WO2024230239A1

WO2024230239A1 - Method, device and computer program product for wireless communication

Info

Publication number: WO2024230239A1
Application number: PCT/CN2024/072153
Authority: WO
Inventors: Yuang FENG; Menghan WANG; Jinguo Zhu
Original assignee: ZTE Corp
Current assignee: ZTE Corp
Priority date: 2024-01-12
Filing date: 2024-01-12
Publication date: 2024-11-14
Anticipated expiration: 2026-07-12

Abstract

A wireless communication method is disclosed. The method comprises receiving, by a repository node from a network node, a request for information of one or more data analytics nodes for an analytics identifier; and transmitting, by the repository node to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Description

METHOD, DEVICE AND COMPUTER PROGRAM PRODUCT FOR WIRELESS COMMUNICATION

TECHNICAL FIELD

This document is directed generally to wireless communications, and in particular to 5^th generation (5G) communications or 6^th generation (6G) communications.

BACKGROUND

In 5G communication, the Network Data Analytics Function (NWDAF) is widely used. The NWDAF is a 5G Core (5GC) Network Function (NF) located on the control plane and performs statistical data analysis and machine learning-related tasks in 5G System (5GS) . The NWDAF is designed to streamline the way core network data is produced and consumed, and to generate insights and take actions to enhance the end-user experience. However, the application of NWDAF is still a topic to be discussed.

SUMMARY

This document relates to methods, systems, and computer program products for a wireless communication.

One aspect of the present disclosure relates to a wireless communication method. In an embodiment, the wireless communication method includes: receiving, by a repository node from a network node, a request for information of one or more data analytics nodes for an analytics identifier; and transmitting, by the repository node to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Various embodiments may preferably implement the following features:

Preferably, the interoperability information comprises at least one of:

information of one or more network functions or vendors fully interoperable to one or more models for the analytics identifier;

information of one or more network functions or vendors partially interoperable to one or more models for the analytics identifier; or

information of one or more network functions or vendors not interoperable to one or more models for the analytics identifier.

Preferably, the request for the information of one or more data analytics nodes for the analytics identifier comprises at least one of:

a network function identifier associated with the network node;

a vendor identifier of the network node; or

the analytics identifier.

Preferably, the analytics identifier indicates a load analytics performing a load analysis of a network function.

Preferably, the wireless communication method further comprises: transmitting, by the repository node to the network node, information of one or more data analytics nodes having an identical level of interoperability for the network node.

Preferably, the wireless communication method further comprises: transmitting the information of the one or more data analytics nodes, information of one or more data analytics nodes providing a first level of interoperability for the network node has a first priority, information of one or more data analytics nodes providing a second level of interoperability for the network node has a second priority, the first level of interoperability is higher than the second level of interoperability, and the first priority is higher than the second priority.

Preferably, the wireless communication method further comprises: transmitting the information of the one or more data analytics nodes, one or more data analytics nodes having Machine Learning models fully interoperable for the network node takes precedence over one or more data analytics nodes having Machine Learning models partially interoperable for the network node, and one or more data analytics nodes having Machine Learning models partially interoperable for the network node takes precedence over one or more data analytics nodes having Machine Learning models not interoperable for the network node.

Preferably, the wireless communication method further comprises: transmitting, by the repository node to the network node, information of data analytics nodes having different levels of interoperability for the network node.

Preferably, the wireless communication method further comprises: receiving, by the repository node from a data analytics node, a request for updating the interoperability information.

Preferably, the wireless communication method further comprises: transmitting, by a repository node to the target data analytics node, a response responding to a request for updating the interoperability information.

Preferably, the wireless communication method further comprises: receiving, by the repository node from a data analytics node, a network function profile comprising information of different levels of interoperability for the data analytics node.

Another aspect of the present disclosure relates to a wireless communication method. In an embodiment, the wireless communication method includes: transmitting, by a network node to a repository node, a request for information of one or more data analytics nodes for an analytics identifier; and receiving, by the network node from the repository node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Various embodiments may preferably implement the following features:

Preferably, the interoperability information comprises at least one of:

a network function identifier associated with the network node;

a vendor identifier of the network node; or

the analytics identifier.

Preferably, the wireless communication method further comprises: receiving, by the network node from the repository node, information of one or more data analytics nodes having an identical level of interoperability for the network node.

Preferably, the wireless communication method further comprises: receiving, by the network node from the repository node, information of data analytics nodes having different levels of interoperability for the network node.

Preferably, the wireless communication method further comprises: transmitting, by the network node to a target data analytics node based on the information of one or more data analytics nodes, a request for information of one or more models in the target data analytics node.

Preferably, the request for the information of the one or more models in the target data analytics node comprises one or more predictions within the analytics identifier.

Preferably, the network node refrains from sending a request for information of one or more models to one or more data analytics nodes having models for the analytics identifier that are not interoperable for the network node.

Preferably, the wireless communication method further comprises: receiving, by the network node from a target data analytics node, a response responding a request for information of one or more models in the target data analytics node.

Preferably, the response responding to the request for the information of one or more models from the data analytics node comprises at least one of:

one or more model file addresses of the one or more models generating one or more requested predictions; or

one or more rejection indications rejecting one or more requested predictions.

Another aspect of the present disclosure relates to a wireless communication method. In an embodiment, the wireless communication method includes: receiving, by a data analytics node from a network node, a request for a service associated with an analytics identifier, wherein the request for the service is transmitted by the network node based on interoperability information for the analytics identifier, and wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Various embodiments may preferably implement the following features:

Preferably, the interoperability information comprises at least one of:

Preferably, the wireless communication method further comprises: receiving, by the data analytics node from the network node, a request for information of one or more models in the data analytics node.

Preferably, the request for the information of models from the data analytics node comprises one or more predictions within the analytics identifier.

Preferably, the wireless communication method further comprises: transmitting, by the data analytics node to the network node, a response responding a request for information of one or more models in the data analytics node.

Preferably, the response responding the request for information of one or more models in the data analytics node comprises at least one of:

one or more indications rejecting one or more requested predictions.

Preferably, the wireless communication method further comprises: transmitting, by the data analytics node to the repository node, a request for updating the interoperability information.

Preferably, the wireless communication method further comprises: receiving, by the data analytics node from the repository node, a response responding to a request for updating the interoperability information.

Preferably, the wireless communication method further comprises: transmitting, by the data analytics node to the repository node, a network function profile comprising information of different levels of interoperability for the data analytics node.

Another aspect of the present disclosure relates to a repository node. In an embodiment, the repository node includes a communication unit and a processor. The processor is configured to: receive, via the communication unit from the network node, a request for information of one or more data analytics nodes for an analytics identifier; and transmit, via the communication unit to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Another aspect of the present disclosure relates to a network node. In an embodiment, the network node includes a communication unit and a processor. The processor is configured to: transmit, via the communication unit to a repository node, a request for information of one or more data analytics nodes for an analytics identifier; and receive, via the communication unit from the repository node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Another aspect of the present disclosure relates to a data analytics node. In an embodiment, the data analytics node includes a communication unit and a processor. The processor is configured to: receive, via the communication unit from a network node, a request for a service associated with an analytics identifier, wherein the request for the service is transmitted by the network node based on interoperability information for the analytics identifier, and wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

The present disclosure relates to a computer program product comprising a computer-readable program medium code stored thereupon, the code, when executed by a processor, causing the processor to implement a wireless communication method recited in any one of foregoing methods.

The exemplary embodiments disclosed herein are directed to providing features that will become readily apparent by reference to the following description when taken in conjunction with the accompanying drawings. In accordance with various embodiments, exemplary systems, methods, devices and computer program products are disclosed herein. It is understood, however, that these embodiments are presented by way of example and not limitation, and it will be apparent to those of ordinary skill in the art who read the present disclosure that various modifications to the disclosed embodiments can be made while remaining within the scope of the present disclosure.

Thus, the present disclosure is not limited to the exemplary embodiments and applications described and illustrated herein. Additionally, the specific order and/or hierarchy of steps in the methods disclosed herein are merely exemplary approaches. Based upon design preferences, the specific order or hierarchy of steps of the disclosed methods or processes can be re-arranged while remaining within the scope of the present disclosure. Thus, those of ordinary skill in the art will understand that the methods and techniques disclosed herein present various steps or acts in a sample order, and the present disclosure is not limited to the specific order or hierarchy presented unless expressly stated otherwise.

The above and other aspects and their implementations are described in greater detail in the drawings, the descriptions, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic diagram of a network according to an embodiment of the present disclosure.

FIG. 2 shows a schematic diagram of a network according to an embodiment of the present disclosure.

FIG. 3 shows a schematic diagram of a network according to an embodiment of the present disclosure.

FIG. 4 shows a schematic diagram of a network according to an embodiment of the present disclosure.

FIG. 5 shows a schematic diagram of a network according to an embodiment of the present disclosure.

FIG. 6 shows a schematic diagram of interoperable information according to an embodiment of the present disclosure.

FIG. 7 shows a schematic diagram of a procedure according to an embodiment of the present disclosure.

FIG. 8 shows a schematic diagram of a procedure according to an embodiment of the present disclosure.

FIG. 9 shows a schematic diagram of a procedure according to an embodiment of the present disclosure.

FIG. 10 shows an example of a schematic diagram of a wireless communication terminal according to an embodiment of the present disclosure.

FIG. 11 shows an example of a schematic diagram of a wireless communication node according to an embodiment of the present disclosure.

FIGS. 12 to 14 show flowcharts of wireless communication methods according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In the paragraphs below, some aspects of the present disclosure are provided, but the present disclosure is not limited thereto. Besides, different aspects described below can be combined unless expressly stated otherwise.

In some embodiments, in the 5G Core Network (5GC) , the interoperability indicator, which indicates whether a Network Data Analytics Function (NWDAF) is willing to share the models (to facilitate the description, machine learning (ML) models will be taken as examples in the present disclosure, but the present disclosure is not limited thereto) therein, may designed as ‘per analytics’ . One analytics (e.g., analytics ID, analytics function) may contain more than one model, and each is responsible for predicting some of the outputs in the analytic. In some cases, the model producer may only want to share some of the models in one analytic. In such cases, the interoperability indicator indicating whether a NWDAF is willing to share the trained machine learning models may not be sufficient.

Besides, in some cases, there may not exist a method to control or manage the model sharing to the third party in 5GC, such as the NWDAF A shares one model with the NWDAF B but the NWDAF B shares the model with the NWDAF C without the permission of the NWDAF A, which is the original producer of the model. Some embodiments of the present disclosure provide a procedure for controlling or managing the model sharing.

FIG. 1 shows the architecture of the 5G system. In this architecture, there are the following functions:

1) A User Equipment (UE) .

2) RAN (Radio Access Network) . The RAN manages the radio resource and delivers the user data received over N3 to the UE and delivers the user data from the UE over the N3 interface. The RAN performs mapping between Dedicated Radio Bearers (DRBs) and the Quality of Service (QoS) flows in the Packet Data Unit (PDU) session.

3) AMF (Access and Mobility Management function) . This function includes the following functionalities: Registration management, Connection management, Reachability management and Mobility Management. This function also performs access authentication and access authorization. The AMF is the NAS security termination and relays the SM NAS between UE and SMF, etc.

4) SMF (Session Management Function) . This function includes the following functionalities: session establishment, modification and release, UE Internet Protocol (IP) address allocation &management (including optional authorization functions) , selection and control of UP function, downlink data notification, etc. The SMF controls the UPF via the N4 association. The SMF provides the Packet Detection Rule (PDR) to the UPF to instruct how to detect user data traffic, Forwarding Action Rule (FAR) , QoS Enforcement Rule QER and Usage Reporting Rule (URR) to instruct the UPF how to perform the user data traffic forwarding, QoS handling and usage reporting for the user data traffic detected by using the PDR.

5) UPF (User plane function) . This function includes the following functionalities: serving as an anchor point for intra-/inter-radio access technology (RAT) mobility, packet routing &forwarding, traffic usage reporting, QoS handling for the user plane, downlink packet buffering and/or downlink data notification triggering, etc. GTP-U tunnel is used over the N3 interface between the RAN and the UPF. The GTP-U tunnel is per PDU session. For the downlink traffic, the UPF binds the downlink traffic to QoS flows within the GTP-U tunnel of the PDU session by using the FARs received from SMF. For the uplink traffic, the RAN transfers the user plane traffic to QoS flows identified by the UE.

6) PCF (Policy Control Function) . The PCF provides QoS policy rules to control plane functions to enforce the rules. The PCF (s) transform (s) the AF requests into PCC rules that apply to PDU Sessions.

7) UDM (Unified Data Management) . The UDM performs the generation of the 3GPP Authentication and Key Agreement (AKA) Authentication Credential, access authorization based on subscription data, UE's Serving Network Function (NF) Registration Management (e.g., storing serving the AMF for the UE and/or storing serving SMF for UE's PDU Session) and Subscription management, etc. The UDM accesses the Unified Data Repository (UDR) to retrieve the UE subscription data and store the UE context in the UDR. The UDM and the UDR may be deployed together.

The NWDAF is a 5GC NF located on the control plane and performs statistical data analysis (i.e., the distribution information of the datasets) and machine learning-related tasks in 5G System (5GS) . The NWDAF may interact with at least one of the following different entities for different purposes:

- Data collection based on subscription to events provided by AMF, SMF, UPF, PCF, UDM, NSACF, Analytics Function (AF) (directly or via Network Exposure Function (NEF) ) and Operations, Administration and Maintenance (OAM) ;

- [Optionally] Analytics and Data collection using the Data Collection Coordination Function (DCCF) ;

- Retrieval of information from data repositories (e.g., UDR via UDM for subscriber-related information or via NEF (Packet Flow Description Function (PFDF) ) for the Packet Flow Description (PFD) information) ;

- Data collection of the location information from the Location Services (LCS) system;

- [Optionally] Storage and retrieval of information from the Analytics Data Repository Function (ADRF) ;

- [Optionally] Analytics and Data collection from the Messaging Framework Adaptor Function (MFAF) ;

- Retrieval of information about NFs (e.g., from the Network function Repository Function (NRF) for NF-related information) ;

- On-demand provision of analytics to consumers;

- Provision of bulked data related to Analytics ID (s) ;

- Provision of Accuracy information about Analytics ID (s) ; and/or

- Provision of ML model accuracy information or ML model accuracy degradation about an ML Model.

A single instance or multiple instances of the NWDAF may be deployed in a Public Land Mobile Network (PLMN) . An NWDAF may contain the following logical functions:

- Analytics logical function (AnLF) : a logical function in the NWDAF, which performs inference, derives analytics information (i.e., derives statistics and/or predictions based on the Analytics Consumer request) and exposes analytics service (i.e., the Nnwdaf_AnalyticsSubscription or the Nnwdaf_AnalyticsInfo) .

- Model Training logical function (MTLF) : a logical function in the NWDAF, which trains Machine Learning (ML) models and exposes new training services (e.g., providing trained ML models) .

A NWDAF can contain an MTLF, an AnLF or both logical functions.

The Data Collection Coordination and Function (DCCF) is also an NF on the control plane of 5GC. The DCCF coordinates the collection and distribution of data requested by NF consumers. It prevents data sources from having to handle multiple subscriptions for the same data and sends multiple notifications containing the same information due to uncoordinated requests from data consumers.

The DCCF is applicable to:

- NWDAFs that request data from a Data Source (e.g., for use in computing analytics) ;

- NF consumers that request analytics from an NWDAF Data Source;

- NF consumers that request data from an ADRF Data Source; and/or

- ADRFs that receive data from an NF Data Source.

FIG. 2 and FIG. 4 illustrate two data collection architectures by the NWDAF to enable data analysis and model training according to some embodiments of the present disclosure. FIG. 3 and FIG. 5 show two possible network data analytics exposure architectures for any NF consumer who subscribes or requests the analytics according to some embodiments of the present disclosure.

In some embodiments, the ML Model interoperability indicator (also referred to as interoperability indicator or model interoperability indicator in the present disclosure) of an NWDAF containing an MTLF comprises a list of NWDAF providers (vendors) that are allowed to retrieve ML models from this NWDAF. The interoperability indicator also indicates that the NWDAF containing the MTLF supports the interoperable ML models to be requested by the NWDAFs from the vendors in the list of the NWDAF providers.

In some embodiments, an NWDAF may have different interoperability indicators for different analytics IDs (e.g., analytics functions) .

The model interoperability indicator per analytics ID is one of the NF profile parameters of the NWDAF which may be considered by the NF for the NWDAF selection through the NRF.

In the paragraphs below, some aspects of the present disclosure are provided, but the present disclosure is not limited thereto. Besides, embodiments in different aspects described below can be combined unless expressly stated otherwise.

Aspect 1:

In some embodiments, there are different categories of interoperability per analytics ID, such as ML models are fully interoperable, ML models are partially interoperable, and ML models not interoperable.

FIG. 6 illustrates an example of different interoperability (e.g., (interoperability indicators) according to an embodiment of the present disclosure. For example, the NWDAF A has an ability to generate several models to perform NF load related analysis and predictions. In some embodiments, the NWDAF A gives NFs with vendor ID = 1 and vendor ID = 2 the authority to fully access the models related to this analytics. The NWDAF A gives NF (s) with vendor ID = 3 the authority to access part of the ML models related to this analytics. NFs with vendor ID = 4 and vendor ID = 5 have no power to access the ML models related to this analytics.

The paragraphs below will discuss some procedures that may involve different interoperability for an analytics.

Aspect 2:

FIG. 7 illustrates a schematic diagram of an NWDAF registration procedure according to an embodiment of the present disclosure. In some embodiments, the procedure may include at least one of the following operations.

1. The NWDAF sends a message (e.g., the Nnrf_NFManagement_NFRegister Request message) to the NRF to inform the NRF of the NF profile of the NWDAF. In some embodiments, The NWDAF sends the message (e.g., the Nnrf_NFManagement_NFRegister Request message) to the NRF when the NF service consumer becomes operative for the first time.

In some embodiments, for the NF profile that the NWDAF reports to the NRF during registration, the NF profile may include the ML model interoperability information per analytics ID. In some embodiments, the ML model interoperability information for an analytics ID may include at least one of: information of one or more vendors and/or NFs (e.g., one or more vendor IDs and/or NF IDs) fully interoperable to the ML model (s) in this NWDAF (e.g., the one or more vendors and/or NFs can fully access all ML model (s) in this NWDAF) , information of one or more vendors and/or NFs (e.g., one or more vendor IDs and/or NF IDs) partially interoperable to the ML model (s) in this NWDAF (e.g., the one or more vendors and/or NFs can access partial of the ML model (s) in this NWDAF) and/or information of one or more vendors and/or NFs (e.g., one or more vendor IDs and/or NF IDs) not interoperable to the ML model (s) in this NWDAF (e.g., the one or more vendors and/or NFs cannot access any of the ML model (s) in this NWDAF) .

2. The NRF stores the NF profile of the NWDAF. The NRF may mark the NWDAF available.

3. The NRF acknowledges that the NWDAF Registration is accepted via a response message (e.g., the Nnrf_NFManagement_NFRegister response) .

Aspect 3:

FIG. 8 illustrates a schematic diagram of a procedure for an NWDAF updating the NF profile according to an embodiment of the present disclosure. In some embodiments, the procedure may include at least one of the following operations.

1. The NWDAF sends a message (e.g., the Nnrf_NFManagement_NFUpdate Request message) (e.g., including the updated NF profile of the NWDAF) to the NRF to inform the NRF of the updated NF profile of the NWDAF (e.g., with the updated capacity) . In some embodiments, for example, the NWDAF sends the Nnrf_NFManagement_NFUpdate Request message to the NRF to inform the NRF of the updated NF profile of the NWDAF when triggered after a scaling operation.

In some embodiments, the NWDAF may update the information of one or more vendors and/or NFs (e.g., one or more vendor IDs and/or NF IDs) in one or more categories of interoperability for one or more analytics IDs. For example, the NWDAF may update at least one of: information of one or more vendors and/or NFs fully interoperable to the ML model (s) for certain analytics ID (s) in this NWDAF, information of one or more vendors and/or NFs partially interoperable to the ML model (s) for certain analytics ID (s) in this NWDAF, and/or information of one or more vendors and/or NFs not interoperable to the ML model (s) for certain analytics ID(s) in this NWDAF.

In some embodiments, the NWDAF can downgrade any vendor (e.g., from partially interoperable to not interoperable for one or more analytics IDs) by updating the interoperability indicator. In some embodiments, the NWDAF can downgrade any vendor if the NWDAF considers that the vendor shares the model file address of the model in the NWDAF to a third party. In some embodiments, the NWDAF can upgrade any vendor, if the vendor is trustworthy.

2. The NRF updates the NF profile of the NWDAF.

3. The NRF acknowledges that the NWDAF Update is accepted via a response message (e.g., the Nnrf_NFManagement_NFUpdate response) .

Aspect 4:

In some embodiments, after the source NWDAF (s) (the model provider (s) ) registered to the NRF with the model interoperability indicator (s) (e.g., the interoperability information per analytics ID) , the NWDAF service consumer could discover the NWDAF through the NRF to obtain ML model (s) .

FIG. 9 illustrates a schematic diagram of a procedure according to an embodiment of the present disclosure. In some embodiments, the procedure may include at least one of the following operations.

1. The NWDAF service consumer (e.g., NF and/or OAM) intends to obtain one or more ML model (s) for a particular analytics ID. In some embodiments, the NWDAF service consumer then sends a discovery request (e.g., comprising at least one of the vendor ID of the NWDAF service consumer, the NF ID of the NWDAF service consumer and/or the analytics ID) to the NRF.

2. The NRF transmits a response responding the discovery request. In some embodiments, the NRF uses the vendor ID (and/or the NF ID) and analytics ID to search the available NWDAFs that are willing to provide the NWDAF service consumer with the ML model (s) related to the requested analytics ID in the Step 1. In some embodiments, the NRF search the available NWDAFs that are willing to provide the NWDAF service consumer with the ML model (s) related to the requested analytics ID based on the interoperability information received from the NWDAFs. There are some options for the NRF in this step.

Option A. The NRF returns information of NWDAFs (e.g., a list of NWDAF IDs) that belong to one category (e.g., one of the fully interoperable, partially interoperable, not interoperable) . In some embodiments, the list of NWDAFs that are fully interoperable takes precedence over partially interoperable. In some embodiments, the list of partially interoperable NWDAFs takes precedence over not interoperable. For example, if the NRF determines that NWDAF 1 and NWDAF 2 can provide models for the requested analytics ID that are fully interoperable to the NWDAF service consumer, and NWDAF 3 and NWDAF 4 can provide models for the requested analytics ID that are partially interoperable to the NWDAF service consumer, the NRF determines that NWDAF 1 and NWDAF 2 have a higher priority than which of the NWDAF 3 and NWDAF 4 in providing the available NWDAFs to the NWDAF service consumer. The NRF transmits the IDs of NWDAF 1 and NWDAF 2 to the NWDAF service consumer.

Option B. The NRF returns information of NWDAFs (e.g., lists of NWDAF IDs) that belong to all different categories (e.g., the fully interoperable, partially interoperable, not interoperable) . For example, the NRF transmits the IDs of NWDAF 1, NWDAF 2, NWDAF 3, and NWDAF 4 described above to the NWDAF service consumer.

3. After receiving the information (e.g., interoperability indicator) which contains one or more lists of NWDAF IDs with vendor IDs that fall into three categories from the NRF (e.g., via option A or option B) the NWDAF service consumer may use the NWDAF ID to request (e.g., transmits a request) information of the ML model from a target NWDAF.

In some embodiments, in the request (e.g., the MLModelProvision_request or the MLModelProvision_subscribe) , the NWDAF service consumer may specify one or more prediction (s) within the same analytics ID (e.g., the prediction of the UE Location and/or the prediction of UE’s geographical distribution in the analytics of the ‘UE mobility’ ) that the NWDAF service consumer want to obtain.

For the option B, the NWDAF service consumer may refrain from sending a request to the NWDAF vendor which is not interoperable for the analytics ID it sent to the NRF in Step 1.

4. The target NWDAF response and/or notify the NWDAF consumer according to the interoperability information (e.g., the interoperability indicators) reported to the NRF. In some embodiments, if the service consumer is in the fully interoperable list, it may respond with model file addresses. In some embodiments, the service consumer can generate all the requested predictions. If the service consumer is in the partially interoperable list, it can reject one or more requests of predictions.

5 and 6. The target NWDAF can update its interoperability information (e.g., the interoperability indicator) . In some embodiments, the update is substantially identical to the procedure described in Aspect 3 above.

In some embodiments of the present disclosure, the interoperability indicator per analytic ID may include different levels/categories, such as ML models fully interoperable, ML models partially interoperable and ML models not interoperable.

In some embodiments of the present disclosure, the NWDAF may perform at least one of:

registering and/or updating its NF profile to the NRF containing the interoperability indicator per analytic ID; or

performing model sharing (e.g., sharing ML model file address to the NWDAF service consumer) according to the interoperability indicator it reported to the NRF.

In some embodiments of the present disclosure, the NWDAF service consumer (e.g., NF, OAM) may perform at least one of:

sending a request with its Vendor ID, NF ID and/or analytic ID to the NRF to find a list of NWDAF IDs that are available;

receiving the list of NWDAFs that the ML models for the analytic ID therein are fully interoperable, partially interoperable, and/or not interoperable to the NWDAF service consumer;

sending a request to the target NWDAF according to the list;

receiving the ML model address from the target NWDAF; or

receiving a rejection by the target NWDAF for one or more ML models if the interoperability indicator is partially interoperable for the requested analytic ID.

FIG. 10 relates to a diagram of a wireless communication terminal 30 according to an embodiment of the present disclosure. The wireless communication terminal 30 may be a tag, a mobile phone, a laptop, a tablet computer, an electronic book or a portable computer system and is not limited herein. The wireless communication terminal 30 may be used to implement the UE described in this disclosure. The wireless communication terminal 30 may include a processor 300 such as a microprocessor or Application Specific Integrated Circuit (ASIC) , a storage unit 310 and a communication unit 320. The storage unit 310 may be any data storage device that stores a program code 312, which is accessed and executed by the processor 300. Embodiments of the storage unit 310 include but are not limited to a subscriber identity module (SIM) , read- only memory (ROM) , flash memory, random-access memory (RAM) , hard-disk, and optical data storage device. The communication unit 320 may a transceiver and is used to transmit and receive signals (e.g., messages or packets) according to processing results of the processor 300. In an embodiment, the communication unit 320 transmits and receives the signals via at least one antenna 322 or via wiring.

In an embodiment, the storage unit 310 and the program code 312 may be omitted and the processor 300 may include a storage unit with stored program code.

The processor 300 may implement any one of the steps in exemplified embodiments on the wireless communication terminal 30, e.g., by executing the program code 312.

The communication unit 320 may be a transceiver. The communication unit 320 may as an alternative or in addition be combining a transmitting unit and a receiving unit configured to transmit and to receive, respectively, signals to and from a wireless communication node.

In some embodiments, the wireless communication terminal 30 may be used to perform the operations of the UE described in this disclosure. In some embodiments, the processor 300 and the communication unit 320 collaboratively perform the operations described in this disclosure. For example, the processor 300 performs operations and transmit or receive signals, message, and/or information through the communication unit 320.

FIG. 11 relates to a diagram of a wireless communication node 40 according to an embodiment of the present disclosure. The wireless communication node 40 may be a satellite, a base station (BS) , a gNB, a network entity, a Domain Name System (DNS) server, a Mobility Management Entity (MME) , Serving Gateway (S-GW) , Packet Data Network (PDN) Gateway (P-GW) , a radio access network (RAN) , a next generation RAN (NG-RAN) , a data network, a core network, a communication node in the core network, or a Radio Network Controller (RNC) , and is not limited herein. In addition, the wireless communication node 40 may include (perform) at least one network function such as an access and mobility management function (AMF) , a session management function (SMF) , a user plane function (UPF) , a policy control function (PCF) , an application function (AF) , etc. The wireless communication node 40 may be used to implement the NRF, the OAM, the NF, or the NWDAF described in this disclosure. The wireless communication node 40 may include a processor 400 such as a microprocessor or ASIC, a storage unit 410 and a communication unit 420. The storage unit 410 may be any data storage device that stores a program code 412, which is accessed and executed by the processor 400. Examples of the storage unit 410 include but are not limited to a SIM, ROM, flash memory, RAM, hard-disk, and optical data storage device. The communication unit 420 may be a transceiver and is used to transmit and receive signals (e.g., messages or packets) according to processing results of the processor 400. In an embodiment, the communication unit 420 transmits and receives the signals via at least one antenna 422 or via wiring.

In an embodiment, the storage unit 410 and the program code 412 may be omitted. The processor 400 may include a storage unit with stored program code.

The processor 400 may implement any steps described in exemplified embodiments on the wireless communication node 40, e.g., via executing the program code 412.

The communication unit 420 may be a transceiver. The communication unit 420 may as an alternative or in addition be combining a transmitting unit and a receiving unit configured to transmit and to receive, respectively, signals, messages, or information to and from a wireless communication node or a wireless communication terminal.

In some embodiments, the wireless communication node 40 may be used to perform the operations of the NRF, the NWDAF service consumer or the NWDAF described in this disclosure. In some embodiments, the processor 400 and the communication unit 420 collaboratively perform the operations described in this disclosure. For example, the processor 400 performs operations and transmit or receive signals through the communication unit 420.

A wireless communication method is provided according to an embodiment of the present disclosure. In an embodiment, the wireless communication method may be performed by using a wireless communication node (e.g., an NRF) . In an embodiment, the wireless communication node may be implemented by using the wireless communication node 40 described in this disclosure, but is not limited thereto.

Referring to FIG. 12, in an embodiment, the wireless communication method includes receiving, by a repository node from a network node, a request for information of one or more data analytics nodes for an analytics identifier; and transmitting, by the repository node to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

Details in this regard can be ascertained with reference to the paragraphs above, and will not be repeated herein.

A wireless communication method is provided according to an embodiment of the present disclosure. In an embodiment, the wireless communication method may be performed by using a wireless communication node (e.g., an NWDAF service consumer) . In an embodiment, the wireless communication node may be implemented by using the wireless communication node 40 described in this disclosure, but is not limited thereto.

Referring to FIG. 13, in an embodiment, the wireless communication method includes transmitting, by a network node to a repository node, a request for information of one or more data analytics nodes for an analytics identifier; and receiving, by the network node from the repository node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

A wireless communication method is provided according to an embodiment of the present disclosure. In an embodiment, the wireless communication method may be performed by using a wireless communication node (e.g., an NWDAF) . In an embodiment, the wireless communication node may be implemented by using the wireless communication node 40 described in this disclosure, but is not limited thereto.

Referring to FIG. 14, in an embodiment, the wireless communication method includes receiving, by a data analytics node from a network node, a request for a service associated with an analytics identifier, wherein the request for the service is transmitted by the network node based on interoperability information for the analytics identifier, and wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.

In some embodiments, the repository node used in the present disclosure may indicate the NRF described above.

In some embodiments, the network node used in the present disclosure may indicate the NWDAF service consumer described above.

In some embodiments, the data analytics node used in the present disclosure may indicate the NWDAF described above.

While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not by way of limitation. Likewise, the various diagrams may depict an example architectural or configuration, which are provided to enable persons of ordinary skill in the art to understand exemplary features and functions of the present disclosure. Such persons would understand, however, that the present disclosure is not restricted to the illustrated example architectures or configurations, but can be implemented using a variety of alternative architectures and configurations. Additionally, as would be understood by persons of ordinary skill in the art, one or more features of one embodiment can be combined with one or more features of another embodiment described herein. Thus, the breadth and scope of the present disclosure should not be limited by any one of the above-described exemplary embodiments.

It is understood that, in the present disclosure, the term “and/or” or symbol “/” may include any and all combinations of one or more of the associated listed items. For example, A and/or B and/or C includes any and all combinations of one or more of A, B, and C, including A, B, C, A and B, A and C, B and C, and a combination of A and B and C. Likewise, A/B/C includes any and all combinations of one or more of A, B, and C, including A, B, C, A and B, A and C, B and C, and a combination of A and B and C.

It is also understood that any reference to an element herein using a designation such as "first, " "second, " and so forth does not generally limit the quantity or order of those elements. Rather, these designations can be used herein as a convenient means of distinguishing between two or more elements or instances of an element. Thus, a reference to first and second elements does not mean that only two elements can be employed, or that the first element must precede the second element in some manner.

Additionally, a person having ordinary skill in the art would understand that information and signals can be represented using any one of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits and symbols, for example, which may be referenced in the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

A skilled person would further appreciate that any one of the various illustrative logical blocks, units, processors, means, circuits, methods and functions described in connection with the aspects disclosed herein can be implemented by electronic hardware (e.g., a digital implementation, an analog implementation, or a combination of the two) , firmware, various forms of program or design code incorporating instructions (which can be referred to herein, for convenience, as "software" or a "software unit” ) , or any combination of these techniques.

To clearly illustrate this interchangeability of hardware, firmware and software, various illustrative components, blocks, units, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware or software, or a combination of these techniques, depends upon the particular application and design constraints imposed on the overall system. Skilled artisans can implement the described functionality in various ways for each particular application, but such implementation decisions do not cause a departure from the scope of the present disclosure. In accordance with various embodiments, a processor, device, component, circuit, structure, machine, unit, etc. can be configured to perform one or more of the functions described herein. The term “configured to” or “configured for” as used herein with respect to a specified operation or function refers to a processor, device, component, circuit, structure, machine, unit, etc. that is physically constructed, programmed and/or arranged to perform the specified operation or function.

Furthermore, a skilled person would understand that various illustrative logical blocks, units, devices, components and circuits described herein can be implemented within or performed by an integrated circuit (IC) that can include a general-purpose processor, a digital signal processor (DSP) , an application specific integrated circuit (ASIC) , a field programmable gate array (FPGA) or other programmable logic device, or any combination thereof. The logical blocks, units, and circuits can further include antennas and/or transceivers to communicate with various components within the network or within the device. A general-purpose processor can be a microprocessor, but in the alternative, the processor can be any conventional processor, controller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other suitable configuration to perform the functions described herein. If implemented in software, the functions can be stored as one or more instructions or code on a computer-readable medium. Thus, the steps of a method or algorithm disclosed herein can be implemented as software stored on a computer-readable medium.

Computer-readable media includes both computer storage media and communication media including any medium that can be enabled to transfer a computer program or code from one place to another. A storage media can be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer.

In this document, the term "unit" as used herein, refers to software, firmware, hardware, and any combination of these elements for performing the associated functions described herein. Additionally, for purpose of discussion, the various units are described as discrete units; however, as would be apparent to one of ordinary skill in the art, two or more units may be combined to form a single unit that performs the associated functions according to embodiments of the present disclosure.

Additionally, memory or other storage, as well as communication components, may be employed in embodiments of the present disclosure. It will be appreciated that, for clarity purposes, the above description has described embodiments of the present disclosure with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units, processing logic elements or domains may be used without detracting from the present disclosure. For example, functionality illustrated to be performed by separate processing logic elements, or controllers, may be performed by the same processing logic element, or controller. Hence, references to specific functional units are only references to a suitable means for providing the described functionality, rather than indicative of a strict logical or physical structure or organization.

Various modifications to the implementations described in this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other implementations without departing from the scope of the claims. Thus, the disclosure is not intended to be limited to the implementations shown herein, but is to be accorded the widest scope consistent with the novel features and principles disclosed herein, as recited in the claims below.

Claims

A wireless communication method comprising:

receiving, by a repository node from a network node, a request for information of one or more data analytics nodes for an analytics identifier; and

transmitting, by the repository node to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The wireless communication method of claim 1, wherein the interoperability information comprises at least one of:

information of one or more network functions or vendors fully interoperable to one or more models for the analytics identifier;

information of one or more network functions or vendors partially interoperable to one or more models for the analytics identifier; or

information of one or more network functions or vendors not interoperable to one or more models for the analytics identifier.
The wireless communication method of claim 1 or 2, wherein the request for the information of one or more data analytics nodes for the analytics identifier comprises at least one of:

a network function identifier associated with the network node;

a vendor identifier of the network node; or

the analytics identifier.
The wireless communication method of any of claims 1 to 3, wherein the analytics identifier indicates a load analytics performing a load analysis of a network function.
The wireless communication method of any of claims 1 to 4 further comprising:

transmitting, by the repository node to the network node, information of one or more data analytics nodes having an identical level of interoperability for the network node.
The wireless communication method of claim 5, wherein in transmitting the information of the one or more data analytics nodes, information of one or more data analytics nodes providing a first level of interoperability for the network node has a first priority, information of one or more data analytics nodes providing a second level of interoperability for the network node has a second priority, the first level of interoperability is higher than the second level of interoperability, and the first priority is higher than the second priority.
The wireless communication method of claim 5 or 6, wherein in transmitting the information of the one or more data analytics nodes, one or more data analytics nodes having Machine Learning models fully interoperable for the network node takes precedence over one or more data analytics nodes having Machine Learning models partially interoperable for the network node, and one or more data analytics nodes having Machine Learning models partially interoperable for the network node takes precedence over one or more data analytics nodes having Machine Learning models not interoperable for the network node.
The wireless communication method of any of claims 1 to 4 further comprising:

transmitting, by the repository node to the network node, information of data analytics nodes having different levels of interoperability for the network node.
The wireless communication method of any of claims 1 to 8 further comprising:

receiving, by the repository node from a data analytics node, a request for updating the interoperability information.
The wireless communication method of any of claims 1 to 9 further comprising:

transmitting, by a repository node to the target data analytics node, a response responding to a request for updating the interoperability information.
The wireless communication method of any of claims 1 to 10 further comprising:

receiving, by the repository node from a data analytics node, a network function profile comprising information of different levels of interoperability for the data analytics node.
A wireless communication method comprising:

transmitting, by a network node to a repository node, a request for information of one or more data analytics nodes for an analytics identifier; and

receiving, by the network node from the repository node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The wireless communication method of claim 12, wherein the interoperability information comprises at least one of:

information of one or more network functions or vendors fully interoperable to one or more models for the analytics identifier;

information of one or more network functions or vendors partially interoperable to one or more models for the analytics identifier; or

information of one or more network functions or vendors not interoperable to one or more models for the analytics identifier.
The wireless communication method of claim 12 or 13, wherein the request for the information of one or more data analytics nodes for the analytics identifier comprises at least one of:

a network function identifier associated with the network node;

a vendor identifier of the network node; or

the analytics identifier.
The wireless communication method of any of claims 12 to 14, wherein the analytics identifier indicates a load analytics performing a load analysis of a network function.
The wireless communication method of any of claims 12 to 15 further comprising:

receiving, by the network node from the repository node, information of one or more data analytics nodes having an identical level of interoperability for the network node.
The wireless communication method of any of claims 12 to 15 further comprising:

receiving, by the network node from the repository node, information of data analytics nodes having different levels of interoperability for the network node.
The wireless communication method of any of claims 12 to 17 further comprising:

transmitting, by the network node to a target data analytics node based on the information of one or more data analytics nodes, a request for information of one or more models in the target data analytics node.
The wireless communication method of claim 18, wherein the request for the information of the one or more models in the target data analytics node comprises:

one or more predictions within the analytics identifier.
The wireless communication method of any of claims 12 to 19, wherein the network node refrains from sending a request for information of one or more models to one or more data analytics nodes having models for the analytics identifier that are not interoperable for the network node.
The wireless communication method of any of claims 12 to 20 further comprising:

receiving, by the network node from a target data analytics node, a response responding a request for information of one or more models in the target data analytics node.
The wireless communication method of claim 21, wherein the response responding to the request for the information of one or more models from the data analytics node comprises at least one of:

one or more model file addresses of the one or more models generating one or more requested predictions; or

one or more rejection indications rejecting one or more requested predictions.
A wireless communication method comprising:

receiving, by a data analytics node from a network node, a request for a service associated with an analytics identifier, wherein the request for the service is transmitted by the network node based on interoperability information for the analytics identifier, and wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The wireless communication method of claim 23, wherein the interoperability information comprises at least one of:

information of one or more network functions or vendors fully interoperable to one or more models for the analytics identifier;

information of one or more network functions or vendors partially interoperable to one or more models for the analytics identifier; or

information of one or more network functions or vendors not interoperable to one or more models for the analytics identifier.
The wireless communication method of claim 23 or 24 further comprising:

receiving, by the data analytics node from the network node, a request for information of one or more models in the data analytics node.
The wireless communication method of claim 25, wherein the request for the information of models from the data analytics node comprises:

one or more predictions within the analytics identifier.
The wireless communication method of any of claims 23 to 26 further comprising:

transmitting, by the data analytics node to the network node, a response responding a request for information of one or more models in the data analytics node.
The wireless communication method of claim 27, wherein the response responding the request for information of one or more models in the data analytics node comprises at least one of:

one or more model file addresses of the one or more models generating one or more requested predictions; or

one or more indications rejecting one or more requested predictions.
The wireless communication method of any of claims 23 to 28 further comprising:

transmitting, by the data analytics node to the repository node, a request for updating the interoperability information.
The wireless communication method of any of claims 23 to 29 further comprising:

receiving, by the data analytics node from the repository node, a response responding to a request for updating the interoperability information.
The wireless communication method of any of claims 23 to 30 further comprising:

transmitting, by the data analytics node to the repository node, a network function profile comprising information of different levels of interoperability for the data analytics node.
A repository node, comprising:

a communication unit; and

a processor configured to:

receive, via the communication unit from the network node, a request for information of one or more data analytics nodes for an analytics identifier; and

transmit, via the communication unit to the network node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The repository node of claim 32, wherein the processor is further configured to perform a wireless communication method of any of claims 2 to 11.
A network node, comprising:

a communication unit; and

a processor configured to:

transmit, via the communication unit to a repository node, a request for information of one or more data analytics nodes for an analytics identifier; and

receive, via the communication unit from the repository node, the information of one or more data analytics nodes based on interoperability information for the analytics identifier, wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The network node of claim 34, wherein the processor is further configured to perform a wireless communication method of any of claims 13 to 22.
A data analytics node, comprising:

a communication unit; and

a processor configured to:

receive, via the communication unit from a network node, a request for a service associated with an analytics identifier, wherein the request for the service is transmitted by the network node based on interoperability information for the analytics identifier, and wherein the interoperability information for the analytics identifier comprises information for different levels of interoperability.
The repository node of claim 36, wherein the processor is further configured to perform a wireless communication method of any of claims 24 to 31.
A computer program product comprising a computer-readable program medium code stored thereupon, the code, when executed by a processor, causing the processor to implement a wireless communication method recited in any of claims 1 to 31.