GB2598100A

GB2598100A - Setting timer value in network

Info

Publication number: GB2598100A
Application number: GB2012661.1A
Authority: GB
Inventors: Gutierrez Estevez David; Kweon Kisuk; Pujol Roig Joan; Jeong Sangsoo
Original assignee: Samsung Electronics Co Ltd
Current assignee: Samsung Electronics Co Ltd
Priority date: 2020-08-13
Filing date: 2020-08-13
Publication date: 2022-02-23
Also published as: GB202012661D0; KR20220021410A; CN116076150A; JP2023539061A; WO2022035063A1

Abstract

A method for setting a value of a timer (e.g. inactivity timer) for transitioning between states (e.g. active/inactive state) of a data session (e.g. PDU session) in a network comprising a first entity (e.g. SMF) and a second entity (e.g. Network Data Analytics Function, NWDAF) providing network analytics. The method comprises: obtaining, by the NWDAF, input data comprising communication description information; and determining, by the NWDAF, based on the input data, output analytics comprising per-data session user equipment (UE) communications analytics, and providing the output analytics to the SMF. The method further comprises, based on the output analytics, determining, by the SMF, whether to update a timer value for a data session. The SMF can transmit a request for (e.g. subscription to) the output analytics, optionally with an analytic filter. The NWDAF can obtain N4 Session parameters from a third entity (UPF) or indirectly via the SMF.

Description

Setting Timer Value in Network BACKGROUND

Field

Certain examples of the present disclosure provide methods, apparatus and systems for setting a value of a timer for transitioning between states of a data session in a network. For example, certain examples of the present disclosure provide methods, apparatus and systems for setting a value of an inactivity timer for transitioning between active/inactive states of a PDU session in a 3GPP 5G network based on NWDAF analytics.

Description of the Related Art

Herein, the following documents are referenced: [1] 3GPP TR 28.809: Study on enhancement of Management Data Analytics (MDA), Rel17 (06-2020).

[2] 3GPP TS 23.288: Architecture enhancements for 5G System (5GS) to support network data analytics services, Rel-16 (06-2020).

[3] 3GPP TR 23.700-91: Study on enablers for network automation for the 5G System (5GS); Phase 2, Rel-17 (06-2020).

[4] 3GPP TS 23.502: Procedures for the 5G System (505), Rel-16 (06-2020).

Various acronyms, abbreviations and definitions used in the present disclosure are defined at the end of this description.

Artificial Intelligence (Al) has been identified as a key enabler for end-to-end network automation in 50 in all network domains, including the domains subject to the standardization process of Radio Access Network (RAN), Core Network (CN), and Management System, also known as Operations, Administration and Maintenance (OAM). Hence, standardization and industry bodies are now in the process of developing specification support for data analytics to enable Al models assist with the ever-increasing complex task of autonomously operating and managing the network.

On the RAN side, the pioneering 0-RAN alliance was established in 2018 by leading operators with the vision of developing open specifications for an open and efficient RAN that leverages Al for automating different network functions (N Es) and reducing operating expenses (OPEX).

Furthermore, standardized support for data analytics by 3GPP is particularly advanced already in Rel-16 on the CN side and the control plane. A data analytics framework anchored in the new so-called network data analytics function (NWDAF), located within the 5GC as a network function following the service-based architecture principles of 5GC has been defined with the purpose of enhancing multiple control-plane functionalities of the network. Moreover, on the DAM side a management data analytics service (MDAS) is also being specified by 3GPP to assist in dealing with longer-term management aspects of the network [1]. The joint operation of RAN analytics entities, NWDAF and MDAS is still work in progress within the relevant bodies.

It is desirable to be able to activate and deactivate 5G PDU sessions on a UE. Such functionality typically resides within the control plane of the CN since it requires decisions being made at a fast timescale, typically much faster than what network management and orchestration systems allow.

5G standards by the 3rd Generation Partnership Project (3GPP) have already developed support for individual and dynamic activation and deactivation of each PDU session a UE has established, but the different transitions from PDU session deactivation to activation as well as the associated UE state incur significant control signaling overhead in the network [5].

Hence, such transitions need to be carefully controlled so that the gains of deactivating PDU sessions will not be offset by the signaling overhead caused by the transitions. An adaptive inactivity timer for individual UE is a tool that has been proposed to address this problem in the past for LTE networks [6], but it did not consider the per-PDU-session granularity required to optimize inactivity timer value in a 5G network. Furthermore, setting the appropriate value at each time instant was done based on a heuristic algorithm, hence resulting in sub-optimal performance.

In order to minimize the UE battery power consumption and network resource usage, assigning an appropriate value to the inactivity timer is crucial. The inactivity timer is designed for controlling the timing of state transitions of a PDU session and eventually a UE. Shortening the length of the inactivity timer may help the UE consume less battery power by staying the UE in CM-IDLE state longer while turning the radio module off, but it incurs frequent transitions of PDU session activation states and UE CM states causing massive control signaling overhead in the network. Particularly, in the case of changing the state of the UE from CM-IDLE to CM-CONNECTED, the required paging message is broadcasted over several cells, consuming a quite significant amount of radio resources. However, prolonging the length of the inactivity timer too much may decrease the efficiency of utilization of radio resources and cause more battery power consumption in the UE experiencing a long tail time during which the UE stays in CM-CONNECTED before transitioning to CM-IDLE.

What is desired is a technique for setting or adjusting a value of an inactivity timer to optimise overall performance.

The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present invention.

SUMMARY

It is an aim of certain examples of the present disclosure to address, solve and/or mitigate, at least partly, at least one of the problems and/or disadvantages associated with the related art, for example at least one of the problems and/or disadvantages described herein. It is an aim of certain examples of the present disclosure to provide at least one advantage over the related art, for example at least one of the advantages described herein.

The present invention is defined in the independent claims. Advantageous features are defined in the dependent claims.

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 annexed drawings,

which disclose examples of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates an exemplary operation of NWDAF; Figure 2 illustrates an example of the present disclosure based on NWDAF and multiple input data sources; Figure 3 illustrates an exemplary procedure to support NWDAF-based user plane optimization; and Figure 4 is a block diagram of an exemplary network entity that may be used in certain examples of the present disclosure.

DETAILED DESCRIPTION

The following description of examples of the present disclosure, with reference to the accompanying drawings, is provided to assist in a comprehensive understanding of the present invention, as defined by the claims. The description includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made without departing from the scope of the invention.

The same or similar components may be designated by the same or similar reference numerals, although they may be illustrated in different drawings.

Detailed descriptions of techniques, structures, constructions, functions or processes known in the art may be omitted for clarity and conciseness, and to avoid obscuring the subject matter of the present invention.

The terms and words used herein are not limited to the bibliographical or standard meanings, but, are merely used to enable a clear and consistent understanding of the invention.

Throughout the description and claims of this specification, the words "comprise", "include" and "contain" and variations of the words, for example "comprising" and "comprises", means "including but not limited to", and is not intended to (and does not) exclude other features, elements, components, integers, steps, processes, operations, functions, characteristics, properties and/or groups thereof Throughout the description and claims of this specification, the singular form, for example "a", "an" and "the", encompasses the plural unless the context otherwise requires. For example, reference to "an object" includes reference to one or more of such objects.

Throughout the description and claims of this specification, language in the general form of "X for Y" (where Y is some action, process, operation, function, activity or step and X is some means for carrying out that action, process, operation, function, activity or step) encompasses means X adapted, configured or arranged specifically, but not necessarily exclusively, to do Y. Features, elements, components, integers, steps, processes, operations, functions, characteristics, properties and/or groups thereof described or disclosed in conjunction with a particular aspect, embodiment, example or claim of the present invention are to be understood to be applicable to any other aspect, embodiment, example or claim described herein unless incompatible therewith.

Certain examples of the present disclosure provide methods, apparatus and systems for setting a value of a timer for transitioning between states of a data session in a network. The following examples are applicable to, and use terminology associated with, 3GPP 5G. For example, certain examples of the present disclosure provide methods, apparatus and systems for setting a value of an inactivity timer for transifioning between active/inactive states of a PDU session in a 3GPP 5G network based on NVVDAF analytics. However, the skilled person will appreciate that the techniques disclosed herein are not limited to these examples or to 3GPP 5G, and may be applied in any suitable system or standard, for example one or more existing and/or future generation wireless communication systems or standards.

For example, the functionality of the various network entities and other features 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 regarded as entities or features that perform the same or similar role, function, operation or purpose within the network.

For example, the functionality of the NWDAF in the examples below may be applied to any other suitable type of entity providing network analytics; the functionality of the UPF in the examples below may be applied to any other suitable type of entity providing user plane functions; the functionality of the AMF in the examples below may be applied to any other suitable type of entity performing mobility management functions; the functionality of the SMF in the examples below may be applied to any other suitable type of entity performing session management functions; and the functionality of the AF in the examples below may be applied to any other suitable type of entity performing corresponding application functions.

The skilled person will appreciate that the present invention is not limited to the specific examples disclosed herein. For example: The techniques disclosed herein are not limited to 3GPP 5G.

One or more entities in the examples disclosed herein may be replaced with one or more alternative entities performing equivalent or corresponding functions, processes or operations.

One or more of the messages in the examples disclosed herein may be replaced with one or more alternative messages, signals or other type of information carriers that communicate equivalent or corresponding information.

One or more further elements, entities and/or messages may be added to the examples disclosed herein.

One or more non-essential elements, entities and/or messages may be omitted in certain examples.

The functions, processes or operations of a particular entity in one example may be divided between two or more separate entities in an alternative example.

* The functions, processes or operations of two or more separate entities in one example may be performed by a single entity in an alternative example.

* Information carried by a particular message in one example may be carried by two or more separate messages in an alternative example. * * * * * *

* Information carried by two or more separate messages in one example may be carried by a single message in an alternative example.

* The order in which operations are performed may be modified, if possible, in alternative examples.

* The transmission of information between network entities is not limited to the specific form, type and/or order of messages described in relation to the examples disclosed herein.

Certain examples of the present disclosure may be provided in the form of an apparatus/device/network entity configured to perform one or more defined network functions and/or a method therefor. Certain examples of the present disclosure may be provided in the form of a system (e.g. a network) comprising one or more such apparatuses/devices/network entities, and/or a method therefor.

A network may include one or more of a User Equipment (UE), a Radio Access Network (RAN), an Access and Mobility Management Function (AM F) entity, a Session Management Function (SMF) entity, a User Plane Function (UPF) entity, a Network Data Analyfics Function (NWDAF) entity, an Application Function (AF) entity, and one or more other Network Function (NF) entities.

A particular network function can be implemented either as a network element on a dedicated hardware, as a software instance running on a dedicated hardware, or as a virtualised function instantiated on an appropriate platform, e.g. on a cloud infrastructure. A NF service may be defined as a functionality exposed by a NF through a service based interface and consumed by other authorized NFs.

As mentioned above, what is desired is a technique for setting or adjusting a value of an inactivity timer to optimise overall performance.

Certain examples of the present disclosure enable an optimization of the trade-off between UE battery consumption and network resource efficiency described above by leveraging the standardized data analytics framework. Hence, a compliant Al-based solution using data analytics may be based on the NWDAF framework. A brief overview of the NWDAF framework, for example as defined in [2], will now be described.

The recently frozen 3GPP Pei-16 has specified the NWDAF framework as illustrated in Figure 1. In the basic operation of NWDAF illustrated in Figure 1, an analytics consumer requests data analytics to NWDAF, which collects data from different entities to perform training and inference before producing the output analytics.

Referring to Figure 1, an analytics service consumer may request a specific type of data analytics to NWDAF, which can be provided by NWDAF in the form of statistics and/or predictions. The analytics consumers defined in Rel-16 are 5GC NFs, Application Functions (AFs), and OAM. NWDAF then triggers the input data collection by means of an exposure framework defined in [2] where the input data sources may again be 5GC NFs, AFs, and/or OAM.

The collected data is then used by NWDAF to perform training and inference, possibly by an Al engine, but the definition of the models is outside the scope of standardization to provide enough flexibility to vendors. This also implies that the Al engine may reside outside NWDAF itself, and the next release of the standard (Rel-17) has already started to study any required interface standardization to enable such NWDAF functional decomposition [3]. The same considerations apply to the input data collection module. In certain examples of the present disclosure, it is assumed the Al engine and input data collection module reside within NWDAF, although the present disclosure is not limited to this case.

In any case, the inference results are then fed to the analytics production entity within NWDAF, which delivers the statistics and/or predictions requested by the service consumer.

A number of data analytics types have also been introduced in 3GPP Pei-16, including analytics for network slice and application service experience, NF and network slice load, network performance, UE aspects (communication, mobility, expected and abnormal behaviour), etc., as described in [2].

In addition to the above basic operation, the already ongoing Rel-17 is expanding the Rel-16 NWDAF framework by addressing a number of new use cases and key issues, including the above mentioned NWDAF functional decomposition, the architecture and interaction of multiple NWDAF instances, efficient data collection mechanisms, support for network slice service level agreement (SLA) guarantee, etc. [3].

Based on the above framework description, certain examples of the present disclosure directly embed in the 5G architecture an autonomous capability to intelligently and dynamically set the inactivity timer value to each 5G PDU session of a UE. This approach has the advantage of being highly implementable in current and at least near-future networks, as the basic data collection capabilities of NWDAF used in certain examples of the present disclosure have

already been defined in the specifications.

In the following, an exemplary instantiation of the framework for the above-mentioned problem, as well as a description of the Al problem framed in the context of NWDAF data analytics, are described However, the skilled person will appreciate that the techniques described herein are not limited to setting or adjusting a timer value, but may be used to set or adjust any other suitable parameter in a network.

In the following, there is described an Al-based technique, leveraging NWDAF, for setting/adjusting an inactivity timer for activation and deactivation of the PDU sessions associated to the multiple services consumed by the UE. In particular, an overall NWDAF-based technique is described, which highlights the applicability of the technique to current standardized networks. A detailed procedure to instantiate the specific framework is also described.

Figure 2 illustrates an exemplary overall NWDAF-based design, utilising the Rel-16 data analytics framework described in [1]. This example is based on multiple input data sources (e.g. OAM, SMF, UPF, AF and AMF, and optionally NG-RAN and UE), the Al-based training and inference module, and the output analytics delivered to SMF and forwarded to UPF. The skilled person will appreciate that the present disclosure is no limited to these examples.

Referring to Figure 2, the internal NWDAF architecture in this example follows the general principle shown in Figure 1, where the generic analytics model outside the scope of standardization efforts has been replaced with a model based on inference, training that is described further below. Furthermore, Figure 2 illustrates the input data sources used for the agent to learn the optimal inactivity timer value and provide the required analytics.

In order to respect the framework already agreed and frozen in 3GPP, certain examples of the present disclosure may only require supported 5GC entities (i.e. SMF, UPF, AM F), AFs, and OAM to provide input data. However, the present disclosure is not limited to this case. For example, Figure 2 indicates other exemplary entities that could provide required input data to NWDAF currently not supported in the standard, namely NG-RAN and the UE. In certain examples, these other entities are not required as they can be replaced by alternative entities currently supported. These other entities as data sources may be supported by future releases of the standard.

In addition, in the following it is described, in the context of an exemplary Al-based training and inference model, which specific input data may be used. In certain examples described below, all input data may be mapped to standardized NWDAF input data, for example UE communication data (e.g. including start and end time stamps, uplink and downlink data rates, traffic volume, etc.), cell load measured in number of activated PDU sessions, and UE type [8]. In certain examples, as opposed to UE communication data and cell load, UE type may need to be collected only once, since it does not change during the network operation.

With respect to the output analytics provided by NWDAF, certain examples of the present disclosure may comply with the current 3GPP framework by generating data analytics in the form of 'optimal prediction values' for the session inactivity timer that can be directly fed to the SMF. NWDAF may also provide past statistics of the timer value.

Hence, the data analytics delivered by NWDAF may then be used by SMF to (i) activate or deactivate PDU sessions when needed, and (ii) update the timer value using the NWDAF predictions and inform UPF of such update. Both actions may be performed, for example by SMF, for example by following the standardized procedures for PDU session activation and deactivation, as well as user plane management, defined in [4].

Data Analytics In certain examples, to enable user plane connection optimization based on PDU session timer, the following existing NWDAF analytics as defined in [2] may be used. However, in their current form they may not be able to support various examples of the present disclosure. Hence, certain examples of the present disclosure extend the current definitions, as described below. In the following, UE Communications Analytics and Network Performance Analytics are described. However, the skilled person will appreciate that the present disclosure is not limited to these specific examples.

UE Communications Analytics An NWDAF supporting UE communication analytics may collect per-application communication description from AFs. In certain examples, if a consumer NF provides an 25 Application ID, the NWDAF may only considers the data from AF, SMF and UPF that corresponds to this application ID.

The consumer of these analytics may indicate in the request one or more of the following non-limiting examples: * The Target of Analytics Reporting, which may be a single UE or a group of UEs.

* Analytics Filter Information, optionally including one or more of the following non-

limiting examples:

S-NSSAI; o DNN; o Application ID; o Area of Interest.

* An Analytics target period indicating a time period over which the statistics and/or predictions are requested.

* Preferred level of accuracy of the analyfics (e.g. low/high).

* A maximum number of objects; * In a subscription, the Notification Correlation ID and the Notification Target Address may be included.

a) Input data: Table 1 shows the current input data specification in [2] for UE communications analytics. Certain examples of the present disclosure may use one or more pieces of such information. The skilled person will appreciate that the exact form of the input data, and/or the sources of such information, is not necessarily limited to the specific examples indicated in Table 1.

Table 1: Service Data from 5GC related to UE communication

Information Source Description

UE ID SMF, AF SUPI in the case of SMF, external UE ID (i.e. GPSI) in the case of AF Group ID SMF, AF To identify UE group if available Internal Group ID in the case of SMF, External Group ID in the case of AF S-NSSAI SMF Information to identify a Network Slice DNN SMF Data Network Name where PDU connectivity service is provided Application ID SMF, AF Identifying the application providing this information Expected UE AF Same as Expected UE Behaviour parameters specified in TS 23.502 [3] Behaviour parameters UE communication (1..max) UPF, AF Communication description per application >Communication start The time stamp that this communication starts >Communication stop The time stamp that this communication stops >UL data rate UL data rate of this communication >DL data rate DL data rate of this communication >Traffic volume Traffic volume of this communication Type Allocation code (TAC) AMF To indicate the terminal model and vendor information of the UE. The UEs with the same TAC may have similar communication behavior. The UE whose communication behavior is unlike other UEs with the same TAC may be an abnormal one.

In certain examples of the present disclosure, one or more pieces of input data shown in Table 2 may be used, for example in addition to one or more pieces of input data according to Table 1. In certain examples, some or all of the input data according to Table 2 may be collected as part of the UE communication service data, or as independent entries per PDU session. The skilled person will appreciate that the exact form of the input data, or the sources of such information, is not necessarily limited to the specific examples indicated in Table 2.

Table 2: Examples of additional Service Data from 5GC related to UE communication

Additional input data Source Description

(>) PDU Session ID (1... max) SMF Identification of PDU Session(s) > N4 Session ID SMF, UPF Identification of N4 Session > Inactivity detection time SMF, UPF Value of session inactivity timer > PDU Session status SMF Status of the PDU Session (activated, deactivated) UE CM state AMF UE connection management state (e.g. CM-IDLE) b) Output analytics: Table 3 shows the current output analytics specification in [2] for UE communications analytics. Statistics may not require the entry 'confidence' whereas predictions may do. Certain examples of the present disclosure may generate one or more pieces of output analytics according to Table 3. The skilled person will appreciate that the exact form of the output analytics is not necessarily limited to the specific examples indicated in Table 3.

Table 3: UE communications output analytics

Information Description

UE group ID or UE ID Identifies an UE or a group of UEs, e.g. internal group ID defined in TS 23.501 [2] clause 5.9.7 or SUPI (see NOTE).

UE communications (1..max) List of communication time slots.

> Periodic communication indicator Identifies whether the UE communicates periodically or not.

> Periodic time Interval Time of periodic communication (average and variance) if periodic.

Example: every hour.

> Start time Start time predicted (average and variance).

> Duration time Duration interval time of communication.

> Traffic characterization S-NSSAI, DNN, ports, other useful information.

> Traffic volume Volume UL_/DL (average and variance).

> Confidence Confidence of the prediction.

> Ratio Percentage of UEs in the group On the case of an UE group).

In certain examples of the present disclosure, one or more pieces of output analytics shown in Table 4 may be generated, for example in addition to one or more pieces of output analytics according to Table 3. The skilled person will appreciate that the exact form of the output analytics is not necessarily limited to the specific examples indicated in Table 4.

Table 4: Examples of additional output analytics data for UE communication

Additional Information Description

(>) PDU Session ID (1 max) Identification of the PDU Session(s) > N4 Session ID Identification of N4 Session > Inactivity detection time Value of session inactivity timer (average, variance) Network Performance Analvtics In certain examples of the present disclosure, network performance analytics by NWDAF may be used On addition or alternatively to UE communications and/or other analytics) to optimize the performance of the user plane. For example, SMF may use network performance analytics in addition to UE communication analytics to derive timer values that optimize not only the performance of the individual UEs but also the network as a whole in general, and the RAN in particular.

a) Input data: Table 5 shows the current input data specification in [2] for UE communications analytics. Certain examples of the present disclosure may use one or more pieces of such information. The skilled person will appreciate that the exact form of the input data, and/or the sources of such information, is not necessarily limited to the specific examples indicated in Table 5.

Table 5: Input Data for network performance analytics

Load information Source Description

Status, load and CAM Statistics on RAN status (up/down), load (i.e. Radio Resource Utilization) and performance per Cell Id in the performance information Area of Interest as defined in TS 28.552 [8].

NF Load information NRF Load per NF Number of UEs AMF Number of UEs in an Area of Interest b) Output analytics: Table 6 shows the current output analytics specification in [2] for network performance analytics. Statistics may not require the entry 'confidence' whereas predictions may do. Certain examples of the present disclosure may generate one or more pieces of output analytics according to Table 6. The skilled person will appreciate that the exact form of the output analytics is not necessarily limited to the specific examples indicated in Table 6.

Table 6: Network performance output analytics

Information Description

List of network performance Predicted analytics during the Analytics target period information (1..max) > Area subset TA or Cell ID within the requested area of interest as defined in clause 6.6.1 > Analytics target period subset Time window within the requested Analytics target period as defined in clause 6.6.1.

> gNB status information Average ratio of gNBs that will be up and running during the entire Analytics target period in the area subset > gNB resource usage Average usage of assigned resources (CPU, memory, disk) (average, peak) > Number of UEs Average number of UEs predicted in the area subset > Communication performance Average ratio of successful setup of PDU Sessions > Mobility performance Average ratio of successful handover > Confidence Confidence of this prediction In certain examples of the present disclosure, one or more pieces of output analytics shown in Table 7 may be generated, for example in addition to one or more pieces of output analytics according to Table 6. The skilled person will appreciate that the exact form of the output analytics is not necessarily limited to the specific examples indicated in Table 7. For example, certain examples may generate output analytics indicated below in bold + italics.

Table 7: Examples of additional network performance output analytics

Information Description

> gNB resource usage Average usage of assigned resources (spectrum, CPU, memory, disk) > Outage Average amount of network outage in the area subset during analytics target period An exemplary procedure supporting NWDAF-based user plane optimization is illustrated in Figure 3. The various operations in the procedure are described below. In various examples, certain operations (e.g. those indicated with dotted arrows/boxes) may be omitted. For conciseness, Figure 3 illustrates two alternative sets of operations (Alt 1 and Alt 2). In various examples, one or the other of these alternatives may be used. The skilled person will appreciate that the present disclosure is not limited to the specific example of Figure 3.

0. A PDU Session gets established. A corresponding user plane connection needs to be activated for data transmission. During the course of the procedure the user plane connection may get deactivated if the inactivity timer expires, and activated if new data traffic is available.

1. SMF subscribes to UE communication analytics from NWDAF.

2. [OPTIONAL] SMF subscribes to network performance analytics from NWDAF.

Input data collection: Two alternatives are possible for data collection related to N4 Session. Alternative 1 uses SMF and its corresponding service exposure framework to retrieve the required input data described in the invention while Alternative 2 relies on implementation-specific mechanisms for UPF input data retrieval.

Alternative 1 [ALL MESSAGES OPTIONAL]: SMF based N4 session data collection 3a. NWDAF requests N4 Session related input data to SMF as defined in Table 2. It may also request other UE communication data with SMF as source NF, as specified in TS 23.288 [2] and Table 2.

3b. SMF requests a N4 Session Level report to UPF.

3c. UPF provides the requested N4 Session Level report to SMF according to clause 4.4.2.2 in TS 23.502 [4].

3d. SMF provides the requested N4 Session related input data to NWDAF. Alternative 2: UPF based N4 session data collection 4. [OPTIONAL] NWDAF collects N4 Session related input data directly from UPF via implementation-specific mechanisms.

5. NWDAF collects the remaining input data required to produce the requested analytics according to TS 23.288 [2].

6. NWDAF may provide UE Communication analytics to SMF as defined in TS 23.288 [2]

and Table 4.

7. [OPTIONAL] If step 2 is performed, NWDAF provides network performance analytics to SMF as specified in TS 23.288 [2]. It may also add output analytics data shown in Table 7.

8. VVhile SMF continues its task of activating and deactivating PDU Sessions, SMF also processes the received analytics provided by NWDAF.

9. Based on its analysis of NWDAF analytics, SMF may decide to update the user plane inactivity timer of certain PDU Session(s) associated to corresponding N4 Session(s).

10. SMF triggers a N4 Session modification procedure according to clause 4.4.1.3 in TS 23.502 [4] to inform UPF of the inactivity timer update.

Certain examples of the present disclosure provide a method, for a second entity (e.g. NWDAF) providing network analytics in a network comprising a first entity (e.g. SMF) and the second entity, the method comprising: obtaining input data comprising communication description information; and determining, based on the input data, output analytics comprising per-data session user equipment (UE) communications analytics, and providing the output analytics to the first entity. Based on the output analytics, the first entity may determine whether to update a timer value for a data session, the timer (e.g. inactivity timer) for transitioning between states (e.g. active/inactive state) of the data session (e.g. PDU session).

Certain examples of the present disclosure provide a second entity (e.g. NWDAF) providing network analytics in a network comprising a first entity (e.g. SMF) and the second entity, the second entity being configured to: obtain input data comprising communication description information; and determine, based on the input data, output analytics comprising per-data session user equipment (UE) communications analytics, and provide the output analytics to the first entity. Based on the output analytics, the first entity may determine whether to update a timer value for a data session, the timer (e.g. inactivity timer) for transitioning between states (e.g. active/inactive state) of the data session (e.g. PDU session).

Certain examples of the present disclosure provide a method for setting a value of a timer (e.g. inactivity timer) for transitioning between states (e.g. active/inactive state) of a data session (e.g. PDU session) in a network comprising a first entity (e.g. SMF) and a second entity (e.g. NWDAF) providing network analytics, the method comprising: obtaining, by the second entity, input data comprising communication description information; determining, by the second entity, based on the input data, output analytics comprising per-data session user equipment (UE) communications analytics, and providing the output analytics to the first entity; and based on the output analytics, determining, by the first entity, whether to update a timer value for a data session.

In certain examples, the method may further comprise receiving, by the second entity from the first entity, a request for (e.g. subscription to) the output analytics.

In certain examples, the request may comprise one or more of: a request for analytics relating to a specific UE or a group of UEs; and an analytics filter.

In certain examples, the analytics filter may specify one or more of the following as filter criteria: information specifying one or more S-NSSAI; information specifying one or more DNN one or more application ID; information indicating one or more area of interest; information specifying an analytics target period indicating the time period over which statistics and/or predictions are requested; information indicating a preferred level of accuracy of the analytics (e.g. low/high); information specifying a maximum number of objects; and in a subscription, a notification correlation ID and a notification target address.

In certain examples, obtaining the input data may comprise: transmitting, by the second entity to the first entity, a request for session parameters (e.g. N4 session parameters); transmitting, by the first entity to a third entity (e.g. UPF), a request for a session report (e.g. N4 Session report); receiving, by the first entity from the third entity, the session parameters; and transmitting, by the first entity to the second entity, the session parameters.

In certain examples, obtaining the input data may comprise performing, with a third entity (e.g. UPF), a procedure for obtaining session parameters (e.g. N4 session parameters) directly from the third entity.

In certain examples, the input data may further comprises additional input data obtained from one or more network entities (e.g. AMF, SMF, UPF, OAM, one or more AFs, NG-RAN and/or 20 UE).

In certain example, obtaining the input data may be performed continuously.

In certain examples, the method may further comprise, if it is determined to update the timer value, initiating a procedure (e.g. N4 session modification procedure) to update the timer value.

In certain examples, the method may further comprise transifioning between states of a data connection based on a corresponding timer value (and optionally traffic).

In certain examples, the input data may comprise one or more pieces of the information specified in Table 1.

In certain examples, the input data may comprise one or more of: an identification of one or more PDU Sessions (e.g. obtained from SMF); an identification of an N4 Session (e.g. obtained from SMF and/or UPF); a value of a session inactivity timer (e.g. obtained from SMF and/or UPF); information indicating the status (e.g. activated or deactivated) of one or more PDU Sessions (e.g. obtained from SMF); and one or more UE states throughout an analytics target period (e.g. obtained from AMF).

In certain examples, the UE communications analytics may comprise one or more pieces of the information specified in Table 3.

In certain examples, the UE communications analytics may comprises one or more of: an identification of one or more PDU Sessions; an identification of an N4 Session; and a value of session inactivity timer (e.g. average or variance).

In certain examples, the output analytics may further comprise network performance analytics.

In certain examples, the input data may comprise one or more pieces of the information specified in Table 5.

In certain examples, the network performance analytics may comprise one or more pieces of the information specified in Table 6.

In certain examples, the network performance analytics may comprise one or more of: an average usage of assigned resources (e.g. spectrum, CPU, memory and/or disk); and an average amount of network outage in an area subset during an analytics target period.

In certain examples, the input data may comprise communication description information relating to one or more of: an Application Function (AF); a data session; a UE; a network slice; and a data network.

Certain examples of the present disclosure provide a network comprising a first entity (e.g. SMF) and a second entity (e.g. NWDAF), the network being configured to operate according to any method disclosed herein.

Certain examples of the present disclosure provide a first entity (e.g. SMF) or a second entity (e.g. NWDAF) being configured to operate in a network according to the preceding example.

Certain examples of the present disclosure provide a computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out any method disclosed herein.

Certain examples of the present disclosure provide a computer or processor-readable data carrier having stored thereon a computer program according to the preceding example.

Figure 4 is a block diagram of an exemplary network entity that may be used in examples of the present disclosure. For example, the UE, AMF, SMF, UPF, NWDAF, AF and/or other NFs may be provided in the form of the network entity illustrated in Figure 4. The skilled person will appreciate that the network entity illustrated in Figure 4 may be implemented, for example, as a network element on a dedicated hardware, as a software instance running on a dedicated hardware, or as a virtualised function instantiated on an appropriate platform, e.g. on a cloud infrastructure.

The entity 400 comprises a processor (or controller) 401, a transmitter 403 and a receiver 405. The receiver 405 is configured for receiving one or more messages or signals from one or more other network entities. The transmitter 403 is configured for transmitting one or more messages or signals to one or more other network entities. The processor 401 is configured for performing one or more operations and/or functions as described above. For example, the processor 401 may be configured for performing the operations of an UE, AM F, SM F, UPF, NWDAF, AF and/or other NFs.

The techniques described herein may be implemented using any suitably configured apparatus and/or system. Such an apparatus and/or system may be configured to perform a method according to any aspect, embodiment, example or claim disclosed herein. Such an apparatus may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and/or method steps for implementing the techniques described herein. For example, an operation/function of X may be performed by a module configured to perform X (or an X-module). The one or more elements may be implemented in the form of hardware, software, or any combination of hardware and software.

It will be appreciated that examples of the present disclosure may be implemented in the form of hardware, software or any combination of hardware and software. Any such software may be stored in the form of volatile or non-volatile storage, for example a storage device like a ROM, whether erasable or rewritable or not, or in the form of memory such as, for example, RAM, memory chips, device or integrated circuits or on an optically or magnetically readable medium such as, for example, a CD, DVD, magnetic disk or magnetic tape or the like.

It will be appreciated that the storage devices and storage media are embodiments of machine-readable storage that are suitable for storing a program or programs comprising instructions that, when executed, implement certain examples of the present disclosure. Accordingly, certain example provide a program comprising code for implementing a method, apparatus or system according to any example, embodiment, aspect and/or claim disclosed herein, and/or a machine-readable storage storing such a program. Still further, such programs may be conveyed electronically via any medium, for example a communication signal carried over a wired or wireless connection.

While the invention has been shown and described with reference to certain examples, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention, as defined by any appended claims.

Acronyms, Abbreviations and Definitions In the present disclosure, the following acronyms, abbreviations and definitions may be used.

3GPP 3rd Generation Partnership Project 5G 5th Generation 5GC 5G Core Network 5GS 5G System AF Application Function Al Artificial Intelligence AMF Access and Mobility Management Function CM Connection Management CN Core Network CPU Central Processing Unit DL DownLink DNN Data Network Name gNB 5G Base Station GPSI General Public Subscription Identifier ID Identifier/Identity LIE Long Term Evolution MDA Management Data Analytics MDAS Management Data Analytics Service N4 Interface between SMF and UPF NF Network Function NG Next Generation NRF Network Repository Function NWDAF Network Data Analytics Function OAM Operation and Maintenance OPEX Operating Expenses PDU Protocol Data Unit RAN Radio Access Network Rel Release RRC Radio Resource Control SLA Service Level Agreement SMF Session Management Function S-NSSAI Single Network Slice Selection Assistance Information SUPI Subscription Permanent Identifier TA Tracking Area TAC Type Allocation Code TR Technical Report

TS Technical Specification

UE User Equipment UL UpLink UPF User Plane Function

Claims

Claims 1. A method for setting a value of a timer (e.g. inactivity timer) for transitioning between states (e.g. active/inactive state) of a data session (e.g. PDU session) in a network comprising a first entity (e.g. SMF) and a second entity (e.g. NWDAF) providing network analytics, the method comprising: obtaining, by the second entity, input data comprising communication description information; determining, by the second entity, based on the input data, output analytics comprising per-data session user equipment (UE) communications analytics, and providing the output analytics to the first entity; and based on the output analytics, determining, by the first entity, whether to update a timer value for a data session.
2. A method according to claim 1, further comprising receiving, by the second entity from the first entity, a request for (e.g. subscription to) the output analytics.
3. A method according to claim 2, wherein the request comprises one or more of: a request for analytics relating to a specific UE or a group of UEs; and an analytics filter.
4. A method according to claim 3, wherein the analytics filter specifies one or more of the following as filter criteria: information specifying one or more S-NSSAI; information specifying one or more DNN one or more application ID; information indicating one or more area of interest; information specifying an analytics target period indicating the time period over which statistics and/or predictions are requested; information indicating a preferred level of accuracy of the analytics (e.g. low/high); information specifying a maximum number of objects; and in a subscription, a notification correlation ID and a notification target address.
5. A method according to any preceding claim, wherein obtaining the input data comprises: transmitting, by the second entity to the first entity, a request for session parameters (e.g. N4 session parameters); transmitting, by the first entity to a third entity (e.g. UPF), a request for a session report (e.g. N4 Session report); receiving, by the first entity from the third entity, the session parameters; and transmitting, by the first entity to the second entity, the session parameters.
6. A method according to any of claims 1 to 4, wherein obtaining the input data comprises performing, with a third entity (e.g. UPF), a procedure for obtaining session parameters (e.g. N4 session parameters) directly from the third entity.
7. A method according to any preceding claim, wherein the input data further comprises additional input data obtained from one or more network entities (e.g. AMF, SMF, UPF, OAM, one or more AFs, NG-RAN and/or UE).
8. A method according to any preceding claim, wherein obtaining the input data is performed continuously.
9. A method according to any preceding claim, further comprising, if it is determined to update the timer value, initiating a procedure (e.g. N4 session modification procedure) to update the timer value.
10. A method according to any preceding claim, further comprising transitioning between states of a data connection based on a corresponding timer value (and optionally traffic).
11. A method according to any preceding claim, wherein the input data comprises one or more pieces of the information specified in Table 1.
12. A method according to any preceding claim, wherein the input data comprises one or more of: an identification of one or more PDU Sessions (e.g. obtained from SMF); an identification of an N4 Session (e.g. obtained from SMF and/or UPF); a value of a session inactivity timer (e.g. obtained from SMF and/or UPF); information indicating the status (e.g. activated or deactivated) of one or more PDU Sessions (e.g. obtained from SMF); and one or more UE states throughout an analytics target period (e.g. obtained from AMF).
13. A method according to any preceding claim, wherein the UE communications analytics comprises one or more pieces of the information specified in Table 3.
14. A method according to any preceding claim, wherein the UE communications analytics comprises one or more of: an identification of one or more PDU Sessions; an identification of an N4 Session; and a value of session inactivity timer (e.g. average or variance).
A method according to any preceding claim, wherein the output analytics further comprises network performance analytics.
16. A method according to claim 15, wherein the input data comprises one or more pieces of the information specified in Table 5.
17. A method according to claim 15 or 16, wherein the network performance analytics comprises one or more pieces of the information specified in Table 6.
18. A method according to claim 15, 16 or 17, wherein the network performance analytics comprises one or more of: an average usage of assigned resources (e.g. spectrum, CPU, memory and/or disk); and an average amount of network outage in an area subset during an analytics target period.
19. A method according to any preceding claim, wherein the input data comprises communication description information relating to one or more of: an Application Function (AF); a data session; a UE; a network slice; and a data network.
20. A network comprising a first entity (e.g. SMF) and a second entity (e.g. NWDAF), the network being configured to operate according to a method of any preceding claim.
21. A first entity (e.g. SMF) or a second entity (e.g. NWDAF) being configured to operate in a network according to claim 20.
22. A computer program comprising instructions which, when the program is executed by a computer or processor, cause the computer or processor to carry out a method according to any of claims 1 to 19.
23. A computer or processor-readable data carrier having stored thereon a computer program according to claim 22.