Supporting network entities generated by analysis in mobile networks

Abstract

The invention relates to a new generation of mobile networks, in particular to the generation of analytic information in a network. To this end, the present disclosure provides a first network entity for generating analysis information, and provides a second network entity and a third network entity for supporting analysis generation, respectively. The first network entity is configured to obtain past and / or current associated information of a region of interest from the second network entity or one or more third network entities. In addition, the first network entity is configured to provide analysis information according to the acquired association information of the region of interest. The past and / or current association information indicates one or more other network entities and / or network attributes that past and / or current map to or serve the region of interest, respectively.

Description

[0001] This application is a divisional application. The original application has the application number 202080090774.1 and the original application date is January 3, 2020. The entire contents of the original application are incorporated herein by reference. Technical Field

[0002] This disclosure relates to next-generation mobile networks, and more specifically to the generation of analytical information within those networks. To this end, this disclosure provides network entities and corresponding methods that support the generation of analytical information. For example, the network entities and methods facilitate the collection of information used for analytical generation. Background Technology

[0003] Figure 1 An example of a possible mobile network architecture is shown, in which embodiments of the present invention can be applied. Figure 1 Specifically, it illustrates a 5G-based mobile network according to the 3GPP TS23.501 specification. Figure 1 The separation between the following planes is shown: management plane (MP), control plane (CP), and user plane (UP). Additionally, the separation between access network (AN), core network (CN), and data network (DN) is also shown.

[0004] Mobile operators can deploy and manage different network slices through MPs. MPs simultaneously configure and manage the resources and entities associated with network slices in both AN and CN. Each network slice is associated with both CP and UP entities, meaning these entities belong to the same network slice. For simplicity, Figure 1 Only one network slice is shown, identified by Single Network Slice Selection Assistance Information (S-NSSAI) #1 and its associated CP and UP entities. The CP entities of the mobile operator network manage user equipment (UE) connectivity from the AN to the DN. Finally, external CPs from external entities (e.g., application functions (AFs)) can also interact with the mobile operator CP entities, while the UP entities are the entities that actually send UE-related data traffic and apply control actions / policies defined by the CP entities.

[0005] The network data analytics function (NWDAF) is a network function (NF) in a 5G system that generates analytics information (e.g., a list of tracking areas (TAs) and / or cell identifiers (IDs)) for specific UEs and / or UE groups and / or “regions of interest”. To generate this analytics information, the NWDAF collects information about 5G System (5GS) entities that have been and / or are currently associated with the UE and / or the “region of interest” indicated in the analytics information request. Examples of such relationships include: the NF serves the UE (e.g., the access and mobility management function (AMF) controls the UE’s connection to the AN); the NF and / or the UE and / or the AF and / or the cell serve or belong to a given region of interest. Summary of the Invention

[0006] In the current 3GPP specifications TS23.288, TS23.501, and TS23.502, NWDAF has a minimal mechanism to identify UE x CP NF associations. If NWDAF requests information about NFs and / or UEs and / or cells, and / or TAs, and / or network slices (e.g., S-NSSAI or network slice instance, NSI) serving the area of ​​interest in the present or past (e.g., one month ago), the current mechanism cannot provide such information.

[0007] According to the inventors' analysis, 5GS already has a mechanism to store information about events that NFs can expose in the unified data repository (UDR). This is defined in section 4.15.3.2.4 of TS23.502, where, according to section 5.2.12.2.1 of TS23.502, the network exposure function (NEF) is used to subscribe to events from NFs and invoke the UDR service to store the events. In this case, as defined in section 5.2.12.1 of TS23.502, the NEF uses the dataset identifier as "open data" to create records in the UDR related to access and mobility information, as well as session management information including the timestamp of the created record (further defined in section 5.2.12.1 of TS23.502).

[0008] However, the current limitations of retrieving historical records from UDR in 5GS are as follows:

[0009] ● There is no mechanism to search the UDR store for each “region of interest”, which would allow NWDAF to identify all UEs and / or NFs in a given “region of interest” with a single search (if information is available) and not have to retrieve / subscribe to information for each UE. This significantly increases the data collection load due to the lack of such a mechanism.

[0010] ● There is no information about which NFs are associated with events stored in the UDR involving UE or Protocol Data Unit (PDU) sessions. This means that when the NWDAF retrieves an event and determines the UE's location, it still needs to search another entity in the network (e.g., Unified Data Management, UDM) to determine which NFs serve the UE. This information is incomplete because the UDM only provides information about the current NFs serving the UE, not historical information. Furthermore, using this mechanism would significantly increase data collection.

[0011] ● There is no mechanism to query the dataset identifier (specifically "open data") based on, for example, timestamp intervals and regions of interest and / or UE identifiers and / or network slice identifiers.

[0012] On the other hand, 5GS has a UDM NF capable of providing services to a given UE. However, the UDM NF has the following limitations:

[0013] ● UDM's event openness does not provide any information about changes to the NFs serving the UE (e.g., session management function (SMF), policy control function (PCF), or AMF).

[0014] ● The UE context service only provides the possibility of searching for UDM based on "UE ID, NF type and access type" (as defined in Section 5.2.3.2.4 of TS23.502).

[0015] Therefore, there is no mechanism in UDM to search the stored information for each “region of interest”, nor is there any mechanism to retain the historical information of 5GS serving the region of interest.

[0016] Section 6.2.2.1 of 3GPP TS23.288 specifies a mechanism for defining the NF services that NWDAF needs to use to determine which NFs serve the UE. However, there is no definition on how NWDAF can determine historical (past) and / or current (current) 5GS entities serving the area of ​​interest.

[0017] The 3GPP TS28 series of specifications defines Operation, Administration and Maintenance (OAM) services for collecting information such as deployment information (current associations between network slice entities), fault information, and performance information. These specifications do not provide any services to collect historical associations between NFs and UEs, nor do they provide network information about each area of ​​interest.

[0018] In view of the above problems and disadvantages, the purpose of this invention is to provide an improved mechanism for data collection to generate analytical information.

[0019] The goal is to provide network entities and methods that can support analytical generation through enhanced data collection.

[0020] Specifically, the goal is to determine past and / or current association information for the region of interest, such as past and / or current 5GS entities serving the region of interest. Therefore, the data collection workload will be minimized.

[0021] A first aspect of this disclosure provides a network entity for analysis-generated mobile networks, the first network entity being configured to: obtain past and / or current association information of a region of interest from a second network entity or one or more third network entities, wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and provide analysis information based on the obtained association information of the region of interest.

[0022] The network entities in the first aspect can acquire correlation information in order to generate analytical information. Specifically, network entities can acquire correlation information with reduced signaling, thereby acquiring correlation information with reduced load. Therefore, network entities support enhanced analytical generation.

[0023] In one implementation of the first aspect, the first network entity is configured to: send a request for and / or subscribe to the association information of the region of interest to a second network entity or one or more third network entities; and, in response to the request and / or according to the subscription, obtain the association information of the region of interest and / or the transaction identifier of the region of interest from the second network entity or from one or more third network entities.

[0024] The first network entity can directly use the association information to generate analytical information from one or more second and / or third network entities. The first network entity can be used to contact different types of second and / or third network entities (e.g., different types of NFs) to obtain association information. Therefore, the first network entity has great flexibility in obtaining the required association information while maintaining low network load.

[0025] In one implementation of the first aspect, the request and / or subscription to the associated information of the region of interest includes at least one of the following: a target region of interest, which is a spatial region associated with the mobile network, from which a first network entity requests past and / or current associated information of the target region of interest; a target type of one or more other network entities and / or network attributes, wherein the target type of the entity and / or attribute describes the type of entity or attribute that should be identified as mapping to or serving the target region of interest; a transaction identifier for the region of interest; an identifier of the first network entity; and a time interval, which is a time window for selecting one or more entities and / or attributes mapped to or serving the target region of interest.

[0026] In one implementation of the first aspect, the region of interest transaction identifier includes at least one of the following: an updated region of interest transaction identifier indicating changes in the associated information of the region of interest; or an unmodified region of interest transaction identifier indicating that the associated information of the region of interest has not changed.

[0027] In one implementation of the first aspect, the target type and / or network attribute of the network entity includes at least one of the following: UE type; cell type; TA type; NF type; network slice type; external entity type; application type; session type; quality of service (QoS) profile type; DN type; public land mobile network (PLMN) type.

[0028] In one implementation of the first aspect, the first network entity is configured to: send multiple requests for and / or subscribe to association information of the region of interest to multiple third network entities; in response to the multiple requests for and / or based on the subscription to the association information of the region of interest, obtain the association information of the region of interest from the multiple third network entities; aggregate the obtained association information; and provide analysis information based on the aggregated association information.

[0029] In one implementation of the first aspect, the first network entity is configured to: send a request for and / or subscribe to association information of the region of interest to the second network entity; in response to the request for association information of the region of interest and / or based on the subscription to the association information of the region of interest, obtain the association information of the region of interest and / or the transaction identifier of the region of interest from the second network entity; and provide analysis information based on the obtained association information.

[0030] For example, because a second network entity can collect association information from a third network entity, a first network entity can also obtain association information from a dedicated network entity (e.g., an NF), which can also be called an intermediate network entity. For the first network entity, this is a very efficient choice to obtain the association information it needs.

[0031] In one implementation of the first aspect, the first network entity is used to: determine one or more other network entities and / or network attributes mapped to or serving the region of interest from the acquired association information of the region of interest; select and / or acquire data from the determined one or more other network entities and / or network attributes; and provide analysis information based on the selected and / or acquired data.

[0032] In one implementation of the first aspect, the first network entity is a control plane entity, specifically including NWDAF.

[0033] A second aspect of this disclosure provides a second network entity for supporting the analysis and generation of a mobile network. The second network entity is configured to: in response to a first request sent to one or more third network entities and / or based on a first subscription by one or more third network entities, obtain past and / or current association information of a region of interest from one or more third network entities; wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or obtain change information from one or more third network entities when the lifecycle of one or more network entities and / or network attributes related to the association information provided by the one or more third network entities changes.

[0034] The second network entity supports analysis generation by collecting and maintaining correlation information. The second network entity can then, for example, provide the first network entity with the correlation information used to generate the analytical information. Specifically, the second network entity supports the collection of data used for analysis generation, including new information that was previously unavailable for analysis generation, which significantly reduces the workload. This significant workload reduction is particularly pronounced when the second network entity acquires changed information rather than complete correlation information.

[0035] In one implementation of the second aspect, the first request and / or first subscription sent includes a target region of interest, which is a spatial region associated with the mobile network, and the second network entity requests past and / or current associated information of the target region of interest from the spatial region.

[0036] In one implementation of the second aspect, the second network entity is used to: aggregate the associated information of the acquired regions of interest.

[0037] The second network entity can provide the aggregated association information to the first network entity. Therefore, the first network entity that generates the analysis information can perform the generation more efficiently and faster based on the pre-processed association information.

[0038] In one implementation of the second aspect, the second network entity is further configured to: request and / or subscribe to obtain association information of regions of interest from the first network entity; and, in response to the second request and / or according to the second subscription, provide the first network entity with the obtained association information of regions of interest and / or the aggregated association information of regions of interest.

[0039] Therefore, the second network entity can provide the first network entity with association information it has collected from one or more other network entities. Thus, the second network entity can act as an intermediary network entity between the first network entity and a third or other network entity.

[0040] In one implementation of the second aspect, the second network entity is used to: acquire or generate a region of interest (ROI) transaction identifier, and provide the acquired ROI association information and / or the aggregated ROI association information and / or ROI transaction identifier to the first network entity.

[0041] In one implementation of the second aspect, the second network entity is further configured to: obtain change information from one or more third network entities, wherein the change information indicates changes in the lifecycle of one or more other network entities and / or network attributes; update association information based on the change information; and provide the updated association information and / or aggregated updated association information to the first network entity.

[0042] In one implementation of the second aspect, the second request and / or second subscription to the associated information of the region of interest includes at least one of the following: a target region of interest; a target type of one or more other network entities and / or network attributes, wherein the target type of the entity and / or attribute describes the type of entity or attribute that should be identified as mapping to or serving the target region of interest; a transaction identifier for the region of interest; an identifier of a first network entity; and a time interval, which is a time window for selecting one or more entities and / or attributes mapped to or serving the target region of interest.

[0043] In one implementation of the second aspect, the second network entity is a control plane entity, specifically including UDM and / or UDR and / or NWDAF.

[0044] A third aspect of this disclosure provides a third network entity for supporting analysis-generated data. The third network entity is configured to: provide past and / or current association information of a region of interest to the first and / or second network entities in response to a request received from a first and / or second network entity, and / or based on a subscription of the first and / or second network entities; wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or provide association information to the first and / or second network entities when one or more target elements associated with the association information change, wherein the one or more target elements are network entities or network attributes.

[0045] The third network entity can support analysis generation by, for example, providing association information to the first network entity. Specifically, the third network entity can support data collection for analysis generation based on information that is not currently available for analysis generation.

[0046] In one implementation of the third aspect, the request received from the first network entity and / or the second network entity and / or the subscription of the first network entity and / or the second network entity includes at least one of the following: a target region of interest, which is a spatial region associated with the mobile network, from which the first network entity requests past and / or current association information of the target region of interest; a target type of one or more other network entities and / or network attributes, wherein the target type of the entity and / or attribute describes the type of entity or attribute that should be identified as mapping to or serving the target region of interest; a region of interest transaction identifier; an identifier of the first network entity; and a time interval, which is a time window used to select one or more entities and / or attributes mapped to or serving the target region of interest.

[0047] In one implementation of the third aspect, the third network entity is the control plane NF, specifically including SMF and / or AMF and / or network slice selection function (NSSF) and / or NEF and / or application function (AF) and / or network repository function (NRF).

[0048] A fourth aspect of this disclosure provides a network entity, which is a first network entity according to the first aspect, a second network entity according to the second aspect, or a third network entity according to the third aspect, wherein the associated information and / or aggregated associated information of the region of interest includes at least one of the following: one or more UE identifiers and / or UE group identifiers mapped to or serving the region of interest; one or more cell identifiers mapped to or serving the region of interest; one or more tracking area identifiers mapped to or serving the region of interest; one or more network slice identifiers mapped to or serving the region of interest; one or more NF identifiers mapped to or serving the region of interest; one or more NF set identifiers mapped to or serving the region of interest; one or more external entity identifiers mapped to or serving the region of interest; one or more application identifiers mapped to or serving the region of interest; one or more session identifiers mapped to or serving the region of interest; one or more QoS profile identifiers mapped to or serving the region of interest; one or more data network identifiers mapped to or serving the region of interest; and one or more PLMN identifiers mapped to or serving the region of interest.

[0049] The fifth aspect of this disclosure provides a method for generating analysis of a first network entity, the method comprising: obtaining past and / or current association information of a region of interest from a second network entity or one or more third network entities, wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and providing analysis information based on the obtained association information.

[0050] The method of the fifth aspect can have an implementation corresponding to the implementation of the first network entity of the first aspect. Therefore, the method of the fifth aspect and its possible implementations achieves the same advantages and effects as the first network entity of the first aspect and its corresponding implementations.

[0051] A sixth aspect of this disclosure provides a method for supporting the analysis and generation of a second network entity, the method comprising: in response to a first request sent to one or more third network entities and / or based on a first subscription of one or more third network entities, obtaining past and / or current association information of a region of interest from one or more third network entities; wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or obtaining change information from one or more third network entities when the lifecycle of one or more network entities and / or network attributes related to the association information provided by one or more third network entities changes.

[0052] The method of the sixth aspect can have an implementation corresponding to the implementation of the second network entity of the second aspect. Therefore, the method of the sixth aspect and its possible implementations achieves the same advantages and effects as the second aspect and its corresponding implementations of the second network entity.

[0053] A seventh aspect of this disclosure provides a method for supporting the analysis and generation of a third network entity, the method comprising: in response to a request received from a first network entity and / or a second network entity, and / or according to a subscription of the first network entity and / or the second network entity, providing past and / or current association information of a region of interest to the first network entity and / or the second network entity; wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or providing association information to the first network entity and / or the second network entity when one or more target elements associated with the association information change, wherein the one or more target elements are network entities or network attributes.

[0054] The method of the seventh aspect can have an implementation method corresponding to the implementation method of the third network entity in the third aspect. Therefore, the method of the seventh aspect and its possible implementations achieves the same advantages and effects as the third aspect and its corresponding implementation method of the third network entity.

[0055] The eighth aspect of this disclosure provides a computer program that includes program code, which, when executed on a computer, performs a method according to any one of the fifth, sixth, or seventh aspects or any implementation thereof.

[0056] The ninth aspect of this disclosure provides a non-transitory storage medium that stores executable program code, which, when executed by a processor, causes the execution of a method according to the fifth, sixth, or seventh aspect or any implementation thereof.

[0057] It should be noted that all devices, elements, units, and modules described in this application can be implemented by software or hardware elements or any combination thereof. All steps performed by the various entities described in this application and the functions to be performed by the various entities are intended to indicate that the respective entities are suitable for or used to perform the respective steps and functions. Even in the description of the following specific embodiments, the specific functions or steps performed by external entities are not reflected in the detailed description of the specific elements of the entity performing the specific steps or functions; however, those skilled in the art will understand that these methods and functions can be implemented by corresponding hardware or software elements or any combination thereof.

[0058] definition

[0059] The following provides general definitions for some of the terms used in this document.

[0060] Region of Interest: For example, a region of interest defines a spatial and / or locational region using any of the following terms:

[0061] ● Access network cell (e.g., identified by cell ID).

[0062] ● Access network TA level (e.g., a list of TA identifiers (TAIs) or a range of TAIs).

[0063] ● Uncertain shapes in geodetic surveying (such as polygons, circles, etc.).

[0064] ● Municipal address (e.g., street, district).

[0065] ●Data center location.

[0066] ● Network slice location (e.g., city A and city B, etc., in network slice S-NSSAI).

[0067] ● Carrier network location (e.g., Carrier A in Country X, Carrier A in Country Y).

[0068] Network entities and / or network attributes (also known as 5GS entities and 5GS attributes): These are entities or attributes (hardware, software, concepts) that are part of the mobile network system, i.e., hardware and / or software and / or concepts that are part of the mobile operator network and / or mobile network architecture. Examples of the types of network entities and network attributes are as follows:

[0069] ●UEs that can be controlled by the operator's network.

[0070] ● Access network cells, such as NR and / or eNB.

[0071] ●TA, a concept used to define communities that are classified into the same group.

[0072] ● Network slices uniquely define network slices deployed by the operator. Examples of how network slices are identified include network slice selection assistance information (NSSAI) and / or S-NSSAI and / or NSI.

[0073] ●NF stands for Functionality in a network, which defines the functional behavior and interface and / or reference point. Examples of NFs include: UDM, AMF, UDR, and AF.

[0074] ● A network function set is a group of NFs with the same NF type. These NFs can be interchanged to support the same services in a network slice.

[0075] ● External AF: Defines an AF that the mobile operator does not trust. For example, a third-party AF is an external AF.

[0076] ●Application: Defines certain specific types of traffic, which can be defined by an application ID (and can be mapped to specific application traffic detection rules).

[0077] ● Session: This is the association between the UE and the DN, used to transmit data traffic with the UE, thereby achieving service connectivity.

[0078] ●QoS Profile: Defines the quality of service attributes for UE communication.

[0079] ●DN: This is a network outside the mobile operator's network, where UE traffic is sent to and / or sent from the DN.

[0080] ●PLMN, which includes the unique identifier of a mobile operator that provides communication services in a mobile communication network.

[0081] Network entities or network attributes serving a region of interest: The term "service" defines a relationship between a network entity and / or network attribute and a region of interest (e.g., a 5GS entity mapped to a region of interest). For example, if a network entity or network attribute belongs to the following types:

[0082] ●UE: The term "serving" refers to a UE located in the region of interest.

[0083] ● Cellular: The term "serves" refers to a cell that belongs to the region of interest.

[0084] ●TA: The term "serving" refers to the TA that belongs to the region of interest.

[0085] ● Network slice: The term “serves” refers to a network slice (e.g., S-NSSAI, NSI, NSSAI) that is available in the region of interest (i.e., that the UE can use).

[0086] ●NF: The term "Serving" refers to an NF related to UE activities (e.g., mobility, session establishment, data transmission) and / or CP activities (e.g., storing information, providing analytics, managing subscription information, processing information disclosure, supporting discovery NFs) within the Area of ​​Interest. For example, the AMF controls UE mobility, the SMF controls session management, the PCF controls policies, the AF influences traffic, the BSF controls the mapping from UE to PCF, and the UPF transmits data traffic to and / or from the UE, etc.

[0087] ●NF set: The term "serves" refers to the NF set located in the region of interest.

[0088] ● External AF: The term “serving” refers to an AF that is related to the UE in the region of interest (e.g., an AF that communicates with the UE via a non-IP data transmission model, or an external AF that affects UE traffic).

[0089] ●Application: The term “serves” refers to an application used in a mobile network within an area of ​​interest.

[0090] ● Session: The term “serving” refers to one or more sessions located in the region of interest. 5GS entity session types can be further typified based on their PDU session type (e.g., IPv4, IPv6, IPv4v6, Ethernet and unstructured) and / or SSC type (session and service continuity, e.g., as defined in 3GPP TS23.501, SSC mode 1, SSC mode 2, SSC mode 3).

[0091] ●QoS Profile: The term “Serving” refers to one or more QoS profiles used for data traffic communication of the UE (e.g., in the UE’s PDU session), where the UE is located in the region of interest.

[0092] ● Data Network: The term "serving" refers to one or more data networks used for UL and / or DL ​​data traffic and / or control plane traffic between the mobile operator's network and a data network outside the mobile operator's network. For example, a data network serving a region of interest is any DNN that receives and / or transmits UL and / or DL ​​traffic associated with the UE and / or receives traffic from or transmits traffic to the CP NF, where the UE and / or the NF is located in the target region of interest.

[0093] ●PLMN: The term “serves” refers to one or more PLMNs associated with data traffic from and / or to the UE and / or NF, where the UE and / or NF are located in the target region of interest.

[0094] Information about network entities and / or network attributes serving the region of interest: This is a list of actual values ​​and / or values ​​(or instances) of a given type of network entity and / or network attribute that serves / maps to the region of interest. For example, if the type of a network entity or network attribute belongs to one of the types listed below, the information about the network entity or network attribute serving the region of interest is as follows:

[0095] ● For UE types of 5GS entities: one or more UE identifiers (e.g., Subscription Permanent Identifier (SUPI), Generic Public Subscription Identifier (GPSI), 5G-Globally Unique Temporary Identifier (5G-GUTI), UE IP address, etc.) and / or UE group identifiers (e.g., internal group identifier, external group identifier).

[0096] ● For 5GS entities, cell type: one or more cell identifiers (e.g., cell ID, Next Generation Radio Access Network (NG-RAN) node ID).

[0097] ●TA type of 5GS entity: one or more TAIs (e.g., 3GPP TAI, non-3GPP TAI)

[0098] ● For 5GS entities, the network slice type is one or more network slice identifiers (e.g., NSSAI and / or S-NSSAI and / or NSI).

[0099] ● For NF types of 5GS entities: one or more NF identifiers (e.g., NF ID).

[0100] ● Network Function (NF) set: One or more NF set identifiers.

[0101] ●For 5GS entities, external AF type: one or more external AF identifiers (e.g., AF ID).

[0102] ● For 5GS entities, the application type is: application identifier (e.g., application ID, AF transaction internal ID, initiator identity, backend data transfer reference ID).

[0103] ● For 5GS entities, the session type is: one or more PDU session IDs and / or PDU session types, and / or SSC mode.

[0104] ● For QoS profile types of 5GS entities: one or more identifiers of the QoS profile (e.g., 5G QoS Identifier, 5QI).

[0105] ● For 5GS entities, the data network type is: one or more DNNs and / or DNAI.

[0106] ● For PLMN information types for 5GS entities: one or more identifiers of the PLMN (e.g., home or visited PLMNID).

[0107] Analytics Functionality: This is an Functionality that receives analytics information requests and / or subscriptions from consumers and can perform analytics information generation. An example of an analytics function is the NWDAF in the 3GPP 5G architecture defined in TS23.501.

[0108] Analysis information: This is the output of the analysis function, such as the analysis ID defined in 3GPP TS23.288, such as the analysis IDs listed in Sections 6.4 to 6.9 of TS23.288V16.1.0.

[0109] Enhanced NF that centralizes information about 5GS entities (also known as network entities and / or network attributes) serving the region of interest: capable of providing information about 5GS entities serving the region of interest for any and / or all types of 5GS entities.

[0110] Detects 5GS entities (also known as network entities and / or network attributes) serving the region of interest: Provides information about 5GS entities serving the region of interest for special type 5GS entities and / or subset type 5GS entities.

[0111] Data collection source: A 5GS entity that provides raw data for generating analytical information.

[0112] A defined data collection source is a 5GS entity that relates to information about 5GS entities serving a region of interest. For example, it is a 5GS entity (e.g., an NF instance) included in a list of information about 5GS entities serving a region of interest, such as: ({TA1: NF#a, NF#b}, {TA2: NF#c}, {TA3: NF#d, NF#e}). In this sense, each NF instance included in this list is a defined data collection source.

[0113] Raw data: This refers to searchable data in formats such as measurements, metrics, events, data files, monitoring information, and logs.

[0114] Analytical information generation: This is the process by which analytical functions use raw data to perform calculations and / or apply statistical analysis and / or apply ML / AI technologies (such as regression models, neural networks, etc.) to generate analytical information.

[0115] Search criteria: These are parameters used to describe the specific characteristics of the data that needs to be queried / retrieved / provided, and this data is related to information about 5GS entities serving the region of interest. Examples of specific characteristics of search criteria are any of the following:

[0116] ● Time aspect (e.g., time intervals associated with historical records).

[0117] ● Quantitative aspects (e.g., number of results, such as the most recent 20 historical stored information).

[0118] Control of 5GS entity lifecycle: This relates to the ability to change a 5GS entity from one phase and / or configuration to another. For example, a phase could be the deployment (e.g., in the case of network slicing), instantiation (e.g., in the case of an NF), establishment (e.g., in the case of a session), or connection (e.g., in the case of a UE, application, or data network). An entity with the ability to change the phase of a 5GS entity (e.g., disconnecting a UE by deregistering it from the network) is an entity that can control this 5GS entity lifecycle. In the case of configuration, an example of the ability to change the configuration is: a PDU session configured with QoE profile 5QI 1, then changed to 5QI 2.

[0119] Lifecycle changes of 5GS entities (e.g., network entities and / or network attributes): This refers to information related to lifecycle changes of 5GS entities and / or attributes. Examples of lifecycle changes of 5GS entities and / or attributes are as follows:

[0120] ● Changes in the UE context can be caused by changes in the UE's location; established sessions; the type of established sessions; or the established sessions using a new data network. In the UE context example, the lifecycle change of a UE 5GS entity is when the UE's location information changes from one region of interest to another.

[0121] ● Changes to the NF configuration file can reflect new NFs and / or network slices added to the region of interest, or NFs and / or network slices removed from the region of interest.

[0122] ● Changes to the DNN used for UE sessions can reflect data networks added to or removed from the region of interest.

[0123] Region of Interest (ROI) Transaction Identifier: Uniquely identifies a group of 5GS entities (also known as network entities and / or network attributes) serving the ROI within a time interval. This transaction identifier ensures that information about the 5GS entities serving the ROI that has not changed due to changes in the 5GS entity's lifecycle will not be exchanged between the entities of this invention. This guarantees that only information about the 5GS entities serving the ROI that has not yet been acquired by the analysis function, or information that has changed since the last time the analysis function acquired that information, will be actually transmitted between the entities of this invention. Using this information can reduce the load on data collection.

[0124] Dataset Identifier: Follows the same definition in Section 5.2.12.2.1 of TS23.501: "Uniquely identifies a dataset in CP NF#2". Examples of dataset identifiers are subscription data, policy data, application data, and open data. Another example of a description of dataset identifiers is provided in the definition of data types used in the UDM in TS23.502 (e.g., the data types mentioned in Table 5.2.3.3.1-3 of TS23.502), where the subscription data type is an example of a list of datasets that are uniquely identified, such as access and mobility subscription data, SMF selected subscription data, and session management subscription data. In these cases listed in the UDM, the dataset identifier may be the exact name of the dataset.

[0125] Data subset identifier: Follows the same definition in Section 5.2.12.2.1 of TS23.501: "Uniquely identifies a subset of data in a dataset". For example, if considering the organization of data in a UDR, examples of subset data identifiers are: access and mobility subscription data, policy set entry data, background data transmission data, access and mobility information, and UE context in SMF data.

[0126] Dataset key and data subkey: These are information used to identify and distinguish values ​​that distinguish a specific dataset and / or subset of data. Following the same example in Table 5.2.12.2.1-1 of TS23.502; the information type defined as SUPI (i.e., UE unique identifier) ​​can be used as the dataset key to identify “Subscription Data”; the information type “PDU Session ID” can be used as the data subkey to further specialize / filter the “UE Context in SMF Data” subset of “Subscription Data”. One example of use for the dataset key and / or data subkey is when a consumer uses this information to filter a specific UE with a specific PDU Session ID in a query on a CP NF enhanced by history. Another example of use for the dataset key and / or data subset key relates to UDM, where requests for data types (i.e., datasets) of the UDM can be filtered using the data key and / or data subkey as described in Table 5.2.3.3.1-3 of TS23.502. For example, a request sent to the UDM to query information about the dataset identifier (i.e., data type) "UE context in SMF data" can also include the dataset key and subkey: SUPI and S-NSSAI, respectively.

[0127] Information type or field (of a record): This refers to the data field to be stored in the CP entity. Examples of data stored in a CP entity include: SM policy data (defined in detail in TS29.519) and AMF subscription data (defined in detail in TS29.505). Typically, the information description is as follows:

[0128] ●UE-related data: For example, UE#1 has subscription information #A, session information #B (e.g., PDU sessions a, b, c), mobility policies, and location information (UE#1 is located in cell x, y, z).

[0129] ● and / or network slice related data: for example, mapping S-NSSAI to TA and corresponding cells at a given point in time.

[0130] The information type is related to the dataset identifier and / or data subset identifier.

[0131] Information value: The actual value associated with the information type.

[0132] Record: A uniquely defined instance / occurrence of a tuple (dataset identifier, data subset identifier, information value) for a given dataset key and / or data subkey. Attached Figure Description

[0133] The above aspects and implementations are set forth in the following description of specific embodiments, in conjunction with the accompanying drawings.

[0134] Figure 1 An example of a mobile network that follows the 5G architecture defined by 3GPP is shown.

[0135] Figure 2 The illustration shows a first network entity for analysis and generation, a second network entity for supporting analysis and generation, and a third network entity for supporting analysis and generation according to an embodiment of the present invention.

[0136] Figure 3 A second network entity for supporting analysis generation, a third network entity for supporting analysis generation, and a first network entity for analysis generation are shown according to embodiments of the present invention.

[0137] Figure 4 A second network entity for supporting analysis generation, a third network entity for supporting analysis generation, and a first network entity for analysis generation are shown according to embodiments of the present invention.

[0138] Figure 5 A diagram of a method is shown that retrieves past and / or current association information about 5GS entities serving a region of interest for analysis generation.

[0139] Figure 6 A diagram of a method is shown that retrieves past and / or current association information about 5GS entities serving a region of interest for analysis generation.

[0140] Figure 7A diagram illustrating a first alternative method for a first operating mode based on UDM and NWDAF interaction is shown.

[0141] Figure 8 A diagram illustrating a second alternative method based on the first operating mode of interaction with UDM, UDR, and NWDAF is shown.

[0142] Figure 9 A diagram illustrates a second operational mode based on UDM, NRF, and NWDAF interactions, following the principles of the event open framework.

[0143] Figure 10 The present invention illustrates a method for a first network entity provided by an embodiment of the present invention.

[0144] Figure 11 The present invention illustrates a method for a second network entity provided by an embodiment of the present invention.

[0145] Figure 12 The present invention illustrates a method for a third network entity provided by an embodiment of the present invention. Detailed Implementation

[0146] This invention provides network entities and methods, specifically, data structures and services for enhancing mobile networks (with a particular focus on 5G mobile network architecture) to determine past (historical) and / or current (actual) association information of other network entities and / or network attributes (e.g., network attributes mapped to or serving the region of interest) that have been mapped to or currently serve the region of interest. Simultaneously, this invention minimizes the overhead of collecting such information. The aim is to support, for example, the analytics capabilities of mobile operators to further collect specialized data from identified network entities and / or network attributes in the region of interest for analysis generation.

[0147] Figure 2 A first network entity 200, a second network entity 210, and a third network entity 220 according to embodiments of the present invention are shown. The first network entity 200 may be a CP entity, specifically, it may be or include NWDAF. The first network entity 200 can implement analysis functions. The second network entity 210 may be a CP entity, specifically, it may be or include UDM and / or UDR and / or NWDAF. The third network entity 220 may be a CP entity, specifically, it may be or include SMF and / or AMF and / or NSSF and / or NEF and / or AF and / or NRF.

[0148] The first network entity 200 is used to obtain past and / or current association information 201 of the region of interest from the second network entity 210 and / or one or more third network entities 220. The past and / or current association information 201 indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest.

[0149] The first network entity 200 is also used to provide analysis information 202, which is based on the acquired association information 201 of the region of interest. That is, the first network entity 200 can generate analysis information 202 based on the association information 201. The network entity 200 can also open and / or send the analysis information 202 and / or association information 201 to another network entity (e.g., to the second network entity 210 and / or the third network entity 220).

[0150] Figure 3 A first network entity 300, a second network entity 310, and a third network entity 320 are shown according to embodiments of the present invention. The first network entity 300 may be... Figure 2 The first network entity 200 and the second network entity 310 shown can be... Figure 2 The second network entity 210 and / or the third network entity 320 shown may be Figure 2 The third network entity 220 is shown.

[0151] Figure 3 The diagram illustrates how, in response to a first request 311 sent to a third network entity 320 and / or based on a first subscription by the third network entity 320, a second network entity 310 obtains past and / or current association information 201 of a region of interest from one or more third network entities 320 (only one third network entity 320 is shown here). That is, the third network entity 320 can receive the first request 311 from the second network entity 310 and, in response, can provide the association information 201 to the second network entity 310. Additionally or alternatively, the second network entity 310 obtains change information 321 from one or more third network entities 320 upon a lifecycle change of one or more network entities and / or network attributes related to the association information 201 (as provided by the third network entity 320). That is, the third network entity 320 can be used to monitor the lifecycle of one or more network entities and / or network attributes, and if a lifecycle change is detected, can provide the change information 321 to the second network entity 310. The change information 321 can indicate one or more changes relative to the previously provided association information 201.

[0152] Figure 3Further illustrated (by dashed lines), the second network entity 310 can be used to obtain a second request 301 and / or a second subscription from the first network entity 300 to acquire association information 201 of the region of interest. Therefore, the first network entity 300 can be used to send the second request 301 and / or the second subscription to the second network entity 310. Then, in response to the second request 301 and / or according to the second subscription, the second network entity 310 can be used to provide the first network entity 300 with the acquired association information 201 of the region of interest (e.g., acquired from a third network entity 320) and / or aggregated association information 201 of the region of interest (e.g., aggregated association information 201 acquired from more than one third network entity 320).

[0153] Figure 4 A first network entity 400, a second network entity 410, and a third network entity 420 are shown according to embodiments of the present invention. The first network entity 400 may be... Figure 2 and Figure 3 The first network entity 200 and / or 300 shown, and the second network entity 410 may be Figure 2 and Figure 3 The second network entity 210 and / or 310 shown, and the third network entity 420 may be Figure 2 and Figure 3 The third network entity 220 and / or 320 shown.

[0154] In response to a request 401 received from a first network entity 400 and / or based on a subscription by the first network entity 400, a third network entity 420 provides past and / or current association information 201 of a region of interest to the first network entity 400. Additionally (alternatively), in response to a request 411 received from a second network entity 410 and / or based on a subscription by the second network entity 410, the third network entity 420 provides past and / or current association information 201 to the second network entity 410. Alternatively or additionally, when one or more target elements related to the association information 201 change, the third network entity 420 provides the association information 201 to the first network entity 400 and / or the second network entity 410, where the one or more target elements are network entities or network attributes.

[0155] Figures 2 to 4Each network entity shown may include processing circuitry (not shown) for performing, conducting, or initiating various operations of the network entity described herein. The processing circuitry may include hardware and software. Hardware may include analog or digital circuitry, or both. Digital circuitry may include components such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), or multi-purpose processors. In one embodiment, the processing circuitry includes one or more processors and non-transitory memory connected to one or more processors. The non-transitory memory may carry executable program code that, when executed by one or more processors, causes the network entity to perform, conduct, or initiate the operations or methods described herein.

[0156] Figure 5 A diagram of a method is shown that retrieves specific past and / or current association information 201 about 5GS entities serving a region of interest for analysis generation. Figure 5 The diagram shows network entities 200, 210, and 220 involved in resolving the problem. It is worth noting that in the following description of the embodiments, reference numerals 200, 210, and 220 (e.g., ...) are used interchangeably. Figure 2 The symbols used are for identifying the first network entity, the second network entity, and the third network entity; however, these network entities can also be network entities 300, 310, and 320. Figure 3 (as shown) or 400, 410 and 420 ( Figure 4 (As shown). In Figure 5 In this context, "analysis function" is or includes the first network entity 200, "NF enhanced by 5GS entity serving region of interest" is or includes the second network entity 210, and "entity that detects region of interest of 5GS entity" is or includes the third network entity 220.

[0157] The conditions under which the first network entity 200 may request association information 201 regarding 5GS entities serving the region of interest can be related to any of the following:

[0158] ● Receive a request to generate analysis information 202 for a given region of interest, without specifying any particular UE and / or NF instance in the request.

[0159] ● It is configured (e.g., a request subscription to analytics information) to generate analytics information periodically 202, therefore the 5GS entity serving the region of interest must be updated periodically.

[0160] ● It is configured (e.g., via script, configuration file) to periodically collect association information 201 about 5GS entities serving the region of interest to support the generation of analysis information 202.

[0161] In this disclosure, two methods are provided for the first network entity 200 to obtain association information 201, specifically association information 201 concerning 5GS entities serving one or more regions of interest.

[0162] Operation Mode 1 (Centralized Acquisition): The first network entity 200 interacts with the second network entity 210, acquiring association information 201 from the second network entity 210. In this Operation Mode 1, the second network entity 210 can detect one or more other network entities (here, 5GS entities) serving the region of interest, and provide and / or maintain association information 201 for any type of such 5GS entity. The second network entity 210 can implicitly acquire association information 201 about 5GS entities serving the region of interest from one or more third network entities 220 that detect 5GS entities serving the region of interest. One or more third network entities 220 can implicitly provide 5GS entity data, for example, due to changes in the lifecycle of these 5GS entities. A description of how the second network entity 210 further acquires association information 201 for different types of 5GS entities serving the region of interest will be provided in conjunction with the following... Figure 6 Please provide a detailed explanation.

[0163] Operation Mode 2 (Distributed Acquisition): A first network entity 200 interacts with one or more third network entities 220 and acquires association information 201 from these third network entities 220. In this operation mode 2, different third network entities 220 may exist, thereby providing different types of association information 201 for different types of other network entities or network attributes. For example, one third network entity 220 may only provide the UE type of 5GS entities serving the region of interest; while another third network entity 220 may only provide TA, cell, and network slice identifier type of 5GS entities serving the region of interest. In this operation mode 2, the first network entity 200 is also responsible for centrally storing / updating association information 201 (e.g., recording), such as association information 201 of 5GS entities serving the region of interest. When the first network entity 200 acquires this information from one or more third network entities 220, the first network entity 200 can aggregate this partial information into a single data structure, which has a general mapping of all 5GS entities for each region of interest.

[0164] Figure 5The steps of "part A" of the method provided according to an embodiment of the present invention are shown (operation modes 1 and 2, respectively). In this method, Figure 5 Steps 2 and 3 described herein are universal for both operation modes 1 and 2.

[0165] The steps for operating mode 1 can be as follows:

[0166] 1a. The second network entity 210 interacts with one or more third network entities 220 to obtain information about 5GS entities serving one or more regions of interest, based on the supported 5GS entity types available from the third network entity 220. Possible alternatives to this interaction are described below. Figure 6 Please describe in detail.

[0167] 1b. The first network entity 200 needs information about 5GS entities serving the region of interest and interacts with the second network entity 210. Examples of ways this interaction may occur are through request 301 and response and / or subscription-notification communication patterns.

[0168] Here is an example of a request-response interaction model:

[0169] ● The first network entity 200 invokes a service from the second network entity 210, which serves the region of interest.

[0170] ● The first network entity 200 invokes such a service, which includes its requested region of interest (e.g., TA in terms of a cell) and a 5GS entity type (e.g., UE, application, NF, etc.) that should be identified as a 5GS entity serving the requested region of interest.

[0171] If this is the first interaction between the first network entity 200 and the second network entity 210 serving the region of interest, the first network entity 200 may omit the region of interest transaction identifier in the interaction.

[0172] ●Based on the parameters used by the first network entity 200 in the invoked service, the second network entity 210 determines a list of 5GS entities serving the region of interest that match the received input parameters (e.g., the requested region of interest and the type and / or the region of interest transaction identifier of the 5GS entity).

[0173] Then, the second network entity 210 checks whether the transaction ID of the region of interest was provided by the first network entity 200.

[0174] – If not (for example, in the case of the first interaction between these entities), the second network entity 210 also generates a region of interest (ROI) transaction identifier and includes such a transaction identifier in the information, as well as including all identified 5GS entities serving the ROI in the response returned to the first network entity 200. The second network entity 210 maintains a mapping between the identified 5GS entities serving the ROI, the first network entity 200 (analysis function) identifier, and the ROI transaction identifier generated for such analysis function identifier.

[0175] – If the first network entity 200 also provides a region of interest transaction identifier in the input parameters, the second network entity 210 determines the record set of the 5GS entities serving the region of interest from the intersection between the currently determined 5GS entities serving the region of interest and the 5GS entities serving the region of interest mapped to the transaction identifier (the terms region of interest transaction identifier or transaction identifier are synonyms).

[0176] When there is no empty record set of 5GS entities serving the region of interest in the intersection of the currently determined 5GS entities serving the region of interest mapped to the provided transaction identifier, the second network entity 210 includes the record set of 5GS entities serving the region of interest in the intersection in its return to the first network entity 200, generates a new transaction identifier, and updates the mapping between the currently determined 5GS entities serving the region of interest, the analysis function identifier, and the region of interest transaction identifier generated for such analysis function identifier. The second network entity 210 may also retain the history of previous mappings.

[0177] It is worth noting how the second network entity 210 determines possible alternatives to the current 5GS entity serving the region of interest. Figure 6 The embodiments described below are described in detail.

[0178] The steps for operating mode 2 can be as follows:

[0179] 1c. One or more third network entities 220 are capable of controlling the lifecycle of 5GS entities and / or network attributes. For example: UE registration to the network, UE session establishment; NF configuration in the region of interest. One or more third network entities 220 map the controlled 5GS entities to the regions of interest. When the lifecycle of a 5GS entity changes (e.g., the UE location changes, and therefore the UE serving the region of interest may change), one or more third network entities 220 update the mapping and retain records of the previous mapping and the current new mapping.

[0180] 1d. The first network entity 200 needs information about 5GS entities serving one or more regions of interest and interacts with one or more third network entities 220 serving the regions of interest. Examples of ways this interaction may occur are through request-response and / or subscription-notification communication patterns.

[0181] The first network entity 200 invokes services from different third network entities 220 serving a region of interest, including at least the region of interest it requires (e.g., TA in the case of a cell). It may also include types of 5GS entities and / or attributes related to retrieval and / or transaction identifiers.

[0182] The description of step 1b involves how the interaction and transaction identifiers regulate the output of one or more third network entities 220 serving the region of interest to the first network entity 200.

[0183] The difference between operation mode 2 and operation mode 1 is that in operation mode 2, the first network entity 200 can also aggregate the acquired information about 5GS entities serving the region of interest to create a mapping of all types of 5GS entities serving the region of interest.

[0184] 1e. When the first network entity 200 receives 5GS entities serving the region of interest from one or more third network entities 220, the first network entity 200 aggregates the acquired information into a data structure that can be used for mapping the region of interest, each 5GS entity type, and the dataset key and / or subkey for each 5GS entity type. The mapping also includes a transaction identifier and / or the time interval of the acquired information, which includes the current mapping of the 5GS entities serving the region of interest.

[0185] The same principles described in step 1b regarding how to identify the current and previous mappings between 5GS entities serving the region of interest also apply to how the first network entity 200 maintains this mapping.

[0186] Regardless of the different interaction methods that the first network entity 200 may use to obtain information about 5GS entities serving the region of interest, such services from the second network entity 210 and / or one or more third network entities 220 serving the region of interest may include further search criteria, such as time or quantity aspects related to the information of 5GS entities serving the region of interest.

[0187] 2. The first network entity 200 retrieves data related to the region of interest and can determine which 5GS entities are data collection sources for the requested region of interest. Based on information obtained from the second network entity 210 and / or one or more third network entities 220 regarding 5GS entities serving the region of interest, the first network entity 200 determines such data collection sources 500.

[0188] For example, if the first network entity 200 must identify NF instances and / or NF sets (e.g., NF types of 5GS entities) serving a region of interest (e.g., a list of TAs), then in step 1, the first network entity 200 obtains information about the NF instances serving the region of interest (e.g., {TA1, TA2, TA3}), which is, for example, a list of all NF instances for each TA: ({TA1: NF#a, NF#b}, {TA2: NF#c}, {TA3: NF#d, NF#e}). In this example, the first network entity 200 determines that the data collection source for TA1, TA2, TA3 (i.e., the region of interest) is the NF instances: NF#a, NF#b, NF#c, NF#d, NF#e.

[0189] 3. Based on the determined data collection source 500, the first network entity 200 selects and / or retrieves data from the determined data collection source 500 and generates analysis information 202.

[0190] Figure 6 The steps of "Part B" (operation mode 1) of the method provided according to an embodiment of the present invention are shown. Specifically, there are two alternatives regarding how a second network entity 210 serving a region of interest can implement a set of information about 5GS entities serving one or more regions of interest. The alternatives and the method steps of each alternative are described below:

[0191] Alternative 1: One or more second network entities 210 serving the region of interest implicitly obtain information about the 5GS entities serving the region of interest from one or more third network entities 220 serving the region of interest.

[0192] 1. One or more third network entities 220 serving the region of interest (ROI) are able to control the lifecycle of 5GS entities and / or attributes. Examples include: UE registration to the network, UE session establishment, and NFs configured in the ROI. When the 5GS entity lifecycle changes (UE location change, session modification, inclusion of a new NF instance in a network slice), the third network entity 220 serving the ROI sends 5GS entity data related to the lifecycle change (e.g., updated UE SMF context or UE AMF context) to one or more second network entities 210 serving the ROI, without explicitly indicating information about the 5GS entities serving the ROI.

[0193] 2. Based on the acquired 5GS entity data, one or more second network entities 210 serving the region of interest identify the context dataset key region, one or more 5GS entity types associated with the 5GS entity data, and the associated 5GS entity data key and / or data subkey for each 5GS entity type from the 5GS entity data.

[0194] 3. One or more second network entities 210 serving the region of interest update the mapping of the current 5GS entities serving the region of interest and store previous records of the 5GS entities serving the region of interest to enable the search of historical information.

[0195] Alternative Solution 2: One or more second network entities 210 serving the region of interest explicitly obtain information records about the 5GS entities serving the region of interest from one or more third network entities 210 serving the region of interest.

[0196] 1. One or more third network entities 210 serving the region of interest have a controlled mapping between 5GS entity lifecycle changes and information about such 5GS entities serving the region of interest. When a 5GS entity lifecycle changes (UE location change, session modification, inclusion of a new NF instance in a network slice), one or more third network entities 220 serving the region of interest update their mapping of 5GS entities serving the region of interest.

[0197] 2. One or more second network entities 210 serving the region of interest interact with one or more third network entities 220 serving the region of interest to obtain information about the 5GS entities serving the region of interest, based on the type of 5GS entities controlled by such entities that detect the 5GS entities serving the region of interest. Examples of ways in which this interaction may occur are through request-response and / or subscription-notification communication patterns.

[0198] One or more second network entities 210 serving a region of interest invoke services from different third network entities 220 serving the region of interest, including at least the region of interest they request (e.g., TA in the case of a cell). This may also include types of 5GS entities and / or attributes related to retrieval and / or transaction identifiers.

[0199] One or more third network entities 220 serving the region of interest provide one or more records of 5GS entities serving the region of interest.

[0200] 3. One or more second network entities 210 serving the region of interest update the mapping of the current 5GS entities serving the region of interest and store previous records of the 5GS entities serving the region of interest to enable the search of historical information.

[0201] The following details are applicable to all operating modes:

[0202] One issue that the first network entity 200 needs to consider is whether it actually performs the generation (and / or updating) of analysis information 202 based on 5GS entities serving the region of interest. This generation (and / or updating) of analysis information 202 based on 5GS entities serving the region of interest has different possibilities, applicable to all operating modes of embodiments of the present invention. For example, the first network entity 200 can use one or more of the following alternatives:

[0203] ●When the acquired 5GS entity serving the region of interest is a new 5GS entity and / or changes, the first network entity 200 can be used to trigger and / or perform an update to the generation of analysis information 202.

[0204] ● The first network entity 200 can be used to periodically trigger and / or execute updates to the analysis generated. Therefore, all changes to 5GS entities serving the region of interest obtained by the first network entity 200 will be queued so that they can be used only when a new analysis generation (and / or update) cycle expires.

[0205] ● The first network entity 200 may be configured with a queue that stores changes of 5GS entities serving the region of interest over a period of time. When the queue is full and / or the time period is close, the first network entity 200 triggers and / or performs the generation and / or updating of analysis information.

[0206] ● The first network entity 200 can be configured with different urgency levels to trigger the generation and / or updating of analysis information 202 based on acquired information about 5GS entities serving the region of interest. For example, a change in a specific type of 5GS entity serving the region of interest or a specific region of interest will immediately trigger and / or execute the generation and / or updating of analysis information 202 based on the change in the 5GS entity serving the region of interest, while other types of 5GS entities serving the region of interest and / or a specific region of interest can operate using the queue mode described above.

[0207] ● When the first network entity 200 receives a request and / or subscription for analytics information (e.g., analytics ID as defined in TS23.288), the first network entity 200 may trigger and / or execute the generation of analytics information 202 based on 5GS entities serving the region of interest. This requires the first network entity 200 to identify which 5GS entities serve the region of interest in order to determine which entities to collect and / or use for analytics computation (i.e., generation).

[0208] The main advantages of the embodiments of the present invention are as follows:

[0209] ● Reduced signaling associated with data collection (for identifying 5GS entities serving the region of interest) by the first network entity 200 (e.g., NWDAF) because the first network entity 200 can obtain this information from the central entity.

[0210] ● Reuse existing messages already exchanged between 5G NFs to derive information about 5GS entities serving the area of ​​interest, thereby reducing the data collection load for analysis generation.

[0211] ● Control over the amount of data exchanged between the first network entity 200 and other NFs (e.g., UDM, UDR) ensures that only information portions about 5GS entities serving the region of interest that are unavailable at the first network entity 200 are sent.

[0212] The following describes exemplary embodiments of the present invention based on a 5G mobile network conforming to the architecture defined in 3GPP TS23.501. In 5GS, these exemplary embodiments have various alternatives.

[0213] The first embodiment based on operation mode 1 with alternative 1 is now described. Specifically, this first embodiment provides current and / or historical 5GS entities and / or attributes (association information 201) to one or more regions of interest based on UDM. In this first embodiment, network entities according to embodiments of the present invention are mapped as follows:

[0214] ●NWDAF is the first network entity 200 (e.g., analysis function).

[0215] ●AMF is a third network entity 220 capable of detecting: UE, cell, TAI, network slice, and / or AMF NF type serving the region of interest.

[0216] ●SMF is a third network entity 220 and is capable of detecting: sessions, applications, data network name (DNN), data network access identifier (DNAI), network slices, and / or SMF NF types serving the area of ​​interest.

[0217] ●UDM is a second network entity 210 serving the region of interest, and is enhanced in the following ways:

[0218] ■ The dataset “Region of Interest Context” stores and maintains association information 201 for 5GS entities serving the region of interest. The fields and information in this dataset can be defined as shown in Table 1.

[0219] Table 1: Entities Serving Regions of Interest, 5GS Entity Types, and Keys

[0220]

[0221]

[0222] The service “Nudm_AoICM” enables consumers (e.g., NWDAF) to invoke these services to retrieve information about 5GS entities serving the region of interest, maintained by the UDM. In this embodiment, this information is maintained by the “Region of Interest Context” dataset at the UDM. Table 2 details the service operations, input and output parameters for each operation of the Nudm_AoICM service.

[0223] Table 2: New UDM Services Related to 5GS Entities Serving Regions of Interest

[0224]

[0225] This embodiment focuses on the use of the Nudm_AoICM_Get service operation to support NWDAF 200 retrieval of 5GS entities serving the region of interest. The Nudm_AoICM_Get service operation supports consumers accessing current and historical 5GS entities serving the region of interest.

[0226] In this embodiment, it is assumed that UDM 210 is configured (e.g., by carrier policy) to have a list of 5GS entity types and a list of regions of interest (AoI) that will be mapped by UDM 120 and stored in the AoI dataset.

[0227] In this embodiment, a key aspect is how existing signaling defined in TS23.502 is used in 5GS entities (which are embodiments of entities relevant to this invention) to enable UDM 210 to acquire the mapping of 5GS entities without using new types of signaling or additional information transmitted in existing signals. This embodiment represents an operating mode 1 with an alternative to implicitly acquiring 5GS entities serving the region of interest. Figure 7 The present invention is described in the figure based on UDM-NWDAF interaction.

[0228] Figure 7 Steps 1 to 3 in the process are Figure 5 An embodiment of step 1a shown. Figure 6 The embodiments of steps 1 and 2 are respectively in Figure 7 Steps 1 (1a to 1d) and 2 (2a to 2c) are described in detail. More specifically, Figure 7 Steps 2a to 2c illustrate the aggregation of associated information. These steps demonstrate how this embodiment utilizes existing signaling at AMF 220 and SMF 220 to provide 5GS entity data (e.g., AMF-related UE context, SMF-related UE context, UE location) related to lifecycle changes of 5GS entities controlled by SMF 220 and AMF 220. Based on the 5GS entity data obtained by UDM 210 from SMF 220 and AMF 220 (which implicitly includes support for identifying 5GS entities serving regions of interest), UDM 210 can aggregate associated information, such as extracting the mapping of 5GS entities to regions of interest, which has been used to track and create records for each region of interest in the AoI context dataset. Figure 6 The embodiment of step 3 in Figure 7 Step 3 is explained in detail.

[0229] like Figure 7 As shown, steps 1 to 3 can occur in parallel multiple times.

[0230] Figure 5 The embodiment of step 1b in Figure 7 Steps 5a and 5b are described in detail. Figure 5 The embodiments of steps 2 and 3 are respectively in Figure 7 Steps 6 and 7 are explained in detail.

[0231] Figure 7 Steps 4 and 8 show one possibility of how the NWDAF 200 can be triggered to obtain 5GS entities serving the region of interest, and how the information obtained from the UDM 210 is reflected in the output of the NWDAF 200.

[0232] The second specific embodiment is based on operation mode 1 with alternative 2. Specifically, this second specific embodiment provides past 5GS entities and / or attributes to the region of interest based on UDM and UDR. In this embodiment, network entities according to embodiments of the present invention are mapped as follows:

[0233] ●NWDA F It is the first network entity 200 (e.g., analysis function).

[0234] ●AMF is a third network entity 220 that can detect: UE, cell, TAI, network slice and / or AMF NF type serving one or more regions of interest.

[0235] ●SMF is a third network entity 220 and is capable of detecting: sessions, applications, DNNs, DNAI, network slices, and / or SMF NF types serving regions of interest.

[0236] ● UDM is the second network entity 210 and is capable of creating 5GS entities that serve the region of interest, which merge information from SMF 220 and AMF 220 into a single record. However, UDM 210 is not an entity that stores such records to support the storage of past association information 201 about 5GS entities serving the region of interest.

[0237] ●UDR is an embodiment of the second network entity 210, enhanced in the following ways:

[0238] ■ The dataset contains the region of interest context, which stores and maintains information about 5GS entities serving the region of interest. The fields and information in this dataset are defined in Table 3.

[0239] Table 3: Entities Serving Regions of Interest, 5GS Entity Types, and Keys

[0240]

[0241] Table 4: Enhanced UDR service for supporting the retrieval of 5GS entities within the region of interest.

[0242]

[0243]

[0244] This embodiment focuses on providing services based on all existing 5GS architectures defined in TS23.502. Enhancements are extensions to NF functionality, new data type structures, and existing service operations. Additionally, this embodiment supports separation of concerns between the roles of UDM 210 and UDR 210, ensuring compatibility with the current 3GPP 5GS architecture, where UDM 210 does not act as an entity for unified data, while UDR 210 acts as an entity for storing data.

[0245] Figure 8 An embodiment of operation mode 1 with alternative 2 based on UDM, UDR and NWDAF interaction is described. Figure 8 Steps 1 to 4 in the process are Figure 5 An example of step 1a. Figure 8 Steps 6a and 6b in the text are Figure 5 An example of step 1b. Figure 8 Steps 5 and 9 also illustrate one possibility of how to trigger NWDAF 200 to obtain 5GS entities serving the region of interest, and how information obtained from URM 210 is reflected in the output of NWDAF 200.

[0246] Figure 8 Steps 1 to 3 in the process are Figure 6 An example of step 1. Figure 8 Step 4 is Figure 6 Examples of steps 2 and 3. Additionally, Figure 8 Steps 2a to 2c in the diagram illustrate the aggregation of related information.

[0247] The third specific embodiment is based on operation mode 2, providing current and / or past 5GS entities and / or attributes to the region of interest based on NRF and UDM (following the event open framework model). In this embodiment, network entities according to embodiments of the present invention are mapped as follows:

[0248] ●AMF is a third network entity 220 that can detect: UE, cell, TAI, network slice and / or AMF NF type serving one or more regions of interest.

[0249] ●SMF is a third network entity 220 that can detect: sessions, applications, DNNs, DNAI, network slices, and / or SMF NF types serving regions of interest.

[0250] ●NRF is a third network entity 220, and is capable of detecting: all types of NFs serving the region of interest.

[0251] ● UDM is a third network entity 220 and is capable of creating 5GS entities that serve the region of interest, which merge information from SMF 220 and AMF 220 into a single record. However, UDM 220 is not an entity that stores such records to support the storage of historical information about 5GS entities serving the region of interest.

[0252] ●NWDAF is the first network entity 200 (e.g., analysis function) and the second network entity 210 serving the region of interest, enhanced in the following ways:

[0253] ■ Dataset AoI Context, which stores and maintains information about 5GS entities serving the region of interest. The fields and information in this dataset are defined in Table 5.

[0254] Table 5: Entities Serving Regions of Interest, 5GS Entity Types, and Keys

[0255]

[0256]

[0257] There are different alternatives to how NF services can be implemented by enhancing the capabilities of entities defined in the embodiments of this invention. Some possible service extensions are described below.

[0258] The following are possible embodiments of how UDM 210 provides services to detected 5GS entities in the region of interest.

[0259] In this embodiment, the event openness framework defined in Section 4.15 of TS23.502 is followed for the services of UDM 210. In this case, as detailed in Table 6, a new monitoring event is defined as being detected by UDM 210.

[0260] Table 6: List of Monitoring Capability Events

[0261]

[0262] In addition, the UDM service used to open new types of events must also be extended as defined in Table 7.

[0263] Table 7: UDM Enhanced Event Open Service to provide services to detected 5GS entities in the region of interest

[0264]

[0265] The following are possible embodiments of how NRF 210 provides services to detected 5GS entities serving the region of interest.

[0266] Table 8: NRF Enhancement Services to Provide 5GS Entities Detected and Serving Regions of Interest

[0267]

[0268]

[0269] This embodiment focuses on providing an implementation based on the Event Open Framework. In this case, NWDAF 200 is the entity responsible for centralizing and storing the mappings of all 5GS entities (types) serving the region of interest. NWDAF 200 obtains this information based on subscriptions to events from UDM 210 and NRF 210 related to the 5GS entities serving the region of interest.

[0270] Additionally, in this embodiment, NWDAF 200 can also provide information about 5GS entities serving the region of interest, collected within NWDAF 200. For example, Figure 9 The interaction between two different NWDAF 200s (200a / 200b) is illustrated. In this case, the NWDAF 200 serving the region of interest is enhanced by the exact same service defined in Table 2 (i.e., the area of ​​interest context management (AoICM) service). In this case, the NWDAF service will be enhanced by a new service (i.e., the Nnwdaf_AoICM service).

[0271] Figure 9 Further details of an embodiment of operating mode 2 and the interaction of UDM, NRF, and NWDAF are shown.

[0272] In this embodiment, Figure 9 Step 0 is Figure 5 An embodiment of step 1d, as indicated by the arrows, shows a first network entity 200 (i.e., NWDAF 200) enhanced by the aggregation (e.g., aggregation of associated information) of 5GS entities serving the region of interest sending a request to a third network entity 220 (i.e., UDM and NRF). In this embodiment, the request follows a subscription-notification model for communication. Therefore, NWDAF 200 subscribes to UDM 220 and NRF 220 events related to the 5GS entities serving the region of interest controlled by these NFs. Figure 9 Steps 1 to 3 and step 5 in the diagram are shown Figure 2 An embodiment of step 1c in the example. Figure 9 Steps 4 and 6 in the diagram show Figure 5In the embodiment of step 1d, from the perspective of the UDM, the NRF sends a response to the requested (e.g., subscribed) changes of 5GS entities in the region of interest. Figure 9 Step 7 is Figure 5 An embodiment of step 1e in the example. Figure 9 Steps 9 and 10 are Figure 5 Examples of steps 2 and 3 in the process. Figure 9 Steps 8 and 11 also illustrate one possibility of how to trigger NWDAF 200 in the analysis output of NWDAF 200 to use the acquired services to 5GS entities in the region of interest.

[0273] at last, Figure 9 Steps 12a and 12b illustrate how an NWDAF 200 enhanced by centrally serving a 5GS entity serving a region of interest can provide services to other entities that also serve a 5GS entity serving a region of interest. In this case, the other entity can be another NWDAF instance.

[0274] Figure 10 A method 1000 for a first network entity 200 is illustrated. Method 1000 is used to generate analysis. Method 1000 includes step 1001, obtaining past and / or current association information 201 of a region of interest from a second network entity 210 or one or more third network entities 220. Additionally or alternatively, method 1000 includes step 1002, providing analysis information 202 based on the obtained association information 201.

[0275] Figure 11 A method 1100 for a second network entity 210 is illustrated. Method 1100 is used to support analysis generation. Method 1100 includes step 1101, in response to a first request 311 sent to one or more third network entities 220 and / or based on a first subscription by one or more third network entities 220, obtaining past and / or current association information 201 of a region of interest from one or more third network entities 220. Alternatively or additionally, method 1100 includes step 1102, obtaining change information 321 from one or more third network entities 220 when the lifecycle of one or more target elements related to the association information 201 provided by one or more third network entities 220 changes, wherein the one or more target elements are network entities or network attributes.

[0276] Figure 12A method 1200 for a third network entity 220 is illustrated. Method 1200 is used to support analysis generation. Method 1200 includes step 1201, providing past and / or current association information 201 of a region of interest to the first network entity 200 and / or the second network entity 210 in response to requests 401, 411 received from the first network entity 200 and / or the second network entity 210, and / or according to subscriptions of the first network entity 200 and / or the second network entity 210. Alternatively or additionally, method 1200 includes step 1202, providing association information 201 to the first network entity 200 and / or the second network entity 210 when one or more target elements associated with the association information 201 change, wherein the one or more target elements are network entities or network attributes.

[0277] The invention has been described in conjunction with various embodiments and implementations as examples. However, based on a study of the drawings and this disclosure, those skilled in the art will be able to understand and implement other variations in practice of the claimed invention. In this specification, the word "comprising" does not exclude other elements or steps, and "a" does not exclude a plurality.

Claims

1. A first network entity generated through analysis of a mobile network, characterized in that, The first network entity is used for: Obtain past and / or current association information of a region of interest from one or more third network entities, wherein the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; Provide analytical information based on the association information of the acquired region of interest.

2. The first network entity according to claim 1, characterized in that, Used for: Send a request for and / or subscribe to the association information of the region of interest to the one or more third network entities; In response to the request and / or according to the subscription, obtain the associated information of the region of interest and / or the transaction identifier of the region of interest from the one or more third network entities.

3. The first network entity according to claim 2, characterized in that: The request and / or subscription for associated information about the region of interest includes at least one of the following: – A target region of interest, which is a spatial region associated with the mobile network, from which the first network entity requests past and / or current association information of the target region of interest. – The target type of the one or more other network entities and / or network attributes, wherein the target type of the entity and / or attribute describes the type of entity or attribute that should be identified as mapping to or serving the target region of interest. – Transaction identifier for the region of interest –The identifier of the first network entity, – Time interval, which is a time window used to select one or more entities and / or attributes mapped to or serving the target region of interest.

4. The first network entity according to any one of claims 1 to 3, characterized in that, Used for: Sending multiple requests for and / or subscribing to association information of regions of interest to multiple third-party network entities; In response to the plurality of requests for association information of the region of interest and / or based on the subscription to the association information of the region of interest, the association information of the region of interest is obtained from the plurality of third network entities; Aggregate the obtained related information; Provide analytical information based on aggregated related information.

5. The first network entity according to any one of claims 1 to 4, characterized in that, Used for: From the obtained association information of the region of interest, determine one or more other network entities and / or network attributes that are mapped to or serve the region of interest. Select and / or retrieve data from one or more other network entities and / or network attributes identified. Provide analytical information based on selected and / or acquired data.

6. The first network entity according to any one of claims 1 to 5, characterized in that: The first network entity is a control plane entity, and the first network entity includes network data analysis functions.

7. A third network entity for supporting analysis-generated data, characterized in that, The third network entity is used for: In response to a request received from a first network entity, and / or based on the first network entity's subscription, provide the first network entity with past and / or current association information of the region of interest; Wherein, the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or When one or more target elements related to the association information change, the association information is provided to a first network entity, wherein the one or more target elements are network entities or network attributes.

8. The third network entity according to claim 7, characterized in that, The request received from the first network entity and / or the subscription of the first network entity includes at least one of the following: – A target region of interest, which is a spatial region associated with the mobile network, from which the first network entity requests past and / or current association information of the target region of interest. – The target type of the one or more other network entities and / or network attributes, wherein the target type of the entity and / or attribute describes the type of entity or attribute that should be identified as mapping to or serving the target region of interest. – Transaction identifier for the region of interest –The identifier of the first network entity, – Time interval, which is a time window used to select one or more entities and / or attributes mapped to or serving the target region of interest.

9. The third network entity according to claim 7 or 8, characterized in that: The third network entity is the control plane (NF), specifically including Session Management Function (SMF) and / or Access and Mobility Management Function (AMF) and / or Network Slice Selection Function (NSSF) and / or Network Openness Function (NEF) and / or Application Function (AF) and / or Network Storage Function (NRF).

10. A network entity, characterized in that, The network entity is a first network entity according to any one of claims 1 to 6, or a third network entity according to any one of claims 7 to 9, wherein: The association information of the region of interest and / or the association information of the aggregated region includes at least one of the following: – One or more user equipment (UE) identifiers and / or UE group identifiers mapped to or serving the region of interest. – One or more cell identifiers mapped to or serving the region of interest. – One or more tracking region identifiers mapped to or serving the region of interest. – One or more network slice identifiers mapped to or serving the region of interest. – One or more Network Function (NF) identifiers mapped to or serving the region of interest. –Identifiers of one or more NF sets mapped to or serving the region of interest. – One or more external entity identifiers mapped to or serving the region of interest. – One or more application identifiers mapped to or serving the region of interest. – One or more session identifiers mapped to or serving the region of interest. – One or more Quality of Service (QoS) profile identifiers mapped to or serving the region of interest. – One or more data network identifiers mapped to or serving the region of interest. – One or more Public Land Mobile Network (PLMN) identifiers mapped to or serving the region of interest.

11. A method for analyzing and generating a first network entity, characterized in that, The method includes: Obtain past and / or current association information of the region of interest from a second network entity or one or more third network entities. Wherein, the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; Provide analytical information, which is based on the acquired correlation information.

12. A method for supporting the analysis and generation of third network entities, characterized in that, The method includes: In response to a request received from a first network entity, and / or based on the first network entity's subscription, provide the first network entity with past and / or current association information of the region of interest; Wherein, the past and / or current association information indicates one or more other network entities and / or network attributes that were previously and / or currently mapped to or serve the region of interest; and / or When one or more target elements related to the association information change, the association information is provided to a first network entity, wherein the one or more target elements are network entities or network attributes.

13. A computer program product, characterized in that, Includes program code that, when run on a computer, performs the method according to claim 11 or 12.

14. A non-transitory storage medium storing executable program code, the program code including instructions for performing the method as claimed in claim 11 or 12.

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