoder 540) and receiver (decoder 640). In other words, the deep neural network is a model that includes a channel in between. In wireless communication, the channel changes constantly. Therefore, it becomes necessary to consider the influence of the dynamic channel on the weight coefficients of the nodes or edges of the split layer of the deep neural network.

[0458] FIG. 25 is a diagram showing an example of the configuration of a deep neural network model to be divided. The deep neural network model is divided at the division point into a first model 540 corresponding to the encoder 540 (integrated source-channel encoder) and a second model 640 corresponding to the decoder 640 (integrated source-channel decoder). In the following description, the first model may be referred to as the first model 540, and the second model may be referred to as the second model 640. The weighting coefficients of each edge between the first model 540 and the second model 640 can be expressed in the form of a matrix. The node values ​​of the output layer of the first model 540 and the node values ​​of the input layer of the second model 640 can be expressed as shown in the following equation (1) using a matrix of weighting coefficients.

[0459]

[0460] 26 is a diagram showing an example of propagation channels and conversion processing for a divided model. The value of each node in the output layer of the first model 540 set in the transmitting device is transmitted from each transmitting antenna (e.g., #1) corresponding to each node (e.g., #1). Here, the correspondence between the node and the transmitting antenna is realized by associating each node (e.g., #1) with the antenna port (e.g., #1) of each transmitting antenna.

[0461] The signals received by each receiving antenna are processed by each port (e.g., #1) of the transformation process corresponding to each receiving antenna (e.g., #1), and input to the corresponding node (e.g., #1) of the input layer of the second model 640 set in the receiving device.

[0462] The relationship between each node in the output layer of the first model 540 and the input layer of the second model 640 can be expressed as in the following equation (2).

[0463]

[0464] Here, the transformation matrix can be derived, for example, as follows:

[0465] From the above formula (1) and formula (2), the relationship shown in the following formula (3) holds.

[0466]

[0467] By multiplying both sides of the above equation (3) by the inverse matrix of the propagation channel matrix from the right, the transformation matrix C can be derived from the following equation (4).

[0468]

[0469] As described above, if the weighting coefficient matrix and the propagation channel matrix at the division point of the deep neural network model are known to the receiving device, the receiving device can derive the transformation matrix C. For example, if the receiving device calculates or estimates the propagation channel, or if the transmitting device notifies the receiving device of information about the propagation channel, the communication device can communicate in this operating mode. In the uplink, the transmitting device is the UE 40, and the receiving device is the RAN / AN 910 (e.g., base station 30). In the downlink, the transmitting device is the RAN / AN 910 (e.g., base station 30), and the receiving device is the UE 40.

[0470] 27 is a diagram showing another example of propagation channels and conversion processing for a divided model. The value of each node (e.g., #1) in the output layer of the first model 540 set in the transmitting device is processed by each port (e.g., #1) of the conversion processing, and then transmitted from each corresponding transmitting antenna (e.g., #1). Here, the correspondence between the node and the transmitting antenna is realized by associating each node (e.g., #1) with the antenna port (e.g., #1) of each transmitting antenna.

[0471] The signal received by each receiving antenna is input to a corresponding node (for example, #1) in the input layer of the second model 640 set in the receiving device.

[0472] The relationship between each node in the output layer of the first model 540 and the input layer of the second model 640 can be expressed as in the following equation (5).

[0473]

[0474] Here, the transformation matrix can be derived, for example, as follows: From the above formula (1) and the above formula (5), the relationship shown in the following formula (6) holds.

[0475]

[0476] By multiplying both sides of the above equation (6) by the inverse matrix of the propagation channel matrix from the left, the transformation matrix C can be derived from the following equation (7).

[0477]

[0478] As described above, if the weighting coefficient matrix and the propagation channel matrix at the division point of the deep neural network model are known to the transmitting device, the transmitting device can derive the transformation matrix C. For example, if the transmitting device calculates or estimates the propagation channel, or if the receiving device notifies the transmitting device of information about the propagation channel, the communication device can communicate in this operating mode. In the uplink, the transmitting device is the terminal device 40, and the receiving device is the RAN / AN 910 (e.g., base station 30). In the downlink, the transmitting device is the RAN / AN 910 (e.g., base station 30), and the receiving device is the UE 40.

[0479] Whether the conversion process using the above-mentioned conversion matrix C is performed on the receiving device side or the transmitting device side may be determined according to the capability of UE 40. For example, when the capability of UE 40 indicates that it has a predetermined or higher computing capacity, RAN / AN 910 may set the conversion process using the conversion matrix C for UE 40 that serves as a transmitting device in the uplink, and may set the conversion process using the conversion matrix C for UE 40 that serves as a receiving device in the downlink.

[0480] Here, the RAN / AN 910 may configure the UE 40 to measure the propagation channel, or the RAN / AN 910 may notify the UE 40 of information on the propagation channel that it has measured.

[0481] On the other hand, if the capability of UE 40 indicates that it does not possess a predetermined level of computing power, RAN / AN 910 may set a conversion process using transformation matrix C for RAN / AN 910, which is a receiving device in the uplink, and may set a conversion process using transformation matrix C for RAN / AN 910, which is a transmitting device in the downlink.

[0482] Here, the RAN / AN 910 performs measurement of the propagation channel, or configures the UE 40 to measure the propagation channel and report information about the measured propagation channel.

[0483] 28 is a diagram illustrating an example of a mapping process between nodes and antenna ports. In the mapping process shown here, each element of the weighting coefficient matrix at the division point of the deep neural network model (i.e., w １１ , w １２ ,...,w ＮＭ ) and each element of the propagation channel matrix (i.e., h １１ , h １２ , ..., h ＮＭ ) is used to determine the correspondence between nodes and antenna ports. More specifically, the correspondence between each node in the output layer of the first model 540 and each antenna port of the transmitting antenna, and the correspondence between each antenna port of the receiving antenna and each node in the input layer of the second model 640 are determined so that larger elements in the weighting coefficient matrix correspond to larger elements in the propagation channel matrix. The value of a node with a larger weighting coefficient is information that has a greater influence on the estimation process of the deep neural network model. Therefore, by transmitting data using a path with better propagation conditions, improvement in estimation accuracy can be expected.

[0484] The following provides an example of a detailed method for determining the correspondence between each node in the output layer of the first model 540 and each antenna port of the transmitting antenna, and the correspondence between each antenna port of the receiving antenna and each node in the input layer of the second model 640. The processing described below may be executed by a communication device that performs the second communication (e.g., the terminal device 40 and / or the base station 30), or may be executed by another information processing device (e.g., the management device 20 and / or the server 10). The following description of an information processing device can be replaced with a communication device as appropriate.

[0485] For example, when N × M = 2 × 2, the weight coefficient matrix [w １１ , w １２ , w ２１ , w ２２] is [0.85, 0.22, 0.53, 0.31], and the propagation channel matrix [h １１ , h １２ , h ２１ , h ２２ ] is [0.11, 0.31, 0.45, 0.78]. The information processing device calculates the largest component (w １１ : 0.85) is the largest diagonal component of the propagation channel matrix (h ２２ Next, the information processing device associates the next largest component (w ２２ : 0.31) is the next largest diagonal element of the propagation channel matrix (h ２２ This means that the node (#1) of the output layer of the first model 540 corresponds to the antenna port (#2) of the transmitting antenna, the antenna port (#2) of the receiving antenna corresponds to the node (#1) of the input layer of the second model 640, the node (#2) of the output layer of the first model 540 corresponds to the antenna port (#1) of the transmitting antenna, and the antenna port (#1) of the receiving antenna corresponds to the node (#2) of the input layer of the second model 640.

[0486] The above example is a method for setting the correspondence relationship based on diagonal elements. However, this embodiment is not limited to this method. For example, the information processing device may set the correspondence relationship based on the elements (w ２１ , w １２ ) may be used as a reference to set the correspondence relationship. That is, the information processing device may set the correspondence relationship based on the components (w ２１ , w １２ ) the largest component (w ２１ : 0.53) is assigned to the diagonal elements (w ２１ , w １２ ) the largest component (h ２１ Next, the information processing device associates the components (w２１ , w １２ ) the next largest component (w １２ : 0.22) is the diagonal element (w ２１ , w １２ The next largest component (h １２ This means that the node (#2) of the output layer of the first model 540 is associated with the antenna port (#2) of the transmitting antenna, the antenna port (#1) of the receiving antenna is associated with the node (#1) of the input layer of the second model 640, the node (#1) of the output layer of the first model 540 is associated with the antenna port (#1) of the transmitting antenna, and the antenna port (#2) of the receiving antenna is associated with the node (#2) of the input layer of the second model 640.

[0487] Furthermore, the information processing device may determine which method to select based on the root mean squared error between the weighting coefficients and the propagation channel. For example, the root mean squared error when the diagonal components are used as a reference is 0.38 (=√((0.85-0.78)×2+(0.22-0.45)×2+(0.53-0.31)×2+(0.31-0.11)×2)). Furthermore, the root mean squared error when the components located diagonally from the bottom left to the top right are used as a reference is 0.88 (=√((0.53-0.45)×2+(0.31-0.78)×2+(0.85-0.11)×2+(0.22-0.31)×2)). Therefore, in this example, the information processing device selects a method based on the diagonal components with a small root mean squared error.

[0488] In the above example, an example of a propagation channel per antenna port has been described, but the example of the propagation channel is not limited to this. For example, the information processing device measures / acquires information on the propagation channel for each frequency. FIG. 29 is a diagram showing an example of the information on the propagation channel for each frequency. Then, in the mapping process, the information processing device may determine a correspondence between the nodes of the deep neural network model and the radio resources divided on the frequency axis based on each element (i.e., w1, w2, ..., wNM) of the weighting coefficient matrix at the division point of the deep neural network model and the information on the propagation channel for each frequency. For example, a communication device (a base station 30 or a terminal device 40) arranges multiple reference signals for measurement so as to correspond to the radio resources divided on the frequency axis. Another communication device (a base station 30 or a terminal device 40) measures these multiple reference signals and calculates the relative reception strength. This allows the information processing device to acquire information on the propagation channel for each frequency. This makes it possible to transmit the values ​​of nodes with larger weighting coefficients using radio resources with better propagation conditions, which is expected to improve estimation accuracy.

[0489] By the above processing, in the form of a split neural network, the weighting coefficients at the split points are made to correspond to the influence of the propagation channel, thereby realizing more accurate joint source-channel coding / decoding.

[0490] Furthermore, the method of considering the influence of the channel on the weight coefficients of the nodes or edges of the layer to be divided in the deep neural network is not limited to the above example. For example, the information processing device (e.g., learning device) may define a finite number of channel matrices for each set of the number of antenna ports of the communication device (transmitting device and receiving device) and generate a learning model for each channel matrix. For example, when the set of the number of antenna ports of the communication device (transmitting device and receiving device) is 2 × 2, the information processing device may define a channel matrix (h １１ , h １２ , h ２１ , h ２２), (-1,-1,-1,-1), (0,-1,-1,-1), (1,-1,-1,-1), (-1,0,-1,-1), (0,0,-1,-1), (1,0,-1,-1), ..., (-1,0,1,1), (0,0,1,1), (1,0,1,1), (-1,1,1,1), (0,1,1,1), (1,1,1,1), which is 81 (=3) ４ ) channel matrices may be defined.

[0491] An information processing device (e.g., a learning device) may set each element of each channel matrix to a weighting coefficient of an edge between divided layers for an AI / ML model for each combination of the number of antenna ports of a communication device (transmitter and receiver), and perform learning of the AI / ML model. In other words, a trained AI / ML model for each channel matrix is ​​generated for each combination of the number of antenna ports of a communication device (transmitter and receiver).

[0492] The UE 40 or the RAN / AN 910 may identify a channel matrix for a set of the number of antenna ports of a communication device (transmitter and receiver) by measuring a propagation channel, and then the UE 40 or the RAN / AN 910 may obtain a trained AI / ML model corresponding to the identified channel matrix.

[0493] For example, the UE 40 or the RAN / AN 910 may identify a channel matrix that minimizes the sum of squares of errors between each element of the measured propagation channel and each element of each channel matrix. That is, the UE 40 or the RAN / AN 910 may identify a channel matrix that is similar to the measured propagation channel by the least squares method. Then, the UE 40 or the RAN / AN 910 may obtain a trained AI / ML model that corresponds to the combination of the number of antenna ports of the communication device (transmitting device and receiving device) and the ID of the identified channel matrix.

[0494] <<5. Modifications>> The above-described embodiment is merely an example, and various modifications and applications are possible.

[0495] In the above-described embodiment, the core network CN (e.g., the management device 20) is exemplified as the information processing device that determines the protocol stack configuration for the second communication. However, the information processing device that determines the protocol stack configuration for the second communication is not limited to this and may be, for example, the server 10. In this case, the server 10 may transmit the determined information (information regarding the protocol stack configuration for the second communication) via the core network CN to one or more communication devices (e.g., the base station 30 and / or the terminal device 40) that support the first communication and the second communication.

[0496] Furthermore, the information processing device that determines the protocol stack configuration for the second communication may be a communication device that performs the second communication (e.g., the base station 30 and / or the terminal device 40). In this case, the communication device may transmit the determined information (information regarding the protocol stack configuration for the second communication) to another communication device that supports the first communication and the second communication (e.g., a communication device that is the communication partner).

[0497] In the above-described embodiment, the information processing device determines the protocol stack configuration for the second communication when it receives a session establishment request including an instruction for the second communication or when the communication device performs a handover. However, the information processing device may control the communication device to determine the protocol stack configuration for the second communication when it receives system information. In this case, the communication device may be the information processing device itself or a device different from the information processing device.

[0498] Furthermore, the semantic communication exemplified in the above-described embodiments may be used in the broader concept of AI-assisted communication (Artificial Intelligence Aided Communication).

[0499] The server 10, the management device 20, the base station 30, or the control device that controls the terminal device 40 in this embodiment may be realized by a dedicated computer system or a general-purpose computer system.

[0500] For example, a program for executing the above-described operations may be stored and distributed on a computer-readable recording medium such as an optical disk, a semiconductor memory, a magnetic tape, or a flexible disk. Then, for example, the program may be installed on a computer and the above-described process may be executed to configure a control device. In this case, the control device may be a device (e.g., a personal computer) external to the server 10, the management device 20, the base station 30, or the terminal device 40. Alternatively, the control device may be a device (e.g., the control unit 13, the control unit 23, the control unit 33, or the control unit 43) internal to the server 10, the management device 20, the base station 30, or the terminal device 40.

[0501] 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 a combination of 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 may be stored in a server device and downloaded to a computer.

[0502] 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 a known method. In addition, 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.

[0503] 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.

[0504] The above-described embodiments can be combined as appropriate within the scope of the present invention without causing any inconsistency in the processing content. The order of the steps shown in the sequence diagrams or flowcharts of the present embodiment can be changed as appropriate.

[0505] Furthermore, for example, the present embodiment can also 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).

[0506] The functions performed by the components described herein may be implemented in circuitry or processing circuitry programmed to perform the described functions. Here, the circuitry or processing circuitry may be a general-purpose processor, an application-specific processor, an integrated circuit, an ASIC (Application Specific Integrated Circuit), a CPU (a Central Processing Unit), conventional circuitry, and / or a combination thereof. Processors include transistors and other circuits. A processor may be considered to be circuitry or processing circuitry. A processor may also be a programmed processor that executes a program stored in a memory.

[0507] In this specification, a circuit, unit, or means may be hardware that is programmed to realize a described function or that performs a described function. The hardware may be any hardware disclosed in this specification or any hardware that is programmed to realize or known to perform the described function. If the hardware is a processor, which is considered a type of circuitry, the circuit, means, or unit may be a combination of hardware and software used to configure the hardware and / or processor.

[0508] Furthermore, for example, the present embodiment can be implemented as any configuration constituting an apparatus or system. For example, the present embodiment can be implemented as a processor as a system LSI (Large Scale Integration), a module using multiple processors, a unit using multiple modules, or a set in which a unit further has additional functions. In other words, the present embodiment can also be implemented as a part of the configuration of an apparatus.

[0509] The system LSI may also be referred to as an SOC (System on Chip). In other words, each of the above-described or later-described devices (e.g., the server 10, the management device 20, the base station 30, and the terminal device 40) may be interpreted as a processor (e.g., a CPU) serving as a system LSI (e.g., SoC), or as a module using or constituting the processor. Additionally or alternatively, the present embodiment may be implemented by any configuration constituting a device or system (e.g., a modem chip (baseband chip) or an RF (Radio Frequency) unit, or a combination thereof). The RF unit may include at least one of an RF circuit and an RF front-end. In other words, each of the above-described or later-described devices may be interpreted as a modem chip (baseband chip) or an RF unit, or a combination thereof. Additionally or alternatively, each of the above-described or later-described devices may be interpreted as a module using or constituting a modem chip or an RF unit.

[0510] The modem chip processes signals related to communications within a device (including the devices described above or below). The modem chip may have at least a modulator or demodulator function. The RF unit may have at least one of an RF transceiver (RF upconverter, RF downconverter), a power amplifier, and a low-noise amplifier function. The RF transceiver converts between baseband signals and RF frequencies. The power amplifier amplifies signals for transmission from an antenna. The low-noise amplifier amplifies weak signals received from the antenna. Additionally or alternatively, the RF unit (particularly, the RF front end) may include at least one of the above-mentioned power amplifier, low-noise amplifier, envelope tracker, filter, duplexer, multiplexer, antenna switch, and antenna tuner.

[0511] The combination of the modem chip and the RF unit may be referred to as a modem-RF system. At least a portion of the modem chip or the RF unit, or a combination thereof, may be included in a system LSI (e.g., SoC). For example, the processing performed by at least a portion of the modem chip or the RF unit, or a combination thereof (e.g., at least a portion of the MAC layer processing / PHY layer processing) may be realized by the system LSI. Here, the MAC layer processing or the PHY layer processing may be at least a portion of the processing performed by the devices (e.g., the server 10, the management device 20, the base station 30, and the terminal device 40) in the above-mentioned or later-described embodiments.

[0512] In this 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. For example, multiple devices housed in separate housings and connected via a network, etc., and a single device in which multiple modules are housed in a single housing are both systems.

[0513] Furthermore, for example, this embodiment can have a cloud computing configuration in which one function is shared and processed jointly by a plurality of devices via a network.

[0514] <<6. Conclusion>> As described above, according to the present embodiment, an information processing device (e.g., management device 20) included in communication system 1 determines a configuration selected from a plurality of configurations for the second communication as the configuration of the protocol stack for the second communication. For example, the information processing device determines one configuration selected from a plurality of configurations including at least the first configuration and the second configuration as the configuration of the protocol stack for the second communication. The information processing device transmits information regarding the setting of the determined configuration to one or more communication devices (e.g., base station 30 and / or terminal device 40) that support the first communication and the second communication.

[0515] A communication device (e.g., a base station 30 and / or a terminal device 40) configures a protocol stack configuration for the second communication based on the configuration setting information. For example, if the configuration information indicates a first configuration, the communication device selects the radio access layer 530 (first encoding unit) and / or the radio access layer 630 (first decoding unit) as a communication processing unit for the second communication, and configures the semantic process layer 520 (pre-encoding unit) that performs pre-encoding for transmission and / or the semantic process layer 620 (post-encoding unit) that performs post-decoding for reception. On the other hand, if the configuration information indicates a second configuration, the communication device selects the encoder 540 (second encoding unit) and / or the decoder 640 (second decoding unit) as a communication processing unit for the second communication.

[0516] As a result, the communication system 1 of the present embodiment can selectively use different forms of semantic communication depending on the situation. For example, the communication system 1 of the present embodiment can selectively use a first form that realizes the second communication using a wireless layer of a conventional communication system and a second form that uses a newly prepared layer for the second communication depending on the capability of the communication device. As a result, the communication system can provide semantic communication in a form suitable for a user or a communication device, thereby providing a high-quality communication service (e.g., communication with little delay) to the user or the communication device.

[0517] 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.

[0518] 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.

[0519] Note that the present technology may also be configured as follows. (1) An information processing device capable of processing first communication that propagates source data as information that can be restored to the same form on a receiving side, and second communication that propagates to the receiving side part or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the information processing device comprising: a determination unit that determines a protocol stack configuration for the second communication; and a transmission unit that transmits information related to the determined configuration to one or more communication devices that support the first communication and the second communication. (2) The information processing device described in (1), wherein the determination unit determines a configuration selected from a plurality of configurations for the second communication as the protocol stack configuration for the second communication. (3) The information processing device described in (2), wherein the plurality of configurations for the second communication include a first configuration that uses encoding or decoding processing for the first communication, and a second configuration that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. (4) The information processing device according to (3), wherein the second mode is a mode in which at least one of the AI / ML models is configured between a transmission encoding unit of a first communication device which is the communication device on the transmitting side and a reception decoding unit of a second communication device which is the communication device on the receiving side. (5) The information processing device according to any one of (2) to (4), wherein the information on the mode includes information on the AI / ML model set by the communication device.(6) The information processing device according to (4), further comprising: a setting unit that performs processing related to setting the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes the following processing: assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit; associating one or more first nodes of an output layer of the first model with one or more first ports of a transmission antenna; and associating one or more second nodes of an input layer of the second model with one or more second ports of a reception antenna. (7) The information processing device according to (6), wherein a first correspondence between one or more first nodes of the output layer of the first model and one or more first ports of the transmitting antenna, and a second correspondence between one or more second nodes of the input layer of the second model and one or more second ports of the receiving antenna are determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (8) The information processing device according to (4), further comprising: a setting unit configured to perform processing related to setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes the following processes: assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit, associating one or more first nodes in an output layer of the first model with one or more radio resources for transmission divided in a frequency direction, and associating one or more second nodes in an input layer of the second model with one or more of the radio resources. (9) The information processing device according to (8), further comprising: a first correspondence relationship between the one or more first nodes in the output layer of the first model and the one or more radio resources for transmission, and a second correspondence relationship between the one or more second nodes in the input layer of the second model and the radio resources, which are determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side, and a weighting coefficient matrix at a division point of the AI / ML model.(10) The information processing device according to any one of (6) to (9), wherein at least one of the reception decoding unit and the transmission encoding unit includes a conversion processing unit, and the conversion processing unit performs conversion processing determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side and a weighting coefficient matrix at a division point of the AI / ML model. (11) The information processing device according to any one of (2) to (10), wherein the determination unit determines the mode depending on a protocol stack supported by the communication device. (12) The information processing device according to any one of (2) to (11), wherein the determination unit determines the mode of the protocol stack for the second communication when a session establishment request including an instruction for the second communication is received, when the communication device receives system information, or when the communication device performs handover. (13) A communication device that supports first communication that propagates source data as information that can be restored to the same form on a receiving side, and second communication that propagates to the receiving side part or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the communication device comprising: an acquisition unit that acquires information related to a protocol stack configuration for the second communication; and a setting unit that sets the protocol stack configuration for the second communication based on the information related to the configuration. (14) The communication device according to (13), wherein the information related to the configuration includes information related to at least one of a first configuration that uses encoding or decoding processing for the first communication, and a second configuration that uses integrated source channel encoding or integrated source channel decoding processing for the second communication.(15) The communication device according to (14), comprising: a first communication processing unit that performs encoding or decoding for the first communication; and a second communication processing unit that performs encoding or decoding for the second communication, wherein the setting unit, when information on a protocol stack type for the second communication indicates a first type, selects the first communication processing unit as the communication processing unit for the second communication and performs setting related to a pre-encoding unit for transmission or a post-decoding unit for reception, and when the information on the protocol stack type for the second communication indicates a second type, selects the second communication processing unit as the communication processing unit for the second communication. (16) The communication device according to (15), wherein, when the information on the protocol stack type for the second communication indicates the second type, the acquisition unit further acquires information related to the AI / ML model to be set in the second communication processing unit. (17) The communication device according to (16), further comprising: a determination unit that determines a relationship between the AI / ML model and a transmitting antenna or a receiving antenna; the second communication processing unit comprises a second encoding unit that performs encoding for the second communication and a second decoding unit that performs decoding for the second communication; the acquisition unit acquires, as information related to the AI / ML model, first information related to a first model to be set in the second encoding unit and second information related to a second model to be set in the second decoding unit; and the determination unit determines a first correspondence relationship between one or more first nodes in an output layer of the first model and one or more first ports of a transmitting antenna, and a second correspondence relationship between one or more second nodes in an input layer of the second model and one or more second ports of a receiving antenna, based on a propagation channel matrix between another device and a weighting coefficient matrix of one or more of the first nodes.(18) An information processing method executed by an information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form on a receiving side, and a second communication that propagates to the receiving side some or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the information processing method comprising: determining a protocol stack configuration for the second communication; and transmitting information related to the determined configuration to one or more communication devices that support the first communication and the second communication. (19) A communication method executed by a communication device that supports a first communication that propagates source data as information that can be restored to the same form on a receiving side, and a second communication that propagates to the receiving side some or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the communication method comprising: acquiring information related to the protocol stack configuration for the second communication; and setting the protocol stack configuration for the second communication based on the information related to the configuration. (20) A communication system comprising: an information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form on a receiving side; and a second communication that propagates to the receiving side some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model; and one or more communication devices that support the second communication, wherein the information processing device comprises: a determination unit that determines a protocol stack configuration for the second communication; and a transmission unit that transmits information related to the determined configuration to one or more communication devices that support the first communication and the second communication, and the communication device comprises: an acquisition unit that acquires information related to the protocol stack configuration for the second communication; and a setting unit that sets the protocol stack configuration for the second communication based on the information related to the configuration.

[0520] <Information Processing Device (Server 10 / Management Device 20 / Base Station 30 / Terminal Device 40)> The present technology may also be configured as follows. (A1) An information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form on a receiving side, and a second communication that propagates part or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving side, the information processing device comprising: a determination unit that determines a protocol stack configuration for the second communication; and a transmission unit that transmits information related to the determined configuration to one or more communication devices that support the first communication and the second communication. (A2) The information processing device described in (A1), wherein the determination unit determines a configuration selected from a plurality of configurations for the second communication as the protocol stack configuration for the second communication. (A3) The information processing device according to (A2), wherein the multiple modes for the second communication include a first mode that uses encoding or decoding processing for the first communication, and a second mode that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. (A4) The information processing device according to (A3), wherein the second mode is a mode in which at least one AI / ML model is configured between a transmission encoding unit of a first communication device that is the communication device on the transmitting side and a reception decoding unit of a second communication device that is the communication device on the receiving side. (A5) The information processing device according to any one of (A2) to (A4), wherein the determination unit determines a protocol stack mode for the second communication when a session establishment request including an instruction for the second communication is received or when the communication device receives system information. (A6) The information processing device according to any one of (A2) to (A5), wherein the information regarding the mode includes information of a network slice corresponding to the second communication.(A7) The information processing device according to (A6), wherein different network slices corresponding to differences in communication direction are prepared as network slices corresponding to the second communication. (A8) The information processing device according to (A7), wherein different network slices corresponding to differences in communication targets are prepared as network slices corresponding to the second communication. (A9) The information processing device according to any one of (A2) to (A8), wherein the information related to the form includes information related to the AI / ML model set by the communication device. (A10) The information processing device according to (A9), wherein different AI / ML models corresponding to differences in communication targets are prepared as the AI / ML models. (A11) The information processing device according to any one of (A2) to (A10), wherein the multiple forms for the second communication include a form constituting a layer that provides support information for the second communication to one or more sublayers constituting a pre-5G protocol stack. (A12) The information processing device according to (A11), wherein the layer that provides the assistance information for the second communication is configured by the AI / ML model. (A13) The information processing device according to (A4), further comprising: a setting unit that performs processing related to setting the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes a process of assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit, a process of associating one or more first nodes in an output layer of the first model with one or more first ports of a transmitting antenna, and a process of associating one or more second nodes in an input layer of the second model with one or more second ports of a receiving antenna.(A14) The information processing device described in (A13), wherein a first correspondence between one or more first nodes of the output layer of the first model and one or more first ports of the transmitting antenna, and a second correspondence between one or more second nodes of the input layer of the second model and one or more second ports of the receiving antenna are determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (A15) The information processing device according to (A4), further comprising: a setting unit configured to perform processing related to setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes the following processes: assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit, associating one or more first nodes in an output layer of the first model with one or more radio resources for transmission divided in a frequency direction, and associating one or more second nodes in an input layer of the second model with one or more of the radio resources. (A16) The information processing device according to (A15), further comprising: a first correspondence relationship between the one or more first nodes in the output layer of the first model and the one or more radio resources for transmission, and a second correspondence relationship between the one or more second nodes in the input layer of the second model and the radio resources, which are determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (A17) The information processing device according to any one of (A13) to (A16), wherein the reception decoding unit includes a conversion processing unit, and the conversion processing unit executes a conversion process determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side and a weighting coefficient matrix at a division point of the AI / ML model.(A18) The information processing device according to any one of (A13) to (A16), wherein the transmission encoding unit includes a conversion processing unit, and the conversion processing unit performs conversion processing determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (A19) The information processing device according to any one of (A2) to (A18), wherein the determination unit determines the mode depending on a protocol stack supported by the communication device. (A20) The information processing device according to (A19), wherein the communication device is a base station, and the determination unit determines the mode depending on a protocol stack supported by the base station. (A21) The information processing device according to (A19), wherein the communication device is a terminal device, and the determination unit determines the mode depending on a protocol stack supported by the terminal device. (A22) The information processing device according to (A2) or (A3), wherein the determination unit determines the mode of the protocol stack for the second communication when the communication device performs handover. (A23) The information processing device according to (A22), wherein the determination unit determines the mode of the protocol stack for the second communication based on wireless capability information of the communication device. (A24) The information processing device according to (A23), wherein the communication device is a terminal device, and the determination unit determines the mode of the protocol stack for the second communication based on wireless capability information of the terminal device. (A25) The information processing device according to (A23), wherein the communication device is a base station, and the determination unit determines the mode of the protocol stack for the second communication based on wireless capability information of the base station.

[0521] <Information Processing Method> The present technology can also be configured as follows. (B1) An information processing method executed by an information processing device capable of processing first communication that propagates source data as information that can be restored to the same form on a receiving side, and second communication that propagates to the receiving side some or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the information processing method comprising: a determining step of determining a protocol stack configuration for the second communication; and a transmitting step of transmitting information related to the determined configuration to one or more communication devices that support the first communication and the second communication. (B2) The information processing method described in (B1), wherein, in the determining step, a configuration selected from a plurality of configurations for the second communication is determined as the protocol stack configuration for the second communication. (B3) The information processing method according to (B2), wherein the multiple modes for the second communication include a first mode using encoding or decoding processing for the first communication and a second mode using integrated source channel encoding or integrated source channel decoding processing for the second communication. (B4) The information processing method according to (B3), wherein the second mode is a mode in which at least one AI / ML model is configured between a transmission encoding unit of a first communication device that is the transmitting communication device and a reception decoding unit of a second communication device that is the receiving communication device. (B5) The information processing method according to any one of (B2) to (B4), wherein the determining step determines a protocol stack mode for the second communication when a session establishment request including an instruction for the second communication is received or when the communication device receives system information. (B6) The information processing method according to any one of (B2) to (B5), wherein the information related to the mode includes information on a network slice corresponding to the second communication.(B7) The information processing method according to (B6), wherein different network slices corresponding to different communication directions are prepared as network slices corresponding to the second communication. (B8) The information processing method according to (B7), wherein different network slices corresponding to different communication targets are prepared as network slices corresponding to the second communication. (B9) The information processing method according to any one of (B2) to (B8), wherein the information related to the form includes information related to the AI / ML model set by the communication device. (B10) The information processing method according to (B9), wherein different AI / ML models corresponding to different communication targets are prepared as the AI / ML models. (B11) The information processing method according to any one of (B2) to (B10), wherein the multiple forms for the second communication include a form constituting a layer that provides support information for the second communication to one or more sublayers constituting a pre-5G protocol stack. (B12) The information processing method according to (B11), wherein the layer that provides the assistance information for the second communication is configured by the AI / ML model. (B13) The information processing method according to (B4), further comprising: a setting step of performing processing related to setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting step executes processing of assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit, processing of associating one or more first nodes in an output layer of the first model with one or more first ports of a transmitting antenna, and processing of associating one or more second nodes in an input layer of the second model with one or more second ports of a receiving antenna.(B14) The information processing method described in (B13), wherein a first correspondence between one or more first nodes of the output layer of the first model and one or more first ports of the transmitting antenna, and a second correspondence between one or more second nodes of the input layer of the second model and one or more second ports of the receiving antenna, are determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (B15) The information processing method according to (B4), further comprising: a setting step for performing processing related to setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting step executes the following processes: a process for assigning the first model to a transmission encoding unit and the second model to a reception decoding unit; a process for associating one or more first nodes in an output layer of the first model with one or more radio resources for transmission divided in the frequency direction; and a process for associating one or more second nodes in an input layer of the second model with one or more of the radio resources. (B16) The information processing method according to (B15), wherein a first correspondence relationship between one or more first nodes in the output layer of the first model and one or more of the radio resources for transmission, and a second correspondence relationship between one or more second nodes in the input layer of the second model and the radio resources, are determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (B17) The information processing method according to any one of (B13) to (B16), wherein the reception decoding unit performs a conversion process determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side, and a weighting coefficient matrix at a division point of the AI / ML model. (B18) The information processing method according to any one of (B13) to (B16), wherein the transmission encoding unit executes a conversion process determined by a propagation channel matrix between the communication device on a transmitting side and the communication device on a receiving side and a weighting coefficient matrix at a division point of the AI / ML model.(B19) The information processing method according to any one of (B2) to (B18), wherein the determining step determines the mode depending on a protocol stack supported by the communication device. (B20) The information processing method according to (B19), wherein the communication device is a base station, and wherein the determining step determines the mode depending on a protocol stack supported by the base station. (B21) The information processing method according to (B19), wherein the communication device is a terminal device, and wherein the determining step determines the mode depending on a protocol stack supported by the terminal device. (B22) The information processing method according to (B2) or (B3), wherein the determining step determines the mode of the protocol stack for the second communication when the communication device performs handover. (B23) The information processing method according to (B22), wherein the determining step determines the mode of the protocol stack for the second communication based on radio capability information of the communication device. (B24) The information processing method according to (B23), wherein the communication device is a terminal device, and the determining step determines a protocol stack configuration for the second communication based on wireless capability information of the terminal device. (B25) The information processing method according to (B23), wherein the communication device is a base station, and the determining step determines a protocol stack configuration for the second communication based on wireless capability information of the base station.

[0522] <Communication Device (Base Station 30 / Terminal Device 40)> The present technology can also be configured as follows. (C1) A communication device that supports a first communication that propagates source data as information that can be restored to the same form on a receiving side, and a second communication that propagates to the receiving side some or all of information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the communication device comprising: an acquisition unit that acquires information regarding a protocol stack configuration for the second communication; and a setting unit that sets the protocol stack configuration for the second communication based on the information regarding the configuration. (C2) The communication device described in (C1), wherein the information regarding the configuration includes information regarding at least one of a first configuration that uses encoding or decoding processing for the first communication, and a second configuration that uses integrated source channel encoding or integrated source channel decoding processing for the second communication. (C3) The communication device according to (C2), comprising: a first communication processing unit that performs encoding or decoding for the first communication; and a second communication processing unit that performs encoding or decoding for the second communication, wherein the setting unit, when information on a protocol stack type for the second communication indicates a first type, selects the first communication processing unit as the communication processing unit for the second communication and performs setting related to a pre-encoding unit for transmission or a post-decoding unit for reception, and when the information on the protocol stack type for the second communication indicates a second type, selects the second communication processing unit as the communication processing unit for the second communication. (C4) The communication device according to (C3), wherein the first communication processing unit comprises a first encoding unit that performs encoding for the first communication, and when the information on the protocol stack type for the second communication indicates the first type, data to be transmitted to another communication device is input to the pre-encoding unit, and the output thereof is input to the first encoding unit.(C5) The communication device according to (C3) or (C4), wherein the first communication processing unit includes a first decoding unit that performs decoding for the first communication, and when the information regarding the protocol stack mode for the second communication indicates the first mode, received data from the other communication device is input to the first decoding unit, and the output of the first decoding unit is input to the post-decoding unit. (C6) The communication device according to any one of (C3) to (C5), wherein the second communication processing unit includes a second encoding unit that performs encoding for the second communication, and when the information regarding the protocol stack mode for the second communication indicates the second mode, data to be transmitted to the other communication device is input to the second encoding unit. (C7) The communication device according to any one of (C3) to (C6), wherein the second communication processing unit includes a second decoding unit that performs decoding for the second communication, and when the information regarding the protocol stack mode for the second communication indicates the second mode, received data from the other communication device is input to the second decoding unit. (C8) The communication device according to any one of (C3) to (C7), wherein, when the information regarding the protocol stack configuration for the second communication indicates the second configuration, the acquisition unit further acquires information regarding the AI / ML model to be set in the second communication processing unit. (C9) The communication device according to (C8), wherein the second communication processing unit includes a second encoding unit that performs encoding for the second communication, and the acquisition unit acquires first information regarding a first model to be set in the second encoding unit as the information regarding the AI / ML model. (C10) The communication device according to (C9), wherein the acquisition unit acquires third information indicating a correspondence between one or more first nodes in an output layer of the first model and one or more first ports of a transmitting antenna. (C11) The communication device according to (C10), including a first conversion processing unit that performs first conversion processing determined by a propagation channel matrix between another communication device and a weighting coefficient matrix of one or more of the first nodes.(C12) The communication device according to (C11), wherein transmission data to another communication device is input to the first conversion processing unit, and the output thereof is input to the second encoding unit. (C13) The communication device according to any one of (C8) to (C12), wherein the second communication processing unit includes a second decoding unit that performs decoding for the second communication, and the acquisition unit acquires second information regarding a second model to be set in the second decoding unit as information regarding the AI / ML model. (C14) The communication device according to (C13), wherein the acquisition unit acquires fourth information indicating a correspondence between one or more second nodes in an input layer of the second model and one or more second ports of a receiving antenna. (C15) The communication device according to (C14), including a second conversion processing unit that executes second conversion processing determined by a propagation channel matrix between another communication device and a weighting coefficient matrix of one or more of the second nodes. (C16) The communication device according to (C15), wherein received data from another communication device is input to the second conversion processing unit, and the output thereof is input to the second decoding unit. (C17) The communication device according to any one of (C2) to (C16), wherein the communication device is a base station, and the acquisition unit acquires information regarding a protocol stack configuration for the second communication during session establishment processing for the second communication. (C18) The communication device according to any one of (C2) to (C17), wherein the communication device is a base station, and the acquisition unit acquires information regarding a protocol stack configuration for the second communication during handover processing for the session for the second communication. (C19) The communication device according to (C18), wherein the information regarding the protocol stack configuration for the second communication is included in a handover request message received from the other communication device.(C20) The communication device according to (C8), further comprising: a determination unit that determines a relationship between the AI / ML model and a transmitting antenna or a receiving antenna; the second communication processing unit comprises a second encoding unit that performs encoding for the second communication and a second decoding unit that performs decoding for the second communication; the acquisition unit acquires, as information related to the AI / ML model, first information related to a first model to be set in the second encoding unit and second information related to a second model to be set in the second decoding unit; and the determination unit determines a first correspondence relationship between one or more first nodes in an output layer of the first model and one or more first ports of a transmitting antenna, and a second correspondence relationship between one or more second nodes in an input layer of the second model and one or more second ports of a receiving antenna, based on a propagation channel matrix between another device and a weighting coefficient matrix of one or more of the first nodes. (C21) A communication method executed by a communication device that supports a first communication that propagates source data as information that can be restored to the same form on the receiving side, and a second communication that propagates some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving side, the communication method comprising: acquiring information regarding the form of a protocol stack for the second communication; and setting the form of the protocol stack for the second communication based on the information regarding the form.

[0523] REFERENCE SIGNS LIST 1 communication system 10 server 20 management device 30 base station 40 terminal device 50 transmitting device 60 receiving device 11, 21 communication unit 31, 41 wireless communication unit 12, 22, 32, 42 storage unit 13, 23, 33, 43 control unit 34, 44, 530, 630 radio access layer 311, 411 transmission processing unit 312, 412 reception processing unit 313, 413 antenna 231, 331, 431 acquisition unit 232, 332, 432 determination unit 233, 333, 433, 500 transmitting unit 234, 334, 434 setting unit 600 receiving unit 341, 441 SDAP sublayer 342, 442 PDCP sublayer 343, 443 RLC sublayer 344, 444 MAC sublayer 345, 445 PHY sublayer 510, 610 Application layer 520, 620 Semantic process layer 540 Encoder 541 Source encoder 542 Channel encoder 640 Decoder 641 Source decoder 642 Channel decoder 550, 650 Mode selector 910 RAN / AN 920 UPF 930 DN 940 Control plane functions 941 AMF 942 NEF 943 NRF 944 NSSF 945 PCF 946 SMF 947 UDM 948 AF 949 AUSF 950 UCMF 951 NWDAF CN Core network

Claims

1. An information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form at the receiving end, and a second communication that propagates some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving end, comprising: a determination unit that determines the form of a protocol stack for the second communication; and a transmission unit that transmits information regarding the determined form to one or more communication devices that support the first communication and the second communication.

2. The information processing device according to claim 1, wherein the determination unit determines a form selected from a plurality of forms for the second communication as the form of the protocol stack for the second communication.

3. An information processing device as described in claim 2, wherein the multiple modes for the second communication include a first mode that uses encoding processing or decoding processing for the first communication, and a second mode that uses integrated source channel encoding processing or integrated source channel decoding processing for the second communication.

4. The information processing device according to claim 3, wherein the second form is a form in which at least one AI / ML model is configured between a transmission encoding unit of a first communication device, which is the communication device on the transmitting side, and a reception decoding unit of a second communication device, which is the communication device on the receiving side.

5. The information processing device according to claim 2, wherein the information relating to the configuration includes information relating to the AI / ML model set by the communication device.

6. An information processing device as described in claim 4, comprising a setting unit that performs processing related to the setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes the following processes: assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit; associating one or more first nodes of an output layer of the first model with one or more first ports of a transmitting antenna; and associating one or more second nodes of an input layer of the second model with one or more second ports of a receiving antenna.

7. The information processing device of claim 6, wherein a first correspondence between one or more first nodes of the output layer of the first model and one or more first ports of the transmitting antenna, and a second correspondence between one or more second nodes of the input layer of the second model and one or more second ports of the receiving antenna, are determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side, and a weighting coefficient matrix at a division point of the AI / ML model.

8. An information processing device as described in claim 4, comprising a setting unit that performs processing related to the setting of the AI / ML model, wherein the AI / ML model is divided into a first model and a second model, and the setting unit executes the following processes: assigning the first model to a transmission encoding unit and assigning the second model to a reception decoding unit; associating one or more first nodes in the output layer of the first model with one or more radio resources for transmission divided in the frequency direction; and associating one or more second nodes in the input layer of the second model with one or more of the radio resources.

9. The information processing device of claim 8, wherein a first correspondence between one or more first nodes in the output layer of the first model and one or more radio resources for transmission, and a second correspondence between one or more second nodes in the input layer of the second model and the radio resources, are determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side, and a weighting coefficient matrix at a division point of the AI / ML model.

10. The information processing device according to claim 6, wherein at least one of the receiving decoding unit and the transmitting encoding unit includes a conversion processing unit, and the conversion processing unit performs conversion processing determined by a propagation channel matrix between the communication device on the transmitting side and the communication device on the receiving side and a weighting coefficient matrix at a division point of the AI / ML model.

11. The information processing device according to claim 2, wherein the determination unit determines the mode according to a protocol stack supported by the communication device.

12. The information processing device according to claim 2, wherein the determination unit determines the form of the protocol stack for the second communication when a session establishment request including an instruction for the second communication is received, when the communication device receives system information, or when the communication device performs a handover.

13. A communications device that supports a first communication that propagates source data as information that can be restored to the same form on the receiving side, and a second communication that propagates some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving side, comprising: an acquisition unit that acquires information regarding the form of a protocol stack for the second communication; and a setting unit that sets the form of the protocol stack for the second communication based on the information regarding the form.

14. The communication device of claim 13, wherein the information relating to the mode includes information relating to at least one of a first mode using encoding or decoding processing for the first communication and a second mode using integrated source channel encoding or integrated source channel decoding processing for the second communication.

15. A communication device as described in claim 14, comprising: a first communication processing unit that performs encoding or decoding for the first communication; and a second communication processing unit that performs encoding or decoding for the second communication, wherein the setting unit, when information regarding the form of the protocol stack for the second communication indicates a first form, selects the first communication processing unit as the communication processing unit for the second communication and performs setting regarding a pre-encoding unit for transmission or a post-decoding unit for reception, and when information regarding the form of the protocol stack for the second communication indicates a second form, selects the second communication processing unit as the communication processing unit for the second communication.

16. The communication device according to claim 15, wherein, when the information relating to the form of the protocol stack for the second communication indicates the second form, the acquisition unit further acquires information relating to the AI / ML model to be set in the second communication processing unit.

17. The communication device according to claim 16, further comprising: a determination unit that determines a relationship between the AI / ML model and a transmitting antenna or a receiving antenna; the second communication processing unit comprises a second encoding unit that performs encoding for the second communication and a second decoding unit that performs decoding for the second communication; the acquisition unit acquires, as information related to the AI / ML model, first information related to a first model to be set in the second encoding unit and second information related to a second model to be set in the second decoding unit; and the determination unit determines a first correspondence relationship between one or more first nodes in an output layer of the first model and one or more first ports of a transmitting antenna, and a second correspondence relationship between one or more second nodes in an input layer of the second model and one or more second ports of a receiving antenna, based on a propagation channel matrix between another device and a weighting coefficient matrix of one or more of the first nodes.

18. An information processing method executed by an information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form at the receiving end, and a second communication that propagates some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model to the receiving end, the information processing method comprising: determining a protocol stack configuration for the second communication; and transmitting information regarding the determined configuration to one or more communication devices that support the first communication and the second communication.

19. A communication method executed by a communication device that supports a first communication that propagates source data as information that can be restored to the same form on the receiving side, and a second communication that propagates to the receiving side some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model, the method comprising: acquiring information regarding the configuration of a protocol stack for the second communication; and setting the configuration of the protocol stack for the second communication based on the information regarding the configuration.

20. A communications system comprising: an information processing device capable of processing a first communication that propagates source data as information that can be restored to the same form on the receiving side; and a second communication that propagates to the receiving side some or all of the information extracted from the source data using an AI (Artificial Intelligence) / ML (Machine Learning) model; and one or more communications devices that support the second communications, wherein the information processing device comprises: a determination unit that determines a protocol stack configuration for the second communications; and a transmission unit that transmits information relating to the determined configuration to one or more communications devices that support the first communications and the second communications, and the communications device comprises: an acquisition unit that acquires information relating to the protocol stack configuration for the second communications; and a setting unit that sets the protocol stack configuration for the second communications based on the information relating to the configuration.

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