Handling of repository registration of federated learning members

Abstract

A first NE for wireless communication capable of, operable to, or configured to send to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, and receive an acknowledgement message from the second network entity.

Description

HANDLING OF REPOSITORY REGISTRATION OF FEDERATED LEARNING MEMBERSTECHNICAL FIELD

[0001] The present disclosure relates to wireless communications, and more specifically to the repository registration of federated learning (FL) members for Artificial Intelligence Machine Learning Enablement (AIMLE).BACKGROUND

[0002] A wireless communications system may include one or multiple network communication devices, such as network equipment (NE), supporting wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE), or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers, or the like)). Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G)).SUMMARY

[0003] An article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a,” “at least one,” “one or more,” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of’ or “one or more of” or “one or both of’) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a conditionAttorney Docket No. PC934559WO14737546-1B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on. Further, as used herein, including in the claims, a “set” may include one or more elements.

[0004] A first NE for wireless communication is described. The first NE may be capable of, operable to, or configured to perform one or more operations as described herein. For example, the first NE may be capable of, operable to, or configured to send to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, and receive an acknowledgement message from the second network entity.

[0005] A processor (e.g., a standalone processor chipset, or a component of a first device) for wireless communication is described. The processor may be capable of, operable to, or configured to perform one or more operations as described herein. For example, the processor may be capable of, operable to, or configured to send to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, and receive an acknowledgement message from the second network entity.

[0006] A method performed or performable by a first NE for wireless communication is described. The method may include sending to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, and receiving an acknowledgement message from the second network entity.

[0007] In some implementations of the first NE, the processor and the method described herein, the request message is a request to delete the resource of the FL member due to at least one of a load of the FL member, an energy of the FL member, and a mobility of the FL member to new Vertical Application Layer, VAL, service areas.

[0008] In some implementations of the first NE, the processor, and the method described herein, the request message identifies at least one of a role of the FL member and capabilities of the FL member.Attorney Docket No. PC934559WO14737546-1

[0009] In some implementations of the first NE, the processor, and the method described herein, the first network equipment is one of a Vertical Application Layer, VAL, server or an Artificial Intelligence Machine Learning Enablement, AIMLE, server.

[0010] In some implementations of the first NE, the processor, and the method described herein, the second network entity is a repository for one or more Artificial Intelligence Machine Learning, AIML, services.

[0011] In some implementations of the first NE, the processor, and the method described herein, the FL member is the first network equipment, or the first network equipment is acting on behalf of the FL member.

[0012] In some implementations of the first NE, the processor, and the method described herein, the request message includes identities of a plurality of FL members.

[0013] In some implementations of the first NE, the processor, and the method described herein, the acknowledgement message indicates a result of the request.

[0014] A second NE for wireless communication is described. The second NE may be capable of, operable to, or configured to perform one or more operations as described herein. For example, the second NE may be capable of, operable to, or configured to receive from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, validate and process the request message, and send an acknowledgement message to the first network entity.

[0015] A processor (e.g., a standalone processor chipset, or a component of a first device) for wireless communication is described. The processor may be capable of, operable to, or configured to perform one or more operations as described herein. For example, the processor may be capable of, operable to, or configured to receive from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member, validate and process the request message, and send an acknowledgement message to the first network entity.

[0016] A method performed or performable by a second NE for wireless communication is described. The method may include receiving from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource of the FLAttorney Docket No. PC934559WO14737546-1member, or delete the resource of the FL member, validating and processing the request message, and sending an acknowledgement message to the first network entity.

[0017] In some implementations of the second NE, the processor, and the method described herein, the request message is a request to delete the resource of the FL member due to at least one of a load of the FL member, an energy of the FL member, and a mobility of the FL member to new Vertical Application Layer, VAL, service areas.

[0018] In some implementations of the second NE, the processor, and the method described herein, the request message identifies at least one of a role of the FL member and capabilities of the FL member.

[0019] In some implementations of the second NE, the processor, and the method described herein, the second network equipment is a repository for one or more Artificial Intelligence Machine Learning, AIML, services.

[0020] In some implementations of the second NE, the processor, and the method described herein, the first network entity is one of a Vertical Application Layer, VAL, server or an Artificial Intelligence Machine Learning Enablement, AIMLE, server.

[0021] In some implementations of the second NE, the processor, and the method described herein, the FL member is the first network equipment, or the first network equipment is acting on behalf of the FL member.

[0022] In some implementations of the second NE, the processor, and the method described herein, the request message includes identities of a plurality of FL members.

[0023] In some implementations of the second NE, the processor, and the method described herein, the acknowledgement message indicates a result of the request.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 illustrates a procedure for the registration of a candidate FL member via the ML repository, serving as an AIML service registry, in accordance with aspects of the present disclosure.

[0025] Figure 2 illustrates an example of a wireless communications system in accordance with aspects of the present disclosure in accordance with aspects of the present disclosure.

[0026] Figure 3 illustrates a procedure where the registration update of a candidate FL member occurs via the ML repository, in accordance with aspects of the present disclosure.Attorney Docket No. PC934559WO14737546-1

[0027] Figure 4 illustrates a procedure where the deregistration of a candidate registered FL member occurs via the ML repository, serving as AIML service registry, in accordance with aspects of the present disclosure.

[0028] Figure 5 depicts a procedure where a service consumer sends a request to the ML repository to register an Individual FL Member, in accordance with aspects of the present disclosure.

[0029] Figure 6 illustrates a procedure where a service consumer sends a request to the ML repository to query an Individual FL Member, in accordance with aspects of the present disclosure.

[0030] Figure 7 illustrates a procedure where a service consumer sends a request to the ML repository to update registration of an Individual Registered FL Member, in accordance with aspects of the present disclosure.

[0031] Figure 8 illustrates a procedure where a service consumer sends a request to the ML repository to deregister an Individual Registered FL Member, in accordance with aspects of the present disclosure.

[0032] Figure 9 illustrates depicts the resource URIs structure for the MLR_FLMember API, in accordance with aspects of the present disclosure.

[0033] Figure 10 illustrates an example of a NE 1000 in accordance with aspects of the present disclosure.

[0034] Figure 11 is a flowchart illustrating a method 1100 performed by a NE in accordance with aspects of the present disclosure.

[0035] Figure 12 is a flowchart illustrating a method 1200 performed by a NE in accordance with aspects of the present disclosure.DETAILED DESCRIPTION

[0036] The 3rd Generation Partnership Project (3GPP) refers to a collaborative initiative among multiple standards organizations that develop protocols for mobile telecommunications technologies. These technologies include, but are not limited to, radio access, core network functionality, and service capabilities, collectively providing a comprehensive system framework for mobile telecommunications.

[0037] Network Data Analytics Function (NWDAF) is a 5G 3GPP standard method used to collect data from user equipment (UEs), network functions (NFs), operations,Attorney Docket No. PC934559WO14737546-1administration, and maintenance (OAM) systems, etc. from the 5G Core (5GC), Cloud, and Edge networks that can be used for analytics. The NWDAF is located within the 5G core network domain. The NWDAF may provide data analytics to allow communication service providers to improve customer experiences and to increase network efficiency and generate new sources of revenue. Via open APIs the NWDAF may also be exposed to external users such as streaming services, financial institutions including banks, etc.

[0038] Typically, the NWDAF makes use of one or more Machine Learning (ML) models, the building of which is an iterative process. A ML model can be identified by its ID and can be provided by the network or operator, a telco vendor, edge provider or an application provider and can be applicable for mobile devices in the 5G system, e.g., image recognition, localization, performance, speech recognition, and video processing, as well as for optimizing performance of the network elements / communication aspects. A ML model can be trained for example for deriving the UE location pattern for a given time and area, the performance for a given cell / network access or for a UE or the load of a network entity. ML models at the network side are stored at network functions serving as ML model repositories using the ML model ID. For external ML models, there is no provisioning of how the ID is configured and where the ML models are stored.

[0039] In the current 3GPP architecture (up to Release 18) the NWDAF provides analytic output to one or more Analytics Consumer NFs based on data collected from one or more Data Producer NFs. Analytics Consumer NFs subscribe to the NWDAF to receive analytics data therefrom.

[0040] This type of shared ML model training is known as “Federated Learning” or FL.

[0041] As described above, current 3GPP specifications allow for FL of ML models between NWDAFs. For example, an FL Server NWDAF can provide an ML model to FL Client NWDAFs for further training using local data. Afterwards, each FL Client NWDAF provides its trained ML model information or the weights of a trained model back to the FL Server NWDAF, which aggregates all the local ML model information and updates the global ML model. The process may be repeated until the desired accuracy is reached or the upper bound for training time expires.

[0042] 3GPP TS 23.482 describes the procedure for the registration of the Federated Learning (FL) members for Artificial Intelligence Machine Learning Enablement (AIMLE) Services at an ML repository. However, the current procedure is not complete and should be expanded to cover creation, registration, querying, updating, modifying, and deregistration of the FL members. More specifically, this disclosure aims to provide theAttorney Docket No. PC934559WO14737546-1procedures for the creation, registration, registration update, and deregistration of candidate FL members in the ML repository which serves as service registry for the FL members undertaking a task related to the ML model lifecycle, such as ML model local training. Candidate FL members can be application layer entities at the server side (e.g., VAL server, AIMLE server), which can potentially be selected as FL clients or FL server for a particular ASP / vertical requirement, or at the client side (e.g. AIMLE client), which can potentially be selected as FL clients. If VAL server or the AIMLE client is the candidate FL member, it registers indirectly via the AIMLE server to the ML repository.

[0043] Figure 1 illustrates a known procedure for the registration of a candidate FL member 100 via the ML repository 102, serving as an AIML service registry. The following steps are illustrated:

[0044] 1 . The candidate FL member (e.g., VAL server via AIMLE server or AIMLE server) sends an FL member registration request to the ML repository for registering to the ML repository which acts as the AIML service registry.

[0045] 2. The ML repository validates the received request and generates the identity and other security related information for all the FL members listed in the registration request.

[0046] 3. The ML repository sends the generated information in the FL member registration response message to the candidate FL member.

[0047] Presented below are procedures to enable creation of a resource for the FL member, replacement of the resource of the FL member, modification of one or more information elements of the resource of the FL member, and deletion of the resource of the FL member.

[0048] Aspects of the present disclosure are described in the context of a wireless communications system.

[0049] Figure 2 illustrates an example of a wireless communications system 200 in accordance with aspects of the present disclosure. The wireless communications system 200 may include one or more NE 202, one or more UE 204, and a core network (CN) 206. The wireless communications system 200 may support various radio access technologies. In some implementations, the wireless communications system 200 may be a 4G network, such as an LTE network or an LTE-Advanced (LTE-A) network. In some other implementations, the wireless communications system 200 may be a NR network, such as a 5G network, a 5G-Advanced (5G-A) network, or a 5G ultrawideband (5G-UWB) network. In other implementations, the wireless communications system 200 may be a combination of a 4G network and a 5G network, or other suitable radio access technology includingAttorney Docket No. PC934559WO14737546-1Institute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20. The wireless communications system 200 may support radio access technologies beyond 5G, for example, 6G. Additionally, the wireless communications system 200 may support technologies, such as time division multiple access (TDMA), frequency division multiple access (FDMA), or code division multiple access (CDMA), etc.

[0050] The one or more NE 202 may be dispersed throughout a geographic region to form the wireless communications system 200. One or more of the NE 202 described herein may be or include or may be referred to as a network node, a base station, a network element, a network function, a network entity, a radio access network (RAN), a NodeB, an eNodeB (eNB), a next-generation NodeB (gNB), or other suitable terminology. An NE 202 and a UE 204 may communicate via a communication link, which may be a wireless or wired connection. For example, an NE 202 and a UE 204 may perform wireless communication (e.g., receive signaling, transmit signaling) over a Uu interface.

[0051] An NE 202 may provide a geographic coverage area for which the NE 202 may support services for one or more UEs 204 within the geographic coverage area. For example, an NE 202 and a UE 204 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc.) according to one or multiple radio access technologies. In some implementations, an NE 202 may be moveable, for example, a satellite associated with a non-terrestrial network (NTN). In some implementations, different geographic coverage areas 112 associated with the same or different radio access technologies may overlap, but the different geographic coverage areas may be associated with different NE 202.

[0052] The one or more UE 204 may be dispersed throughout a geographic region of the wireless communications system 200. A UE 204 may include or may be referred to as a remote unit, a mobile device, a wireless device, a remote device, a subscriber device, a transmitter device, a receiver device, or some other suitable terminology. In some implementations, the UE 204 may be referred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 204 may be referred to as an Internet-of-Things (loT) device, an Internet-of-Everything (loE) device, or machine-type communication (MTC) device, among other examples.

[0053] A UE 204 may be able to support wireless communication directly with other UEs 204 over a communication link. For example, a UE 204 may support wireless communication directly with another UE 204 over a device-to-device (D2D) communicationAttorney Docket No. PC934559WO14737546-1link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to- everything (V2X) deployments, or cellular-V2X deployments, the communication link 114 may be referred to as a sidelink. For example, a UE 204 may support wireless communication directly with another UE 204 over a PC5 interface.

[0054] An NE 202 may support communications with the CN 206, or with another NE 202, or both. For example, an NE 202 may interface with other NE 202 or the CN 206 through one or more backhaul links (e.g., S1 , N2, N2, or network interface). In some implementations, the NE 202 may communicate with each other directly. In some other implementations, the NE 202 may communicate with each other or indirectly (e.g., via the CN 206. In some implementations, one or more NE 202 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC). An ANC may communicate with the one or more UEs 204 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs).

[0055] The CN 206 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The CN 206 may be an evolved packet core (EPC), or a 5G core (5GC), which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME), an access and mobility management functions (AMF)) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW), a Packet Data Network (PDN) gateway (P-GW), or a user plane function (UPF)). In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc.) for the one or more UEs 204 served by the one or more NE 202 associated with the CN 206.

[0056] The CN 206 may communicate with a packet data network over one or more backhaul links (e.g., via an S1 , N2, N2, or another network interface). The packet data network may include an application server. In some implementations, one or more UEs 204 may communicate with the application server. A UE 204 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the CN 206 via an NE 202. The CN 206 may route traffic (e.g., control information, data, and the like) between the UE 204 and the application server using the established session (e.g., the established PDU session). The PDU session may be an example of a logical connection between the UE 204 and the CN 206 (e.g., one or more network functions of the CN 206).Attorney Docket No. PC934559WO14737546-1

[0057] In the wireless communications system 200, the NEs 202 and the UEs 204 may use resources of the wireless communications system 200 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers)) to perform various operations (e.g., wireless communications). In some implementations, the NEs 202 and the UEs 204 may support different resource structures. For example, the NEs 202 and the UEs 204 may support different frame structures. In some implementations, such as in 4G, the NEs 202 and the UEs 204 may support a single frame structure. In some other implementations, such as in 5G and among other suitable radio access technologies, the NEs 202 and the UEs 204 may support various frame structures (i.e. , multiple frame structures). The NEs 202 and the UEs 204 may support various frame structures based on one or more numerologies.

[0058] One or more numerologies may be supported in the wireless communications system 200, and a numerology may include a subcarrier spacing and a cyclic prefix. A first numerology (e.g., / z=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., / z=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., / z=1) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., / z=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., / z=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., / z=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.

[0059] A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames). Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.

[0060] Additionally or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 200. For instance, the first, second, third, fourth, and fifth numerologies (i.e., / z=0, / z=1 , / z=2, / z=3,Attorney Docket No. PC934559WO14737546-1= ) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols). In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing), a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extended cyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., [i =0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots.

[0061] In the wireless communications system 200, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 200 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz - 7.125 GHz), FR2 (24.25 GHz - 52.6 GHz), FR3 (7.125 GHz - 24.25 GHz), FR4 (52.6 GHz - 114.25 GHz), FR4a or FR4-1 (52.6 GHz - 71 GHz), and FR5 (114.25 GHz - 300 GHz). In some implementations, the NEs 202 and the UEs 204 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the NEs 202 and the UEs 204, among other equipment or devices for cellular communications traffic (e.g., control information, data). In some implementations, FR2 may be used by the NEs 202 and the UEs 204, among other equipment or devices for short-range, high data rate capabilities.

[0062] FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies). For example, FR1 may be associated with a first numerology (e.g., / z=0), which includes 15 kHz subcarrier spacing; a second numerology (e.g., / z=1), which includes 30 kHz subcarrier spacing; and a third numerology (e.g., / z=2), which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies). For example, FR2 may be associated with a third numerology (e.g., / z=2), which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., / z=3), which include s 120 kHz subcarrier spacing.

[0063] As noted above, 3GPP TS 23.482 provides a procedure for the registration of the FL members for AIMLE services at an ML repository.Attorney Docket No. PC934559WO14737546-1

[0064] Figure 3 illustrates a procedure where the registration update of a candidate FL member 300 occurs via the ML repository 302. [NB. Whilst Figure 3 shows the request being sent by the FL member, in the case that the FL member is a VAL server the request will be sent on behalf of the VAL server by the AIMLE server.] The following steps are shown:

[0065] 1. The candidate FL member 300 (VAL server via AIMLE server or AIMLE Server) sends an FL member registration update request to the ML repository acting as AIML service registry in order to update the registration of the FL member. The update may be a complete representation of the FL member, or it may be limited to modification of the one or more information elements as listed in Table 8.4.4.4-1 of 3GPP TS 23.482.

[0066] 2. The ML repository 302 validates the received update request and generates the identity and other security related information for the FL member.

[0067] 3. The ML repository 302 sends the generated information in the FL member registration update response message to the candidate FL member 300.

[0068] The procedure for the AIMLE client to update its registration to the ML repository as FL member is introduced in clause 8.7.2.3 of 3GPP TS 23.482.

[0069] Figure 4 illustrates the procedure where the deregistration of a candidate registered FL member 400 occurs via the ML repository 402, serving as AIML service registry. The procedure may be used to deregister a plurality of candidate registered FL members identified in a single request. The following steps are shown:

[0070] 1 . The candidate registered FL member 400 (e.g., VAL server via AIMLE server or AIMLE server) sends an FL member deregistration request to the ML repository 402 for registering to the ML repository which acts as the AIML service registry. The deregistration request may result from a determination, for example by the FL member, that the FL member cannot act as an FL member for some reason, e.g., due to load, energy limitation, or certain analytics; thus the candidate registered FL member (e.g., VAL server via AIMLE server or AIMLE server) triggers the deregistration.

[0071] 2. The ML repository 402 validates the received request and generates the identity and other security related information for the registered FL member listed in the deregistration request (this may be repeated if the request identifies multiple candidate FL members).

[0072] 3. The ML repository 402 sends the generated information in the FL member deregistration response message to the candidate registered FL member. If there areAttorney Docket No. PC934559WO14737546-1multiple candidate FL members, response messages may be sent separately, e.g., via the AIMLE server.

[0073] The procedure forthe AIMLE client to deregister to the ML repository as FL member is introduced in clause 8.7.2.4 of 3GPP TS 23.482.

[0074] The information flows associated with registration (for reference), update and deregistration will now be considered.

[0075] Table 8.4.4.2-1 below describes information elements for the FL member registration request from the candidate FL member (VAL server, AIMLE server) to the ML repository / registry.

[0076] Table 8.4.4.3-1 below describes information elements for the FL member registration response to the candidate FL member (VAL server, AIMLE server) from the ML repository / registry.

[0077] Table 8.4.4.4-1 below describes information elements for the FL member registration update request from the candidate FL member (VAL server, AIMLE server) to the ML repository / registry.

[0078] Table 8.4.4.5-1 below describes information elements for the FL member registration update response to the candidate FL member (VAL server, AIMLE server) from the ML repository / registry.

[0079] Table 8.4.4.6-1 below describes information elements for the FL member deregistration request from the candidate FL member (VAL server, AIMLE server) to the ML repository / registry.

[0080] Table 8.4.4.7-1 below describes information elements for the FL member deregistration response to the candidate registered FL member (VAL server, AIMLE server) from the ML repository / registry.

[0081] Table 9.3.1.1-1 below illustrates the API for FL member registration. This API enables the VAL server (candidate FL member) to communicate with the ML repository for registering as candidate FL member.

[0082] Whilst the above discussion may be considered to relate to the “Stage 2” standard, the following discussion concerns “Stage 3” for registration, complete update or modification, querying and de- registration of an FL member from a depository. The numbering used for the various clauses is intended to align with that used in 3GPP TS 23.482.Stage 3Attorney Docket No. PC934559WO14737546-15.3.X MLR_FLMember Service5.3.X.1 Service DescriptionFederated Learning Member Service allows the ML repository with the capability to enable registering, handling, and deleting FL members consisting of AIMLE clients based on MLR_FLMember service operations as defined in 3GPP TS 23.482.5.3.X.2 Service Operations5.3.X.2.1 IntroductionThe service operation defined for MLR_FLMember API for is shown in the Table 5.3.X.2.1- 1.5.3.X.2.2 MLR_FLMember_Register5.3.X.2.2.1 GeneralThis service operation is used by a service consumer e.g., AIMLE Server to request the ML repository to register an Individual FL Member.The following procedure is supported by the "MLR_FLMember_Register" service operation:MLR FL Member Register.5.3.X.2.2.2MLR FL Member RegisterFigure 5 depicts a scenario where a service consumer 500, e.g., AIMLE Server sends a request to the ML repository 502 to register an Individual FL Member. (See clause 8.4 of 3GPP TS 23.482). Figure 5 illustrates the following steps:1 . In order to register an Individual FL Member, the service consumer e.g., AIMLE Server shall send an HTTP POST request to the ML Repository targeting the URI of the corresponding resource (i.e., "FL Member Configurations"), with the request body including the FIMbr data structure.2a. Upon success that the request to register the Individual FL Member is successfully received and processed, the ML Repository shall respond with an HTTP "201 Created" status code with the request body including the FIMbr data structure.2b. On failure, the appropriate HTTP status code indicating the error shall be returned and appropriate additional error information should be returned in the HTTP POST response body, as specified in clause 6.2.X.7.5.3.X.2.3 MLR_FLMember_Query5.3.X.2.3.1 GeneralAttorney Docket No. PC934559WO14737546-1This service operation is used by a service consumer e.g., AIMLE Server to request the ML repository to query an Individual FL Member.The following procedure is supported by the "MLR_FLMember_Query" service operation: MLR FL Member Query.5.3.X.2.3.2MLR FL Member QueryFigure 6 depicts a scenario where a service consumer 600, e.g., AIMLE Server sends a request to the ML repository 602 to query an Individual FL Member. (See clause 8.17 of 3GPP°TS°23.482). Figure 6 illustrates the following steps:1. In order to query an Individual Registered FL Member, the service consumer e.g., AIMLE Server, shall send an HTTP GET request to the ML repository targeting the URI of the corresponding resource (i.e., "Query Registered FL Member").2a. Upon success that the request to query the Registered FL Member is successfully received and processed, the ML repository shall respond with an HTTP "200 OK" status code with the request body including the FIMbr data structure.2b. On failure, the appropriate HTTP status code indicating the error shall be returned and appropriate additional error information should be returned in the HTTP GET response body, as specified in clause 6.2.X.7.5.3.X.2.4 MLR_FLMember_Update_Register5.3.X.2.4.1 GeneralThis service operation is used by a service consumer e.g., AIMLE Server to request the ML repository to update registration of an Individual Registered FL Member.The following procedure is supported by the "MLR_FLMember_Update_Register" service operation:MLR FL Member Update Register.5.3.X.2.4.2MLR FL Member Update RegisterFigure 7 depicts a scenario where a service consumer 700, e.g., AIMLE Server, sends a request to the ML repository 702 to update registration of an Individual Registered FL Member. (See clause 8.4 of 3GPP TS 23.482). Figure 7 illustrates the following steps:1. In order to update an Individual Registered FL Member, the service consumer e.g., AILME Server shall send an HTTP PUT / PATCH request to the ML repository targeting the URI of the corresponding resource (i.e., "Individual Registered FL Member Configuration"), with the request body including either: the updated representation of the resource within the FIMbr data structure, in case the HTTP PUT method is used; orAttorney Docket No. PC934559WO14737546-1the requested modifications to the resource within the FIMbrPatch data structure, in case the HTTP PATCH method is used.NOTE: An alternative service consumer (i.e. other than the one that requested the creation of the targeted resource) can initiate this request.2a. Upon success that the request to update the Individual Registered FL Member is successfully received and processed, the ML Repository shall respond with an HTTP "200 OK" status code with the request body including the FIMbr data structure. an HTTP "200 OK" status code with the response body containing a representation of the updated "Individual Registered FL Member Configuration" resource within the FIMbr data structure; or an HTTP "204 No Content" status code.2b. On failure, the appropriate HTTP status code indicating the error shall be returned and appropriate additional error information should be returned in the HTTP PUT / PATCH response body, as specified in clause 6.2.X.7.5.3.X.2.5 MLR_FLMember_Deregister5.3.X.2.5.1 GeneralThis service operation is used by a service consumer e.g., AIMLE Server to request the repository to deregister an Individual Registered FL Member.The following procedure is supported by the "MLR_FLMember_Deregister" service operation:MLR FL Member Deregister.5.3.X.2.5.2MLR FL Member DeregisterFigure 8 depicts a scenario where a service consumer 800, e.g., AIMLE Server, sends a request to the ML repository 802 to deregister an Individual Registered FL Member, (see also clause XYZ of 3GPP TS 23.482). Figure 8 illustrates the following steps:1. In order to delete an Individual Registered FL Member, the service consumer e.g., AIMLE Server shall send an HTTP DELETE request to the ML repository targeting the URI of the corresponding resource (i.e., "Individual Registered FL Member Configuration"). 2a. Upon success that the request to delete the Individual Registered FL Member is successfully received and processed, the ML repository shall respond with an HTTP "204 No Content" status code.2b. On failure, the appropriate HTTP status code indicating the error shall be returned and appropriate additional error information should be returned in the HTTP DELETE response body, as specified in clause 6.2.X.7.Attorney Docket No. PC934559WO14737546-16.2.X MLR_FLMember API6.2.X.1 IntroductionThe Federated Learning Member Service shall use the MLR_FLMember API.The API URI of the MLR_FLMember API shall be:{apiRoot} / <apiName> / <apiVersion>The request URIs used in HTTP requests shall have the Resource URI structure defined in clause 5.2.4 of 3GPP TS 29.122, i.e.:{apiRoot} / <apiName> / <apiVersion> / <apiSpecificSuffixes> with the following components:The {apiRoot} shall be set as described in clause 5.2.4 of 3GPP TS 29.122.The <apiName> shall be "mlr-fl".The <apiVersion> shall be "v1".The <apiSpecificSuffixes> shall be set as described in clause 5.2.4 of 3GPP TS 29.122.NOTE: When 3GPP TS 29.122 is referenced for the common protocol and interface aspects for API definition in the clauses under clause 5, the service producer (i.e. <NF or Entity, e.g. UAE Server>) takes the role of the SCEF and the service consumer (i.e. AMLE server) takes the role of the SCS / AS.6.2.X.2 Usage of HTTP and common API related aspectsThe provisions of clause 5.2 of 3GPP TS 29.122 shall apply for the MLR_FLMember API.6.2.X.3 Resources6.2.X.3.1 OverviewThis clause describes the structure for the Resource URIs and the resources and methods used for the service.Figure 9 depicts the resource URIs structure for the MLR_FLMember API.Table 6.2.X.3.1-1 below provides an overview of the resources and applicable HTTP methods.6.2.X.3.2 Resource: FL Member Configurations6.2.X.3.2.1 DescriptionThis resource represents the FL Member Configurations resource managed by the ML repository.Attorney Docket No. PC934559WO14737546-16.2.X.3.2.2 Resource DefinitionResource URI: {apiRoot} / mlr-fl / <apiVersion> / configurationsThis resource shall support the resource URI variables defined in Table 6.2.X.3.2.2-1 below.6.2.X.3.2.3Resource Standard Methods6.2.X.3.2.3.1 POSTThe HTTP POST method enables the AIMLE service consumer to register an FL Member at the ML repository.This method shall support the URI query parameters specified in Table 6.2.X.3.2.3.1-1 below.This method shall support the request data structures specified in Table 6.2.X.3.2.3.1-2 below and the response data structures and response codes specified in Table6.2.X.3.2.3.1-3 below.6.2.X.3.2.4Resource Custom OperationsThere are no resource custom operations defined for this resource in this release of the specification.6.2.X.3.3 Resource: Individual FL Member Configuration6.2.X.3.3.1 DescriptionThis resource represents the individual FL Member Configuration resource managed by the ML repository.6.2.X.3.3.2 Resource DefinitionResource URI: {apiRoot} / mlr-fl / <apiVersion> / configurations / {configurationld}This resource shall support the resource URI variables defined in Table 6.2.X.3.3.2-1 below.6.2.X.3.3.3Resource Standard Methods6.2.X.3.3.3.1 GETThe HTTP GET method enables the service consumer e.g., the AIMLE Server to query an Individual Registered FL Member at the ML repository.This method shall support the URI query parameters specified in Table 6.2.X.3.3.3.1-1 below.This method shall support the request data structures specified in Table 6.2.X.3.3.3.1-2 below and the response data structures and response codes specified in Table6.2.X.3.3.3.1-3 below.6.2.X.3.3.3.2 PUTThe HTTP PUT method enables the service consumer, e.g., the AIMLE Server, to update an Individual Registered FL Member at the ML repository.Attorney Docket No. PC934559WO14737546-1This method shall support the URI query parameters specified in Table 6.2.X.3.3.3.2-1 below.This method shall support the request data structures specified in Table 6.2.X.3.3.3.2-2 below and the response data structures and response codes specified in Table6.2.X.3.3.3.2-3 below.6.2.X.3.3.3.3 PATCHThe HTTP PATCH method enables the service consumer, e.g., the AIMLE Server, to modify an Individual Registered FL Member at the ML repository.This method shall support the URI query parameters specified in Table 6.2.X.3.3.3.3-1 below.This method shall support the request data structures specified in Table 6.2.X.3.3.3.3-2 below and the response data structures and response codes specified in Table6.2.X.3.3.3.3-3 below.6.2.X.3.3.3.4 DELETEThe HTTP DELETE method enables the service consumer, e.g., AIMLE Server, to deregister an Individual Registered FL Member at the ML repository.This method shall support the URI query parameters specified in Table 6.2.X.3.3.3.4-1 below.This method shall support the request data structures specified in Table 6.2.X.3.3.3.4-2 below and the response data structures and response codes specified in Table6.2.X.3.3.3.4-3 below.6.2.X.3.3.4Resource Custom OperationsThere are no resource custom operations defined for this resource in this release of the specification.6.2.X.4 Custom Operations without associated resources6.2.X.4.1 OverviewThere is no custom operation defined for the MLR_FLMember API in this release of the specification.6.2.X.5 Notifications6.2.X.5.1 GeneralThere is no notification defined for the MLR_FLMember API in this release of the specification.Attorney Docket No. PC934559WO14737546-16.2.X.6 Data Model6.2.X.6.1 GeneralThis clause specifies the application data model supported by the API.Table 6.2.X.6.1-1 below specifies the data types defined for the MLR_FLMember API.6.2.X.6.2 Structured data types6.2.X.6.2.1 IntroductionThis clause defines the structures to be used in resource representations.6.2.X.6.2.2Type: FIMbrTable 6.2.X.6.2.2-1 below defines type FIMbr6.2.X.6.2.3Type: FIMbrPatchTable 6.2.X.6.2.3-1 below defines type FIMbrPatch6.2.X.6.2.4Type: FICapabilityTypeTable 6.2.X.6.2.4-1 defines type FICapabilityType6.2.X.6.2.5Type: FIMbrAvailScheduleTable 6.2.X.6.2.5-1 below defines type FIMbrAvailSchedule6.2.X.6.3 Simple data types and enumerations6.2.X.6.3.1 IntroductionThis clause defines simple data types and enumerations that can be referenced from data structures defined in the previous clauses.6.2.X.6.3.2Simple data typesThe simple data types defined in Table 6.2.X.6.3.2-1 below shall be supported.6.2.X.6.3.3Enumeration: SuppAimIRoleTypeThe enumeration SuppAimIRoleType represents information regarding the supported AIML role identity of the FL member. It shall comply with the provisions defined in Table6.2.X.6.3.3-1 below.6.2.X.6.3.4Enumeration: MLAppTypeThe enumeration MLAppType represents information regarding the supported ML application related to the capability of the FL member. It shall comply with the provisions defined in Table 6.2.X.6.3.4-1 below.6.2.X.6.3.5Enumeration: AvailabilityTypeThe enumeration AvailabilityType represents information regarding the availability of the FL member. It shall comply with the provisions defined in Table 6.2. X.6.3.5-1.Attorney Docket No. PC934559WO14737546-16.2.X.6.4 Data types describing alternative data types or combinations of data types There are no data types describing alternative data types or combination of data types for MLR_FLMember API in this release of the specification.6.2.X.6.5 Binary data6.2.X.6.5.1 Binary Data TypesThe binary data types defined for the MLR_FLMember API are listed in Table 6.2.X.6.5.1-1 below.6.2.X.7 Error Handling6.2.X.7.1 GeneralFor the MLR_FLMember API, HTTP error responses shall be supported as specified in clause 5.2.6 of 3GPP TS 29.122. Protocol errors and application errors specified in clause 5.2.6 of 3GPP TS 29.122 shall be supported for the HTTP status codes specified in Table 5.2.6-1 of 3GPP TS 29.122.In addition, the requirements in the following clauses are applicable for the MLR_FLMember API.6.2.X.7.2 Protocol ErrorsNo specific procedures for the MLR_FLMember API are specified.6.2.X.7.3 Application ErrorsThe application errors defined for the MLR_FLMember API are listed in Table 6.2.X.7.3-1 below.6.2.X.8 Feature negotiationThe optional features in Table 6.2.X.8-1 below are defined for the MLR_FLMember API. They shall be negotiated using the extensibility mechanism defined in clause 5.2.7 of 3GPP TS 29.122.6.2.X.9 SecurityThe provisions of clause 6 of 3GPP TS 29.122 shall apply for the MLR_FLMember API.

[0083] Figure 10 illustrates an example of a network equipment (NE) 1000 in accordance with aspects of the present disclosure. The NE 1000 may include a processor 1002, a memory 1004, a controller 1006, and a transceiver 1008. The processor 1002, the memory 1004, the controller 1006, or the transceiver 1008, or various combinations thereofAttorney Docket No. PC934559WO14737546-1or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. These components may be coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces.

[0084] The processor 1002, the memory 1004, the controller 1006, or the transceiver 1008, or various combinations or components thereof may be implemented in hardware (e.g., circuitry). The hardware may include a processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other programmable logic device, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure.

[0085] The processor 1002 may include an intelligent hardware device (e.g., a general- purpose processor, a DSP, a CPU, an ASIC, an FPGA, or any combination thereof). In some implementations, the processor 1002 may be configured to operate the memory 1004. In some other implementations, the memory 1004 may be integrated into the processor 1002. The processor 1002 may be configured to execute computer-readable instructions stored in the memory 1004 to cause the NE 1000 to perform various functions of the present disclosure.

[0086] The memory 1004 may include volatile or non-volatile memory. The memory 1004 may store computer-readable, computer-execuTable code including instructions when executed by the processor 1002 cause the NE 1000 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such the memory 1004 or another type of memory. Computer-readable media includes both non- transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer.

[0087] In some implementations, the processor 1002 and the memory 1004 coupled with the processor 1002 may be configured to cause the NE 1000 to perform one or more of the functions described herein (e.g., executing, by the processor 1002, instructions stored in the memory 1004). For example, the processor 1002 may support wireless communication at the NE 1000 in accordance with examples as disclosed herein. The NE 1000 may be configured to support a means for sending to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource ofAttorney Docket No. PC934559WO14737546-1the FL member, or delete the resource of the FL member, and receiving an acknowledgement message from the second network entity.

[0088] The controller 1006 may manage input and output signals for the NE 1000. The controller 1006 may also manage peripherals not integrated into the NE 1000. In some implementations, the controller 1006 may utilize an operating system such as iOS®, ANDROID®, WINDOWS®, or other operating systems. In some implementations, the controller 1006 may be implemented as part of the processor 1002.

[0089] In some implementations, the NE 1000 may include at least one transceiver 1008. In some other implementations, the NE 1000 may have more than one transceiver 1008. The transceiver 1008 may represent a wireless transceiver. The transceiver 1008 may include one or more receiver chains 1010, one or more transmitter chains 1012, or a combination thereof.

[0090] A receiver chain 1010 may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receiver chain 1010 may include one or more antennas for receive the signal over the air or wireless medium. The receiver chain 1010 may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain 1010 may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receiver chain 1010 may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

[0091] A transmitter chain 1012 may be configured to generate and transmit signals (e.g., control information, data, packets). The transmitter chain 1012 may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The transmitter chain 1012 may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmitter chain 1012 may also include one or more antennas for transmitting the amplified signal into the air or wireless medium.

[0092] Figure 11 illustrates a flowchart of a method in accordance with aspects of the present disclosure. The operations of the method may be implemented by a first NE asAttorney Docket No. PC934559WO14737546-1described herein. In some implementations, the first NE may execute a set of instructions to control the function elements of the second NE to perform the described functions.

[0093] At 1102, the method may include sending to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member. The operations of 1102 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1102 may be performed by a NE as described with reference to Figure 10.

[0094] At 1104, the method may include receiving an acknowledgement message from the second network entity. The operations of 1104 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1104 may be performed by a NE as described with reference to Figure 10.

[0095] Figure 12 illustrates a flowchart of a method in accordance with aspects of the present disclosure. The operations of the method may be implemented by a second NE as described herein. In some implementations, the second NE may execute a set of instructions to control the function elements of the second NE to perform the described functions.

[0096] At 1202, the method may include receiving from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member. The operations of 1202 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1202 may be performed by a NE as described with reference to Figure 10.

[0097] At 1204, the method may include validating and processing the request message. The operations of 1204 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1204 may be performed by a NE as described with reference to Figure 10.

[0098] At 1206, the method may include sending an acknowledgement message to the first network entity. The operations of 1206 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1206 may be performed by a NE as described with reference to Figure 10.Attorney Docket No. PC934559WO14737546-1

[0099] It should be noted that the method described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0100] It should be noted that the method described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0101] The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.Attorney Docket No. PC934559WO14737546-1Table 8.4.4.2-1: FL member registration requestTable 8.4.4.3-1: FL member registration responseAttorney Docket No. PC934559WO14737546-1Table 8.4.4.4-1: FL member registration update requestTable 8.4.4.5-1: FL member registration update responseTable 8.4.4.6-1 : FL member deregistration requestAttorney Docket No. PC934559WO14737546-1Table 8.4.4.7-1: FL member deregistration responseTable 9.3.1.1-1: MLR_FLMemberRegister APITable 5.3.X.2.1-1 : Operations for MLR_FLMember APIAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.1-1 : Resources and methods overviewTable 6.2.X.3.2.2-1 : Resource URI variables for this resourceTable 6.2.X.3.2.3.1-1 : URI query parameters supported by the POST method on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.2.3.1-2: Data structures supported by the POST Request Body on this resourceTable 6.2.X.3.2.3.1-3: Data structures supported by the POST Response Body on this resourceTable 6.2.X.3.2.3.1-4: Headers supported by the 201 Response Code on this resourceTable 6.2.X.3.3.2-1 : Resource URI variables for this resourceTable 6.2.X.3.3.3.1 -1 : URI query parameters supported by the GET method on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.1-2: Data structures supported by the GET Request Body on this resourceTable 6.2.X.3.3.3.1-3: Data structures supported by the GET Response Body on this resourceTable 6.2.X.3.3.3.1-4: Headers supported by the 307 Response Code on this resourceTable 6.2.X.3.3.3.1-5: Headers supported by the 308 Response Code on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.2-1 : URI query parameters supported by the PUT method on this resourceTable 6.2.X.3.3.3.2-2: Data structures supported by the PUT Request Body on this resourceTable 6.2.X.3.3.3.2-3: Data structures supported by the PUT Response Body on this resourceTable 6.2.X.3.3.3.2-4: Headers supported by the 307 Response Code on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.2-5: Headers supported by the 308 Response Code on this resourceTable 6.2.X.3.3.3.3-1 : URI query parameters supported by the PATCH method on this resourceTable 6.2.X.3.3.3.3-2: Data structures supported by the PATCH Request Body on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.3-3: Data structures supported by the PATCH Response Body on this resourceTable 6.2.X.3.3.3.3-4: Headers supported by the 307 Response Code on this resourceTable 6.2.X.3.3.3.3-5: Headers supported by the 308 Response Code on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.4-1 : URI query parameters supported by the DELETE method on this resourceTable 6.2.X.3.3.3.4-2: Data structures supported by the DELETE Request Body on this resourceTable 6.2.X.3.3.3.4-3: Data structures supported by the DELETE Response Body on this resourceTable 6.2.X.3.3.3.4-4: Headers supported by the 307 Response Code on this resourceAttorney Docket No. PC934559WO14737546-1Table 6.2.X.3.3.3.4-5: Headers supported by the 308 Response Code on this resourceTable 6.2.X.6.1-1 : MLR_FLMember API specific Data TypesTable 6.2.X.6.1-2: MLR_FLMember API re-used Data TypesAttorney Docket No. PC934559WO14737546-1Table 6.2.X.6.2.2-1 : Definition of type FIMbrAttorney Docket No. PC934559WO14737546-1Attorney Docket No. PC934559WO14737546-1Table 6.2.X.6.2.3-1: Definition of type FIMbrPatchTable 6.2.X.6.2.4-1: Definition of type FICapabilityTypeTable 6.2.X.6.2.5-1: Definition of type FIMbrAvailScheduleAttorney Docket No. PC934559WO14737546-1Table 6.2.X.6.3.2-1 : Simple data typesTable 6.2.X.6.3.3-1 : Enumeration SuppMITaskTypeTable 6.2.X.6.3.4-1 : Enumeration MLAppTypeTable 6.2.X.6.3.-1 : Enumeration AvailabilityTypeTable 6.2.X.6.5.1-1 : Binary Data TypesAttorney Docket No. PC934559WO14737546-1Table 6.2.X.7.3-1 : Application errorsTable 6.2.X.8-1 : Supported FeaturesAttorney Docket No. PC934559WO14737546-1

Claims

42What is claimed is:1 . A first network equipment for wireless communication comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the first network equipment to: send to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member; and receive an acknowledgement message from the second network entity.

2. The first network equipment of claim 1 , wherein the request message is a request to delete the resource of the FL member due to at least one of: a load of the FL member, an energy of the FL member; and a mobility of the FL member to new Vertical Application Layer, VAL, service areas.

3. The first network equipment of claim 1 or 2, wherein the request message identifies at least one of a role of the FL member and capabilities of the FL member.

4. The first network equipment of any preceding claim, wherein the first network equipment is one of a Vertical Application Layer, VAL, server or an Artificial Intelligence Machine Learning Enablement, AIMLE, server.

5. The first network equipment of claim 4, wherein the second network entity is a repository for one or more Artificial Intelligence Machine Learning, AIML, services.

6. The first network equipment of any preceding claim, wherein the FL member is the first network equipment, or the first network equipment is acting on behalf of the FL member.Attorney Docket No. PC934559WO14737546-1437. The first network entity of any preceding claim, wherein the request message includes identities of a plurality of FL members.

8. The first network entity of any preceding claim, wherein the acknowledgement message indicates a result of the request.

9. A second network equipment for wireless communication comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the second network equipment to: receive from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, create a resource for the FL member, replace the resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member; validate and process the request message; and send an acknowledgement message to the first network entity.

10. The second network equipment of claim 9, wherein the request message is a request to delete the resource of the FL member due to at least one of: a load of the FL member, an energy of the FL member; and a mobility of the FL member to new Vertical Application Layer, VAL, service areas.

11. The second network equipment of claim 9 or 10, wherein the request message identifies at least one of a role of the FL member and capabilities of the FL member.

12. The second network equipment of any of claims 9 to 11 , wherein the second network equipment is a repository for one or more Artificial Intelligence Machine Learning, AIML, services.Attorney Docket No. PC934559WO14737546-14413. The second network equipment of claim 12, wherein the first network entity is one of a Vertical Application Layer, VAL, server or an Artificial Intelligence Machine Learning Enablement, AIMLE, server.

14. The second network equipment of any of claims 9 to 13, wherein the FL member is the first network equipment, or the first network equipment is acting on behalf of the FL member.

15. The second network entity of any of claims 9 to 14, wherein the request message includes identities of a plurality of FL members.

16. The second network entity of any of claims 9 to 15, wherein the acknowledgement message indicates a result of the request.

17. A method performed by a first network equipment for wireless communication comprising: sending to a second network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member, modify one or more information elements of the resource of the FL member, or delete the resource of the FL member; and receiving an acknowledgement message from the second network entity.

18. The method of claim 17, wherein the request message is a request to delete the resource of the FL member due to at least one of: a load of the FL member, an energy of the FL member; and a mobility of the FL member to new Vertical Application Layer, VAL, service areas.

19. A method performed by a second network equipment for wireless communication comprising: receiving from a first network entity a request message, including an identity of at least one Federated Learning, FL, member, to, replace a resource of the FL member,Attorney Docket No. PC934559WO14737546-1modify one or more information elements of the resource of the FL member, or delete the resource of the FL member; validating and processing the request message; and sending an acknowledgement message to the first network entity.

20. The method of claim 19, wherein the request message is a request to delete the resource of the FL member due to at least one of: a load of the FL member, an energy of the FL member; and a mobility of the FL member to new Vertical Application Layer, VAL, service areasAttorney Docket No. PC934559WO14737546-1

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