Network slice analysis

Abstract

A method for providing network slice analytics is disclosed. The method includes operations of obtaining, by a first network entity, input data from one or more data sources in a network, processing, by the first network entity, the input data to obtain an output analysis, and providing the output analysis to one or more network analysis consumers. The input data includes information regarding one or more of UE registration at the network slice, establishment of PDU sessions at the network slice, and resource usage at the network slice. The output analysis includes information regarding one or more of UE load, PDU session load, and resource usage at the network slice.

Description

[Technical Field]

[0001] The present invention relates to a method, an apparatus, and a system for providing network slice analytics, more particularly, to a method, an apparatus, and a system for providing network slice load analysis in a 3GPP 5G network based on NWDAF. [Background technology]

[0002] Since the commercialization of 4G communication systems, efforts have been made to develop improved 5G or pre-5G communication systems to meet the increasing demand for wireless data traffic. Therefore, 5G or pre-5G communication systems are also called "Beyond 4G Networks" or "Post-LTE Systems."

[0003] 5G communication systems are expected to be implemented in higher frequency (mmWave) bands such as the 60 GHz band to achieve higher data rates. To reduce radio wave propagation loss and extend transmission distances, technologies being discussed for 5G communication systems include beamforming, massive multiple-input multiple-output (MIMO), full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, and large-scale antennas.

[0004] Additionally, in the 5G communication system, development is underway to improve the system network based on advanced small cells, cloud Radio Access Networks (cloud RAN), ultra-dense networks, device-to-device (D2D) communications, wireless backhaul, moving networks, cooperative communications, CoMP (Coordinated Multi-Points), and receiver interference cancellation.

[0005] For 5G systems, advanced coding modulation (ACM) methods such as FQAM (Hybrid FSK and QAM Modulation) and SWSC (Sliding Window Superposition Coding) and advanced access technologies such as FBMC (Filter Bank Multi Carrier), NOMA (non-orthogonal multiple access), and SCMA (sparse code multiple access) are being developed.

[0006] This document makes reference to the following documents: [1]3GPP TS23.501 “System Architecture for the 5G System; Stage 2” [2]3GPP TS23.288 “Architecture enhancements for 5G System (5GS) to support network data analytics services” [3]3GPP TS23.502:Procedures for the 5G System (5GS), Rel-16 (06-2020).

[0007] Various acronyms, abbreviations and definitions used herein are defined at the end of the Detailed Description of the Invention.

[0008] There is an increasing desire to improve the performance of communication networks so that network operators can improve user experience without unnecessarily investing in excess equipment. This means that network operators are eager to optimize the performance of their installed infrastructure. Until now, network optimization has primarily been a manually managed process, with skilled operators adjusting network parameters as needed. Over time, more automation has been introduced. Recently, artificial intelligence (AI) and machine learning (ML) techniques have been adopted. In fifth-generation (5G) networks, various network structures and protocols have been adopted to improve user experience. Therefore, there is a desire to fully utilize these new structures and protocols to improve network performance and / or user experience.

[0009] AI has been identified as a key enabler for 5G end-to-end network automation in all network domains, including the radio access network (RAN), core network (CN), and domains covered by the standardization process for management systems, also known as operations, administration, and maintenance (OAM). Accordingly, standardization and industry organizations are in the process of developing supporting specifications for data analytics so that AI models can support the increasingly complex tasks of autonomously operating and managing networks.

[0010] From the RAN perspective, the pioneering O-RAN Alliance was established in 2018 by leading operators with the vision of developing open specifications for an open and efficient RAN that utilizes AI to automate various network functions (NFs) and reduce operating expenses (OPEX). Furthermore, standardized support for data analytics by 3GPP has already progressed in Rel-16, particularly on the CN side and control plane. As a network function that follows the service-based architecture principles of 5GC, a new data analytics framework anchored in the so-called network data analytics function (NWDAF) within 5GC has been defined with the aim of enhancing multiple control plane functions in the network. Furthermore, in the OAM aspect, a management data analytics service (MDAS) has also been specified by 3GPP to help handle the long-term management aspects of the network [1]. The joint operation of the RAN analytics entity, the network data analytics function (NWDAF), and the MDAS is still underway within the relevant organizations.

[0011] The following are defined in 3GPP 5GS (e.g., 3GPP TS23.501): A Network Slice (NS) is defined as a logical network that provides specific network functions and network characteristics. A Network Slice Instance (NSI) is defined as a collection of network function instances and the necessary resources (e.g., computing, storage, and network resources) that form a deployed NS. A Network Function (NF) is defined as a 3GPP-adopted or 3GPP-defined processing function in the network, which defines functional operations and 3GPP-defined interfaces. An NF in 3GPP 5GC includes the above-mentioned NWDAF (as defined in 3GPP TS23.288).

[0012] The NWDAF represents an operator-managed network analysis logic function that provides slice-specific network data analysis to the NF. The 5GS Stage 2 architecture extensions to support network data analysis services in 5GC are defined in 3GPP TS 23.288 (e.g., V16.4.0). The NWDAF is part of the architecture specified in 3GPP TS 23.501 (e.g., V16.5.1).

[0013] The NWDAF service is used to expose load level analysis from the NWDAF to consumer NFs. The analysis can be filtered by (i) network slice instance, (ii) load level threshold; the NWDAF reports when the load level crosses a threshold provided in the analytics subscription; if no threshold is provided in the subscription, the reporting (notification action) is considered periodic.

[0014] The NWDAF provides load level information to NFs at the network slice instance level. The NWDAF does not need to be aware of the current subscribers using the slice. The NWDAF notifies slice-specific network status analysis information to NFs that subscribe to it. NFs may collect slice-specific network status analysis information directly from the NWDAF. This information is not subscriber-specific.

[0015] What is desired is a technique that improves the provision of data analytics in communications networks, for example, the provision of load data analytics per network slice using NWDAF.

[0016] The above information is presented solely as background information to aid in the understanding of the present invention, and no determination has been made, or any assertion made, as to whether any of the above is applicable as prior art with respect to the present invention. Summary of the Invention [Problem to be solved by the invention]

[0017] It is an object of the present invention to address, solve, and / or mitigate, at least in part, at least one of the problems and / or disadvantages associated with the related art, e.g., at least one of the problems and / or disadvantages described herein. It is an object of the present invention to provide at least one advantage over the related art, e.g., at least one of the advantages described herein.

[0018] Other aspects, advantages, and salient features will become apparent to those skilled in the art from the following detailed description, taken in conjunction with the drawings, which disclose examples of the invention. [Means for solving the problem]

[0019] A particular example of the present invention provides network slice analytics, the method including: obtaining, by a first network entity (e.g., NWDAF), input data from one or more data sources in a network; processing, by the first network entity, the input data to obtain output analysis; and providing the output analysis to one or more network analysis consumers (e.g., NFs), wherein the input data includes information regarding one or more of UE registration at the network slice, establishment of PDU sessions at the network slice, and resource usage at the network slice, and / or the output analysis includes information regarding one or more of UE load, PDU session load, and resource usage at the network slice.

[0020] In a particular example of the present invention, the one or more data sources include one or more of a 5GC NF, AMF, SMF, OAM, and NRF.

[0021] In a particular example of the present invention, the input data includes one or more of information regarding the number of UE registrations in the network (e.g., from an AMF), information regarding the number of PDU session establishments in the network (e.g., from an SMF), information indicating the maximum number of UEs allowed in a network slice (e.g., from an OAM), information indicating the maximum number of PDU sessions allowed in a network slice (e.g., from an OAM), information indicating resource usage of a network slice instance (e.g., from an OAM and / or an NRF), and time information (e.g., a timestamp) associated with one or more of the above (e.g., from a 5GC NF).

[0022] In a particular example of the present invention, the output analysis is obtained per network slice or per network slice instance.

[0023] In a particular example of the present invention, the output analysis includes one or more of information indicating the UE load at the network slice instance and / or the network slice, and the number of times the UE load at the network slice instance or the network slice exceeds (exceeds) a particular threshold during a particular period of time.

[0024] In a particular example of the present invention, the information indicating the UE load includes a value between a lower limit (e.g., 0) corresponding to a lower limit load (e.g., zero load) and an upper limit (e.g., 1) corresponding to an upper limit load (e.g., a UE allocation amount of a network slice instance and / or a network slice).

[0025] In a particular example of the present invention, the output analysis includes one or more of information indicating a PDU session load at the network slice instance and / or network slice, and the number of times that the PDU session load at the network slice instance and / or network slice exceeds a particular threshold during a particular period of time.

[0026] In a particular example of the present invention, the information indicating the PDU session load includes a value between a lower limit (e.g., 0) corresponding to a lower limit load (e.g., zero load) and an upper limit (e.g., 1) corresponding to an upper limit load (e.g., an allocated amount of PDU sessions for a network slice instance and / or network slice).

[0027] In certain examples of the present invention, the output analysis includes one or more of information indicative of a network slice instance and / or resource usage on the network slice, and a number of times that resource usage on the network slice exceeds a certain threshold during a network slice instance and / or a certain period of time.

[0028] In a particular example of the present invention, the output analysis includes time information (e.g., one or more timestamps) indicating one or more times that the UE load at the network slice instance and / or network slice, the PDU session load at the network slice instance and / or network slice, and / or the resource usage at the network slice instance and / or network slice crosses a corresponding threshold.

[0029] In a particular example of the present invention, the output analysis includes one or more of information identifying one or more network slices corresponding to the output analysis, information identifying one or more network slice instances corresponding to the output analysis, and information indicating a list of one or more network slice instances within the network slice corresponding to the output analysis.

[0030] In certain examples of the present invention, the output analysis comprises statistics and / or predictions.

[0031] In a particular example of the present invention, the one or more network analysis consumers include one or more of a Policy Control Function (PCF), a Charging Function (CHF), a Network Slice Selection Function (NSSF), and an AMF.

[0032] In certain examples of the present invention, the output analytics are obtained by applying one or more analytics filters (eg, specified in an analytics subscription request message).

[0033] In a particular example of the present invention, the one or more analysis filters are applied based on one or more of one or more network slice identities (e.g., S-NSSAI), one or more network slice instance identities (e.g., NSI ID), one or more load level thresholds, one or more regions of interest (e.g., TAI), and one or more GST parameters of interest.

[0034] In certain examples of the present invention, the method further includes an act of receiving a message from a network analysis consumer requesting a network analysis (eg, a subscription request message).

[0035] In a particular example of the present invention, the operation of obtaining the input data includes an operation of subscribing to input data from an OAM (e.g., network slice allocations for UEs and PDU sessions and / or resource usage related information for network slice instances), an operation of subscribing to input data from an AMF (e.g., the number of UEs currently registered in a particular network slice), and / or an operation of subscribing to input data from an SMF (e.g., the number of PDU sessions currently registered in a particular network slice).

[0036] In a particular example of the present invention, the operation of obtaining the input data includes an operation of obtaining, from the NRF, information of one or more network entity (e.g., AMF, SMF, and / or NSSF) instances associated with one or more specified analysis filters, an operation of obtaining, from the NSSF, one or more network slice instance identifiers corresponding to a specified network slice, and / or an operation of obtaining, from the NRF, information for deriving a resource usage analysis (e.g., for a network slice instance).

[0037] In a particular example of the present invention, there is provided a first network entity (eg, NWDAF) configured to operate in accordance with any of the preceding examples.

[0038] In a particular example of the present invention, the network includes a first network entity, one or more data sources, and one or more network analytics consumers.

[0039] A particular example of the invention is a computer program comprising instructions which, when executed by a computer or processor, cause said computer or processor to carry out a method according to any of the examples above.

[0040] A particular example of the invention is a computer or processor readable data carrier storing a computer program. [Effects of the Invention]

[0041] According to the present invention, it is possible to improve the provision of load data analysis per network slice using NWDAF. [Brief explanation of the drawings]

[0042] [Figure 1] 1 illustrates an exemplary procedure supporting NWDAF-based slice load analysis. [Figure 2] FIG. 2 is a block diagram of exemplary network entities that may be used in certain examples of the present invention. [Figure 3] 1 is a flowchart of a specific example of a Network Data Analysis Function (NWDAF). DETAILED DESCRIPTION OF THE INVENTION

[0043] The following detailed description of embodiments of the present invention, with reference to the drawings, is provided to facilitate a comprehensive understanding of the present invention. Although the detailed description includes various specific details to facilitate understanding, they shall be considered merely as examples. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present invention.

[0044] The same or similar components may be shown in different drawings but are designated by the same or similar reference numbers.

[0045] Detailed descriptions of techniques, structures, configurations, functions, or processes known in the art are omitted for clarity and conciseness, and to avoid obscuring the gist of the present invention.

[0046] The terms and words used in this specification are not limited to their bibliographical or standard meanings, but are merely used to enable a clear and consistent understanding of the present invention.

[0047] In the description herein, the terms "comprise," "include," and "contain," and variations of these terms, such as "comprising" and "comprises," mean "including but not limited to" and are not intended to exclude (or exclude) other features, elements, components, integers, steps, processes, operations, functions, characteristics, attributes, and / or groups thereof.

[0048] In the description herein, singular forms such as "a," "an," and "the" include plural forms unless the context requires otherwise. For example, a reference to an "object" includes a reference to one or more of such objects.

[0049] In the description herein, language of the general form "X for Y" (where Y is any action, process, operation, function, activity, or step, and X is any means for performing that action, process, operation, function, activity, or step) includes, but is not necessarily exclusive of, means for which X is particularly adapted, configured, or arranged to perform Y.

[0050] It is to be understood that any feature, element, component, integer, step, process, operation, function, characteristic, attribute, and / or group thereof described or disclosed in connection with a particular aspect, embodiment, or example of the invention is applicable to any other aspect, embodiment, or example described herein, unless separately compatible therewith.

[0051] Particular examples of the present invention provide methods, apparatus, and systems for providing network slice analysis. The following examples are applicable to 3GPP 5G and use terminology related to 3GPP 5G. For example, particular examples of the present invention provide methods, apparatus, and systems for providing network slice analysis in an NWDAF-based 3GPP 5G network. However, those skilled in the art will understand that the techniques disclosed herein are not limited to these examples or to 3GPP 5G, but may be applied to any suitable system or standard, for example, one or more existing and / or next-generation wireless communication systems or standards.

[0052] For example, the functionality and other features of various network entities disclosed herein may be applied to corresponding or equivalent entities or features in other communication systems or standards. Corresponding or equivalent entities or features may be considered entities or functions that perform the same or similar role, function, operation, or purpose within a network. For example, in the following example, the functionality of the NWDAF may be applied to any other suitable type of entity that provides network analysis.

[0053] Those skilled in the art will appreciate that the present invention is not limited to the specific examples disclosed herein.

[0054] - The techniques disclosed herein are not limited to 3GPP 5G;

[0055] - in the examples disclosed herein, one or more entities are replaced by one or more alternative entities that perform equivalent or corresponding functions, processes, or operations;

[0056] - In the examples disclosed herein, one or more messages are replaced with one or more alternative messages, signals, or other types of information carriers that communicate equivalent or corresponding information;

[0057] - one or more additional elements, entities, and / or messages may be added to the examples disclosed herein;

[0058] - In certain instances, one or more non-essential elements, entities, and / or messages may be omitted;

[0059] - a function, process, or operation of a particular entity in one example is split into two or more separate entities in another example;

[0060] - functions, processes, or actions of two or more separate entities in one example may be performed by a single entity in another example;

[0061] - Information conveyed by a particular message in one example may be conveyed by two or more separate messages in another example;

[0062] - Information conveyed by two or more separate messages in one example may be conveyed by a single message in another example;

[0063] - the order in which the operations are performed is changed in other examples where possible; and

[0064] - The transmission of information between network entities is not limited to the particular formats, types, and / or sequences of messages described in connection with the examples disclosed herein.

[0065] Particular examples of the present invention may be provided in the form of an apparatus / device / network entity configured to perform one or more defined network functions and / or methods therefor, or a system (e.g., a network) including one or more such apparatus / device / network entities and / or methods therefor, and a method therefor.

[0066] The network includes one or more of a Network Data Analytics Function (NWDAF) entity, an Access and Mobility Management Function (AMF) entity, a Session Management Function (SMF) entity, a Network Slice Selection Function (NSSF) entity, a Network Repository Function (NRF) entity, and an Operation and Maintenance (OAM) entity. The network may include one or more service consumers (including one or more of the above entities and / or one or more other entities) that receive analytics from the NWDAF. Those skilled in the art will understand that the network may omit one or more of the above entities and / or include one or more additional entities.

[0067] A particular network function may be embodied as a network element on dedicated hardware, as a software instance running on dedicated hardware, or as a virtualized function instantiated on a suitable platform, e.g., a cloud infrastructure. An NF service is defined as a function exposed by an NF and consumed by other authorized NFs through a service-based interface.

[0068] As described above, there is a need for techniques to improve the provision of data analytics in communication networks, for example, the provision of load data analytics per network slice using NWDAF.

[0069] Particular examples of the present invention address a problem in the context of network automation, namely the use of data analytics for slice service level agreement (SLA) guarantees. Particular examples of the present invention therefore provide the ability for service consumers to subscribe to such analytics and receive statistics and / or forecasts regarding the load of said slices.

[0070] The slice load level data analysis described in Rel-16 TS 23.288 [2] refers to the network slice instance level and is provided in two possible forms: (i) if a load threshold is provided as an analysis filter by the consumer NF in the slice load subscription message, the NWDAF notifies the consumer NF whenever such a threshold crossing occurs, and (ii) if no load threshold is provided by the consumer NF, the NWDAF provides periodic notifications to the consumer NF reporting the load of the network slice instance.

[0071] The current status of load analysis specification for network slice instances has several issues.

[0072] It is unclear what metric should be used to represent the load value of a network slice instance and how to derive such a value. For example, the load can be measured in terms of UE registrations, PDU sessions, resource usage, etc. Even if the derivation itself depends on the specific implementation, the specification should provide support for such functionality, for example, if it is assumed that the load of a network slice instance can be derived from the NF load value in a proprietary way.

[0073] It is currently unclear whether it is necessary to determine the load per network slice instance and / or per network slice.

[0074] NWDAF is assumed to provide statistics and forecasts for each analysis type. However, for network slice instances, it is currently unclear whether load statistics and forecasts are provided, and if so, whether load values ​​are provided directly and / or whether load thresholds are exceeded.

[0075] Several network-related functions (e.g., slice SLA guarantees, slice load balancing) can greatly benefit from using the slice load data analysis provided by the NWDAF. Therefore, specific examples of the present invention provide various network optimizations by providing the specification of slice load analysis, which is currently missing from the related specification [Non-Patent Document 2].

[0076] In a particular example of the present invention, the load analysis of a network slice is specified by specifying input data, output analysis, and procedures of a data analysis type.

[0077] A general description of specific examples is provided first, including one or more of the following:

[0078] In a particular example, the NWDAF may provide slice load level information (e.g., statistics and / or predictions) to the NF at the network slice instance level based on the number of UEs and / or PDU sessions subscribed to the slice instance.

[0079] In certain examples, the NWDAF may provide information regarding resource usage based on input data from the OAM.

[0080] In certain examples, the NWDAF may provide information regarding the load across the network slice.

[0081] In certain examples, the NWDAF may not need to know the identity of the subscribers using the slice. The NWDAF may notify slice-specific network status analysis information to NFs that subscribe to it. The NFs may collect slice-specific network status analysis information directly from the NWDAF. This information may not be subscriber-specific.

[0082] In a particular example, the NWDAF service defined in clauses 7.2 and 7.3 of TS 23.288 [2] is used to expose slice load level analysis from the NWDAF to consumer NFs (PCF, CHF, NSSF, AMF, etc.).

[0083] In a specific example, one or more of the following analysis IDs are used for slice load level related network data analysis:

[0084] Load level information

[0085] In particular examples, one or more of the following analytics filters may be included in the associated message by the consumer (eg, Nnwdaf_AnalyticsSubscription_Subscribe and Nnwdaf_AnalyticsInfo_Request service actions):

[0086] ·S-NSSAI and NSI ID Load level threshold Area of ​​interest, i.e., TAI of the geographical area of ​​interest GST parameters of interest

[0087] In certain instances, the use of the NSI ID in the network may be optional and dependent on the operator's deployment choices. If used, the NSI ID is associated with the S-NSSAI.

[0088] In a particular example, the analysis filter for a GST parameter may refer to the number of terminals, the number of connections (i.e., PDU sessions), or both.

[0089] Next, an exemplary specification of input data and output analysis is described.

[0090] Input data

[0091] Particular examples of the present invention use one or more of the input data set forth below in Table 1. Those skilled in the art will appreciate that the exact form of input data and / or source of such information is not necessarily limited to the particular example set forth in Table 1.

[0092] [Table 1]

[0093] Table 1 shows possible source entities for input data collection that can be considered authoritative input data sources for the identified data. However, in certain examples, the entries in Table 1 with an asterisk (*) in the source entity, i.e., AMF, SMF, and OAM, are replaced with fewer entities, e.g., a single entity (including three of them) that contains all four input data types in the above table, as a way to simplify the signaling overhead of the data collection procedure. Various examples of the present invention handle such (e.g., default) configurations as above, as well as any other possible optimizations.

[0094] In a particular example, for resource usage of a network slice instance, the NWDAF may collect data directly from the OAM, or may receive a list of configured NF instance identifiers of the network slice instance from the OAM, and the NWDAF may connect to the NRF to obtain resource usage data for each NF instance whose identifier is provided by the OAM.

[0095] In Rel-16, NWDAF was able to provide threshold-based notifications (i.e., a notification is sent whenever a load threshold is reached in a network slice instance). However, its implementation was not feasible because the metric to which the load threshold refers (e.g., resource usage, UE registration, PDU session, etc.) was not specified. Furthermore, while "periodic" notifications are presumed to be enabled, there is no specification of what the notifications refer to, since load is an abstract concept.

[0096] A particular example of the present invention extends the above concept in two ways:

[0097] · Threshold-based notifications may still be propagated by the NWDAF whenever a service consumer indicates that it is an output format of interest.

[0098] If the Service Consumer is interested in receiving NWDAF-compliant statistics and / or forecasts, such as the remainder of data analysis (regular or one-off), the following specifications apply:

[0099] If a threshold is used to generate the analysis, the threshold may be provided by the service consumer. If a threshold is not provided, threshold-related output analysis may be omitted.

[0100] Output Analysis

[0101] Particular examples of the present invention generate one or more portions of the output analysis according to Table 2. Those skilled in the art will appreciate that the exact form of the output analysis is not necessarily limited to the particular example shown in Table 2.

[0102] [Table 2]

[0103] In certain examples, if multiple network slice instances are not configured for the S-NSSAI or an NSI ID is not available, only one slice instance service experience entry may be provided, in which case the NSI ID may not be provided and the slice instance service experience may indicate the service experience of the S-NSSAI.

[0104] In certain examples of the present invention, the output analysis may additionally or alternatively include one or more of the items shown in Table 3 and / or Table 4 below:

[0105] 1) Output analysis on resource usage per network slice instance:

[0106] [Table 3]

[0107] 2) The output analysis for each network slice (i.e., S-NSSAI) is as follows:

[0108] [Table 4]

[0109] Next, an exemplary procedure for the NWDAF to derive a slice load analysis will be described with reference to FIG. 1. Various operations in the procedure are described below. In various examples, certain operations (e.g., those indicated by dotted arrows) may be omitted. Those skilled in the art will understand that the present invention is not limited to the specific example of FIG. 1.

[0110] 1. A service consumer subscribes to slice load analytics, for example, via the Nnwdaf_AnalyticsSubscription_Subscribe or Nnwdaf_AnalyticsInfo_Request service operations. In addition, the service consumer provides various information, such as an "Analytics ID = Load level information" and a set of event filters. An analytics filter (e.g., a mandatory analytics filter) may include an S-NSSAI and an area of ​​interest. Other filters (e.g., optional event filters) may include one or more NSI IDs and a load threshold.

[0111] 2. [Optional] If the NWDAF does not already have the above information, find the AMF, SMF, and NSSF instances related to the analysis filters provided in the analysis subscription, e.g., from the NRF.

[0112] 3. [Optional] If the NSI ID is not provided in the analysis subscription by the service consumer, the NWDAF invokes an operation (such as the Nnssf_NSSelection_Get service operation) from the NSSF to obtain the NSI ID corresponding to the S-NSSAI in the subscription.

[0113] 4a. The NWDAF subscribes to input data from the OAM, for example, according to the procedure defined in section 6.2.3.2 of TS 23.288 [2]. The input data may include, for example, information about the resource usage of the network slice instance and / or its constituent NF instances, as well as network slice allocations for UEs and PDU sessions.

[0114] 4b. [Optional] The NWDAF collects input data from the NRF to derive slice instance resource usage statistics and predictions for network slice instances (e.g., see Table 6.5.2-1 of TS 23.288 [2]).

[0115] 5. The NWDAF subscribes to the AMF's Event Exposure Service to collect data on the number of UEs currently registered in a particular network slice and, if available, in its configured network slice instances. UE access and mobility information events are used for purposes as defined in TS 23.502 [3], for example, using the S-NSSAI as an event filter and, if available, the NSI ID. If necessary, the NWDAF collects the corresponding UE ID.

[0116] 6. The NWDAF subscribes to the SMF's event exposure service and collects data on the number of PDU sessions currently registered in a particular network slice and, if available, its constituent network slice instances. PDU session-related events are used for purposes such as those defined in TS 23.502 [3]. Possible event filters include S-NSSAI, NSI ID, UE ID, etc.

[0117] 7. NWDAF derives slice load analysis.

[0118] 8. The NWDAF communicates the analysis to the service consumer, for example by invoking the Nnwdaf_AnalyticsSubscription_Notify or Nnwdaf_AnalyticsInfo_Request response service operations.

[0119] A particular example of the present invention provides a method for providing network slice analytics, the method including: an operation of obtaining, by a first network entity (e.g., an NWDAF), input data from one or more data sources in a network; an operation of processing, by the first network entity, the input data to obtain an output analysis; and an operation of providing the output analysis to one or more network analysis consumers (e.g., NFs), wherein the input data includes information related to one or more of: UE registration at the network slice; establishment of a PDU session at the network slice; and resource usage at the network slice, and / or the output analysis includes information related to one or more of: UE load; PDU session load; and resource usage at the network slice.

[0120] In a particular example, the one or more data sources include one or more of a 5GC NF, AMF, SMF, OAM, and NRF.

[0121] In a particular example, the input data includes one or more of: information regarding the number of UE registrations in the network (e.g., from an AMF); information regarding the number of PDU session establishments in the network (e.g., from an SMF); information indicating the maximum number of UEs allowed on a network slice (e.g., from an OAM); information indicating the maximum number of PDU sessions allowed on a network slice (e.g., from an OAM); information indicating resource usage of a network slice instance (e.g., from an OAM and / or an NRF); and time information (e.g., a timestamp, etc.) associated with one or more of the above (e.g., from a 5GC NF).

[0122] In certain examples, the above output analysis is obtained for each network slice and / or for each network slice instance.

[0123] In a particular example, the output analysis includes one or more of: information indicating the UE load at the network slice instance and / or network slice; and the number of times the UE load at the network slice instance or network slice exceeds (exceeds) a particular threshold during a particular period of time.

[0124] In a particular example, the information indicating the UE load includes a value between a lower limit (e.g., 0) corresponding to a lower limit load (e.g., zero load) and an upper limit (e.g., 1) corresponding to an upper limit load (e.g., a UE allocation amount of a network slice instance and / or network slice).

[0125] In certain examples, the output analysis includes one or more of: information indicating the PDU session load on the network slice instance and / or network slice; and the number of times the PDU session load on the network slice instance and / or network slice exceeds a certain threshold during a certain period of time.

[0126] In a particular example, the information indicating the PDU session load includes a value between a lower limit (e.g., 0) corresponding to a lower limit load (e.g., zero load) and an upper limit (e.g., 1) corresponding to an upper limit load (e.g., PDU session quota of a network slice instance and / or network slice).

[0127] In certain examples, the output analysis includes one or more of: information indicating resource usage on the network slice instance and / or network slice; and the number of times resource usage on the network slice instance and / or network slice exceeds a certain threshold during a certain period of time.

[0128] In certain examples, the output analysis includes UE load at the network slice instance and / or network slice; PDU session load at the network slice instance and / or network slice; and / or time information (e.g., one or more time stamps) indicating one or more times that resource usage at the network slice instance and / or network slice exceeds a corresponding threshold.

[0129] In certain examples, the output analysis includes one or more of: information identifying one or more network slices corresponding to the output analysis; information identifying one or more network slice instances corresponding to the output analysis; and information indicating a list of one or more network slice instances within the network slice corresponding to the output analysis.

[0130] In certain instances, the output analysis may include statistics and / or predictions.

[0131] In a particular example, the one or more network analysis consumers include one or more of: PCF; CHF; NSSF; and AMF.

[0132] In certain examples, the output analytics are obtained by applying one or more analytics filters (eg, specified in the analytics subscription request message).

[0133] In particular examples, the one or more analysis filters are applied based on one or more of: one or more network slice identities (e.g., S-NSSAI); one or more network slice instance identities (e.g., NSI ID); one or more load level thresholds; one or more regions of interest (e.g., TAI); and one or more GST parameters of interest.

[0134] In certain examples, the method further includes an act of receiving a message from a network analysis consumer requesting a network analysis (e.g., a subscription request message).

[0135] In a particular example, the operation of obtaining the input data includes an operation of subscribing to input data from an OAM (e.g., network slice allocations for UEs and PDU sessions, and / or resource usage related information for network slice instances); an operation of subscribing to input data from an AMF (e.g., the number of UEs currently registered in a particular network slice); and / or an operation of subscribing to input data from an SMF (e.g., the number of PDU sessions currently registered in a particular network slice).

[0136] In certain examples, the operation of obtaining the input data includes an operation of obtaining, from the NRF, information on one or more network entity (e.g., AMF, SMF, and / or NSSF) instances associated with one or more specified analysis filters; an operation of obtaining, from the NSSF, one or more network slice instance identifiers corresponding to specified network slices; and / or an operation of obtaining, from the NRF, information for deriving resource usage analysis (e.g., network slice instances).

[0137] Particular examples of the present invention provide a first network entity (e.g., NWDAF) configured to operate according to any of the examples disclosed herein.

[0138] A particular example of the present invention provides a network including a first network entity according to the previous example, one or more data sources, and one or more network analytics consumers.

[0139] Particular examples of the present invention provide a computer program comprising instructions that, when the computer program is executed by a computer or processor, cause the computer or processor to perform a method according to any of the examples disclosed herein.

[0140] A particular example of the invention provides a computer or processor readable data carrier storing a computer program according to the previous example.

[0141] A particular example of the present invention provides a unit for use in a communications network operable to receive input from at least one data source associated with a network slice, process the received input data, and output slice load data analysis associated with the network slice.

[0142] Particular examples of the present invention provide methods and apparatus for providing data analysis per network slice and network slice instance so as to achieve improved network performance and user experience.

[0143] In a particular example, the unit is a network data analytics function (NWDAF).

[0144] Figure 2 is a block diagram of exemplary network entities used in examples of the present invention. For example, a service consumer, an NWDAF, an AMF, an SMF, an NSSF, an NRF, an OAM, and / or other NFs may be provided in the form of the network entities shown in Figure 2. Those skilled in the art will understand that the network entities shown in Figure 2 may be implemented, for example, as network elements on dedicated hardware, as software instances running on dedicated hardware, or as virtualized functions instantiated on a suitable platform, for example, on a cloud infrastructure.

[0145] Entity 200 includes a processor (or controller) 201, a transmitter 203, and a receiver 205. Receiver 205 is configured to receive one or more messages or signals from one or more other network entities. Transmitter 203 is configured to transmit one or more messages or signals to one or more other network entities. Processor 201 is configured to perform one or more operations and / or functions as described above. For example, processor 201 is configured to perform operations of a service consumer, NWDAF, AMF, SMF, NSSF, NRF, OAM, and / or other NFs.

[0146] 3 is a flow diagram of a specific example, in which the unit is a network data analysis function (NWDAF). To provide the data analysis for each network slice and network slice instance, the NWDAF acquires input data from one or more data sources in the network by a first network entity (302), processes the input data by the first network entity to obtain output analysis (303) (the input data includes information related to one or more of UE registration in the network slice, establishment of PDU sessions in the network slice, and resource usage in the network slice), and provides the output analysis to one or more network analysis consumers (304) (the output analysis includes information related to one or more of UE load, PDU session load, and resource usage on the network slice).

[0147] The NWDAF method and apparatus may be further configured to receive a message from a network analysis consumer requesting a network analysis.

[0148] The NWDAF method and apparatus may be further configured to receive a message from a network analysis consumer requesting a network analysis.

[0149] The above NWDAF method and apparatus may be further configured to subscribe to input data from an OAM, an AMF, or an SMF.

[0150] The above-mentioned NWDAF method and apparatus may be further configured to obtain, from the NRF, information of one or more network entity instances associated with one or more specified analysis filters, or to obtain, from the NSSF, one or more network slice instance identifiers corresponding to a specified network slice, or to obtain, from the NRF, information for deriving a resource usage analysis.

[0151] The techniques described herein can be implemented using any suitably configured device and / or system. Such a device and / or system may be configured to perform a method according to any aspect, embodiment, or example disclosed herein. Such a device may include one or more elements, such as one or more receivers, transmitters, transceivers, processors, controllers, modules, units, etc., each configured to perform one or more corresponding processes, operations, and / or methods to implement the techniques described herein. For example, operation / function X is performed by a module configured to perform X (or an X module). One or more elements may be implemented in hardware, software, or any combination of hardware and software.

[0152] It should be understood that examples of the present invention can be implemented in the form of hardware, software, or any combination of hardware and software. Any such software can be stored in the form of volatile or non-volatile storage, for example, in the form of a storage device such as a ROM, whether erasable or rewritable, or in memory such as a RAM, memory chip, device, or integrated circuit, or on an optically or magnetically readable medium such as a CD, DVD, magnetic disk, or magnetic tape.

[0153] It will be understood that storage devices and storage media are embodiments of machine-readable storage suitable for storing a program or programs that, when executed, include instructions to implement particular examples of the present invention. Particular examples therefore provide a program including code for implementing a method, apparatus, or system according to any example, embodiment, aspect, and / or claim disclosed herein, and / or machine-readable storage for storing such a program. Furthermore, such a program may be transmitted electronically over any medium, such as, for example, a communications signal transmitted over a wired or wireless connection.

[0154] Although the present invention has been shown and described with reference to particular examples, it will be understood by those skilled in the art that various changes in form and detail can be made therein without departing from the spirit and scope of the invention.

[0155] Acronyms, Abbreviations, and Definitions

[0156] The following acronyms, abbreviations, and definitions are used herein:

[0157] 3GPP: 3rd Generation Partnership Project 5G: 5th Generation 5GC: 5G Core Network 5GS: 5G System AI:Artificial Intelligence AMF: Access and Mobility Management Function CHF: Charging Function CN: Core Network GST: Generic Slice Template ID: Identifier / Identity MDAS: Management Data Analytics Service ML: Machine Learning NF: Network Function NRF: Network Repository Function NWDAF: Network Data Analytics Function NS: Network Slice NSI: Network Slice Instance NSSF: Network Slice Selection Function OAM: Operation and Maintenance OPEX: Operating Expenses PCF: Policy Control Function PDU: Protocol Data Unit RAN: Radio Access Network Rel: Release SLA: Service Level Agreement SMF: Session Management Function S-NSSAI: Single Network Slice Selection Assistance Information TAI: Tracking Area Identifier TS: Technical Specification UE: User Equipment [Explanation of symbols]

[0158] 200 entities 201 processor 203 Transmitter 205 Receiver

Claims

1. A method for providing analysis of network slices performed by a network data analytics function (NWDAF), comprising: receiving a subscription request from a consumer, the subscription request including an analytics filter; searching for a network function (NF) associated with the analysis filter; Obtaining first input data including information about a user equipment (UE) registration from an access and mobility management function (AMF) of a network; obtaining second input data including information related to a protocol data unit (PDU) session setup from a session management function (SMF) of the network; An operation of obtaining third input data including resource utilization information of a network slice instance from a network repository function (NRF) of the network; providing the output analytics to one or more network analytics consumers; The information regarding the UE registration includes information regarding the number of UE registrations in the network slice instance; The output analysis First information regarding the UE for the network slice instance; Second information regarding a PDU session for the network slice instance; Including resource usage in the network slice instance, The NF includes at least one of the AMF, a session management function (SMF), and a network slice selection function (NSSF).

2. the first input data includes information indicating a maximum number of UEs allowed in a network slice; 2. The method of claim 1, wherein the second input data includes information indicating a maximum number of PDU sessions allowed in a network slice.

3. The method of claim 1 , wherein the output analysis is obtained per network slice or per network slice instance.

4. The output analysis Information regarding the UE in the network slice instance or network slice; or The number of times the network slice instance or the UE at the network slice exceeds a certain threshold during a certain time period.

2. The method of claim 1, comprising one or more of:

5. The output analysis Information regarding the PDU session in the network slice instance or network slice; or The number of times the PDU session in the network slice instance or the network slice exceeds a certain threshold during a certain time period.

2. The method of claim 1, comprising one or more of:

6. The output analysis 2. The method of claim 1, wherein the resource usage at the network slice instance or the network slice includes a number of times exceeding a particular threshold during a particular period of time.

7. The output analysis 2. The method of claim 1, further comprising information indicating a list of one or more network slice instances within the network slice corresponding to the output analysis.

8. The one or more network analytics consumers:

2. The method of claim 1, comprising one or more of a Policy Control Function (PCF), a Charging Function (CHF), a Network Slice Selection Function (NSSF), or an AMF.

9. the output analysis is obtained by applying one or more analysis filters; The one or more analysis filters: Identification of one or more network slices; Identification of one or more network slice instances; one or more load level thresholds; one or more regions of interest, or One or more generic slice template (GST) parameters of interest 10. The method of claim 1, wherein the method is applied based on one or more of:

10. 10. The method of claim 1, further comprising an act of receiving a message from a network analysis consumer requesting a network analysis.

11. The operation of acquiring the third input data includes: obtaining, from said NRF, information of one or more network entity instances associated with one or more applied analysis filters; or obtaining information from the NRF for deriving a resource usage analysis; 2. The method of claim 1, comprising:

12. A network providing analysis of network slices performed by a network data analytics function (NWDAF), comprising: one or more data sources and one or more network analytics consumers; The NWDAF is receiving a subscription request from a consumer that includes an analytics filter; retrieving a network function (NF) associated with the analysis filter; Obtain first input data including information about a user equipment (UE) registration from an access and mobility management function (AMF) of a network; Obtain second input data including information about a protocol data unit (PDU) session setup from a session management function (SMF) of the network; Obtain third input data including resource utilization information of a network slice instance from a network repository function (NRF) of the network; providing the output analytics to one or more network analytics consumers; The information regarding the UE registration includes information regarding the number of UE registrations in the network slice instance; The output analysis First information regarding the UE for the network slice instance; Second information regarding a PDU session for the network slice instance; Including resource usage in the network slice instance, The NF includes at least one of the AMF, a session management function (SMF), and a network slice selection function (NSSF).

13. The operation of searching for an NF (network function) related to the analysis filter comprises: sending a search request to the NRF to search for the NF; and The method of claim 1 , further comprising an act of receiving a search response message from the NRF corresponding to the search request.

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