CN116076150A - Method and apparatus for setting timer values in a network - Google Patents

Abstract

The present disclosure provides a method for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis. The method includes obtaining, by a second entity, input data including communication description information of at least one User Equipment (UE), and providing, by the second entity, to the first entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session, wherein the output analysis is used to determine whether to update a value of an inactivity timer for the data session.

Description

Method and apparatus for setting timer values in a network

Technical Field

The present disclosure relates to methods, apparatus, and systems for setting a timer value for transitioning between states of data sessions in a network.

Background

In view of the development of the generation and generation of wireless communication, these technologies have been developed mainly for services targeted for personal purposes, such as voice calls, multimedia services, and data services. With the commercialization of the fifth generation (5G) communication system, it is expected that the number of connected devices will increase exponentially. These will increasingly be connected to a communication network. Examples of the internet of things may include vehicles, robots, drones, home appliances, displays, smart sensors connected to various infrastructure, construction machinery, and factory equipment. Mobile devices are expected to evolve in a variety of forms such as augmented reality glasses, virtual reality headphones, and holographic devices. In order to provide various services by connecting several billions of devices and things in the sixth generation (6G) era, efforts have been made to develop an improved 6G communication system. For these reasons, the 6G communication system is called a super 5G system.

It is expected that a 6G communication system commercialized around 2030 will have a peak data rate of megabits (tera) (1,000 giga) level bps and a radio delay of less than 100 musec, and thus will be 50 times that of a 5G communication system, and have a radio delay of 1/10 thereof.

To achieve such high data rates and ultra-low delays, it has been considered to implement 6G communication systems in terahertz (e.g., 95GHz to 3THz bands). It is expected that a technology capable of securing a signal transmission distance (i.e., coverage) will become more critical since path loss and atmospheric absorption in the terahertz band are more serious than those in the millimeter wave (mmWave) band introduced in 5G. As a main technique of ensuring coverage, it is necessary to develop a Radio Frequency (RF) element, an antenna, a novel waveform having better coverage than Orthogonal Frequency Division Multiplexing (OFDM), beamforming and massive Multiple Input Multiple Output (MIMO), full-dimensional MIMO (FD-MIMO), an array antenna, and a multi-antenna transmission technique such as a massive antenna. Furthermore, new technologies to improve terahertz band signal coverage, such as metamaterial-based lenses and antennas, orbital angular momentum (orbital angular momentum, OAM) and reconfigurable smart surfaces (reconfigurable intelligent surface, RIS), are always being discussed.

Furthermore, in order to improve spectral efficiency and overall network performance, the following techniques have been developed for 6G communication systems: full duplex techniques for enabling uplink and downlink transmissions to use the same frequency resources simultaneously; network technologies utilizing satellites, high-altitude platform stations, HAPS, etc. in an integrated manner; an improved network structure for supporting mobile base stations and the like and making network operation optimization, automation and the like possible; dynamic spectrum sharing via collision avoidance based on spectrum usage prediction: using Artificial Intelligence (AI) in wireless communications to improve overall network operation by leveraging AI from the design phase of development 6G and internalizing end-to-end AI support functions; and next generation distributed computing technologies that overcome the computational capability limitations of User Equipment (UE) through ultra-high performance communications and computing resources, such as mobile edge computing (mobile edge computing, MEC), cloud, etc., reachable over the network. Further, attempts are being continued to strengthen connectivity between devices, optimize networks, promote the software of network entities, and increase the openness of wireless communications by designing new protocols to be used in 6G communication systems, developing mechanisms for achieving secure use of hardware-based secure environments and data, and developing techniques for maintaining privacy.

It is expected that research and development of 6G communication systems in hyperlinks, including person-to-machine (person to machine, P2M) and machine-to-machine (machine to machine, M2M), will bring about the next hyperlink experience. In particular, it is desirable to provide services such as true immersive augmented reality (XR), high fidelity mobile holograms, and digital replicas through 6G communication systems. In addition, services such as teleoperation for safety and reliability enhancement, industrial automation and emergency response will be provided through the 6G communication system, so that the technology can be applied to various fields such as industry, health care, automobiles and home appliances.

The following documents are referenced herein:

[1] third generation partnership project (3 GPP) Technical Report (TR) 28.809: management Data Analysis (MDA) enhanced study, version 17 (06-2020).

[2]3gpp TS 23.288: the 5G system (5 GS) architecture supporting the network data analysis service is enhanced, version 16 (06-2020).

[3]3GPP TR 23.700-91: network automation enabling factor research of a 5G system (5 GS); phase 2, version 17 (06-2020).

[4]3gpp TS 23.502: program of 5G system (5 GS), version 16 (06-2020).

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

Artificial Intelligence (AI) has been identified as a key enabling factor for 5G end-to-end network automation in all network areas, including areas affected by standardized flows of Radio Access Networks (RANs), core Networks (CNs) and management systems (also known as operations, administration and maintenance (administration and maintenance, OAM)). Thus, standardization and industry organizations are now developing canonical support for data analysis to enable AI models to assist in the increasing complex tasks of autonomously operating and managing networks.

In terms of RAN, leading operators established an pioneering O-RAN alliance in 2018, which is looking to develop an open specification for an open, efficient RAN, to utilize AI to automate different Network Functions (NF) and reduce operational expenditures (operating expense, OPEX).

Furthermore, standardized support for data analysis by 3GPP has been particularly advanced in release 16 on the CN side and control plane. A data analysis framework anchored in a new so-called network data analysis function (NWDAF) has been defined, which is located within the 5GC as a network function following the service-based architecture principle of the 5GC, with the aim of enhancing multiple control plane functions of the network. In addition, in terms of OAM, 3GPP also specifies management data analysis services (management data analytics service, MDAS) to help handle long-term management aspects of the network [1]. The joint operation of the RAN analysis entity, the network data analysis function (NWDAF) and the MDAS is still performed within the relevant authorities.

Disclosure of Invention

Technical problem

It is desirable to be able to activate and deactivate 5G Protocol Data Unit (PDU) sessions on a UE. Such functionality is typically located within the control plane of the CN, as it needs to make decisions on a fast time scale, typically much faster than the network management and coordination system allows.

The third generation partnership project (3 GPP) 5G standard has developed support for separate and dynamic activation and deactivation of each PDU session that the UE has established, but the different transitions from PDU session deactivation to activation and associated UE states result in significant control signaling overhead in the network.

Thus, such transitions need to be carefully controlled so that the gain of deactivating the PDU session is not offset by the signaling overhead caused by the transition. An adaptive inactivity timer for a single UE is a proposed tool to address this problem, but it does not consider the per PDU session granularity required to optimize inactivity timer values in a 5G network. Furthermore, setting the appropriate value at each instant is done based on heuristics, thus resulting in suboptimal performance.

To minimize UE battery power consumption and network resource usage, it is critical to assign appropriate values to the inactivity timers. The inactivity timer is designed to control the timing of the PDU session and eventually the state transitions of the UE. Shortening the length of the inactivity timer may help the UE consume less battery power by placing the UE in CM-IDLE (CM IDLE) state for a longer period of time when the radio is turned off, but this results in PDU session active state and frequent transitions of the UE CM state, resulting in a significant amount of control signaling overhead in the network. In particular, in case of changing the state of the UE from CM-IDLE to CM-CONNECTED, a required paging message is broadcast on several cells, consuming a considerable amount of radio resources. However, extending the length of the inactivity timer too much may reduce the efficiency of radio resource utilization and result in more battery power consumption in UEs that experience long tail times during which the UE maintains CM-CONNECTED before transitioning to CM-IDLE.

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

The above information is presented merely as background information to aid in the understanding of the present disclosure. No determination is made, nor is an assertion made, as to whether any of the above may be applied to the present disclosure as prior art.

For example, certain examples of the present disclosure may 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 analysis.

Technical proposal

Aspects of the present disclosure address at least the problems and/or disadvantages described above and provide at least the advantages described below. Accordingly, one aspect of the present disclosure is to provide a method and apparatus for setting a value of a timer for transitioning between states of data sessions in a network.

Additional aspects will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the presented embodiments.

According to one aspect of the present disclosure, a method for setting a value of an inactivity timer for transitioning between states of data sessions in a network including a first entity and a second entity providing network analysis is provided. The method performed by the second entity includes obtaining, by the second entity, input data including communication description information of at least one User Equipment (UE), and providing, by the second entity to the first entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session, wherein the output analysis is used to determine whether to update a value of an inactivity timer for the data session.

According to another aspect of the present disclosure there is provided a telecommunications network operable to perform the method of the first aspect.

According to another aspect of the present disclosure, a method for setting a value of an inactivity timer for transitioning between states of data sessions in a network including a first entity and a second entity providing network analysis is provided. The method performed by the first entity comprises: transmitting, by a first entity, input data including communication description information of at least one User Equipment (UE) to a second entity; receiving, by the first entity from the second entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session; and determining transitions between states of the data session by using a value of an inactivity timer of the data session updated based on the output analysis.

According to another aspect of the present disclosure, there is provided an apparatus for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis. The apparatus of the second entity includes a transceiver and a processor coupled to the transceiver, the processor configured to: input data including communication description information of at least one User Equipment (UE) is obtained, and an output analysis generated based on the input data is provided to the first entity, the output analysis including a UE communication analysis for each data session, wherein the output analysis is used to determine whether to update a value of an inactivity timer for the data session.

According to another aspect of the present disclosure, there is provided an apparatus for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis. The apparatus of the first entity includes a transceiver and a processor coupled to the transceiver, the processor configured to: transmitting input data including communication description information of at least one User Equipment (UE) to a second entity; receiving, from the second entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session; and determining transitions between states of the data session by using a value of an inactivity timer of the data session updated based on the output analysis.

It is an object of certain examples of the present disclosure to at least partially address, solve, and/or mitigate at least one problem and/or disadvantage associated with the related art, such as at least one problem and/or disadvantage described herein. It is an object of certain examples of the present disclosure to provide at least one advantage over the related art, such as at least one advantage described herein.

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

Other aspects, advantages, and salient features of the disclosure will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the annexed drawings, discloses various embodiments of the disclosure.

Drawings

The foregoing and other aspects, features, and advantages of certain embodiments of the disclosure will become more apparent from the following description, taken in conjunction with the accompanying drawings, in which:

fig. 1 illustrates an operation of a network data analysis function (NWDAF) according to an embodiment of the present disclosure;

FIG. 2 illustrates an example of the present disclosure based on NWDAF and multiple input data sources, in accordance with an embodiment of the present disclosure;

fig. 3a and 3b illustrate a process of supporting NWDAF-based user plane optimization in accordance with various embodiments of the present disclosure; and

fig. 4 is a block diagram of a network entity that may be used in some examples in accordance with an embodiment of the present disclosure.

Like reference numerals will be understood to refer to like parts, assemblies and structures throughout the drawings.

Detailed Description

The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of the various embodiments of the disclosure as defined by the claims and their equivalents. It includes various specific details to aid understanding, but these are to be considered exemplary only. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the various embodiments described herein can be made without departing from the scope and spirit of the present disclosure. In addition, descriptions of well-known functions and constructions may be omitted for clarity and conciseness.

The terms and words used in the following description and claims are not limited to literature meanings, but are used only by the inventors to enable clear and consistent understanding of the present disclosure. Accordingly, it will be apparent to those skilled in the art that the following descriptions of the various embodiments of the present disclosure are provided for illustration only and not for the purpose of limiting the disclosure as defined by the appended claims and their equivalents.

It should be understood that the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a component surface" includes reference to one or more such surfaces.

The same or similar components may be denoted by the same or similar reference numerals although they may be shown in different drawings.

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

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

Throughout the description and claims of this specification, the words "comprise," "include" and "contain" and variations of the words, such as "comprises" and "comprising," mean "including but not limited to" and are not intended to (and do not exclude) other features, elements, components, integers, steps, procedures, operations, functions, properties, attributes and/or combinations thereof.

For example, a reference to an "object" includes a reference to one or more such objects.

Throughout the description and claims of this specification, means X is included in the general form of "X for Y" (where Y is an action, process, operation, function, activity or step and X is a device for performing the action, process, operation, function, activity or step) that is specifically, but not necessarily exclusively, adapted, configured or arranged to perform Y.

Features, elements, components, integers, steps, processes, operations, functions, characteristics, properties, and/or combinations thereof described or disclosed in connection with a particular aspect, embodiment, example, or claim of the disclosure 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 data sessions in a network. The following examples apply to 3gpp 5g and use terminology associated therewith. 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 analysis. However, those skilled in the art will appreciate that the techniques disclosed herein are not limited to these examples or 3gpp 5g and may be applied to any suitable system or standard, such as 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. A corresponding or equivalent entity or feature may be seen as an entity or feature that performs the same or similar role, function, operation or purpose within a network.

For example, the functionality of NWDAF in the following examples may be applied to any other suitable type of entity that provides network analysis; the functions of the User Plane Functions (UPFs) in the following examples may be applied to any other suitable type of entity that provides user plane functions; the functions of the access and mobility management functions (AMFs) in the following examples may be applied to any other suitable type of entity performing mobility management functions; the functionality of the Session Management Function (SMF) in the following examples may be applied to any other suitable type of entity that performs session management functions; and the functions of AF in the following examples may be applied to any other suitable type of entity that performs the corresponding application functions.

Those skilled in the art will appreciate that the present disclosure is not limited to the specific examples disclosed herein. For example:

the techniques disclosed herein are not limited to 3gpp 5g.

One or more of the entities in the examples disclosed herein may be replaced by one or more alternative entities that perform equivalent or corresponding functions, processes, or operations.

One or more messages in examples disclosed herein may be replaced with one or more alternative messages, signals, or other types of information carriers conveying equivalent or corresponding information.

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

In some examples, one or more unnecessary elements, entities, and/or messages may be omitted.

In one example, the functionality, process, or operation of a particular entity may be divided among two or more separate entities in another example.

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

In one example, the information carried by a particular message may be carried by two or more separate messages in another example.

In one example, information carried by two or more separate messages may be carried by a single message in another example.

In alternative examples, the order in which operations are performed may be modified, if possible.

The transmission of information between network entities is not limited to the specific form, type, and/or sequence of messages described in connection with 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 methods thereof. Certain examples of the present disclosure may be provided in the form of a system (e.g., a network) including one or more such apparatus/devices/network entities and/or methods thereof.

The network may include one or more of a User Equipment (UE), a Radio Access Network (RAN), an access and mobility management function (AMF) entity, a Session Management Function (SMF) entity, a User Plane Function (UPF) entity, a network data analysis function (NWDAF) entity, an Application Function (AF) entity, and one or more other Network Function (NF) entities.

The particular network functions may be implemented as network elements on dedicated hardware, as software instances running on dedicated hardware, or as virtualized functions instantiated on an appropriate platform (e.g., on a cloud infrastructure). NF services may be defined as functions exposed by the NF through a service-based interface and consumed by other authorized NFs.

As described above, a technique for setting or adjusting the value of the inactivity timer to optimize overall performance is needed.

Certain examples of the present disclosure are capable of optimizing the above-described tradeoff between UE battery consumption and network resource efficiency by utilizing a standardized data analysis framework. Thus, a compatible AI-based solution using data analysis may be based on the NWDAF framework. A brief overview of an NWDAF framework, such as defined in [2], will now be described.

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

3GPP: third generation partnership project

5G: fifth generation of

5GC:5G core network 5

5GS:5G system

AF: application function

AI: artificial intelligence

AMF: access and mobility management functions

CM: connection management

CN: core network

CPU: central processing unit

DL: downlink link

DNN: data network name

gNB:5G base station

GPSI: public subscription identifier

ID: identifier/identification

LTE: long term evolution

MDA: management data analysis

MDAS: managing data analysis services

N4: interface between SMF and UPF

NF: network function

NG: next generation

NRF: network repository function

NWDAF: network data analysis function

OAM: operation and maintenance

OPEX: operational expenditure

PDU: protocol data unit

RAN: radio access network

Rel: version of

RRC: radio resource control

SLA: service level agreement

SMF: session management function

S-NSSAI: single network slice selection assistance information

SUPI: subscribing to permanent identifiers

TA: tracking areas

TAC: type assignment code

TR: technical report

TS: technical specification of

UE: user equipment

UL: uplink channel

UPF: user plane functionality

Fig. 1 illustrates an operation of an NWDAF according to an embodiment of the present disclosure. Recently frozen 3GPP release 16 has specified an NWDAF framework as shown in fig. 1. In the basic operation of the NWDAF shown in fig. 1, the analysis consumer requests a data analysis from the NWDAF, which gathers data from different entities to perform training and inference before generating an output analysis.

Referring to fig. 1, analysis consumer 102 may request a particular type of data analysis from NWDAF 100, which may be provided by NWDAF 100 in a statistical and/or predictive form. The analysis consumers defined in release 16 (e.g., analysis consumer 102) are 5GC NF, application Functions (AF), and OAM. NWDAF 100 then triggers input data collection through the public framework defined in [2], where the input data source (e.g., 5gc NF 104, AF 106, and/or OAM 108).

The collected data is then used by NWDAF 100 to perform training and inference, possibly by the AI engine, but the definition of the model is outside of the scope of standardization to provide sufficient flexibility to the vendor. This also means that the AI engine may reside outside the NWDAF 100 itself and the next version of the standard (version 17) has begun to study any required interface standardization to achieve such NWDAF functional decomposition [3]. The same considerations apply to the input data collection module. In certain examples of the present disclosure, the AI engine and the input data collection module are assumed to reside within NWDAF 100, although the present disclosure is not limited in this context.

In any event, the inferred results are then fed to an analytics production entity within NWDAF 100 that delivers statistics and/or predictions requested by the service consumer.

Many data analysis types as described in [2] are also introduced in 3GPP release 16, including analysis of network slicing and application service experience, NF and network slicing load, network performance, UE aspects (communication, mobility, expected and anomalous behavior), etc.

In addition to the basic operations described above, release 17, which is already ongoing, is expanding the release 16NWDAF framework by solving many new use cases and key issues, including the above described NWDAF functional decomposition, architecture and interactions of multiple NWDAF instances, efficient data collection mechanisms, support for network slice Service Level Agreement (SLA) guarantees, and the like.

Based on the above framework description, certain examples of the present disclosure embed autonomous capabilities directly in the 5G architecture to intelligently and dynamically set inactivity timer values to each 5G PDU session of the UE. This approach has the advantage of being highly achievable in current and at least near future networks, as the basic data collection capabilities of NWDAFs used in certain examples of the present disclosure are already defined in the specification.

Hereinafter, an instantiation of the framework of the above-described problem is described, as well as a description of the AI problem constructed in the context of NWDAF data analysis.

However, those skilled in the art will appreciate that the techniques described herein are not limited to setting or adjusting timer values, but may be used to set or adjust any other suitable parameter in a network.

Hereinafter, an AI-based technique for setting/adjusting inactivity timers for activating and deactivating PDU sessions associated with multiple services consumed by a UE using NWDAF is described. In particular, an overall NWDAF-based technique is described that emphasizes the applicability of this technique to current standardized networks. A detailed process of instantiating a particular framework is also described.

Fig. 2 illustrates an overall NWDAF-based design utilizing a version 16 data analysis framework (e.g., described in [1 ]) in accordance with an embodiment of the present disclosure. This example is based on a number of input data sources (e.g., OAM 202, SMF 210, UPF/AF 204, and AMF 206, and optionally NG-RAN and UE), AI-based training and inference modules in NWDAF 200, and output analysis delivered to SMF 210 and forwarded to UPF 208. The skilled artisan will appreciate that the present disclosure is not limited to these examples.

Referring to fig. 2, the internal NWDAF architecture in this example follows the general principles shown in fig. 1, where the general analytical model outside the scope of standardized operation has been replaced by an inference, training-based model, as will be described further below. In addition, FIG. 2 shows the input data source for the agent to learn the optimal inactivity timer value and provide the required analysis.

To respect the framework that has been agreed and frozen in 3GPP, certain examples of the present disclosure may only require supported 5GC entities (i.e., SMF 210, UPF 208, AMF 206), AF 204, and OAM202 to provide the input data. However, the present disclosure is not limited to this case. For example, fig. 2 indicates various other entities, namely NG-RAN and UE, that may provide required input data to NWDAF 200 that is not currently supported in the standard. In some examples, these other entities are not required as they may be replaced by alternative entities currently supported. Future versions of the standard may support these other entities as data sources.

Furthermore, in the following, in the context of AI-based training and inference models, it is described which specific input data can be used. In some examples described below, all input data may be mapped to standardized NWDAF input data, such as UE communication data 222 (e.g., including start and end time stamps, uplink and downlink data rates, traffic, etc.), cell load information 220 measured in number of active PDU sessions, and UE type [8]. In some examples, the UE type or UE information 224 may only need to be collected once, as opposed to the UE communication data and cell load, because it does not change during network operation.

With respect to the output analysis provided by NWDAF 200, certain examples of the present disclosure may conform to current 3GPP framework by generating a data analysis (e.g., including UE communication analysis 226 and/or network performance analysis) in the form of a "best predictor" for session inactivity timers, which may be fed directly to SMF 210.NWDAF 200 may also provide past statistics of timer values.

Thus, the data analysis delivered by NWDAF 200 may then be used by SMF 210 to (i) activate or deactivate PDU sessions when needed, and (ii) update timer values (e.g., timer value 228 of PDU session) using NWDAF predictions and notify UPF 208 of such updates. These two actions may be performed, for example, by the SMF 210, e.g., by following standardized procedures of PDU session activation and deactivation and user plane management as defined in [4 ].

Data analysis

In some examples, to enable PDU session timer based user plane connection optimization, the following existing NWDAF analysis defined in [2] may be used. However, in their current form, they may not support the various examples of the present disclosure. Thus, as described below, certain examples of the present disclosure extend the current definition. Hereinafter, UE communication analysis 226 and network performance analysis are described. However, the skilled artisan will appreciate that the present disclosure is not limited to these specific examples.

UE communication analysis

The NWDAF supporting UE communication analysis may collect a communication description of each application from the AF. In some examples, if the consumer NF provides an application ID, the NWDAF may consider only the data from the AF, SMF, and UPF corresponding to the application ID.

The consumer of these analyses may indicate in the request one or more of the following non-limiting examples:

the target of the analysis report may be a single UE or a group of UEs.

Analyze filter information, optionally including one or more of the following non-limiting examples:

o S-NSSAI；

o DNN；

o application ID;

o region of interest.

-analysing the target period, indicating a time period for which statistics and/or predictions are requested.

A preferred level of analytical accuracy (e.g., low/high).

-a maximum number of objects;

in the subscription, a notification related ID and a notification target address may be included.

a) Input data: table 1 shows the current input data specification for UE communication analysis in [2 ]. Certain examples of the present disclosure may use one or more of such information. Those skilled in the art will appreciate that the exact form of the input data and/or the source of such information is not necessarily limited to the specific examples shown in table 1. Table 1 shows service data related to UE communication from 5 GC.

[ Table 1 ]

In certain examples of the present disclosure, one or more of the input data shown in table 2 may be used, for example, in addition to one or more of the input data according to table 1. In some 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 separate entries for each PDU session. Those skilled in the art will appreciate that the exact form of the input data or the source of such information is not necessarily limited to the specific examples shown in table 2. Table 2 shows an example of additional service data related to UE communication from 5 GC.

[ Table 2]

/>

b) Output analysis: table 3 shows the current output analysis specification for UE communication analysis in [2 ]. Statistics may not require the input of "confidence", but predictions may. Certain examples of the present disclosure may generate one or more output analyses from table 3. Those skilled in the art will appreciate that the exact form of output analysis need not be limited to the specific examples shown in table 3. Table 3 shows UE communication output analysis.

[ Table 3 ]

In certain examples of the present disclosure, one or more output analyses shown in table 4 may be generated, for example, in addition to one or more output analyses according to table 3. Those skilled in the art will appreciate that the exact form of output analysis need not be limited to the specific examples shown in table 4. Table 4 shows an example of additional output analysis data for UE communication.

[ Table 4 ]

Additional information	Description of the invention
		(>) PDU session ID (1 … maximum)	Identification of PDU session
>N4 Session ID	Identification of N4 sessions
		>Inactivity detection time	Session inactivity timer value (average, variance)

Network performance analysis

In certain examples of the present disclosure, network performance analysis of NWDAF (in addition to or instead of UE communication and/or other analysis) may be used to optimize performance of the user plane. For example, in addition to UE communication analysis, the SMF may use network performance analysis to derive timer values that optimize not only the performance of individual UEs, but also the performance of the entire network, especially the RAN.

a) Input data: table 5 shows the current input data specification for UE communication analysis in [2 ]. Certain examples of the present disclosure may use one or more of such information. Those skilled in the art will appreciate that the exact form of the input data and/or the source of such information is not necessarily limited to the specific examples shown in table 5. Table 5 shows the input data for the network performance analysis.

[ Table 5 ]

b) Output analysis: table 6 shows the current output analysis specifications for the network performance analysis in [2 ]. Statistics may not require the input of "confidence", but predictions may. Certain examples of the present disclosure may generate one or more output analyses from table 6. Those skilled in the art will appreciate that the exact form of output analysis need not be limited to the specific examples shown in table 6. Table 6 shows the network performance output analysis.

[ Table 6 ]

In certain examples of the present disclosure, one or more output analyses shown in table 7 may be generated, for example, in addition to one or more output analyses according to table 6. Those skilled in the art will appreciate that the exact form of output analysis need not be limited to the specific examples shown in table 7. For example, some examples may generate output analysis displayed in bold + italics. Table 7 shows additional network performance output analysis examples.

[ Table 7 ]

Fig. 3a and 3b illustrate a process of supporting NWDAF-based user plane optimization in accordance with various embodiments of the present disclosure.

Fig. 3a and 3b show a procedure for supporting NWDAF-based user plane optimization. Various operations in the procedure are as follows. In various examples, certain operations (e.g., those indicated with dashed arrows/boxes) may be omitted. For simplicity, fig. 3a and 3b show two sets of alternative operations (alternative 1 and alternative 2). In various examples, one or the other of these alternatives may be used. Those skilled in the art will appreciate that the present disclosure is not limited to the specific examples of fig. 3a and 3 b.

Referring to fig. 3a and 3b, in operation 300, a PDU session may be established through UE, RAN, AMF, SMF and UPF. A corresponding user plane connection needs to be activated for data transmission. During this procedure, the user plane connection may be deactivated if the inactivity timer expires and activated if new data services are available.

In operation 301, an SMF (e.g., SMF 210) subscribes to UE communication analysis from an NWDAF (e.g., NWDAF 200).

In operation 302, the [ optional ] SMF may subscribe to the network performance analysis from the NWDAF.

Input data collection: there are two alternatives for data collection related to the N4 session.

Alternative 1 uses SMF and its corresponding service disclosure framework to retrieve the required input data described in this disclosure, while alternative 2 relies on implementation-specific mechanisms for UPF input data retrieval.

Alternative 1[ all messages optional ]: SMF-based N4 session data collection

In operation 303a, the nwdaf may request N4 session related input data from the SMF, as defined in table 2. For example, as specified in TS 23.288[2] and Table 2, it may also request other UE communication data with SMF as source NF.

At operation 303b, the smf may request an N4 session level report from a UPF (e.g., UPF 208).

In operation 303c, the UPF may provide the requested N4 session level report to the SMF, e.g., according to clause 4.4.2.2 in TS 23.502[4 ].

At operation 303d, the smf may provide the NWDAF with the requested N4 session related input data.

Alternative 2: UPF-based N4 session data collection

In operation 304, [ optional ] NWDAF may collect N4 session related input data directly from the UPF via implementation specific mechanisms.

In operation 305, the NWDAF may collect the remaining input data needed to generate the requested analysis, e.g., according to TS 23.288 < 2 >.

In operation 306, the nwdaf may provide the UE communication analysis to the SMF, e.g., as defined in TS 23.288[2] and table 4.

In operation 307, optional if operation 302 is performed, the NWDAF may provide the network performance analysis to the SMF, e.g., as specified in TS 23.288[2 ]. It may also add output analysis data as shown in table 7.

The SMF may also process the received analysis provided by the NWDAF as the SMF continues its task of activating and deactivating PDU sessions in operation 308.

At operation 309, based on its analysis of NWDAF analysis, the SMF may decide to update the user plane inactivity timers for certain PDU sessions associated with the corresponding N4 session.

At operation 310, the SMF may trigger an N4 session modification procedure to notify the UPF of the update of the inactivity timer, e.g., according to clause 4.4.1.3 in TS 23.502[4 ].

Certain examples of the present disclosure provide a method for setting a value of an inactivity timer for transitioning between states of data sessions in a network including a first entity and a second entity providing network analysis, the method performed by the second entity may include obtaining, by the second entity, input data including communication description information of at least one User Equipment (UE), and providing, by the second entity, to the first entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session, wherein the output analysis is used to determine whether to update the value of the inactivity timer for the data session.

Certain examples of the present disclosure provide a method for setting a value of an inactivity timer for transitioning between states of data sessions in a network that includes a first entity and a second entity that provides network analysis, the method performed by the first entity may include: the method includes transmitting, by a first entity, input data including communication description information of at least one User Equipment (UE) to a second entity, receiving, by the first entity, from the second entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session, and determining transitions between states of the data sessions by using a value of an inactivity timer for the data session updated based on the output analysis.

Certain examples of the present disclosure provide an apparatus for setting a value of an inactivity timer for transitioning between states of a data session in a network comprising a first entity and a second entity providing network analysis, the apparatus of the second entity may include a transceiver and a processor coupled with the transceiver, the processor configured to: input data including communication description information of at least one User Equipment (UE) is obtained, and an output analysis generated based on the input data is provided to the first entity, the output analysis including a UE communication analysis for each data session, wherein the output analysis is used to determine whether to update a value of an inactivity timer for the data session.

Certain examples of the present disclosure provide an apparatus for setting a value of an inactivity timer for transitioning between states of a data session in a network comprising a first entity and a second entity providing network analysis, the apparatus of the first entity may include a transceiver and a processor coupled with the transceiver, the processor configured to: the method includes transmitting input data including communication description information of at least one User Equipment (UE) to a second entity, receiving an output analysis generated based on the input data from the second entity, the output analysis including UE communication analysis for each data session, and determining transitions between states of the data sessions by using a value of an inactivity timer for the data session updated based on the output analysis.

Certain examples of the present disclosure provide a method for a second entity (e.g., NWDAF) to provide network analysis in a network comprising a first entity (e.g., SMF) and the second entity, the method comprising: obtaining input data including communication description information; and determining an output analysis based on the input data including a per data session User Equipment (UE) communication analysis and providing the output analysis to the first entity. Based on the output analysis, the first entity may determine whether to update a timer value of the data session, the timer (e.g., inactivity timer) being used to transition between states (e.g., active/inactive states) of the data session (e.g., PDU session).

Certain examples of the present disclosure provide a second entity (e.g., NWDAF) that provides network analysis in a network that includes the first entity (e.g., SMF) and the second entity, the second entity configured to: obtaining input data including communication description information; and determining an output analysis based on the input data including a per data session User Equipment (UE) communication analysis and providing the output analysis to the first entity. Based on the output analysis, the first entity may determine whether to update a timer value of the data session, the timer (e.g., inactivity timer) being used to transition between states (e.g., active/inactive states) 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 states) 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) that provides network analysis, the method comprising: obtaining, by a second entity, input data comprising communication description information; determining, by the second entity, an output analysis including per data session User Equipment (UE) communication analysis based on the input data and providing the output analysis to the first entity; and determining, by the first entity, whether to update a timer value of the data session based on the output analysis.

In some examples, the method may further include receiving, by the second entity, a request (e.g., a subscription) for output analysis from the first entity.

In some examples, the request may include one or more of the following: a request for analysis related to a particular UE or group of UEs; and an analysis filter.

In some examples, the analysis filter may specify one or more of the following as filtering criteria: information specifying one or more S-nsais; information specifying one or more DNNs; one or more application IDs; information indicative of one or more regions of interest; information specifying an analysis target period indicating a time period for which statistics and/or predictions are requested; information indicating a preferred level of analysis accuracy (e.g., low/high); information specifying a maximum number of objects; and in the subscription, notifying the relevant ID and notifying the destination address.

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

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

In some examples, the input data may also include additional input data obtained from one or more network entities (e.g., AMF, SMF, UPF, OAM, one or more AFs, NG-RANs, and/or UEs).

In some examples, acquiring the input data may be performed continuously.

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

In some examples, the method may further include transitioning between states of the data connection based on the corresponding timer value (and optional traffic).

In some examples, the input data may include one or more of the information specified in table 1.

In some examples, the input data may include one or more of the following: an identification of one or more PDU sessions (e.g., obtained from the SMF); an identification of the N4 session (e.g., obtained from SMF and/or UPF); a value of a session inactivity timer (e.g., obtained from the SMF and/or UPF); information (e.g., obtained from an SMF) indicating a status (e.g., active or inactive) of one or more PDU sessions; and analyzing one or more UE states (e.g., obtained from the AMF) of the target period throughout (throughput).

In some examples, the UE communication analysis may include one or more of the information specified in table 3.

In some examples, the UE communication analysis may include one or more of the following: an identification of one or more PDU sessions; identification of the N4 session; and a value (e.g., average or variance) of the session inactivity timer.

In some examples, the output analysis may further include a network performance analysis.

In some examples, the input data may include one or more of the information specified in table 5.

In some examples, the network performance analysis may include one or more of the information specified in table 6.

In some examples, the network performance analysis may include one or more of the following: average usage of allocated resources (e.g., spectrum, CPU, memory, and/or disk); and an average network outage in the subset of regions during the analysis target period.

In some examples, the input data may include communication description information related to one or more of the following: an Application Function (AF); a data session; a UE; slicing the network; 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) configured to operate according to any of the methods disclosed herein.

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

Certain examples of the present disclosure provide a computer program comprising instructions that, when executed by a computer or processor, cause the computer or processor to perform any of the methods 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 examples.

In some examples of the present disclosure, the value of the inactivity timer may be set for activation and deactivation of data sessions associated with multiple services in the network.

In some examples of the present disclosure, the input data may include UE communication data, cell load measured in number of active data sessions, and UE type.

In certain examples of the present disclosure, the UE communication data may include at least one of start and end time stamps, uplink and downlink data rates, traffic volume.

Fig. 4 is a block diagram of a network entity that may be used in examples according to embodiments of the present disclosure. For example, UE, AMF, SMF, UPF, NWDAF, AF and/or other NFs may be provided in the form of network entities as shown in fig. 4. Those skilled in the art will appreciate that the network entities shown in fig. 4 may be implemented as, for example, network elements on dedicated hardware, software instances running on dedicated hardware, or virtualized functions instantiated on a suitable platform (e.g., on a cloud infrastructure).

Referring to fig. 4, an entity 400 may include at least one of a processor (or controller) 401, a transmitter 403, and a receiver 405. The receiver 405 may be configured to receive one or more messages or signals from one or more other network entities, either wirelessly or by wire. The transmitter 403 may be configured to transmit one or more messages or signals to one or more other network entities, either wirelessly or by wire. The processor 401 may be configured to perform one or more operations and/or functions as described above. For example, the processor 401 may be configured to perform UE, AMF, SMF, UPF, NWDAF, AF and/or other NF operations.

The techniques described herein may be implemented using any suitably configured device and/or system. Such apparatus and/or systems may be configured to perform methods according to any aspect, embodiment, example, or claim disclosed herein. Such an apparatus may comprise one or more elements, e.g., one or more of a receiver, transmitter, transceiver, processor, controller, module, unit, etc., each configured to perform one or more corresponding processes, operations, and/or method steps to implement the techniques described herein. For example, the operations/functions of X may be performed by a module (or X module) configured to perform X. One or more elements may be implemented in hardware, software, or any combination of hardware and software.

It should be understood that examples of the present disclosure may be implemented in hardware, software, or any combination of hardware and software. Any such software may be stored in the form of volatile or non-volatile memory, such as a storage device like read-only memory (ROM), whether erasable or rewritable or not, or in the form of memory, such as Random Access Memory (RAM), memory chips, devices or integrated circuits, or on an optically or magnetically readable medium, such as a Compact Disc (CD), digital Versatile Disc (DVD), magnetic disk or tape, etc.

It should be appreciated that the storage devices and storage media are embodiments of machine-readable storage that are adapted to store one or more programs comprising instructions that, when executed, implement certain examples of the present disclosure. Accordingly, certain examples 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. Further, such programs may be transmitted electronically via any medium, such as communication signals transmitted via a wired or wireless connection.

While the present disclosure has been shown and described with reference to various embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by any appended claims and their equivalents.

Claims (15)

1. A method for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis, the method performed by the second entity comprising:

obtaining, by a second entity, input data comprising communication description information of at least one User Equipment (UE); and

providing, by the second entity, to the first entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session,

wherein the output analysis is used to determine whether to update the value of the inactivity timer for the data session.

2. The method of claim 1, wherein the input data comprises one or more of:

an identification of each of one or more Protocol Data Unit (PDU) sessions obtained from at least one Session Management Function (SMF);

an identification of an N4 session between the at least one SMF and at least one User Plane Function (UPF) obtained from the at least one SMF and/or the at least one UPF;

A value of a session inactivity timer obtained from the at least one SMF and/or the at least one UPF;

information obtained from the at least one SMF indicating that the state of one or more PDU sessions is active or inactive; and

one or more UE states obtained from at least one access and mobility management function (AMF) throughout an analysis target period.

3. The method of claim 1, wherein UE communication analysis comprises one or more of:

an identification of an N4 session between the first entity and at least one User Plane Function (UPF); and

a value of a session inactivity timer.

4. A method according to claim 1, wherein the method comprises,

wherein the output analysis further comprises a network performance analysis

Wherein the network performance analysis includes one or more of:

average usage of allocated resources, and

during the analysis target period, an average number of network outages in the subset of regions.

5. The method of claim 1, wherein the input data includes communication description information related to one or more of:

at least one Session Management Function (SMF);

at least one User Plane Function (UPF); and

at least one access and mobility management function (AMF).

6. A method for setting a value of an inactivity timer for transitioning between states of a data session in a network comprising a first entity and a second entity providing network analysis, the method performed by the first entity comprising:

transmitting, by a first entity, input data including communication description information of at least one User Equipment (UE) to a second entity;

receiving, by the first entity from the second entity, an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session; and

transitions between states of the data session are determined by using a value of an inactivity timer for the data session that is updated based on the output analysis.

7. The method of claim 6, wherein the input data comprises one or more of:

an identification of each of one or more Protocol Data Unit (PDU) sessions;

an identification of an N4 session between the first entity and at least one User Plane Function (UPF);

a value of a session inactivity timer;

information indicating that a state of one or more PDU sessions is active or inactive; and

one or more UE states throughout an analysis target period.

8. The method of claim 6, wherein UE communication analysis comprises one or more of:

An identification of an N4 session between the first entity and at least one User Plane Function (UPF); and

a value of a session inactivity timer.

9. The method of claim 6, wherein the output analysis further comprises a network performance analysis, and

wherein the network performance analysis includes one or more of:

average usage of allocated resources, and

during the analysis target period, an average number of network outages in the subset of regions.

10. The method of claim 6, wherein the input data includes communication description information related to one or more of:

a first entity;

at least one User Plane Function (UPF); and

at least one access and mobility management function (AMF).

11. The method of claim 6, further comprising:

receiving a request from a second entity for session parameters related to a session between the first entity and a User Plane Function (UPF);

transmitting, by the first entity, a request for a session report to the UPF;

receiving, by the first entity, session parameters from the UPF; and

the session parameters are sent by the first entity to the second entity.

12. An apparatus for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis, the apparatus of the second entity comprising:

A transceiver; and

a processor coupled with the transceiver and configured to:

obtaining input data comprising communication description information of at least one User Equipment (UE), and

providing an output analysis to the first entity, the output analysis comprising a UE communication analysis for each data session,

wherein the output analysis is used to determine whether to update the value of the inactivity timer for the data session.

13. The apparatus of claim 12, wherein the processor is configured to perform the method of one of claims 2 to 5.

14. An apparatus for setting a value of an inactivity timer for transitioning between states of data sessions in a network comprising a first entity and a second entity providing network analysis, the apparatus of the first entity comprising:

a transceiver; and

a processor coupled with the transceiver and configured to:

transmitting input data comprising communication description information of at least one User Equipment (UE) to a second entity,

receiving from the second entity an output analysis generated based on the input data, the output analysis including a UE communication analysis for each data session, and

Transitions between states of the data session are determined by using a value of an inactivity timer for the data session that is updated based on the output analysis.

15. The apparatus of claim 14, wherein the processor is configured to perform the method of one of claims 7 to 11.

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