Authorization of joint learning participants in 5G system (5GS)

Abstract

Embodiments include a method of a first network function, NF, configured to operate as a server of a Joint Learning, FL, group in a communications network. The method includes registering in a network repository function, NRF, of the communication network information: a vendor ID associated with a first NF, and an interoperability ID corresponding to one or more vendor IDs associated with a further NF authorized to join the FL group as a client. The method includes receiving an indication that a second NF of the communication network is a candidate client of an FL group, and creating or updating the FL group to include the second NF as a client in the FL group based on one of: a first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or a second token indicating that the second NF is authorized to join the FL group as the client.

Description

Technical Field

[0001] The present application relates generally to the field of communication networks, and more specifically to techniques for protecting artificial intelligence / machine learning (AI / ML) models used to generate analytics in communication networks (e.g., 5G core networks). Background Art

[0002] Currently, the fifth generation (5G) cellular system, also known as New Radio (NR), is being standardized within the 3rd Generation Partnership Project (3GPP). NR was developed to provide maximum flexibility to support multiple and distinct use cases. These use cases include enhanced mobile broadband (eMBB), machine type communications (MTC), ultra-reliable low latency communications (URLLC), sidelink device-to-device (D2D), and several others.

[0003] At a high level, the 5G system (5GS) consists of an access network (AN) and a core network (CN). The AN provides connectivity from the UE to the CN, for example via base stations (e.g., gNB or ng-eNB) described below. The CN includes various network functions (NFs) that provide a wide range of different functions (e.g., session management, connection management, charging, authentication, etc.).

[0004] Figure 1 A high-level view of an exemplary 5G network architecture is shown, which consists of a next-generation radio access network (NG-RAN) 199 and a 5G core (5GC) 198. The NG-RAN 199 may include one or more gNodeBs (gNBs) connected to the 5GC via one or more NG interfaces, such as gNB 100, gNB 150 connected via interfaces (NG) 102, 152, respectively. More specifically, the gNB 100, gNB 150 may be connected to one or more access and mobility management functions (AMFs) in the 5GC 198 via respective NG-C interfaces. Similarly, the gNB 100, gNB 150 may be connected to one or more user plane functions (UPFs) in the 5GC 198 via respective NG-U interfaces. Various other network functions (NFs) may be included in the 5GC 198, as described in more detail below.

[0005] In addition, the gNBs may be connected to each other via one or more Xn interfaces (e.g., Xn interface 140 between gNB 100 and gNB 150). The radio technology of NG-RAN is generally referred to as "New Radio" (NR). With respect to the NR interface to the UE, each gNB may support frequency division duplex (FDD), time division duplex (TDD), or a combination thereof. Each gNB may provide service for a geographic coverage area including one or more cells, and in some cases, may also use various directional beams to provide coverage in the corresponding cells.

[0006] NG-RAN 199 is layered into Radio Network Layer (RNL) and Transport Network Layer (TNL). The NG-RAN architecture (i.e., NG-RAN logical nodes and the interfaces between them) is defined as part of the RNL. For each NG-RAN interface (NG, Xn, F1), the relevant TNL protocols and functions are specified. TNL provides services for user plane transport and signaling transport.

[0007] Figure 1 The NG-RAN logical nodes shown include a central unit (CU or gNB-CU) and one or more distributed units (DU or gNB-DU). For example, gNB 100 includes gNB-CU 110 and gNB-DU 120 and gNB-DU 130. CU (e.g., gNB-CU 110) is a logical node that hosts high-layer protocols and performs various gNB functions (e.g., controls the operation of DU). DU (e.g., gNB-DU 120, gNB-DU 130) is a decentralized logical node that hosts low-layer protocols and can include various subsets of gNB functions depending on the functional split option.

[0008] gNB-CU through the corresponding F1 logical interface (for example, Figure 1 The F1 interface is connected to one or more gNB-DUs (see interfaces 122 and 132). However, a gNB-DU can only be connected to a single gNB-CU. The gNB-CU and the connected gNB-DUs are visible only as gNBs to other gNBs and the 5GC. In other words, the F1 interface is not visible outside the gNB-CU.

[0009] Another change in 5G networks (e.g., 5GC) is that the traditional peer-to-peer interfaces and protocols found in previous generation networks are modified and / or replaced by a service-based architecture (SBA), in which a network function (NF) provides one or more services to one or more service consumers. For example, this can be done through a hypertext transfer protocol / representational state transfer (HTTP / REST) ​​application programming interface (API). Typically, various services are self-contained functions that can be changed and modified in an isolated manner without affecting other services.

[0010] In addition, these services include various "service operations" which are finer-grained divisions of the overall service functionality. The interactions between service consumers and producers can be of "request / response" or "subscribe / notify" type. In 5G SBA, the Network Repository Function (NRF) allows each network function to discover the services provided by other network functions, and the Data Storage Function (DSF) allows each network function to store its context. The 5G SBA model is based on the principles of modularity, reusability, and self-containment including NFs, which can enable network deployments to take advantage of the latest virtualization and software technologies.

[0011] A 5GC NF of particular interest in this disclosure is the Network Data Analysis Function (NWDAF). This NF provides network analysis information (e.g., statistics of past events and / or prediction information) to other NFs at the network slice instance level. The NWDAF can collect data from any 5GC NF. Note that a "network slice" is a logical partition of a 5G network that provides specific network capabilities and features, e.g., to support a specific service. A network slice instance is a collection of NF instances and the network resources (e.g., compute, storage, communication) required to provide the capabilities and features of a network slice.

[0012] Machine learning (ML) is a type of artificial intelligence (AI) that focuses on using data and algorithms to mimic the way humans learn, gradually improving in accuracy as more data becomes available. ML algorithms build a model based on sample (or "training") data, which is then used to make predictions or decisions. ML algorithms can be used in a variety of applications (e.g., medicine, email filtering, speech recognition, etc.) where it is difficult or infeasible to develop conventional algorithms to perform the desired task. A subset of ML is closely related to computational statistics.

[0013] Traditionally, AI models are hosted on cloud-based servers that also store training data. In contrast, federated learning (FL, also known as collaborative learning) trains ML models on multiple decentralized edge devices that hold local data samples without exchanging training data between devices. Edge devices (e.g., clients) train their respective model copies using their own local data, and then send parameters / weights from their locally trained models to the master device (e.g., server), which aggregates these parameters and updates the global ML model.

[0014] The 5G system architecture allows any NF to obtain analytics from the NWDAF using the Data Collection Coordination Function (DCCF) and associated Ndccf services. The NWDAF can also store and retrieve analytics information from the Analytics Data Repository Function (ADRF). 3GPP TS 23.288 (v17.2.0) specifies that the NWDAF is the main NF that calculates analytics based on ML models, and classifies the NWDAF into two sub-functions (or logical functions): an analysis logic function (AnLF), which performs the analysis process; and a model training logic function (MTLF), which performs training and retraining of the ML model used by the AnLF.

[0015] 3GPP TR 23.700-81 (v1.0.0) specifies: Support for FL in 5GC is a key issue for further study in 3GPP. This document identifies that ML model security is an important requirement for supporting FL in 5GC, especially in the corresponding NWDAF (MTLF) that will operate as a FL client and server. Specifically, the temporary ML models trained by the FL client and the final ML models exported by the FL server are important intellectual property of their owners and should be treated as such in 5GC. Therefore, it is very important to authorize NWDAFs to participate in their corresponding FL roles. However, the granularity of the current authorization capabilities in the 3GPP SBA framework is not fine enough to provide this level of security required. Summary of the invention

[0016] Embodiments of the present disclosure address these and other issues, problems, and / or difficulties, thereby facilitating other advantageous deployments of federated learning for network analytics.

[0017] Some embodiments of the present disclosure include a method (e.g., process) of a first NF configured to operate as a server of a FL group in a communication network (e.g., 5GC).

[0018] The exemplary methods may include registering the following information in a network repository function (NRF) of the communication network: a vendor identifier (ID) associated with the first NF, and an interoperability ID corresponding to one or more vendor IDs associated with additional NFs authorized to join the FL group as clients. The exemplary methods may also include receiving an indication that a second NF of the communication network is a candidate client of the FL group. The exemplary methods may also include creating or updating the FL group to include the second NF as a client based on one of the following:

[0019] - a first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0020] - A second token indicating that the second NF is authorized to join the FL group as a client.

[0021] In some embodiments, the registered information also includes an analysis ID associated with the ML model for FL, and the interoperability ID indicates authorization specific to the analysis ID.

[0022] In some embodiments, creating or updating the FL group to include the second NF as a client in the FL group may include the following operations:

[0023] - in response to the indication, obtaining a first token from the NRF;

[0024] - sending a first request to the second NF to make the second NF join the FL group as a client, wherein the first request includes a first token; and

[0025] - Receive a first response from the second NF, the first response indicating that the second NF will join the FL group as a client.

[0026] In some of these embodiments, the indication that the second NF is a candidate client is received from the NRF as one of: a response to a client discovery request of the first NF, or a notification in response to a subscription request by the first NF requesting registration information of candidate clients of the FL group in the NRF.

[0027] In some of these embodiments, the indication that the second NF is a candidate client is based on one or more of the following items registered by the second NF in the NRF: an interoperability ID corresponding to one or more vendor IDs associated with additional NFs authorized to add the second NF as a client to the FL group; and an analysis ID associated with an ML model for the FL.

[0028] In other embodiments, the indication that the second NF is a candidate client is a FL join request message received from the second NF and including the second token. In this case, creating or updating the FL group to include the second NF as a client in the FL group includes: verifying the second token received from the second NF.

[0029] In some embodiments, the first NF is a NWDAF and / or the second NF is a NWDAF.

[0030] Other embodiments include exemplary methods (eg, processes) of a second NF configured to operate as a client of a FL group in a communication network (eg, 5GC).

[0031] The exemplary methods may include registering the following information in an NRF of the communication network: a vendor ID associated with the second NF, and an interoperability ID corresponding to one or more vendor IDs associated with another NF authorized to add the second NF as a client to the FL group. The exemplary methods may also include subsequently joining the FL group as a client. The first NF is configured to operate as a server of the FL group, and joining the FL group is based on one of the following:

[0032] - a first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0033] - A second token indicating that the second NF is authorized to join the FL group as a client.

[0034] In some embodiments, the registered information also includes an analysis ID associated with the ML model for FL, and the interoperability ID indicates authorization specific to the analysis ID.

[0035] In some embodiments, joining the FL group as a client includes the following operations:

[0036] - receiving a first request from the first NF for the second NF to join the FL group as a client, wherein the first request includes a first token;

[0037] - verifying the first token received from the first NF; and

[0038] - Based on the verification, a first response is sent to the first NF, the first response indicating that the second NF will join the FL group as a client.

[0039] In other embodiments, joining the FL group as a client includes the following operations:

[0040] - discover the FL group and the first NF that is the server of the FL group via the NRF;

[0041] - sending a second request to the first NF to join the FL group as a client, wherein the second request includes a second token; and

[0042] - receiving a second response from the first NF, the second response indicating that the first NF accepted the second request.

[0043] In some of these embodiments, joining the FL group as a client may further include: obtaining a second token from the NRF in response to discovering the FL group and the first NF as a server of the FL group. The obtained second token is sent to the first NF together with the second request.

[0044] Other embodiments include methods (eg, processes) of an NRF of a communication network (eg, 5GC).

[0045] These exemplary methods may include the following information associated with a first NF and a second NF of a communication network:

[0046] - a first vendor ID associated with a first NF, the first NF being configured to operate as a server of the FL group,

[0047] - a first interoperability ID corresponding to one or more vendor IDs associated with further NFs authorized to join the FL group as clients,

[0048] - a second vendor ID associated with a second NF, the second NF being configured to operate as a FL client, and

[0049] - A second interoperability ID corresponding to one or more vendor IDs associated with a further NF authorized to add the second NF as a client to the FL group.

[0050] The exemplary methods may also include providing one or more of the following based on the registered information:

[0051] - providing a first token to the first NF, the first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0052] - Providing a second token to the second NF, the second token indicating that the second NF is authorized to join the FL group as a client.

[0053] In some embodiments, the registered information also includes one or more of the following:

[0054] - a first analysis ID associated with the ML model used by the first NF for FL;

[0055] - a second analysis ID associated with the ML model used for FL by the second NF;

[0056] - an indication of one or more first FL capabilities associated with the first NF; and

[0057] - an indication of one or more second FL capabilities associated with the second NF.

[0058] In some embodiments, these exemplary methods may further include discovering the second NF based on one or more of the following matching or corresponding relationships:

[0059] - a match between the second vendor ID and one of the vendor IDs corresponding to the first interoperability ID,

[0060] - a match between the first analysis ID and the second analysis ID, and

[0061] - A matching or corresponding relationship between the first capability and the second capability.

[0062] In such embodiments, the exemplary methods may further include sending an indication to the first NF that the second NF is a candidate client of the FL group.

[0063] In some of these embodiments, discovering the second NF and sending the indication is in response to one of: a client discovery request by the first NF, or a subscription request by the first NF to registration information of candidate clients of the FL group in the NRF.

[0064] In other embodiments, these exemplary methods may further include discovering the first NF based on one or more of the following matching or corresponding relationships:

[0065] - a match between the first vendor ID and one of the vendor IDs corresponding to the second interoperability ID,

[0066] - a match between the first analysis ID and the second analysis ID, and

[0067] - A matching or corresponding relationship between the first capability and the second capability.

[0068] In such embodiments, the exemplary methods may further include sending an indication to the second NF regarding the FL group and regarding the first NF being a server of the FL group.

[0069] In some of these embodiments, discovering the first NF and sending the indication is in response to one of: registering information associated with the second NF, or a server discovery request of the second NF.

[0070] Other embodiments include a NF (e.g., NWDAF, NRF) or a network node hosting such a NF, which is configured to perform operations corresponding to any of the exemplary methods described herein. Other embodiments also include a non-transitory computer-readable medium storing computer-executable instructions, which, when executed by a processing circuit, configures such a NF or a network node to perform operations corresponding to any of the exemplary methods described herein.

[0071] These and other disclosed embodiments may prevent unauthorized NFs (e.g., NWDAFs) from joining a FL group as a client and / or prevent NFs from joining a group as a client to perform fraudulent and / or inauthentic FL operations. In this way, embodiments may prevent confidential and / or sensitive ML models from being exposed to unauthorized parties during FL, and may prevent security risks to NFs that are able to participate in FL. By improving security, embodiments facilitate deployment of FL in multi-vendor communication networks (e.g., 5GC).

[0072] These and other objects, features and advantages of the present disclosure will become apparent when the following detailed description is read in conjunction with the accompanying drawings which are briefly described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 to Figure 2 Various aspects of an exemplary 5G network architecture are shown.

[0074] Figure 3 A high-level diagram showing the process for client NWDAF selection during the FL preparation phase.

[0075] Figure 4 A high-level diagram of the process for client NWDAF monitoring and reselection during the FL execution phase is shown.

[0076] Figures 5 and 6 A high-level diagram showing the two processes for dynamic discovery and new NWDAF joining in the FL execution phase.

[0077] Figure 7 A signaling diagram of processes involving a server NWDAF, an NRF, and various client NWDAFs according to various embodiments of the present disclosure is shown.

[0078] Figure 8 An exemplary method (eg, process) of a first NF of a communication network according to various embodiments of the present disclosure is illustrated.

[0079] Fig. 9 An exemplary method (eg, process) of a second NF of a communication network according to various embodiments of the present disclosure is illustrated.

[0080] Fig.10Exemplary methods (eg, processes) of an NRF of a communication network according to various embodiments of the present disclosure are illustrated.

[0081] Fig.11 A communication system according to various embodiments of the present disclosure is shown.

[0082] Fig.12 A UE according to various embodiments of the present disclosure is shown.

[0083] Fig.13 A network node according to various embodiments of the present disclosure is shown.

[0084] Fig.14 A host computing system according to various embodiments of the present disclosure is shown.

[0085] Fig.15 is a block diagram of a virtualization environment that may virtualize functionality implemented by some embodiments of the present disclosure.

[0086] Fig.16 Communications between a host computing system, a network node, and a UE via multiple connections are illustrated according to various embodiments of the present disclosure. DETAILED DESCRIPTION

[0087] The embodiments briefly summarized above will now be described more fully with reference to the accompanying drawings. These descriptions are provided by way of example to illustrate the subject matter to those skilled in the art and should not be construed as limiting the scope of the subject matter to only the embodiments described herein. More specifically, examples illustrating the operation of various embodiments according to the above advantages are provided below.

[0088] Generally, unless clearly given and / or different meanings are implied from the context, all terms used herein will be interpreted according to their common meanings in the relevant technical field. Unless otherwise clearly stated, all references to "one / an / element, equipment, component, device, step, etc." should be openly interpreted as referring to at least one instance in an element, equipment, component, device, step, etc. Unless a step must be explicitly described as after or before another step and / or implicitly a step must be after or before another step, the steps of any method and / or process disclosed herein do not have to be performed in the exact order disclosed. Where appropriate, any feature of any embodiment disclosed herein may be applied to any other embodiment. Similarly, any advantage of any embodiment may be applicable to any other embodiment, and vice versa. By the following description, other purposes, features and advantages of the disclosed embodiment will be apparent.

[0089] Furthermore, the following terms are used throughout the description given below:

[0090] - Radio access node: As used herein, a "radio access node" (or equivalently, a "radio network node", "radio access network node" or "RAN node") may be any node in a radio access network (RAN) of a cellular communication network that operates to wirelessly send and / or receive signals. Some examples of radio access nodes include, but are not limited to, base stations (e.g., new radio (NR) base stations (gNBs) in 3GPP fifth generation (5G) NR networks or enhanced or evolved NodeBs (eNBs) in 3GPP LTE networks), base station distributed components (e.g., CUs and DUs), high power or macro base stations, low power base stations (e.g., micro, pico, femto or home base stations, etc.), integrated access backhaul (IAB) nodes (or components thereof, such as MTs or DUs), transmission points, remote radio units (RRUs or RRHs), and relay nodes.

[0091] -Core network node: As used herein, a "core network node" is any type of node in the core network. Some examples of core network nodes include, for example, a mobility management entity (MME), a serving gateway (SGW), a packet data network gateway (P-GW), etc. A core network node may also be a node that implements a specific core network function (NF) such as an access and mobility management function (AMF), a session management function (SMF), a user plane function (UPF), a service capability exposure function (SCEF), etc.

[0092] -Wireless device: As used herein, a "wireless device" (or "WD" for short) is any type of device capable of, configured, arranged and / or operable to wirelessly communicate with a network node and / or other wireless devices. Wireless communication may include sending and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves and / or other types of signals suitable for sending information through the air. Unless otherwise specified, the term "wireless device" is used interchangeably herein with the term "user equipment" ("UE" for short), and both terms have different meanings from the term "network node".

[0093] - Radio node: As used herein, a "radio node" may be a "radio access node" (or equivalent terms) or a "wireless device".

[0094] - Network node: As used herein, a "network node" is any node that is part of a radio access network (e.g., a radio access node or equivalent term) or part of a core network (e.g., the core network node discussed above) of a cellular communication network. Functionally, a network node is a device that is capable, configured, arranged and / or operable to communicate directly or indirectly with a wireless device and / or with other network nodes or devices in a cellular communication network to enable and / or provide radio access to a wireless device, and / or perform other functions (e.g., management) in the cellular communication network.

[0095] -Node: As used herein, the term "node" (without a prefix) may be any type of node capable of operating in or with a wireless network (including a RAN and / or a core network), including a radio access node (or equivalent terms), a core network node, or a wireless device. However, the term "node" may be limited to a specific type (e.g., a radio access node) based on its specific characteristics in any given context.

[0096] Note that the description given herein focuses on 3GPP cellular communication systems, and therefore often uses 3GPP terminology or terms similar to 3GPP terminology. However, the concepts disclosed herein are not limited to 3GPP systems. Other wireless systems (including but not limited to Wideband Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB), and Global System for Mobile Communications (GSM)) may also benefit from these concepts, principles, and / or embodiments described herein.

[0097] In addition, the functions and / or operations performed by a wireless device or network node described herein may be distributed across multiple wireless devices and / or network nodes. In addition, although the term "cell" is used herein, it should be understood that (particularly for 5GNR) a beam may be used instead of a cell, and therefore, the concepts described herein are equally applicable to both cells and beams.

[0098] Figure 2 An exemplary non-roaming reference architecture of a 5GC (200) with service-based interfaces and various 3GPP-defined NFs within the control plane (CP) is shown. These include the following:

[0099] - Application Function (AF, with Naf interface), interacts with 5GC to provide information to the network operator and subscribe to specific events occurring in the operator's network. AF provides applications with services delivered in a layer different from the layer where the service has been requested (i.e., the signaling layer), controlling flow resources according to what has been negotiated with the network. AF delivers dynamic session information to PCF (via N5 interface), including a description of the media to be delivered by the transport layer.

[0100] -Policy Control Function (PCF, with Npcf interface), supports a unified policy framework to manage network behavior, and provides PCC rules to SMF via N7 reference point (e.g., regarding the processing of each service data flow under PCC control). PCF provides policy control decisions and flow-based charging control (including service data flow detection, gating, QoS) and flow-based charging (in addition to credit management) to SMF. PCF receives session and media related information from AF, and notifies AF of service (or user) plane events.

[0101] - User Plane Function (UPF) - supports the processing of user plane traffic based on rules received from the SMF, including packet inspection and different execution actions (e.g., event detection and reporting). The UPF communicates with the RAN (e.g., NG-RNA) via the N3 reference point, with the SMF (discussed below) via the N4 reference point, and with external packet data networks (PDNs) via the N6 reference point. The N9 reference point is used for communication between two UPFs.

[0102] -Session Management Function (SMF, with Nsmf interface), interacts with the decoupled service (or user) plane, including creating, updating, and deleting protocol data unit (PDU) sessions and managing session context with the user plane function (UPF), such as for event reporting. For example, SMF performs data flow detection (based on filter definitions included in PCC rules), online and offline charging interactions, and policy enforcement.

[0103] - Charging Function (CHF, with Nchf interface), responsible for merging online and offline charging functions. The Charging Function provides quota management (for online charging), re-authorization triggers, rating conditions, etc., and is informed about usage reports from the SMF. Quota management involves granting a specific number of units (e.g., bytes, seconds) for a service. The CHF also interacts with the charging system.

[0104] - Access and Mobility Management Function (AMF, with Namf interface) terminates the RAN CP interface and handles all mobility and connection management of the UE (similar to the MME in EPC). The AMF communicates with the UE via the N1 reference point and with the RAN (e.g., NG-RAN) via the N2 reference point.

[0105] - Network Exposure Function (NEF) with Nnef interface - serves as an entry point to the operator network by securely exposing network functions and events provided by 3GPP NFs to the AF and providing a way for the AF to securely provide information to the 3GPP network. For example, the NEF provides services that allow the AF to provide specific subscription data (e.g., expected UE behavior) for various UEs.

[0106] - Network Repository Function (NRF, 220) with Nnrf interface – provides service registration and discovery, enabling NFs to identify appropriate services available from other NFs.

[0107] - Network Slice Selection Function (NSSF) with Nnssf interface - A "network slice" is a logical partition of a 5G network that provides specific network capabilities and features, e.g., to support a specific service. A network slice instance is a collection of NF instances and the network resources (e.g., compute, storage, communication) required to provide the capabilities and features of a network slice. NSSF enables other NFs (e.g., AMF) to identify a network slice instance that is suitable for the service desired by the UE.

[0108] - Authentication Server Function (AUSF) with NAUSF interface – Based on the user’s home network (HPLMN), it performs user authentication and computes security key material for various purposes.

[0109] - A network data analysis function (NWDAF, 210) having an Nnwdaf interface, described in more detail above and below.

[0110] - Location Management Function (LMF) with Nlmf interface - supports various functions related to the determination of the UE location, including location determination of the UE and obtaining any of the following: DL location measurements or position estimates from the UE; UL location measurements from the NG RAN; and non-UE associated assistance data from the NG RAN.

[0111] The Unified Data Management (UDM) function supports access authorization based on subscription data, user identity processing, generation of 3GPP authentication credentials, and other subscriber-related functions. To provide this function, UDM uses subscription data (including authentication data) stored in the 5GC Unified Data Repository (UDR). In addition to UDM, UDR also supports storage and retrieval of policy data by PCF and storage and retrieval of application data by NEF.

[0112] NRF allows each NF to discover services provided by other NFs, and Data Storage Function (DSF) allows each NF to store its context. In addition, NEF provides exposure to 5GC capabilities and events to AFs within and outside 5GC. For example, NEF provides services that allow AF to provide specific subscription data (e.g., expected UE behavior) for various UEs.

[0113] The communication link between the UE and the 5G network (AN and CN) can be grouped into two different layers. The UE communicates with the CN through the non-access stratum (NAS) and communicates with the AN through the access stratum (AS). All NAS communications are carried out via the NAS protocol ( Figure 2 The N1 interface in the UE layer is between the UE and the AMF. The security of the communication on these layers is provided by the NAS protocol (for NAS) and the PDCP protocol (for AS).

[0114] 3GPP Release 17 enhances SBA by adding a data management framework, which includes the Data Collection Coordination Function (DCCF) and the Messaging Framework Adapter Function (MFAF) defined in detail in 3GPP TR23.700-91 (v17.0.0). As mentioned above, the data management framework is backward compatible with the NWDAF functions of Release 16. For Release 17, the baseline of the services provided by the DCCF (e.g., to the NWDAF) are the NF services of Release 16 for obtaining data. For example, the baseline of the DCCF service used by the NWDAF consumer to obtain UE mobility data is Namf_EventExposure.

[0115] As briefly mentioned above, machine learning (ML) is a type of artificial intelligence (AI) that focuses on using data and algorithms to mimic the way humans learn, gradually improving in accuracy as more data becomes available. ML algorithms build a model based on sample (or "training") data, which is then used to make predictions or decisions. ML models can be used in a variety of applications (e.g., medicine, email filtering, speech recognition, etc.) where it is difficult or infeasible to develop conventional algorithms to perform the required tasks.

[0116] 3GPP TS 23.288 (v17.2.0) specifies that NWDAF is the main NF for computing analysis based on ML models, and classifies NWDAF into two sub-functions (or logical functions): an analysis logic function (AnLF), which performs the analysis process; and a model training logic function (MTLF), which performs training and retraining of the ML model used by AnLF. In the following, the terms "AnLF", "NWDAF AnLF" and "NWDAF (AnLF)" will be used interchangeably. Similarly, the terms "MTLF", "NWDAF MTLF" and "NWDAF (MTLF)" will be used interchangeably.

[0117] 3GPP TS 23.288 (v17.2.0) specifies a subscription / notification procedure for consumer NFs to retrieve ML models associated with one or more analysis IDs whenever a new ML model has been trained by the NWDAF MTLF and becomes available. This is called ML model provisioning and is implemented by the Nnwdaf_MLModelProvision service.

[0118] Traditionally, ML models are trained on cloud-based servers that also store training data. In contrast, federated learning (FL, also known as collaborative learning) trains ML models on multiple decentralized edge devices that hold local data samples without exchanging training data between devices. Edge devices (e.g., clients) train their respective model copies using their own local data, and then send parameters / weights from their locally trained models to the master device (e.g., server), which aggregates these parameters and updates the global ML model.

[0119] 3GPP TR 23.700-81 (v1.0.0) specifies: Support for FL in 5GC is a key issue for further study in 3GPP. This document identifies that ML model security is an important requirement for supporting FL in 5GC, especially in the corresponding NWDAF (MTLF) that will operate as FL client and server. The following text from 3GPP TR 23.700-81 (v1.0.0) describes various aspects of this key issue to be studied.

[0120] ***BEGIN 3GPP TEXT***

[0121] 5.8.1 Description

[0122] This contribution is related to WT#4.1.

[0123] The current NWDAF drivers for implementing network automation architecture still face the following major challenges:

[0124] -User data privacy and security (protected by GDPR, etc.) has become a global issue, and it is difficult for NWDAF to collect UE-level network data.

[0125] -With the introduction of MTLF in Version 17, various data from a wide area are required to train the ML model of NWDAF with MTLF. However, it is difficult for NWDAF with MTLF to collect all the raw data from distributed data sources in different regions.

[0126] To address these challenges, 3GPP attempts to adopt federated learning (also known as federated machine learning) technology in NWDAFs containing MTLF to train ML models, where no original data transmission (e.g., centralized to NWDAF) is required, but only cooperation between multiple NWDAFs (MTLFs) is required, that is, ML models and learning results are shared among multiple NWDAFs (MTLFs). However, in Release 17, cooperation between multiple NWDAFs containing MTLF is explicitly prohibited, and only NWDAFs containing AnLF are allowed to subscribe to or request ML models from the configured NWDAF containing MTLF.

[0127] This key issue aims to study architectural enhancements to support federated learning that allows the cooperation of multiple NWDAFs including MTLF to train ML models in 3GPP networks in terms of:

[0128] - Identify use cases in 5GC that require federated learning;

[0129] - Research the registration and discovery of NWDAFs that support federated learning;

[0130] - Study how to decide whether an existing analysis ID or a new analysis ID needs to be federated learned;

[0131] - Study how to coordinate multiple NWDAFs, including the selection of participant NWDAF instances in a federated learning group, e.g., the auxiliary information used to perform that selection (if any), and the decision on the roles of the participant NWDAFs;

[0132] - Study whether and how to perform performance (e.g., network performance and model performance) monitoring of NWDAF federated learning operations.

[0133] Note 1: Performance monitoring of federated learning operations should be consistent with the mechanisms defined in WT#1.2 for improved analysis correctness.

[0134] Note 2: Collaboration with SA3 is required on improvements to user data privacy and security.

[0135] Note 3: The impact of this critical issue on UE and RAN should be avoided.

[0136] Note 4: Solutions for model distribution that require FL should be consistent with the mechanism for model sharing defined in WT#3.2.

[0137] Note 5: The server NWDAF is connected to one layer of the client NWDAF, and any client NWDAF cannot cascade more sub-layers.

[0138] Note 6: All NWDAFs participating in the joint learning should belong to the same PLMN.

[0139] ***END 3GPP TEXT***

[0140] Some candidate solutions for participant NWDAF discovery and selection are described in 3GPP TR 23.700-81 (v1.0.0). One of these solutions ("Solution #51") is described in the following text from 3GPP TR 23.700-81 (v1.0.0):

[0141] ***BEGIN 3GPP TEXT***

[0142] 6.51.1 Description

[0143] This solution is proposed to solve key problem #8: Supporting federated learning in 5GC. The key points of this key problem include:

[0144] - Study how to coordinate multiple NWDAFs, including the selection of participant NWDAF instances in a federated learning group, e.g., the auxiliary information (if any) used to perform that selection, and the decision on the roles of the participant NWDAFs.

[0145] - Study whether and how to perform performance (e.g., network performance and model performance) monitoring of NWDAF federated learning operations.

[0146] To address the challenges of the above-mentioned key points in supporting federated learning in 5GC, this solution focuses on NWDAF selection in the federated learning preparation phase, and NWDAF monitoring and maintenance in the federated learning execution phase.

[0147] Many factors affect the selection of client NWDAF in the federated learning preparation phase, such as the capabilities of the NWDAF, the interoperability and availability of the client NWDAF to join the federated learning.

[0148] During the joint learning execution phase, due to the dynamic changes of the joint network, the current client NWDAF may leave or join, and the client NWDAF should be considered to dynamically join and leave the joint learning multiple rounds of learning / training process in 5GC. In addition, the server NWDAF can also use methods to monitor the status changes of the client NWDAF (e.g., changes in capabilities and availability).

[0149] ***END 3GPP TEXT***

[0150] In the FL preparation phase, server and (potential) client NWDAFs are discovered via NRF, and a client NWDAF is selected by means of a handshake mode. Client NWDAF selection is based on availability, capabilities, etc. Figure 3A high-level diagram shows the process for client NWDAF selection during the FL preparation phase. Figure 3 The operations in are given numerical labels, but this is intended to facilitate the following description and is not intended to require or imply any particular order of operations unless explicitly stated otherwise.

[0151] In operation 0 (which can be regarded as a preparation phase), the NWDAF registers the FL capability into the NRF. The server NWDAF discovers the client NWDAF based on, for example, the FL capability, analysis ID, and the like.

[0152] In operation 1, the server NWDAF sends a FL preparation request to the client NWDAF by calling the Nnwdaf_MLPreparation_Request service operation with interoperability information. An indication of the role of the NWDAF (i.e., as a client NWDAF) may be included in the preparation request. Note that the interoperability information indicates which capabilities the client NWDAF needs to support the FL process (e.g., being able to run certain models), for example, whether and how the server NWDAF and the client NWDAF can share models. The interoperability information is determined between different vendors and its content is not specified by 3GPP.

[0153] In operation 2, the client NWDAF determines whether to join the FL process based on its respective availability, capability and interoperability information. In operation 3, one or more client NWDAFs respond to the server NWDAF indicating that they want to join the FL process.

[0154] In operation 4, the server NWDAF may send a test task to the client NWDAF that wants to join the FL process. The client NWDAF runs the test task and sends the result to the server NWDAF. Note that the test task may be a micro-computation or training task, so that the requirements for completing the micro-task are the same or similar to those for completing the main task. For example, the test task may be a small task for the client NWDAF to collect local data and send local model weights back to the server; or to perform some tests to ensure that the server and client NWDAF can communicate if they use the same FL framework or library. How to retrieve and run the test task is beyond the scope of the 3GPP specification.

[0155] In operation 5, the server NWDAF selects the client NWDAF of the FL according to the need and / or desire considering the result of the test task.

[0156] In the FL execution phase, the server NWDAF monitors the status changes of the client NWDAFs and can reselect the client NWDAFs to perform the FL task based on the update status, availability and / or capability of the client NWDAFs. Figure 4 A high-level diagram of the process for NWDAF monitoring and reselection during the FL execution phase is shown. Figure 4 The operations in are given numerical labels, but this is intended to facilitate the following description and is not intended to require or imply any particular order of operations unless explicitly stated otherwise.

[0157] In operation 1, when monitoring the status of the client NWDAF during FL execution, the server NWDAF receives the updated status of the client NWDAF. The server NWDAF may perform monitoring and obtain the updated status of the client NWDAF directly and / or via the NRF. For example, the status of the client NWDAF may be NF load, NF availability, capability change (e.g., no longer supporting FL), etc.

[0158] In operation 2, the server NWDAF checks the client NWDAF status based on the received information and determines whether the client NWDAF needs to be reselected for the next round of FL. The determination is based on the updated status of the client NWDAF, including availability, capability, etc. If it is determined that reselection is required, in operation 3, the server NWDAF selects the client NWDAF based on the received information. Figure 3 To reselect the client NWDAF, follow steps 1 to 5 in the following. Figure 5 The process for discovering a new client NWDAF in the FL execution phase is described below.

[0159] In operation 4, if the client NWDAF receives a termination request from the server NWDAF, it terminates the operation of the FL.

[0160] There are two possible ways for the server NWDAF to obtain information about the new client NWDAF: directly from the new client, or indirectly via the NRF. Figure 5 A high-level diagram shows the process in the FL execution phase for dynamically discovering and joining a new NWDAF when a new client directly informs the server of the NWDAF. Figure 5 The operations in are given numerical labels, but this is intended to facilitate the following description and is not intended to require or imply any particular order of operations unless explicitly stated otherwise.

[0161] As a prerequisite, the server NWDAF selects clients NWDAF 1 to NWDAF N to participate in the current round of FL. New clients NWDAF N+(1-X) are available and / or have the ability to join subsequent rounds of FL. These new clients NWDAF know information about the server NWDAF. In operation 0, the server NWDAF registers the FL process with the NRF using the following parameters:

[0162] -FL correlation ID, used to identify a specific FL process. For example, a server NWDAF or a client NWDAF can be part of multiple FL processes at the same time, so when they receive a message or data from other NWDAFs, they must know the FL process associated with the message or data.

[0163] -Analysis ID

[0164] When the server NWDAF starts the FL process, it registers the FL process in the NRF using the FL association ID, analysis ID. When the client NWDAF later wants to dynamically join the FL, for example, it wants to update its local model with global information, it will query the NRF if there is an ongoing FL for the analysis ID. The NRF will then provide the server NWDAF ID and the FL association ID to the client NWDAF, and the client NWDAF can then contact the server NWDAF to join the FL process. With the FL association ID, the server NWDAF knows which FL process the client NWDAF wants to join and which model should be provided to the client.

[0165] In operation 1, if information about the server NWDAF and the corresponding FL process is known via the NRF, the new client NWDAF N+(1-X) informs the server NWDAF by calling the Nnwdaf_MLPreparation_Request service operation indicating its interoperability and availability information.

[0166] In operation 2, before starting the next round of training, the server NWDAF selects a client NWDAF from NWDAF 1-(N+X) based on the updated information of the client NWDAF. Figure 3 Perform operations 1 to 5 in the

[0167] Figure 6 A high-level diagram shows the process for dynamically discovering and joining a new NWDAF in the FL execution phase when the server NWDAF obtains information about the NWDAF from the NRF. Figure 6 The operations in are given numerical labels, but this is intended to facilitate the following description and is not intended to require or imply any particular order of operations unless explicitly stated otherwise.

[0168] As a prerequisite, the server NWDAF selects clients NWDAF 1 to NWDAF N to participate in the current round of FL. New clients NWDAF N+(1-X) are available and / or have the ability to join subsequent rounds of FL. Operation 0 and Figure 5 The same as operation 0 in operation 1. In operation 1, the server NWDAF dynamically obtains information about the new client NWDAF via the NRF, that is, by subscribing to the event that the new client NWDAF registers with the NRF, or discovering the new client NWDAF via the NRF when reselection of the client NWDAF is required. Operation 2 is the same as operation 3. Figure 5 The same as operation 2 in .

[0169] The temporary ML models trained by the FL client and the final ML models exported by the FL server are important intellectual property rights of their owners and should be treated as such in 5GC. Therefore, it is very important to authorize NWDAFs to participate in their corresponding FL roles. For example, if a client NWDAF instance joins an unauthorized FL group, the following security threats and / or issues may result:

[0170] - The resources of the client NWDAF (MTLF) may be exhausted by being included in many unauthorized FL groups.

[0171] -Sensitive data may be used to train ML models by unauthorized FL groups.

[0172] - An unauthorized FL group may exploit the local model received from the client NWDAF (MTLF) to infer sensitive training data details.

[0173] Typically, if the client NWDAF joins the FL group without the server NWDAF authorization, the following security threats and / or problems may result:

[0174] - Unauthorized client NWDAF may negatively impact ML model generation of the FL group.

[0175] -Sensitive training data and ML models of the FL group may be exposed to unauthorized clients NWDAF.

[0176] Therefore, it is necessary to selectively authorize the participant NWDAF instances in the FL group. Specifically, the client NWDAF should be able to authorize the server NWDAF whether it can include it into the FL group, and the server NWDAF should be able to authorize the client NWDAF whether it can join the FL group. However, the current authorization capabilities in the 3GPP SBA framework only support authorization at the SBA service, resource or operation level, which is not fine-grained enough to ensure that the server and client NWDAF are authorized to participate in the FL process, and / or that the provided FL process is authentic and / or does not pose a security threat to potential participants.

[0177] Embodiments of the present disclosure solve these and other problems, problems and / or difficulties through the following techniques: The server NWDAF provides an authorization profile for a specific FL group, which enables the issuance of a token for the authorization profile, wherein the token authorizes the client NWDAF to join the FL group. In addition, upon receiving a request to join the FL group from the client NWDAF, the server NWDAF retrieves the NF profile of the client NWDAF from the NRF, and the server NWDAF authorizes the client NWDAF to join the FL group based on the NF profile. In addition, the NRF grants a token for joining the FL group based on the interoperability of different vendors of the server NWDAF and the client NWDAF.

[0178] More specifically, it is expected that authorization of a participant NWDAF may occur at the time of initial creation of a FL group or when a participant NWDAF joins an existing FL group and is undergoing a training process. For embodiments related to the initial creation of a FL group, it is expected that the server NWDAF creates the FL group by discovering and selecting a client NWDAF via the NRF. Based on the trust between the server NWDAF and the NRF, discovery of the client NWDAF via the NRF provides the server NWDAF with an implicit indication that the discovered client NWDAF is authorized to participate in the FL process. Similarly, the server NWDAF obtains an SBA OAuth token to invoke a FL service request to the discovered client NWDAF, and the discovered client NWDAF authorizes the server NWDAF based on the received token and the FL service request.

[0179] During the initiation of the FL process by the server NWDAF or the reselection of the FL client involved in the ongoing FL process, the NRF verifies whether the vendor ID of the server NWDAF is included in (or corresponds to) the interoperability ID of the client NWDAF selected for the analysis ID associated with the FL process. If yes, the NRF grants the token based on the information provided in the NF profile of the selected client NWDAF.

[0180] For embodiments related to a new client NWDAF joining an existing / ongoing FL group, there are two variants. In one variant, the server NWDAF learns about the new client NWDAF via NRF discovery or notification, and invites the new client NWDAF to join the FL group. The method for authorizing server / client participants is the same as the initial process.

[0181] In another variant, the client NWDAF detects an ongoing FL group and an associated server NWDAF (e.g., via an NRF) and proactively sends a join request to the server NWDAF. The client NWDAF obtains the SBA Oauth token for joining the FL group from the NRF and includes the token in the join request. The NRF issues the token to the client NWDAF based on the authorization of the FL group, which has been registered in the NRF by the server NWDAF when the FL group was created. Based on the token received with the join request, the server NWDAF authorizes the client NWDAF to join the FL group. As an alternative, the server NWDAF retrieves the NF profile of the client NWDAF from the NRF and performs authorization based on this information.

[0182] The client NWDAF may authorize the server NWDAF in various ways. In some variants, the client NWDAF may implicitly authorize the server NWDAF based on sending a join response to the server NWDAF's join request. In other variants, the client NWDAF may include a token in the join request, which the server NWDAF may use in the following message to invite the client NWDAF to join the FL group. These variants may be similar to the embodiments related to the initial creation of the FL group.

[0183] For the case where the client NWDAF dynamically joins the FL group during the FL execution phase, the NRF verifies whether the vendor ID of the client NWDAF is included in the interoperability ID of the server NWDAF for the analysis ID associated with the FL process. If yes, the NRF grants the token based on the information stored in the NF profile of the server NWDAF.

[0184] Embodiments of the present disclosure may provide various benefits and / or advantages. For example, embodiments may prevent unauthorized NFs (e.g., NWDAFs) from joining a FL group as a client and / or prevent NFs from joining a group as a client to perform fraudulent and / or unauthentic FL operations. In this way, embodiments may prevent confidential and / or sensitive ML models from being exposed to unauthorized parties during FL, and may prevent security risks to NFs that are able to participate in FL. Therefore, embodiments improve the security of FL in a multi-vendor communication network (e.g., 5GC), thereby facilitating the deployment of FL in a multi-vendor communication network.

[0185] Figure 7 A signaling diagram is shown of a process involving a server NWDAF (710), an NRF (720), clients NWDAFs 1 to NWDAF N (collectively referred to as 730), and a client NWDAF X (740) according to various embodiments of the present disclosure. Figure 7 The operations shown are given numerical labels, but this is intended to facilitate explanation and is not intended to require or imply any particular order of operations unless otherwise noted below.

[0186] In operations 0a to 0b, the server NWDAF and the clients NWDAFs 1 to NWDAF N register their corresponding NF profiles in the NRF, including FL capability type (e.g., server and / or client), vendor ID, interoperability ID, address information, service area, analysis ID, etc. For example, the interoperability ID may indicate and / or be associated with a list of NWDAF vendors (e.g., vendor IDs) that are allowed to retrieve ML models from the MTLF of the registered NWDAF.

[0187] In operation 1, the server NWDAF discovers the clients NWDAF 1 to NWDAFN via the NRF based on the FL selection criteria. For example, the client NWDAF FL capabilities, interoperability ID, analysis ID, etc. match the corresponding values ​​of the server NWDAF. In addition, the server NWDAF requests a token for each discovered client NWDAF from the NRF, which verifies whether the vendor ID of the server NWDAF is included in the interoperability ID of each discovered client NWDAF for the analysis ID, that is, based on the NF profile information registered by the corresponding client NWDAF. The NRF generates a token ("Token 1") for each discovered client NWDAF (e.g., clients NWDAF 1 to NWDAF N) verified in this manner, and sends the generated token to the server NWDAF.

[0188] In operation 2, the server NWDAF sends a FL preparation request to the client NWDAFs 1 to N by calling the Nnwdaf_MLPreparation_Request service operation using the corresponding token authorized by the NRF. An indication of the FL role of the receiving NWDAF (ie, as a client NWDAF) may be included in the FL preparation request.

[0189] In operation 3, the clients NWDAF 1 to NWDAF N verify whether the server NWDAF has the right to form the FL group based on the corresponding tokens, and determine whether to join the FL group. For example, the determination may be made based on their respective availability and capabilities. In operation 4, the clients NWDAF 1 to NWDAF N respond to the server NWDAF, indicating that they want to join the FL group. In operation 5, the server NWDAF forms the FL group from the clients NWDAF 1 to NWDAF N based on the positive response in operation 4.

[0190] In operation 6, the server NWDAF registers or updates its registration in the NRF to include information about the formed FL group, including the following items:

[0191] - FL related ID or FL group ID, as described above Figure 5 as stated;

[0192] - Analysis ID;

[0193] - Interoperability ID; and

[0194] - The scope of authorization, including one or more of the following:

[0195] o the allowed requester NF types,

[0196] o The allowed requester NF ID, and

[0197] o Allowed requester FL capabilities (e.g., FL client).

[0198] In some embodiments, the NRF may verify whether the authorization information registered by the server NWDAF is authentic, for example, whether the FL group owner ID is correct and the same as the ID of the registration server NWDAF.

[0199] Subsequently, the new client NWDAF X joins the FL group according to different embodiments described below. In some embodiments, in operation 7a, the new client NWDAF X registers with the NRF in a similar manner to the existing clients NWDAF 1 to NWDAF N in operation 0b. In operation 8a, the server NWDAF obtains information about the new client NWDAF X via the NRF by, for example, the new client NWDAF subscribing to a registration event, or discovering the new client NWDAF via the NRF when the server NWDAF determines that one or more client NWDAFs need to be reselected. In operation 9a, the server NWDAF repeats operations 1 to 4 discussed above to include the client NWDAF X in the FL group. In this case, the behavior of the NRF is the same as that described above in operation 1.

[0200] In other embodiments, in operation 7b, the new client NWDAF X discovers the FL group and the corresponding server NWDAF via the NRF. In operation 8b, the client NWDAF X requests a token from the NRF for joining the discovered FL group. In the request, the client NWDAF X includes the associated analysis ID and the vendor ID and FL capability information of the client NWDAF. Upon receipt, the NRF verifies whether the vendor ID of the client NWDAF is included in the interoperability ID of the server NWDAF for the analysis ID associated with the FL group, i.e., is registered in the NF profile of the server NWDAF. Based on the verification in this manner, the NRF generates a token ("Token 2") and sends the token to the client NWDAF.

[0201] In operation 9b, the client NWDAF X sends a FL join request to the server NWDAF, including the obtained token 2. In operation 10b, the server NWDAF determines whether the client NWDAF has the right to join the ongoing FL group based on the received token 2. Based on the positive determination in operation 10b, in operation 11b, the server NWDAF responds to the new client NWDAF X, indicating that it accepts the FL join request from the client NWDAF.

[0202] Although the embodiments have been described above in the specific context of an NWDAF arranged as a client or server, the skilled person will understand that the basic principles of the above embodiments are equally applicable to other NFs, logical functions, nodes, etc. (e.g., with different names) that perform similar operations as these corresponding entities.

[0203] You can refer to Figures 8 to 10 To further illustrate the above embodiments, Figures 8 to 10 Exemplary methods (eg, processes) of the first NF, the second NF, and the NRF are depicted, respectively. In other words, various features of the operations described below correspond to the various embodiments described above. Figures 8 to 10 The exemplary methods shown can be used in conjunction (eg, with each other and with other processes described herein) to provide the benefits, advantages, and / or solutions to the problems described herein. Fig.10 These exemplary methods are shown in the figures by specific blocks in a specific order, but the operations corresponding to the blocks can be performed in an order different from the order shown, and can be combined and / or divided into blocks and / or operations with functions different from those shown. Optional blocks and / or operations are indicated by dotted lines.

[0204] More specifically, Figure 8An exemplary method (e.g., process) of a first NF configured to operate as a server of a federated learning (FL) group in a communication network (e.g., 5GC) according to various embodiments of the present disclosure is shown. As described elsewhere herein, Figure 8 The illustrated exemplary method may be performed by a FL server such as an NWDAF (or a logical function thereof, such as an MTLF) or a network node hosting the NWDAF.

[0205] The exemplary method may include the operation of block 810, wherein the first NF may register the following information in a network repository function (NRF) of the communication network: a vendor identifier (ID) associated with the first NF, and an interoperability ID corresponding to one or more vendor IDs, the one or more vendor IDs being associated with another NF authorized to join the FL group as a client. The exemplary method may also include the operation of block 820, wherein the first NF may receive an indication that a second NF of the communication network is a candidate client of the FL group. The exemplary method may also include the operation of block 830, wherein the first NF may create or update the FL group to include the second NF as a client based on one of the following:

[0206] - a first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0207] - A second token indicating that the second NF is authorized to join the FL group as a client.

[0208] In some embodiments, the registered information also includes an analysis ID associated with the ML model for FL, and the interoperability ID indicates authorization specific to the analysis ID.

[0209] In some embodiments, the registered information also includes one or more of the following:

[0210] - an indication of one or more FL capabilities associated with the first NF;

[0211] - a service area associated with the first NF;

[0212] - address information associated with the first NF; and

[0213] - An indication of the authorized scope of the FL group, including an indication of one or more of the following criteria for a NF to join the FL group as a client: one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

[0214] In some embodiments, creating or updating the FL group in block 830 to include the second NF as a client in the FL group includes the following operations labeled with corresponding sub-block numbers:

[0215] - (831) in response to the indication, obtaining a first token from the NRF;

[0216] - (832) sending a first request to the second NF for the second NF to join the FL group as a client, wherein the first request includes a first token; and

[0217] - (833) A first response is received from the second NF, the first response indicating that the second NF will join the FL group as a client.

[0218] In some of these embodiments, the first request is a FL Prepare Request message and the first response is a FL Prepare Response message.

[0219] In some of these embodiments, the indication that the second NF is a candidate client (e.g., in block 820) is received from the NRF as one of the following: a response to a client discovery request of the first NF, or a notification in response to a subscription request of the first NF requesting registration information of candidate clients of the FL group in the NRF. In some variants of these embodiments, the client discovery request or subscription request includes one or more of the following:

[0220] - the vendor ID associated with the first NF,

[0221] - the analysis ID associated with the machine learning (ML) model used for FL, and

[0222] - An indication of one or more FL capabilities associated with the first NF.

[0223] In some variations of these embodiments, the indication from the NRF is used to indicate multiple NFs that are candidate clients of the FL group, including the second NF, and a corresponding multiple first tokens are obtained from the NRF and sent to the multiple NFs in corresponding first requests.

[0224] In some of these embodiments, the indication (e.g., received in block 820) that the second NF is a candidate client is based on one or more of the following items registered by the second NF in the NRF: an interoperability ID corresponding to one or more vendor IDs associated with additional NFs that are authorized to add the second NF as a client to the FL group; and an analysis ID associated with an ML model for the FL.

[0225] In other embodiments, the indication that the second NF is a candidate client is a FL join request message received from the second NF and including the second token. In this case, creating or updating the FL group in block 830 to include the second NF as a client in the FL group includes the operation of sub-block 834, wherein the first NF can verify the second token received from the second NF.

[0226] In some embodiments, creating or updating the FL group in block 830 to include the second NF as a client in the FL group includes the operation of sub-block 835, wherein the first NF may register one or more of the following information with the NRF (i.e., after adding the second NF as a client):

[0227] - an identifier of a FL group and / or an identifier of a FL process performed by the FL group; and

[0228] - An indication of the authorized scope of the FL group, including an indication of one or more of the following criteria for a NF to join the FL group as a client: one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

[0229] In some embodiments, the first NF is a NWDAF and / or the second NF is a NWDAF.

[0230] also, Fig. 9 An exemplary method (e.g., process) of a second NF configured to operate as a client of a FL group in a communication network (e.g., 5GC) according to various embodiments of the present disclosure is shown. As described elsewhere herein, Fig. 9 The illustrated exemplary method may be performed by a FL client such as an NWDAF (or its logical functions, such as an MTLF) or a network node hosting the NWDAF.

[0231] The exemplary method may include the operation of block 910, wherein the second NF may register the following information in a network repository function (NRF) of the communication network: a vendor ID associated with the second NF, and an interoperability ID corresponding to one or more vendor IDs, the one or more vendor IDs being associated with another NF that is authorized to add the second NF as a client to the FL group. The exemplary method may also include the operation of block 920, wherein the second NF may then join the FL group as a client. The first NF is configured to operate as a server of the FL group, and joining the FL group is based on one of the following:

[0232] - a first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0233] - A second token indicating that the second NF is authorized to join the FL group as a client.

[0234] In some embodiments, the registered information also includes an analysis ID associated with the ML model for FL, and the interoperability ID indicates authorization specific to the analysis ID. In some embodiments, the registered information also includes one or more of the following:

[0235] - an indication of one or more FL capabilities associated with the second NF;

[0236] - a service area associated with the second NF; and

[0237] - Address information associated with the first NF.

[0238] In some embodiments, joining the FL group as a client in block 920 includes the following operations labeled with corresponding sub-block numbers:

[0239] - (921) receiving a first request from the first NF for the second NF to join the FL group as a client, wherein the first request includes a first token;

[0240] - (922) verifying the first token received from the first NF; and

[0241] - (923) Based on the verification, a first response is sent to the first NF, the first response indicating that the second NF will join the FL group as a client.

[0242] In some of these embodiments, the first request is a FL Prepare Request message and the first response is a FL Prepare Response message.

[0243] In other embodiments, joining the FL group as a client in block 920 includes the following operations labeled with corresponding sub-block numbers:

[0244] - (924) discovering the FL group and the first NF serving as a server of the FL group via the NRF;

[0245] - (926) sending a second request to the first NF to join the FL group as a client, wherein the second request includes a second token; and

[0246] - (927) A second response is received from the first NF, the second response indicating that the first NF accepts the second request.

[0247] In some embodiments, joining the FL group as a client in block 920 may also include the operation of sub-block 925, where the second NF may obtain a second token from the NRF in response to discovering the FL group and the first NF as a server of the FL group (e.g., in block 924). The obtained second token is sent to the first NF together with the second request (e.g., in sub-block 926).

[0248] In some of these embodiments, the second request is a FL Join Request message, and the second response is a FL Join Request Accept message. In some of these embodiments, finding the FL group and the first NF as a server in subblock 924 is based on one or more of the following items registered by the first NF in the NRF:

[0249] - an identifier of a FL group and / or an identifier of a FL process performed by the FL group;

[0250] - an interoperability ID corresponding to one or more vendor IDs associated with further NFs that are authorized to join the FL group as clients;

[0251] - the analysis ID associated with the machine learning (ML) model used for FL; and

[0252] - An indication of the authorized scope of the FL group, including an indication of one or more of the following criteria for a NF to join the FL group as a client: one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

[0253] In some embodiments, the first NF is a NWDAF and / or the second NF is a NWDAF.

[0254] also, Fig.10 An exemplary method (e.g., process) of an NRF of a communication network (e.g., 5GC) according to various embodiments of the present disclosure is shown. As described elsewhere herein, Fig.10 The exemplary method shown in may be performed by an NRF or a network node hosting an NRF.

[0255] The example method may include the operations of block 1010, where the NRF may register the following information associated with first and second network functions (NFs) of the communication network:

[0256] a first vendor identifier ID associated with a first NF, the first NF being configured to operate as a server of a federated learning FL group,

[0257] - a first interoperability ID corresponding to one or more vendor IDs associated with further NFs authorized to join the FL group as clients,

[0258] - a second vendor ID associated with a second NF, the second NF being configured to operate as a FL client, and

[0259] - A second interoperability ID corresponding to one or more vendor IDs associated with a further NF authorized to add the second NF as a client to the FL group.

[0260] The example method may also include the operations of block 1060, wherein, based on the registered information, the NRF may provide one or more of the following:

[0261] - providing a first token to the first NF, the first token indicating that the first NF is authorized to add the second NF as a client to the FL group; or

[0262] - Providing a second token to the second NF, the second token indicating that the second NF is authorized to join the FL group as a client.

[0263] In some embodiments, the registered information also includes one or more of the following:

[0264] - a first analysis ID associated with a machine learning (ML) model used by the first NF for the FL;

[0265] - a second analysis ID associated with the ML model used for FL by the second NF;

[0266] - an indication of one or more first FL capabilities associated with the first NF; and

[0267] - an indication of one or more second FL capabilities associated with the second NF.

[0268] In some of these embodiments, the registered information further includes one or more of the following:

[0269] - Respective service areas associated with the first NF and the second NF;

[0270] - Respective address information associated with the first NF and the second NF; and

[0271] - An indication of the authorized scope of the FL group, including an indication of one or more of the following criteria for a NF to join the FL group as a client: one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

[0272] In some embodiments, the exemplary method may further include the operation of block 1020, wherein the NRF may discover the second NF based on one or more of the following matching or corresponding relationships:

[0273] - a match between the second vendor ID and one of the vendor IDs corresponding to the first interoperability ID,

[0274] - a match between the first analysis ID and the second analysis ID, and

[0275] - A matching or corresponding relationship between the first capability and the second capability.

[0276] In such an embodiment, the exemplary method may also include the operation of block 1030, where the NRF may send an indication to the first NF that the second NF is a candidate client of the FL group.

[0277] In some of these embodiments, discovering the second NF (e.g., in block 1020) and sending the indication (e.g., in block 1030) is in response to one of: a client discovery request by the first NF, or a subscription request by the first NF for registration information of candidate clients of the FL group in the NRF. In some variants of these embodiments, the client discovery request or the subscription request includes one or more of the following items on which the matching or correspondence is based: a first vendor ID associated with the first NF, a first analysis ID, and an indication of one or more FL capabilities associated with the first NF.

[0278] In some of these embodiments, providing the first token to the first NF (e.g., in block 1060) is in response to a token request from the first NF in response to sending an indication that the second NF is a candidate client of the FL group (e.g., in block 1030).

[0279] In some of these embodiments, the second NF is one of a plurality of candidate clients of the FL group, the indication sent to the first NF (e.g., in block 1030) identifies the plurality of candidate clients, and a plurality of first tokens associated with the respective candidate clients are provided to the first NF (e.g., in block 1060).

[0280] In other embodiments, the exemplary method may further include the operation of block 1040, wherein the NRF may discover the first NF based on one or more of the following matching or corresponding relationships:

[0281] - a match between the first vendor ID and one of the vendor IDs corresponding to the second interoperability ID,

[0282] - a match between the first analysis ID and the second analysis ID, and

[0283] - A matching or corresponding relationship between the first capability and the second capability.

[0284] In such an embodiment, the exemplary method may also include the operation of block 1050, where the NRF may send an indication to the second NF regarding the FL group and regarding the first NF being a server of the FL group.

[0285] In some of these embodiments, discovering the first NF (e.g., in block 1040) and sending the indication (e.g., in block 1050) is in response to one of: registering information associated with the second NF, or a server discovery request of the second NF. In some variations of these embodiments, the server discovery request includes one or more of the following items on which the match or correspondence is based: a second vendor ID associated with the second NF, a second analysis ID, and an indication of one or more FL capabilities associated with the second NF.

[0286] In some of these embodiments, providing the second token to the second NF (e.g., in block 1060) is in response to a token request from the second NF in response to sending the indication about the FL group and about the first NF being a server of the FL group (e.g., in block 1050).

[0287] In some embodiments, the first NF is a NWDAF and / or the second NF is a NWDAF.

[0288] Although various embodiments are described above in terms of methods, techniques and / or processes, a person of ordinary skill in the art will readily appreciate that such methods, techniques and / or processes may be embodied in various combinations of hardware and software, communication devices, computing devices, control devices, apparatuses, non-transitory computer-readable media, computer program products, etc., in various systems.

[0289] Fig.11 An example of a communication system 1100 according to some embodiments is shown. In this example, the communication system 1100 includes: a telecommunications network 1102, including an access network 1104 such as a radio access network (RAN); and a core network 1106, including one or more core network nodes 1108. The access network 1104 includes one or more access network nodes, such as network nodes 1110a and 1110b (one or more of which may be generally referred to as network nodes 1110), or any other similar 3GPP access nodes or non-3GPP access points. The network node 1110 facilitates direct or indirect connection of UEs, such as connecting UEs 1112a to UE 1112d (one or more of which may be collectively referred to as UEs 1112) to the core network 1106 via one or more wireless connections.

[0290] Example wireless communications via wireless connections include sending and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for transmitting information without using wiring, cables, or other material conductors. In addition, in different embodiments, the communication system 1100 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that can facilitate or participate in the communication of data and / or signals (whether via a wired connection or via a wireless connection). The communication system 1100 may include any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system, and / or be connected to any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system interface.

[0291] UE 1112 may be any of a variety of communication devices, including wireless devices that are arranged, configured and / or operable to wirelessly communicate with network node 1110 and other communication devices. Similarly, network node 1110 is arranged, capable, configured and / or operable to communicate directly or indirectly with UE 1112 and / or with other network nodes or devices in telecommunication network 1102 to enable and / or provide network access (e.g., wireless network access) and / or to perform other functions (e.g., management) in telecommunication network 1102.

[0292] In the depicted example, the core network 1106 connects the network node 1110 to one or more hosts (such as the host 1116). These connections may be direct connections or indirect connections via one or more intermediate networks or devices. In other examples, the network node may be directly coupled to the host. The core network 1106 includes one or more core network nodes (e.g., core network node 1108) composed of hardware and software components. The features of these components may be substantially similar to those described with respect to the UE, network nodes, and / or hosts, so that their descriptions are generally applicable to the corresponding components of the core network node 1108. The example core network node includes the functions of one or more of the following items: a mobile switching center (MSC), a mobility management entity (MME), a home subscriber server (HSS), an access and mobility management function (AMF), a session management function (SMF), an authentication server function (AUSF), a subscription identifier cancellation function (SIDF), a unified data management (UDM), a security edge protection agent (SEPP), a network open function (NEF), and / or a user plane function (UPF).

[0293] The host 1116 may be owned or under the control of a service provider other than the operator or provider of the access network 1104 and / or the telecommunications network 1102, and may be operated by or on behalf of the service provider. The host 1116 may host a variety of applications to provide one or more services. Examples of such applications include real-time and pre-recorded audio / video content, data collection services (e.g., retrieving and compiling data about various environmental conditions detected by multiple UEs), analysis functions, social media, functions for controlling or otherwise interacting with remote devices, functions for alarm and monitoring centers, or any other such functions performed by a server.

[0294] As a whole, Fig.11 The communication system 1100 implements the connection between the UE, the network node and the host. In this sense, the communication system can be configured to operate according to predefined rules or procedures such as a specific standard, including but not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE) and / or other suitable 2G, 3G, 4G, 5G standards, or any future generation standards that may be applicable (e.g., 6G); Wireless Local Area Network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard (WiFi); and / or any other suitable wireless communication standards, such as Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any Low Power Wide Area Network (LPWAN) standards such as LoRa and Sigfox.

[0295] In some examples, the telecommunication network 1102 is a cellular network implementing 3GPP standardized features. Thus, the telecommunication network 1102 can support network slicing to provide different logical networks to different devices connected to the telecommunication network 1102. For example, the telecommunication network 1102 can provide ultra-reliable low-latency communication (URLLC) services to some UEs, while providing enhanced mobile broadband (eMBB) services to other UEs, and / or providing massive machine type communication (mMTC) / massive IoT services to yet other UEs.

[0296] In some examples, UE 1112 is configured to send and / or receive information without direct human interaction. For example, the UE may be designed to send information to the access network 1104 according to a predetermined schedule when triggered by an internal or external event or in response to a request from the access network 1104. In addition, the UE may be configured to operate in a single RAT mode or a multi-RAT mode or a multi-standard mode. For example, the UE may operate using any one or a combination of Wi-Fi, NR (New Radio), and LTE, i.e., configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved UMTS Terrestrial Radio Access Network) New Radio-Dual Connectivity (EN-DC).

[0297] In this example, the hub node 1114 communicates with the access network 1104 to facilitate indirect communication between one or more UEs (e.g., UE 1112c and / or UE 1112d) and a network node (e.g., network node 1110b). In some examples, the hub node 1114 may be a controller, a router, a content source and an analyzer, or any other communication device described herein with respect to a UE. For example, the hub node 1114 may be a broadband router that enables a UE to access the core network 1106. As another example, the hub node 1114 may be a controller that sends commands or instructions to one or more actuators of the UE. The command or instruction may be received from the UE, the network node 1110, or received through an executable code, script, process, or other instruction in the hub node 1114. As another example, the hub node 1114 may be a data collector that acts as a temporary storage device for UE data, and in some embodiments, may perform analysis or other processing of the data. As another example, the hub node 1114 may be a content source. For example, for a UE that is a VR headset, display, speaker, or other media delivery device, the hub node 1114 can retrieve VR assets, video, audio, or other media or data related to sensory information via the network node, and then the hub node 1114 provides it directly to the UE after performing local processing and / or after adding additional local content. In yet another example, the hub node 1114 acts as a proxy server or orchestrator for the UE, especially if one or more of the UEs are low-energy IoT devices.

[0298] The hub node 1114 may have a continuous / persistent or intermittent connection to the network node 1110b. The hub node 1114 may also allow different communication schemes and / or scheduling between the hub node 1114 and the UE (e.g., UE 1112c and / or UE 1112d) and between the hub node 1114 and the core network 1106. In other examples, the hub node 1114 is connected to the core network 1106 and / or one or more UEs via a wired connection. In addition, the hub node 1114 may be configured to connect to an M2M service provider through the access network 1104, and / or to another UE via a direct connection. In some scenarios, the UE may establish a wireless connection with the network node 1110 while still being connected through the hub node 1114 via a wired or wireless connection. In some embodiments, the hub node 1114 may be a dedicated hub node, that is, a hub node whose main function is to route communications from the network node 1110b to the UE / route communications from the UE to the network node 1110b. In other embodiments, the hub node 1114 may be a non-dedicated hub node—ie, a device operable to route communications between UEs and network node 1110b but additionally operable as a communications origin and / or endpoint for certain data channels.

[0299] Fig.12 A UE 1200 according to some embodiments is shown. Examples of UEs include, but are not limited to, smart phones, mobile phones, cellular phones, voice over IP (VoIP) phones, wireless local loop phones, desktop computers, personal digital assistants (PDAs), wireless cameras, game consoles or devices, music storage devices, playback devices, wearable terminal devices, wireless endpoints, mobile stations, tablet computers, laptop computers, laptop embedded equipment (LEE), laptop-mounted equipment (LME), smart devices, wireless client equipment (CPE), vehicle-mounted or vehicle-embedded / integrated wireless devices, etc. Other examples include any UE identified by the Third Generation Partnership Project (3GPP), including narrowband Internet of Things (NB-IoT) UEs, machine type communication (MTC) UEs, and / or enhanced MTC (eMTC) UEs.

[0300] The UE may, for example, support device-to-device (D2D) communications by implementing 3GPP standards for sidelink communications, dedicated short-range communications (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to-everything (V2X). In other examples, the UE may not necessarily have a user in the sense of a human user who owns and / or operates the associated device. Alternatively, the UE may represent a device that is intended to be sold to or operated by a human user but may not or may not initially be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, the UE may represent a device that is not intended to be sold to or operated by an end user but may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0301] UE 1200 includes a processing circuit 1202 that is operably coupled to an input / output interface 1206, a power supply 1208, a memory 1210, a communication interface 1212, and / or any other components or any combination thereof via a bus 1204. Some UEs may utilize Fig.12 All or a subset of the components shown. The level of integration between components may vary from UE to UE. In addition, some UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0302] The processing circuit 1202 is configured to process instructions and data, and may be configured to implement any sequential state machine operable to execute instructions stored in the memory 1210 as a machine-readable computer program. The processing circuit 1202 may be implemented as: one or more hardware-implemented state machines (e.g., implemented in discrete logic, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors (e.g., microprocessors or digital signal processors (DSPs)) together with appropriate software; or any combination of the above. For example, the processing circuit 1202 may include multiple central processing units (CPUs).

[0303] In an example, the input / output interface 1206 may be configured to provide one or more interfaces to an input device, an output device, or one or more input and / or output devices. Examples of output devices include speakers, sound cards, video cards, displays, monitors, printers, actuators, transmitters, smart cards, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 1200. Examples of input devices include touch-sensitive or presence-sensitive displays, cameras (e.g., digital cameras, digital video cameras, web cameras, etc.), microphones, sensors, mice, trackballs, directional keyboards, trackpads, scroll wheels, smart cards, etc. A presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. The sensor may be, for example, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use an interface port of the same type as an input device. For example, a universal serial bus (USB) port may be used to provide input devices and output devices.

[0304] In some embodiments, the power supply 1208 is configured as a battery or a battery pack. Other types of power supplies may be used, such as an external power supply (e.g., a power outlet), a photovoltaic device, or a battery. The power supply 1208 may also include a power supply circuit for delivering power from the power supply 1208 itself and / or an external power supply to various parts of the UE 1200 via an input circuit or an interface such as a power cable. The delivered power may be used, for example, for charging the power supply 1208. The power supply circuit may perform any formatting, conversion, or other modification on the power from the power supply 1208 so that the power is suitable for the corresponding components of the UE 1200 to which the power is supplied.

[0305] The memory 1210 may be or be configured to include a memory, such as a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic disk, an optical disk, a hard disk, a removable tape, a flash drive, etc. In one example, the memory 1210 includes one or more application programs 1214, such as an operating system, a web browser application, a widget, a gadget engine, or other applications, and corresponding data 1216. The memory 1210 may store any of a variety of operating systems or a combination of operating systems used by the UE 1200.

[0306] The memory 1210 may be configured to include multiple physical drive units, such as a redundant array of independent disks (RAID), a flash memory, a USB flash drive, an external hard drive, a thumb drive, a pen drive, a key drive, a high-density digital versatile disc (HD-DVD) optical drive, a built-in hard drive, a Blu-ray optical drive, a holographic digital data storage (HDDS) optical drive, an external mini dual in-line memory module (DIMM), a synchronous dynamic random access memory (SDRAM), an external micro DIMM SDRAM, a smart card memory (e.g., a tamper-proof module in the form of a universal integrated circuit card (UICC), including one or more subscriber identity modules (SIMs), such as USIM and / or ISIM), other memories, or any combination thereof. The UICC may be, for example, an embedded UICC (eUICC), an integrated UICC (iUICC), or a removable UICC commonly referred to as a "SIM card". The memory 1210 may allow the UE 1200 to access instructions, applications, etc. stored on a temporary or non-temporary storage medium to offload data or upload data. An article of manufacture, such as an article of manufacture utilizing a communication system, may be tangibly embodied as or in memory 1210, which may be or include a device-readable storage medium.

[0307] The processing circuit 1202 may be configured to communicate with an access network or other network using a communication interface 1212. The communication interface 1212 may include one or more communication subsystems and may include an antenna 1222 or be communicatively coupled to the antenna 1222. The communication interface 1212 may include one or more transceivers for communication (such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network)). Each transceiver may include a transmitter 1218 and / or a receiver 1220 suitable for providing network communications (e.g., optical, electrical, frequency allocation, etc.). In addition, the transmitter 1218 and the receiver 1220 may be coupled to one or more antennas (e.g., antenna 1222) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0308] In the illustrated embodiment, the communication functionality of the communication interface 1212 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communication such as Bluetooth, near field communication, location-based communication (e.g., using a global positioning system (GPS) to determine location), another type of communication functionality, or any combination thereof. Communication may be implemented according to one or more communication protocols and / or standards (e.g., IEEE 802.11, code division multiple access (CDMA), wideband code division multiple access (WCDMA), GSM, LTE, new radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / Internet protocol (TCP / IP), synchronous optical network (SONET), asynchronous transfer mode (ATM), QUIC, hypertext transfer protocol (HTTP), etc.).

[0309] Regardless of the type of sensor, the UE may provide an output of data captured by its sensor through its communication interface 1212 via a wireless connection to a network node. The data captured by the UE's sensor may be transmitted via another UE via a wireless connection to a network node. The output may be periodic (e.g., every 15 minutes if it reports the sensed temperature), random (e.g., to balance the load of reports from several sensors), in response to a trigger event (e.g., sending an alarm when humidity is detected), in response to a request (e.g., a user-initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0310] As another example, the UE includes an actuator, motor, or switch associated with a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input, the state of the actuator, motor, or switch can change. For example, the UE can include a motor that adjusts a control surface or rotor of a drone in flight based on the received input, or adjusts a robotic arm performing a medical procedure based on the received input.

[0311] When the UE is in the form of an Internet of Things (IoT) device, the UE can be a device used in one or more application areas, including but not limited to urban wearable technology, extended industrial applications, and healthcare. Non-limiting examples of such IoT devices are the following devices or devices embedded in the following devices: connected refrigerators or freezers, televisions, connected lighting devices, electricity meters, robotic vacuum cleaners, voice-controlled smart speakers, home security cameras, motion detectors, thermostats, smoke detectors, door and window sensors, flood / humidity sensors, electronic door locks, connected doorbells, air conditioning systems (such as heat pumps), autonomous vehicles, monitoring systems, weather monitoring devices, vehicle parking monitoring devices, electric vehicle charging stations, smart watches, fitness trackers, head-mounted displays for augmented reality (AR) or virtual reality (VR), wearable devices for tactile enhancement or sensory enhancement, sprinklers, animal tracking or item tracking devices, sensors for monitoring plants or animals, industrial robots, unmanned aerial vehicles (UAVs), and any kind of medical equipment (such as heart rate monitors or teleoperated surgical robots). In addition to the above, Fig.12 In addition to the other components depicted in the illustrated UE 1200 , a UE in the form of an IoT device may include circuitry and / or software depending on the intended application of the IoT device.

[0312] As yet another specific example, in an IoT scenario, a UE may represent a machine or other device that performs monitoring and / or measurement and sends the results of such monitoring and / or measurement to another UE and / or a network node. In this case, the UE may be an M2M device, which may be referred to as an MTC device in the 3GPP context. As a specific example, the UE may implement the 3GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle (e.g., a car, bus, truck, ship, and airplane) or other device that is capable of monitoring and / or reporting its operating status or other functions associated with its operation.

[0313] In fact, for a single use case, any number of UEs may be used together. For example, a first UE may be a drone or integrated in a drone and provide the drone's speed information (obtained via a speed sensor) to a second UE, which is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g., by controlling an actuator) to increase or decrease the drone's speed. The first UE and / or the second UE may also include more than one of the above functions. For example, a UE may include a sensor and an actuator and handle data communications for both the speed sensor and the actuator.

[0314] Fig.13A network node 1300 according to some embodiments is shown. As used herein, a network node refers to a device capable of, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or devices in a telecommunications network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, NodeBs, evolved NodeBs (eNBs), and NR NodeBs (gNBs)).

[0315] Base stations may be classified based on the amount of coverage they provide (or in other words, their transmit power level), and thus may be referred to as femto, pico, micro or macro base stations, depending on the amount of coverage provided. A base station may be a relay node or a relay donor node that controls a relay. A network node may also include one or more (or all) parts of a distributed radio base station, such as a centralized digital unit and / or a remote radio unit (RRU), sometimes referred to as a remote radio head (RRH). These remote radio units may or may not be integrated with an antenna as an antenna-integrated radio. Portions of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0316] Other examples of network nodes include a multi-transmission point (multi-TRP) 5G access node, a multi-standard radio (MSR) device (e.g., an MSR BS), a network controller (e.g., a radio network controller (RNC) or a base station controller (BSC)), a base transceiver station (BTS), a transmission point, a transmission node, a multi-cell / multicast coordination entity (MCE), an operation and maintenance (O&M) node, an operation support system (OSS) node, a self-organizing network (SON) node, a positioning node (e.g., an evolved serving mobile location center (E-SMLC)), and / or a minimization of drive tests (MDT).

[0317] For example, one or more network nodes 1300 may be configured to perform the operations attributed to a FL server NF (eg, server NWDAF), FL client NF (eg, client NWDAF), or NRF in the various methods or processes described herein.

[0318] The network node 1300 includes a processing circuit 1302, a memory 1304, a communication interface 1306, and a power supply 1308. The network node 1300 may be composed of multiple physically separated components (e.g., a NodeB component and an RNC component, or a BTS component and a BSC component, etc.), which may have their own corresponding components. In certain scenarios where the network node 1300 includes multiple separate components (e.g., a BTS and a BSC component), one or more separate components may be shared between several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique "NodeB and RNC pair" may be considered as a single separate network node in some cases. In some embodiments, the network node 1300 may be configured to support multiple radio access technologies (RATs). In such an embodiment, some components may be duplicated (e.g., separate memories 1304 exist for different RATs), and some components may be reused (e.g., the same antenna 1310 may be shared by different RATs). The network node 1300 may also include multiple sets of the various components shown for different wireless technologies (e.g., GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, RFID, or Bluetooth wireless technologies) integrated into the network node 1300. These wireless technologies may be integrated into the same or different chips or chipsets and other components within the network node 1300.

[0319] The processing circuit 1302 may include a combination of one or more of the following: a microprocessor, a controller, a microcontroller, a central processing unit, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic that is operable to provide network node 1300 functionality alone or in combination with other network node 1300 components (e.g., memory 1304).

[0320] In some embodiments, processing circuitry 1302 includes a system on a chip (SOC). In some embodiments, processing circuitry 1302 includes one or more of radio frequency (RF) transceiver circuitry 1312 and baseband processing circuitry 1314. In some embodiments, radio frequency (RF) transceiver circuitry 1312 and baseband processing circuitry 1314 may be on separate chips (or chipsets), boards, or units (e.g., a radio unit and a digital unit). In alternative embodiments, part or all of RF transceiver circuitry 1312 and baseband processing circuitry 1314 may be on the same chip or chipset, board set, or unit set.

[0321] The memory 1304 may include any form of volatile or non-volatile computer-readable memory, including but not limited to permanent storage devices, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (e.g., hard disk), removable storage media (e.g., flash drive, compact disk (CD) or digital video disk (DVD)), and / or any other volatile memory or non-volatile, non-transitory device-readable and / or computer-executable memory device that stores information, data and / or instructions that can be used by the processing circuit 1302. The memory 1304 may store any suitable instructions, data or information, including computer programs, software, applications including one or more of logic, rules, codes, tables, and / or other instructions that can be executed by the processing circuit 1302 and used by the network node 1300 (collectively referred to as computer program products 1304a). The memory 1304 may be used to store any calculations performed by the processing circuit 1302 and / or any data received via the communication interface 1306. In some embodiments, processing circuit 1302 and memory 1304 are integrated together.

[0322] The communication interface 1306 is used for wired or wireless communication of signaling and / or data between network nodes, access networks and / or UEs. As shown, the communication interface 1306 includes a port / terminal 1316 for, for example, sending data to the network and receiving data from the network via a wired connection. The communication interface 1306 also includes a radio front-end circuit 1318, which can be coupled to the antenna 1310, or in some embodiments, coupled to a part of the antenna 1310. The radio front-end circuit 1318 includes a filter 1320 and an amplifier 1322. The radio front-end circuit 1318 can be connected to the antenna 1310 and the processing circuit 1302. The radio front-end circuit can be configured to adjust the signal transmitted between the antenna 1310 and the processing circuit 1302. The radio front-end circuit 1318 can receive digital data to be sent to other network nodes or UEs via a wireless connection. The radio front-end circuit 1318 can use a combination of a filter 1320 and / or an amplifier 1322 to convert the digital data into a radio signal with appropriate channel and bandwidth parameters. The radio signal can then be sent via the antenna 1310. Similarly, when data is received, antenna 1310 may collect the radio signal, which may then be converted to digital data by radio front end circuit 1318. The digital data may be passed to processing circuit 1302. In other embodiments, the communication interface may include different components and / or different combinations of components.

[0323] In certain alternative embodiments, the network node 1300 does not include a separate radio front end circuit 1318, instead the processing circuit 1302 includes the radio front end circuit and is connected to the antenna 1310. Similarly, in some embodiments, all or some of the RF transceiver circuit 1312 is part of the communication interface 1306. In yet another embodiment, the communication interface 1306 includes one or more ports or terminals 1316, the radio front end circuit 1318, and the RF transceiver circuit 1312 as part of a radio unit (not shown), and the communication interface 1306 communicates with the baseband processing circuit 1314, which is part of the digital unit (not shown).

[0324] Antenna 1310 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals. Antenna 1310 may be coupled to radio front end circuit 1318 and may be any type of antenna capable of wirelessly sending and receiving data and / or signals. In some embodiments, antenna 1310 is separate from network node 1300 and may be connected to network node 1300 via an interface or port.

[0325] Antenna 1310, communication interface 1306 and / or processing circuit 1302 may be configured to perform any receiving operation and / or certain obtaining operations performed by a network node as described herein. Any information, data and / or signal may be received from a UE, another network node and / or any other network device. Similarly, antenna 1310, communication interface 1306 and / or processing circuit 1302 may be configured to perform any transmission operation performed by a network node as described herein. Any information, data and / or signal may be sent to a UE, another network node and / or any other network device.

[0326] The power supply 1308 provides power to the various components of the network node 1300 in a form suitable for the various components (e.g., at the voltage and current levels required by each corresponding component). The power supply 1308 may also include power management circuitry or be coupled to power management circuitry to supply power to the components of the network node 1300 for performing the functions described herein. For example, the network node 1300 may be connected to an external power source (e.g., a power grid, a power outlet) via an input circuit or interface (e.g., a cable), whereby the external power source supplies power to the power circuit of the power supply 1308. As another example, the power supply 1308 may include a power source in the form of a battery or a battery pack, which is connected to the power circuit or integrated in the power circuit. If the external power source fails, the battery can provide backup power.

[0327] Embodiments of network node 1300 may include beyond Fig.13Additional components to the components shown are used to provide certain aspects of the functionality of the network node (including any functionality described herein and / or any functionality required to support the subject matter described herein). For example, the network node 1300 may include a user interface device to allow information to be input into the network node 1300 and to allow information to be output from the network node 1300. This may allow a user to perform diagnostic, maintenance, repair, and other management functions for the network node 1300.

[0328] Fig.14 is a block diagram of a host 1400 according to various aspects described herein, which host 1400 may be Fig.11 1400 is an embodiment of a host 1116. As used herein, the host 1400 can be or include various combinations of hardware and / or software (including processing resources in a standalone server, a blade server, a cloud-implemented server, a distributed server, a virtual machine, a container, or a server cluster). The host 1400 can provide one or more services to one or more UEs.

[0329] Host 1400 includes processing circuitry 1402, which is operably coupled to input / output interface 1406, network interface 1408, power supply 1410, and memory 1412 via bus 1404. Other components may be included in other embodiments. The features of these components may be substantially similar to those described with respect to the previous figures (e.g., Fig.12 and Fig.13 ) so that its description is generally applicable to corresponding components of the host 1400.

[0330] The memory 1412 may include one or more computer programs including data 1416 and one or more host applications 1414, which may include user data, such as data generated by a UE for the host 1400, or data generated by the host 1400 for the UE. An embodiment of the host 1400 may utilize only a subset or all of the components shown. The host application 1414 may be implemented in a container-based architecture and may provide support for video codecs (e.g., Versatile Video Coding (VVC), High Efficiency Video Coding (HEVC), Advanced Video Coding (AVC), MPEG, VP9) and audio codecs (e.g., FLAC, Advanced Audio Coding (AAC), MPEG, G.711), including transcoding for a variety of different categories, types, or implementations of UE (e.g., mobile phones, desktop computers, wearable display systems, head-up display systems). The host application 1414 may also provide user authentication and permission checks, and may periodically report health status, routing, and content availability to a central node (such as a device in a core network or a device on the edge of a core network). Thus, the host 1400 can select and / or indicate to the UE a different host for an over-the-top service. The host application 1414 can support various protocols, such as HTTP Live Streaming (HLS) protocol, Real-Time Messaging Protocol (RTMP), Real-Time Streaming Protocol (RTSP), Dynamic Adaptive Streaming over HTTP (MPEG-DASH), etc.

[0331] Fig.15 1500 is a block diagram showing a virtualized environment 1500 in which the functions implemented by some embodiments may be virtualized. In this context, virtualization means creating a virtual version of an apparatus or device that may include a virtualized hardware platform, storage device, and network resources. As used herein, virtualization may be applied to any device or component thereof described herein, and relates to an implementation in which at least a portion of the functions are implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 1500 hosted by one or more of a hardware node (e.g., a hardware computing device operating as a network node, UE, core network node, or host). In addition, in an embodiment in which a virtual node does not require a radio connection (e.g., a core network node or host), the node may be fully virtualized.

[0332] Application 1502 (which may alternatively be referred to as a software instance, a virtual appliance, a network function, a virtual node, a virtual network function, etc.) operates in virtualized environment 1500 to implement some features, functions, and / or benefits of some embodiments disclosed herein.

[0333] For example, various NFs (or portions thereof) described herein with respect to other figures may be implemented as virtual network functions 1502 in the virtualization environment 1500. As a more specific example, a FL server NF (e.g., NWDAF), a FL client NF (e.g., NWDAF), and / or an NRF may be implemented as a virtual network function 1502 in the virtualization environment 1500.

[0334] Hardware 1504 includes processing circuitry, memory storing software and / or instructions (collectively referred to as computer program product 1504a) executable by the hardware processing circuitry, and / or other hardware devices described herein (e.g., network interfaces, input / output interfaces, etc.). The software may be executed by the processing circuitry to instantiate one or more virtualization layers 1506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 1508a and VMs 1508b (one or more of which may be generally referred to as VMs 1508), and / or perform any functions, features, and / or benefits described in connection with some embodiments described herein. Virtualization layer 1506 may present a virtual operating platform to VM 1508 that appears to be network hardware.

[0335] VM 1508 includes virtual processing, virtual memory, virtual network or interface, and virtual storage, and can be operated by corresponding virtualization layer 1506. Different embodiments of instances of virtual device 1502 can be implemented on one or more VMs 1508, and these embodiments can be made in different ways. In some contexts, virtualization of hardware is referred to as network function virtualization (NFV). NFV can be used to unify numerous network device types onto industry standard high-capacity server hardware, physical switches, and physical storage that can be located in data centers and customer premises equipment (CPE).

[0336] In the context of NFV, VM 1508 can be a software implementation of a physical machine whose operating program is executed as if it were executed on a physical, non-virtualized machine. Each VM 1508 and the hardware portion of hardware 1504 that executes the VM (whether it is hardware dedicated to the VM and / or hardware shared by the VM with other VMs) form a separate virtual network element. Still in the context of NFV, a virtual network function is responsible for handling a specific network function that operates in one or more VMs 1508 on top of hardware 1504 and corresponds to an application 1502.

[0337] Hardware 1504 may be implemented in a standalone network node with general or specific components. Hardware 1504 may implement some functions via virtualization. Alternatively, hardware 1504 may be part of a larger hardware cluster (e.g., in a data center or CPE), where many hardware nodes work together and are managed by management and orchestration 1510, which oversees, among other things, the lifecycle management of application 1502. In some embodiments, hardware 1504 is coupled to one or more radio units, each of which includes one or more transmitters and one or more receivers that may be coupled to one or more antennas. The radio unit may communicate directly with other hardware nodes via one or more appropriate network interfaces, and may be used in conjunction with virtual components to provide radio capabilities to virtual nodes (e.g., radio access nodes or base stations). In some embodiments, some signaling may be provided by using a control system 1512, which may alternatively be used for communication between hardware nodes and radio units.

[0338] Fig.16 A communication diagram is shown in which a host 1602 communicates with a UE 1606 via a network node 1604 over a partially wireless connection according to some embodiments. Fig.16 Describe the UE discussed in the previous paragraphs (e.g., Fig.11 UE 1112a and / or Fig.12 UE 1200), network node (e.g., Fig.11 The network node 1110a and / or Fig.13 network node 1300) and a host (e.g., Fig.11 Host 1116 and / or Fig.14 An example implementation of a host 1400 according to various embodiments.

[0339] Similar to the host 1400, an embodiment of the host 1602 includes hardware, such as a communication interface, a processing circuit, and a memory. The host 1602 also includes software that is stored in the host 1602 or can be accessed by the host 1602 and can be executed by the processing circuit. The software includes a host application that is operable to provide services to a remote user, such as a UE 1606 connected via an over-the-top (OTT) connection 1650 extending between the UE 1606 and the host 1602. When providing services to the remote user, the host application can provide user data sent using the OTT connection 1650.

[0340] The network node 1604 includes hardware that enables it to communicate with the host 1602 and the UE 1606. The connection 1660 can be a direct connection or through a core network (such as Fig.11The core network 1106 of the present invention) and / or one or more other intermediate networks (eg, one or more public, private, or managed networks). For example, the intermediate network may be a backbone network or the Internet.

[0341] UE 1606 includes hardware and software that is stored in or accessible by UE 1606 and can be executed by the processing circuitry of the UE. The software includes a client application (e.g., a web browser or an operator-specific "app") that is operable to provide services to a human or non-human user via UE 1606 with the support of host 1602. In host 1602, an executing host application can communicate with an executing client application via an OTT connection 1650, which terminates at UE 1606 and host 1602. When providing services to a user, the client application of the UE can receive request data from the host application of the host and provide user data in response to the request data. The OTT connection 1650 can send both request data and user data. The client application of the UE can interact with the user to generate user data that is provided to the host application via the OTT connection 1650.

[0342] The OTT connection 1650 may extend via a connection 1660 between the host 1602 and the network node 1604 and via a wireless connection 1670 between the network node 1604 and the UE 1606 to provide connectivity between the host 1602 and the UE 1606. The connection 1660 and the wireless connection 1670 through which the OTT connection 1650 may be provided have been drawn abstractly to illustrate communications between the host 1602 and the UE 1606 via the network node 1604 without explicitly involving any intermediate devices and the precise routing of messages via those devices.

[0343] As an example of sending data via OTT connection 1650, in step 1608, host 1602 provides user data, which can be performed by executing a host application. In some embodiments, the user data is associated with a specific human user who interacts with UE 1606. In other embodiments, the user data is associated with UE 1606, which shares data with host 1602 without explicit human interaction. In step 1610, host 1602 initiates a transmission to UE 1606, which carries the user data. Host 1602 may initiate the transmission in response to a request sent by UE 1606. The request may be caused by human interaction with UE 1606 or by the operation of a client application executed on UE 1606. In accordance with the teachings of the embodiments described throughout the present disclosure, the transmission may be transmitted via network node 1604. Thus, in step 1612, in accordance with the teachings of the embodiments described throughout the present disclosure, network node 1604 sends the user data carried in the transmission initiated by host 1602 to UE 1606. In step 1614, UE 1606 receives the user data carried in the transmission, which may be performed by a client application executing on UE 1606 that is associated with a host application executed by host 1602.

[0344] In some examples, UE 1606 executes a client application that provides user data to host 1602. User data may be provided as a reaction or response to data received from host 1602. Therefore, in step 1616, UE 1606 may provide user data, which may be performed by executing the client application. When providing user data, the client application may also take into account user input received from a user via an input / output interface of UE 1606. Regardless of the specific manner in which user data is provided, in step 1618, UE 1606 initiates a transmission of user data to host 1602 via network node 1604. In step 1620, in accordance with the teachings of the embodiments described throughout this disclosure, network node 1604 receives user data from UE 1606 and initiates sending the received user data to host 1602. In step 1622, host 1602 receives the user data carried in the transmission initiated by UE 1606.

[0345] One or more of the various embodiments improves the performance of an OTT service provided to a UE 1606 using an OTT connection 1650 in which a wireless connection 1670 forms the final part. More specifically, an embodiment may prevent an unauthorized NF (e.g., NWDAF) from joining a FL group as a client and / or prevent an NF from joining a group as a client to perform fraudulent and / or unauthentic FL operations. In this way, an embodiment may prevent confidential and / or sensitive ML models from being exposed to unauthorized parties during FL, and may mitigate security risks for NFs participating in FL. By improving security, an embodiment facilitates the deployment of FL in a multi-vendor communication network (e.g., 5GC), which may improve ML models for network performance analysis in such a network. This may result in improved network performance, thereby increasing the value of OTT services delivered to both end users and service providers over such an improved network.

[0346] In an example scenario, host 1602 may collect and analyze plant status information. As another example, host 1602 may process audio and video data that may have been retrieved from a UE for use in creating a map. As another example, host 1602 may collect and analyze real-time data to help control vehicle congestion (e.g., control traffic lights). As another example, host 1602 may store surveillance videos uploaded by a UE. As another example, host 1602 may store or control access to media content such as video, audio, VR, or AR, which may be broadcast, multicast, or unicast to a UE. As other examples, host 1602 may be used for energy pricing, remote control of non-time-critical power loads to balance power generation demand, positioning services, presentation services (e.g., compiling charts based on data collected from remote devices, etc.), or any other function of collecting, retrieving, storing, analyzing, and / or sending data.

[0347] In some examples, a measurement process may be provided for monitoring data rate, latency, and other factors that are the object of improvement of one or more embodiments. There may also be an optional network function for reconfiguring the OTT connection 1650 between the host 1602 and the UE 1606 in response to changes in the measurement results. The measurement process and / or the network function for reconfiguring the OTT connection may be implemented in the software and hardware of the host 1602 and / or the UE 1606. In some embodiments, sensors (not shown) may be deployed in other devices through which the OTT connection 1650 passes, or associated with the other devices; the sensors may participate in the measurement process by providing the values ​​of the monitoring quantities exemplified above or providing the values ​​of other physical quantities from which the software can calculate or estimate the monitoring quantities. The reconfiguration of the OTT connection 1650 may include message formats, retransmission settings, preferred routes, etc.; the reconfiguration does not require direct changes to the operation of the network node 1604. Such processes and functions may be known and practiced in the art. In some embodiments, the measurement may involve proprietary UE signaling that facilitates the host 1602 to measure throughput, propagation time, latency, etc. Measurements may be made by software using the OTT connection 1650 to send messages (particularly empty or "dummy" messages) while monitoring propagation times, errors, etc.

[0348] The above merely illustrates the principles of the present disclosure. In view of the teachings herein, various modifications and changes to the described embodiments will be apparent to those skilled in the art. Therefore, it should be understood that those skilled in the art will be able to design many systems, arrangements and programs that, although not explicitly shown or described herein, embody the principles of the present disclosure and therefore can be used within the spirit and scope of the present disclosure. As will be understood by those of ordinary skill in the art, the various embodiments can be used together or interchangeably.

[0349] The term unit as used herein may have a conventional meaning in the field of electronics, electrical devices and / or electronic devices, and may include, for example, electrical and / or electronic circuits, devices, modules, processors, memories, logical solid-state and / or discrete devices, computer programs or instructions for performing various tasks, processes, calculations, output and / or display functions, etc., such as those described herein.

[0350] Any suitable steps, methods, features, functions or benefits disclosed herein may be performed by one or more functional units or modules of one or more virtual devices. Each virtual device may include multiple of these functional units. These functional units may be implemented by processing circuits, which may include one or more microprocessors or microcontrollers and other digital hardware (which may include digital signal processors (DSPs), dedicated digital logic, etc.). The processing circuit may be configured to execute program codes stored in a memory, which may include one or more types of memory, such as read-only memory (ROM), random access memory (RAM), cache memory, flash memory device, optical storage device, etc. The program code stored in the memory includes program instructions for executing one or more telecommunications and / or data communication protocols and instructions for executing one or more technologies described herein. In some implementations, the processing circuit may be used to cause each functional unit to perform a corresponding function according to one or embodiments of the present disclosure.

[0351] As described herein, a device and / or apparatus may be represented by a semiconductor chip, a chipset, or a (hardware) module including such a chip or chipset; however, this does not exclude the possibility that the functionality of the device or apparatus is not implemented by hardware but is implemented as a software module (e.g., a computer program or computer program product including an executable software code portion for execution or operation on a processor). In addition, the functionality of the device or apparatus may be implemented by any combination of hardware and software. A device or apparatus may also be considered as a combination of multiple devices and / or apparatuses, whether they functionally cooperate with each other or are independent of each other. In addition, as long as the functionality of the device or apparatus is retained, the device and apparatus may be implemented in a distributed manner throughout the system. This principle and similar principles are considered to be known to technicians.

[0352] Unless otherwise defined, all terms used herein, including technical and scientific terms, have the same meanings as those commonly understood by those of ordinary skill in the art to which the present disclosure belongs. It will be further understood that the terms used herein should be interpreted as being consistent with their meanings in the context of this specification and the relevant technology, and not interpreted as ideal or overly formal meanings, unless so explicitly defined herein.

[0353] In addition, certain terms used in this disclosure (including the specification and the drawings) may be used synonymously in certain instances (e.g., "data" and "information"). It should be understood that although these terms and / or their terms that may be synonymous with each other may be used synonymously herein, there may be instances where such words may not be intended to be used synonymously.

[0354] Example embodiments of the techniques and apparatus described herein are not limited to the appended claims.

Claims

1. A method of a first network function NF (710), the first network function NF (710) being configured to operate as a server (710) of a federated learning FL group in a communication network, the method comprising: registering (810) the following information in a network repository function NRF (720) of the communication network: a vendor identifier ID associated with the first NF (710), and an interoperability ID corresponding to one or more vendor IDs associated with further NFs (730, 740) authorized to join the FL group as clients (730, 740); receiving (820) an indication that a second NF (730, 740) of the communication network is a candidate client (730, 740) of the FL group; and The FL group is created or updated (830) to include the second NF (730, 740) as a client in the FL group based on one of the following: a first token indicating that the first NF (710) is authorized to add the second NF (730, 740) as a client (730, 740) to the FL group; or A second token indicating that the second NF (730, 740) is authorized to join the FL group as a client (730, 740).

2. The method according to claim 1, wherein: The registration information also includes an analysis ID associated with the machine learning (ML) model used for FL; and The interoperability ID indicates an authorization specific to the analysis ID.

3. The method according to any one of claims 1 to 2, wherein: The registration information also includes one or more of the following items: an indication of one or more FL capabilities associated with the first NF (710); a service area associated with the first NF (710); address information associated with the first NF (710); or An indication of an authorized scope of the FL group, comprising an indication of one or more of the following criteria for a NF (730, 740) to join the FL group as a client (730, 740): one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

4. The method according to any one of claims 1 to 3, wherein: Creating or updating (830) the FL group to include the second NF (730, 740) as a client in the FL group comprises: In response to the indication, obtaining (831) the first token from the NRF (720); sending (832) a first request to the second NF (730, 740) for the second NF (730, 740) to join the FL group as a client (730, 740), wherein the first request includes the first token; and A first response is received (833) from the second NF (730, 740), the first response indicating that the second NF (730, 740) will join the FL group as a client (730, 740).

5. The method according to claim 4, wherein: The first request is a FL Prepare Request message, and the first response is a FL Prepare Response message.

6. The method according to any one of claims 4 to 5, wherein: Receiving an indication from the NRF (720) that the second NF (730, 740) is a candidate client (730, 740) is received from the NRF (720) as one of: a response to the client discovery request of the first NF (710); or In response to the first NF (710) requiring notification of a subscription request for registration information in the NRF (720) by candidate clients (730, 740) of the FL group.

7. The method according to claim 6, wherein: The client discovery request or the subscription request includes one or more of the following items: the vendor ID associated with the first NF (710), The analysis ID associated with the ML model used for FL, or An indication of one or more FL capabilities associated with the first NF (710).

8. The method according to any one of claims 6 to 7, wherein: The indication from the NRF (720) is used to indicate a plurality of NFs (730, 740) as candidate clients (730, 740) of the FL group, including the second NF (730, 740); and A corresponding plurality of first tokens are obtained from the NRF (720), and the corresponding plurality of first tokens are sent to the plurality of NFs (730, 740) in respective first requests.

9. The method according to any one of claims 4 to 8, wherein: The indication that the second NF (730, 740) is a candidate client (730, 740) is based on one or more of the following items registered by the second NF (730, 740) in the NRF (720): an interoperability ID corresponding to one or more vendor IDs associated with a further NF authorized to add the second NF (730, 740) as a client (730, 740) to the FL group; and The analysis ID associated with the ML model used for FL.

10. The method according to any one of claims 1 to 3, wherein: The indication that the second NF (730, 740) is a candidate client (730, 740) is a FL Join Request message received from the second NF (730, 740) and including the second token; and Creating or updating (830) the FL group to include the second NF (730, 740) as a client (730, 740) in the FL group includes validating (834) a second token received from the second NF (730, 740).

11. The method according to any one of claims 1 to 9, wherein: Creating or updating (830) the FL group to include the second NF (730, 740) as a client (730, 740) in the FL group includes registering (835) one or more of the following information with the NRF (720): an identifier of the FL group and / or an identifier of a FL process performed by the FL group; and The indication of the authorized scope of the FL group includes an indication of one or more of the following criteria for a NF (730, 740) to join the FL group as a client (730, 740): one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

12. The method according to any one of claims 1 to 10, wherein: One or more of the following applies: the first NF (710) is a Network Data Analysis Function NWDAF, and the second NF (730, 740) is a NWDAF.

13. A method of a second network function NF (730, 740), the second network function NF (730, 740) being configured to operate as a client (730, 740) of a federated learning FL group in a communication network, the method comprising: registering (910) the following information in a network repository function NRF (720) of the communication network: a vendor identifier (ID) associated with the second NF (730, 740), and an interoperability ID corresponding to one or more vendor IDs associated with further NFs authorized to add the second NF (730, 740) as a client (730, 740) to a FL group; Subsequently joining (920) the FL group as a client (730, 740), wherein the first NF (710) is configured to operate as a server (710) of the FL group, and wherein joining (920) the FL group is based on one of the following: a first token indicating that the first NF (710) is authorized to add the second NF (730, 740) as a client (730, 740) to the FL group; or A second token indicating that the second NF (730, 740) is authorized to join the FL group as a client (730, 740).

14. The method according to claim 13, wherein: The registration information also includes an analysis ID associated with the machine learning ML model for FL; and The interoperability ID indicates an authorization specific to the analysis ID.

15. The method according to any one of claims 13 to 14, wherein: The registration information also includes one or more of the following items: an indication of one or more FL capabilities associated with the second NF (730, 740); a service area associated with the second NF (730, 740); or Address information associated with the second NF (730, 740).

16. The method according to any one of claims 13 to 15, wherein: Joining (920) the FL group as a client (730, 740) includes: receiving (921) a first request from the first NF (710) for the second NF (730, 740) to join the FL group as a client (730, 740), wherein the first request includes the first token; verifying (922) the first token received from the first NF (710); and Based on the verification (922), a first response is sent (923) to the first NF (710), the first response indicating that the second NF (730, 740) will join the FL group as a client (730, 740).

17. The method according to claim 16, wherein: The first request is a FL prepare request message, and the first response is a FL prepare response message.

18. The method according to any one of claims 13 to 15, wherein: Joining (920) the FL group as a client (730, 740) includes: discovering (924) the FL group and a first NF (710) serving as a server (710) of the FL group via the NRF (720); sending (926) a second request to the first NF (710) to join the FL group as a client (730, 740), wherein the second request includes the second token; and A second response is received (927) from the first NF (710), the second response indicating that the first NF (710) accepted the second request.

19. The method according to claim 18, wherein: Joining (920) the FL group as a client (730, 740) further comprises: in response to discovering (924) the FL group and the first NF (710) as a server (710) of the FL group, obtaining (925) the second token from the NRF (720), wherein the obtained second token is sent to the first NF (710) together with the second request.

20. The method according to any one of claims 18 to 19, wherein: The second request is a FL Join Request message, and the second response is a FL Join Request Accept message.

21. The method according to any one of claims 18 to 20, wherein: Discovering (924) the FL group and the first NF (710) as the Server 2 (710) is based on one or more of the following items registered by the first NF (710) in the NRF (720): an identifier of the FL group and / or an identifier of a FL process performed by the FL group; an interoperability ID corresponding to one or more vendor IDs associated with further NFs authorized to join the FL group as clients (730, 740); The analysis ID associated with the ML model used for FL; and The indication of the authorized scope of the FL group includes an indication of one or more of the following criteria for a NF (730, 740) to join the FL group as a client (730, 740): one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

22. The method according to any one of claims 13 to 19, wherein: One or more of the following applies: the first NF (710) is a Network Data Analysis Function NWDAF, and the second NF (730, 740) is a NWDAF.

23. A method of a network repository function (NRF) (720) of a communication network, the method comprising: The following information associated with a first network function NF (710) and a second NF (730, 740) of the communication network is registered (1010): a first vendor identifier ID associated with the first NF (710), the first NF (710) being configured to operate as a server (710) of a federated learning FL group, a first interoperability ID corresponding to one or more vendor IDs associated with further NFs (730, 740) that are authorized to join the FL group as clients (730, 740), a second vendor ID associated with a second NF (730, 740), the second NF (730, 740) being configured to operate as a FL client (730, 740), and a second interoperability ID corresponding to one or more vendor IDs associated with a further NF authorized to add the second NF (730, 740) as a client (730, 740) to the FL group; Based on the registered information, one or more of the following are provided (1060): providing a first token to the first NF (710), the first token indicating that the first NF (710) is authorized to add the second NF (730, 740) as a client (730, 740) to the FL group; or A second token is provided to the second NF (730, 740), the second token indicating that the second NF (730, 740) is authorized to join the FL group as a client (730, 740).

24. The method according to claim 23, wherein: The registered information also includes one or more of the following: a first analysis ID associated with a machine learning ML model used by the first NF (710) for FL; a second analysis ID associated with the ML model used for FL by the second NF (730, 740); an indication of one or more first FL capabilities associated with the first NF (710); or An indication of one or more second FL capabilities associated with the second NF (730, 740).

25. The method according to claim 24, wherein the registered information further comprises one or more of the following items: Respective service areas associated with the first NF (710) and the second NF (730, 740); Relevant address information associated with the first NF (710) and the second NF (730, 740); or An indication of an authorized scope of the FL group, comprising an indication of one or more of the following criteria for a NF (730, 740) to join the FL group as a client (730, 740): one or more allowed NF types, one or more allowed NF IDs, and one or more allowed FL capabilities.

26. The method according to any one of claims 24 to 25, further comprising: The second NF is discovered (1020) based on one or more of the following matches or correspondences: a match between the second vendor ID and one of the vendor IDs corresponding to the first interoperability ID, a match between the first analysis ID and the second analysis ID, and the matching or correspondence between the first capability and the second capability; An indication is sent (1030) to the first NF (710) that the second NF (730, 740) is a candidate client (730, 740) of the FL group.

27. The method according to claim 26, wherein: Discovering (1020) the second NF (730, 740) and sending (1030) the indication is in response to one of: A client discovery request of the first NF (710); or The first NF (710) requests a subscription to registration information of candidate clients (730, 740) of the FL group in the NRF (720).

28. The method according to claim 27, wherein: The client discovery request or the subscription request includes one or more of the following items on which the matching or corresponding relationship is based: a first vendor ID associated with the first NF (710), the first analysis ID, and An indication of one or more FL capabilities associated with the first NF (710).

29. A method according to any one of claims 26 to 28, wherein: Providing (1060) the first token to the first NF (710) is in response to a token request from the first NF (710); and The token request from the first NF (710) is in response to sending (1030) an indication that the second NF (730, 740) is a candidate client (730, 740) of the FL group.

30. The method according to any one of claims 26 to 29, wherein: The second NF (730, 740) is one of a plurality of candidate clients (730, 740) of the FL group; The indication sent to the first NF (710) identifies the plurality of candidate clients (730, 740); and A plurality of first tokens associated with respective candidate clients (730, 740) are provided to the first NF (710).

31. The method according to any one of claims 24 to 25, further comprising: The first NF (710) is discovered (1040) based on one or more of the following matches or correspondences: a match between the first vendor ID and one of the vendor IDs corresponding to the second interoperability ID, a match between the first analysis ID and the second analysis ID, and the matching or correspondence between the first capability and the second capability; An indication is sent (1050) to the second NF (730, 740) regarding the FL group and that the first NF (710) is a server (710) of the FL group.

32. The method according to claim 31, wherein: Discovering (1040) the first NF and sending (1050) the indication is in response to one of: registering information associated with the second NF (730, 740), or a server discovery request of the second NF (730, 740).

33. The method of claim 32, wherein: The server discovery request includes one or more of the following items on which the matching or correspondence is based: a second vendor ID associated with the second NF (730, 740), the second analysis ID, and An indication of one or more FL capabilities associated with the second NF (730, 740).

34. A method according to any one of claims 31 to 33, wherein: Providing (1060) the second token to the second NF (730, 740) is in response to a token request from the second NF (730, 740); and The token request from the second NF (730, 740) is in response to sending (1050) an indication about the FL group and about the first NF being a server of the FL group.

35. The method according to any one of claims 23 to 34, wherein: One or more of the following applies: the first NF (710) is a Network Data Analysis Function NWDAF, and the second NF (730, 740) is a NWDAF.

36. A first network function NF (710) configured to operate as a server (710) of a federated learning FL group in a communication network, wherein: The first NF (710) is implemented by a communication interface circuit and a processing circuit that are operably coupled; and The processing circuit and the interface circuit are configured to perform operations corresponding to the method according to any one of claims 1 to 12.

37. A first network function NF (710) configured to operate as a server (710) of a federated learning FL group in a communication network, the first NF (710) being further configured to perform operations corresponding to the method according to any one of claims 1 to 12.

38. A non-transitory computer-readable medium storing computer-executable instructions, which, when executed by a processing circuit associated with a first network function NF (710), configure the first NF (710) to perform operations corresponding to the method according to any one of claims 1 to 12, wherein: The first NF (710) is configured to operate as a server (710) of a joint learning FL group in a communication network.

39. A computer program product comprising computer executable instructions, which, when executed by a processing circuit associated with a first network function NF (710), configure the first NF (710) to perform operations corresponding to the method according to any one of claims 1 to 12, wherein: The first NF (710) is configured to operate as a server (710) of a joint learning FL group in a communication network.

40. A second network function NF (730, 740) configured to operate as a client (730, 740) of a federated learning FL group in a communication network, wherein: The second NF (730, 740) is implemented by a communication interface circuit and a processing circuit that are operably coupled; and The processing circuit and the interface circuit are configured to perform operations corresponding to the method according to any one of claims 13 to 22.

41. A second network function NF (730, 740) configured to operate as a client (730, 740) of a federated learning FL group in a communication network, the second NF (730, 740) being further configured to perform operations corresponding to the method according to any one of claims 13 to 22.

42. A non-transitory computer-readable medium storing computer-executable instructions, which, when executed by a processing circuit associated with a second network function NF (730, 740), configure the second NF (730, 740) to perform operations corresponding to the method according to any one of claims 13 to 22, wherein: The second NF (730, 740) is configured to operate as a client (730, 740) of a joint learning FL group in a communication network.

43. A computer program product comprising computer executable instructions, which, when executed by a processing circuit associated with a second network function NF (730, 740), configure the second NF (730, 740) to perform operations corresponding to the method according to any one of claims 13 to 22, wherein: The second NF (730, 740) is configured to operate as a client (730, 740) of a joint learning FL group in a communication network.

44. A network repository function (NRF) (720) of a communication network, wherein: The NRF (720) is implemented by a communication interface circuit and a processing circuit that are operably coupled; and The processing circuit and the interface circuit are configured to perform operations corresponding to the method according to any one of claims 23 to 35.

45. A Network Repository Function (NRF) (720) of a communication network, the NRF (720) being configured to perform operations corresponding to the method according to any one of claims 23 to 35.

46. ​​A non-transitory computer-readable medium storing computer-executable instructions which, when executed by processing circuitry associated with a network repository function (NRF) (720) of a communication network, configure the NRF (720) to perform operations corresponding to the method according to any one of claims 23 to 35.

47. A computer program product comprising computer executable instructions which, when executed by processing circuitry associated with a Network Repository Function (NRF) (720) of a communication network, configure the NRF (720) to perform operations corresponding to the method according to any one of claims 23 to 35.

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