JP7767393B2 - Method and apparatus for setting timer values in a network - Google Patents

Description

The present invention relates to a method and apparatus for setting timer values for transitioning between states of a data session in a network.

Looking back at the evolution of wireless communications through successive generations, technologies have been developed primarily for human-oriented services, such as voice, multimedia, and data. Following the commercialization of 5G (5th-generation) communications systems, an explosive increase in connected devices is expected to be connected to communications networks. Examples of network-connected things include vehicles, robots, drones, home appliances, displays, smart sensors installed in various infrastructures, construction machinery, and factory equipment. Mobile devices are expected to evolve into various form factors, such as augmented reality glasses, virtual reality headsets, and holographic devices. In the 6G (6th-generation) era, efforts are underway to develop improved 6G communications systems to connect hundreds of billions of devices and things and provide a variety of services. For this reason, 6G communications systems are being referred to as systems beyond 5G.

In 6G communication systems, which are predicted to be realized around 2030, the maximum transmission speed will be terabits per second (i.e., 1,000 gigabits per second) and the wireless latency will be 100 microseconds (μsec). In other words, the transmission speed in 6G communication systems will be 50 times faster than in 5G communication systems, and the wireless latency will be one-tenth of that in 5G communication systems.

To achieve such high data rates and ultra-low latency, 6G communication systems are being considered for implementation in the terahertz band (e.g., the 95 gigahertz (95 GHz) to 3 terahertz (3 THz) band). Compared to the millimeter wave (mmWave) band introduced with 5G, the terahertz band has more severe path loss and atmospheric absorption, making technology to ensure signal reach, or coverage, even more important. Key technologies to ensure coverage include radio frequency (RF) elements, antennas, new waveforms with better coverage than orthogonal frequency division multiplexing (OFDM), beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antennas, large scale antennas, and other multi-antenna transmission technologies. Other new technologies being discussed to improve the coverage of terahertz band signals include metamaterial-based lenses and antennas, high-dimensional spatial multiplexing technology using orbital angular moment (OAM), and reconfigurable intelligent surface (RIS).

In addition, to improve frequency efficiency and system network performance, 6G communication systems will incorporate a variety of technologies, including full duplex technology, which allows uplink and downlink to simultaneously utilize the same frequency resources at the same time; network technology that integrates satellites and high-altitude platform stations (HAPS); innovative network structure technology that supports mobile base stations and enables optimization and automation of network operations; dynamic spectrum sharing technology that avoids collisions based on spectrum usage prediction; AI-based communication technology that utilizes AI (artificial intelligence) from the design stage to incorporate end-to-end AI support functions to achieve system optimization; and user Development is underway on next-generation distributed computing technologies that utilize ultra-high-performance communications and computing resources (such as mobile edge computing (MEC) and the cloud) to provide services of a complexity exceeding the limits of the computing power of user equipment (UE). Furthermore, efforts are ongoing to further strengthen connectivity between devices, further optimize networks, promote the softwarization of network entities, and increase the openness of wireless communications through the design of new protocols to be used in 6G communications systems, the realization of hardware-based security environments, the development of mechanisms for secure data utilization, and the development of technologies related to privacy maintenance methods.

Research and development into such 6G communication systems is expected to enable a new level of hyper-connected experience through the hyper-connectivity of the 6G communication system, which encompasses connections not only between things but also between people and things. Specifically, the 6G communication system is expected to enable services such as truly immersive extended reality (truly immersive XR), high-fidelity mobile holograms, and digital replicas. In addition, with improved security and reliability, services such as remote surgery, industrial automation, and emergency response will be provided via 6G communication systems, leading to applications in a variety of fields, including industry, medicine, automobiles, and home appliances.

Please refer to the following document below.

[1] 3GPP (registered trademark) (3rd Generation Partnership Project) TR (Technical Report) 28.809: Study on enhancement of Management Data Analytics (MDA), Rel-17 (06-2020)
[2] 3GPP (registered trademark) TS23.288: Architecture enhancements for 5G System (5GS) to support network data analytics services, Rel-16 (06-2020)
[3] 3GPP (registered trademark) TR23.700-91: Study on enablers for network automation for the 5G System (5GS); Phase 2, Rel-17 (06-2020)
[4] 3GPP (registered trademark) TS23.502: Procedures for the 5G System (5GS), Rel-16 (06-2020)

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

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

A pioneer in terms of RAN, the O-RAN Alliance was founded in 2018 by leading operators with the vision to develop open specifications for an open and efficient RAN that uses AI to automate various network functions (NFs) and reduce operating expenses (OPEX).

Furthermore, standardized support for data analytics by 3GPP® is already progressing in Rel-16, particularly on the CN side and control plane. As a network function following the principles of 5GC's service-based architecture, a new data analytics framework anchored in the so-called network data analytics function (NWDAF) located within 5GC has been defined with the aim of enhancing the network's multiple control plane functions. Furthermore, on the OAM side, 3GPP has also specified a management data analytics service (MDAS) to help handle the long-term management aspects of the network [1]. The joint operation of the RAN analytics entity, the network data analytics function (NWDAF), and the MDAS is still underway within the relevant organizations.

It is preferable for the UE to be able to activate and deactivate 5G protocol data session (PDU) sessions. Such functionality typically resides in the control plane of the CN, as it requires fast timescales, i.e., decisions to be made much faster than network management and integration systems generally allow.

5G standards from the 3rd Generation Partnership Project (3GPP) have already developed support for individual and dynamic activation/deactivation of each PDU session established by the UE, but the various transitions from deactivation to activation of PDU sessions and the associated UE states generate significant control signaling overhead in the network.

Therefore, this transition must be carefully controlled so that the benefits of deactivating a PDU session are not offset by the signaling overhead caused by the transition. While adaptive inactivity timers for individual UEs are a proposed tool to address the above issues, they do not take into account the per-PDU-session granularity required to optimize the inactivation timer value in 5G networks. Furthermore, they rely on heuristic algorithms to set an appropriate value instantaneously, resulting in suboptimal performance.

To minimize UE battery power consumption and network resource usage, it is important to assign an appropriate value to the inactivity timer. The inactivity timer is designed to control the timing of PDU session and ultimately UE state transitions. A shorter inactivity timer length reduces UE battery power consumption by keeping the UE in CM (connection management)-IDLE state while the UE powers off its radio module, but it results in frequent transitions between PDU session activation states and UE CM states, resulting in significant control signaling overhead within the network. In particular, changing the UE state from CM-IDLE to CM-CONNECTED requires the necessary paging messages to be broadcast over multiple cells, consuming significant radio resources. However, making the inactivity timer too long can result in less efficient use of radio resources and result in more battery power consumption for UEs that experience a long tail time while remaining in CM-CONNECTED before transitioning to CM-IDLE.

Therefore, a technique is needed to set or adjust the inactivity timer value to optimize overall performance.

The above information is presented solely as background information to aid in the understanding of the present invention. No determination has been made, and no assertion is being made, as to the applicability of any of the above as prior art with respect to the present invention.

For example, one embodiment of the present invention provides a method, apparatus, and system for setting an inactivity timer value for transitions between active and inactive states of a PDU session in a 3GPP 5G network based on NWDAF analysis. Aspects of the present invention address at least the problems and/or drawbacks described above and provide at least the advantages described below.

The present invention was made in consideration of the above-mentioned problems with the conventional technology, and its object is to provide a method and apparatus for setting timer values for transitioning between data session states in a network.

Further aspects will be set forth in part in the description that follows, and in part will be apparent from the description or may be learned by practice of the embodiments presented.

In order to achieve the above object, one aspect of the present invention provides a method performed by a first entity and a second entity that provides network analysis to set inactivity timer values for transitions between states of data sessions in a network including the first entity and the second entity, the method comprising: obtaining, by the second entity, input data including communication description information for at least one user equipment (UE); and providing, by the second entity, to the first entity, output analysis generated based on the input data and including UE communication analysis for each data session, the output analysis being used to determine whether to update the inactivity timer value for the data session.

According to another aspect of the present invention, a communications network operable to perform the method of the above aspect is disclosed.

In order to achieve the above object, one aspect of the present invention provides a method performed by a first entity for setting inactivity timer values for transitions between states of data sessions in a network including the first entity and a second entity that provides network analysis, the method comprising: transmitting, by the first entity, input data including communication description information for at least one user equipment (UE) to the second entity; receiving, by the first entity, output analysis from the second entity, the output analysis being generated based on the input data and including UE communication analysis for each data session; and determining transitions between states of the data sessions using inactivity timer values for the data sessions updated based on the output analysis.

In order to achieve the above object, one aspect of the present invention provides an apparatus for a second entity that sets an inactivity timer value for transitioning between states of data sessions in a network including a first entity and a second entity that provides network analysis. The apparatus includes a transceiver and a processor coupled to the transceiver, the processor being configured to perform the following steps: acquiring input data including communication description information for at least one user equipment (UE); and providing output analysis generated by the second entity based on the input data to the first entity, the output analysis including UE communication analysis for each data session; the output analysis being used to determine whether to update the inactivity timer value for the data session.

In order to achieve the above object, one aspect of the present invention provides a first entity apparatus for setting an inactivity timer value for transitioning between states of data sessions in a network including the first entity and a second entity that provides network analysis. The first entity apparatus includes a transceiver and a processor coupled to the transceiver, and the processor is configured to perform the following steps: sending input data including communication description information for at least one user equipment (UE) to the second entity; receiving output analysis from the second entity, the output analysis being generated based on the input data and including UE communication analysis for each data session; and determining a transition between states of the data sessions using an inactivity timer value for the data session updated based on the output analysis.

It is an object of one embodiment of the present invention to at least partially address, solve, and/or mitigate at least one of the problems and/or shortcomings associated with the related art, such as at least one of the problems and/or shortcomings described herein. It is further an object of one embodiment of the present invention to provide at least one advantage over the related art, such as at least one of the advantages described herein.

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

According to the present invention, by assigning an appropriate value to the deactivation timer, it is possible to minimize the UE's battery power consumption and the use of network resources.

Other aspects, advantages, and salient features of the present invention will become apparent to those skilled in the art from the following detailed description taken in conjunction with the drawings, which disclose various embodiments of the invention. These and other aspects, features, and advantages of particular embodiments of the present invention will become more apparent from the following description taken in conjunction with the drawings.

1 illustrates an example operation of a network data analytics function (NWDAF) according to an embodiment of the present invention. 1 illustrates an example based on an NWDAF and multiple input data sources according to an embodiment of the present invention. 1 illustrates a procedure for supporting NWDAF-based user plane optimization according to various embodiments of the present invention. 1 illustrates a procedure for supporting NWDAF-based user plane optimization according to various embodiments of the present invention. FIG. 2 is a block diagram of an example of a network entity used in an embodiment of the present invention.

Specific examples of embodiments of the present invention will now be described in detail with reference to the drawings. It will be understood that like reference numerals refer to similar parts, components, and structures throughout the drawings.

The following description, which refers to the drawings, is provided to facilitate a comprehensive understanding of various embodiments of the present invention as defined by the claims and their equivalents. While various specific details are included to facilitate understanding, these should be considered merely as examples. Accordingly, those skilled in the art will recognize that various changes and modifications can be made to the various embodiments described herein without departing from the scope and spirit of the present invention. Additionally, descriptions of well-known functions and configurations are omitted for the sake of clarity and conciseness.

The terms and phrases used in the following description and claims are not limited to their bibliographical meaning, but are used by the inventor to enable a clear and consistent understanding of the present invention. Therefore, it will be apparent to those skilled in the art that the following description of various embodiments of the present invention is provided for illustrative purposes only, and not for the purpose of limiting the present invention, as defined by the claims and their equivalents.

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

The same or similar components may be shown in different drawings but are designated by the same or similar reference numerals.

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

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

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

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

Throughout this specification and the claims, language of the general form "X for Y" (where Y is any action, process, operation, function, activity, or step, and X is any means for performing that action, process, operation, function, activity, or step) includes, but is not necessarily exclusive of, means X for which X is particularly adapted, configured, or arranged to perform Y.

It should be understood that any features, elements, components, integers, steps, processes, operations, functions, characteristics, attributes, and/or groups thereof described or disclosed in connection with a particular aspect, embodiment, example, or claim of the present invention may also be applied to any other aspect, embodiment, example, or claim described herein, unless inconsistent therewith.

Embodiments of the present invention provide methods, apparatus, and systems for setting timer values for transitioning between states of a data session in a network. The following examples are applicable to 3GPP 5G and use terminology associated therewith. For example, embodiments of the present invention provide methods, apparatus, and systems for setting inactivity timer values 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 understand that the techniques disclosed herein are not limited to these examples or to 3GPP 5G, but may be applied to any suitable system or standard, for example, one or more existing and/or next-generation wireless communication systems or standards.

For example, the functionality and other characteristics of various network entities disclosed herein may apply to corresponding or equivalent entities or features in other communications systems or standards. Corresponding or equivalent entities or features are considered to be entities or functions that perform the same or similar role, function, operation, or purpose within a network.

For example, in the examples below, the functions of the NWDAF apply to any other suitable type of entity that provides network analysis. In the examples below, the functions of the user plane function (UPF) apply to any other suitable type of entity that provides user plane functions. In the examples below, the functions of the access and mobility management function (AMF) apply to any other suitable type of entity that performs mobility management functions. In the examples below, the functions of the session management function (SMF) apply to any other suitable type of entity that performs session management functions. In the examples below, the functions of the AF apply to any other suitable type of entity that performs the functions of the application.

Those skilled in the art will understand that the present invention is not limited to the embodiments disclosed herein. For example,

The technology disclosed in this specification is not limited to 3GPP 5G.

- In the embodiments disclosed herein, one or more entities may be replaced by one or more alternative entities that perform equivalent or corresponding functions, processes, or operations.

- In the embodiments disclosed herein, one or more messages may be replaced with one or more alternative messages, signals, or other types of information carriers that convey equivalent or corresponding information.

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

- In one embodiment, one or more non-essential elements, entities, and/or messages are omitted.

- A function, process, or operation of a particular entity in one embodiment may be split into two or more separate entities in other embodiments.

- Functions, processes, or operations of two or more separate entities in one embodiment may be performed by a single entity in another embodiment.

- Information conveyed by a particular message in one embodiment may be conveyed by two or more separate messages in other embodiments.

- Information conveyed by two or more separate messages in one embodiment is conveyed by a single message in another embodiment.

- The order in which the operations are performed may be changed in other embodiments where possible.

- The transmission of information between network entities is not limited to the particular format, type, and/or order of messages described in connection with the embodiments disclosed herein.

Embodiments of the present invention are provided in the form of apparatuses/devices/network entities configured to perform one or more defined network functions and/or methods therefor. Embodiments of the present invention are provided in the form of systems (e.g., networks) that include one or more such apparatuses/devices/network entities and/or methods therefor.

The network includes 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 analytics function (NWDAF) entity, an application function (AF) entity, and one or more other network function (NF) entities.

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

As mentioned above, a technique for setting or adjusting the inactivity timer value is desirable to optimize overall performance.

Embodiments of the present invention enable optimization of the aforementioned trade-off between UE battery consumption and network resource efficiency by utilizing a standardized data analytics framework. Therefore, an adaptive AI-based solution using data analytics is based on the NWDAF framework. For example, an overview of the NWDAF framework defined in [2] is provided below.

The following acronyms, abbreviations, and definitions are used in this specification:

3GPP: 3rd Generation Partnership Project
5G: 5th Generation
5GC: 5G Core Network
5GS: 5G System
AF: Application Function
AI: 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
LTE: 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

Figure 1 illustrates the operation of an example NWDAF according to one embodiment of the present invention. The recently confirmed 3GPP Rel-16 specifies the NWDAF framework, as shown in Figure 1. In the basic operation of the NWDAF 100 shown in Figure 1, an analytics consumer 102 requests data analysis from the NWDAF, which collects data from different entities to perform training and inference before generating an output analysis.

Referring to FIG. 1, analytics consumers 102 request specific types of data analytics from NWDAF 100, which are provided by NWDAF 100 in the form of statistics and/or predictions. Analytics consumers (e.g., analytics consumers 102) defined in Rel-16 are 5GC NFs, application functions (AFs), and OAMs. Accordingly, NWDAF 100 triggers input data collection from input data sources (e.g., 5GC NFs 104, AFs 106, and/or OAMs 108) via the exposure framework defined in [2].

The collected data is then used by the NWDAF 100, possibly by an AI engine, to perform training and inference, although the definition of the model is outside the scope of standardization to provide sufficient flexibility to providers. This also means that the AI engine will exist outside the NWDAF 100 itself, and the next release of the standard (Rel-17) has already begun to explore standardizing the interfaces necessary to enable such decomposition of NWDAF functionality [3]. Similar considerations apply to the input data collection module. In embodiments of the present invention, it is assumed that the AI engine and input data collection module reside within the NWDAF 100, but the present invention is not limited to this case.

In any event, the inference results are provided to an analytics generation entity within NWDAF 100, which delivers the statistics and/or predictions requested by the service consumer.

As described in [2], several data analysis information types are also introduced in 3GPP Rel-16, including analysis of at least one of network slice and application service experience, NF and network slice load, network performance, or UE aspects (communication, mobility, predictions, and abnormal behavior).

In addition to the above fundamental work, Rel-17, already underway, is extending the Rel-16 NWDAF framework by addressing several new use cases and key issues, including at least one of the following: decomposition of the above NWDAF functions, architecture and interaction of multiple NWDAF instances, efficient data collection mechanisms, or network slice service level agreement (SLA) guarantee support [3].

Based on the framework description above, embodiments of the present invention embed directly into the 5G architecture the autonomous capability to intelligently and dynamically set the inactivity timer value for each 5G PDU session of a UE. This approach has the advantage that it is highly feasible in current and at least near-future networks, since the basic data collection capabilities of the NWDAF used in embodiments of the present invention are already defined herein.

Next, we provide a description of the AI problem framed in the context of NWDAF data analysis, as well as an instantiation of the framework for the problem described above.

However, those skilled in the art will understand 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 parameters within a network.

The following describes an AI-based technique that utilizes NWDAF to configure/adjust inactivity timers for activation and deactivation of PDU sessions related to multi-services consumed by a UE. In particular, the overall NWDAF-based technique is described, highlighting the applicability of the technique to currently standardized networks. Detailed procedures for demonstrating the specific framework are also described.

Figure 2 illustrates an example based on an NWDAF and multiple input data sources according to an embodiment of the present invention, illustrating an example of an overall NWDAF-based design utilizing the Rel-16 data analysis framework described in [1]. This example is based on output analysis from multiple input data sources (e.g., OAM 202, SMF 210, UPF and AF 204, and AMF 206, and optionally NG-RAN and UE) communicated to SMF 210 via an AI-based training and inference module in NWDAF 200 and sent to UPF 208 (e.g., the same as UPF 204). Those skilled in the art will understand that the present invention is not limited to these examples.

Referring to Figure 2, the internal NWDAF architecture of this embodiment follows the general principles shown in Figure 1. Here, the general analytical model outside the scope of the standardization activity is replaced with an inference-based model, the training of which is further described below. Furthermore, Figure 2 shows the input data sources used by the agent to learn the optimal inactivity timer value and provide the necessary analysis.

To respect the framework already agreed and finalized in 3GPP, embodiments of the present invention require supported 5GC entities (i.e., SMF 210, UPF 208, AMF 206), AF 204, and OAM 202 to provide input data. However, the present invention is not limited to this case. For example, FIG. 2 shows other entities that can provide the necessary input data to NWDAF 200, i.e., NG-RAN and UE, that are not currently supported in the standard. In one embodiment, these other entities are not required, as they can be replaced by alternative entities that are currently supported. These other entities as data sources will be supported in future standard releases.

Furthermore, the following is described in the context of an exemplary AI-based training and inference model that uses specific input data. In the embodiment described below, all input data is mapped to standardized NWDAF input data, such as UE communication data 222 (e.g., including at least one of start and end timestamps, uplink and downlink data rates, or traffic volume), cell load information 220 measured in terms of the number of activated PDU sessions, and UE type [8]. In one embodiment, unlike UE communication data and cell load, UE type or UE information 224 need only be collected once, as they do not change during network operation.

With respect to the output analysis provided by NWDAF200, embodiments of the present invention comply with the current 3GPP framework by generating data analysis 226 (e.g., including UE communication analysis and/or network performance analysis) in the form of "optimal prediction values" for session inactivity timers that are provided directly to SMF210. NWDAF200 also provides historical statistics of timer values.

The data analysis provided by NWDAF200 is therefore used by SMF210 to (i) activate or deactivate PDU sessions as needed, and (ii) update timer values (e.g., PDU session inactivity timer value 228) using NWDAF predictions and notify UPF208 of the update. As defined in [4], standardized procedures for activating and deactivating PDU sessions as well as user plane management are used, e.g., by SMF210, to perform both operations.

<Data Analysis>

In one embodiment, NWDAF analytics, as defined in [2], are used to enable optimization of user plane connections based on PDU session timers. However, in its current form, this does not support various implementations of the present invention. Therefore, embodiments of the present invention extend the current definition as described below. UE communications analytics 226 and network performance analytics are described below. However, those skilled in the art will understand that the present invention is not limited to these embodiments.

<UE communication analysis>

The NWDAF, which supports UE communication analysis, collects per-application communication descriptions from the AFs. In one embodiment, when the consumer NF provides an application ID, the NWDAF considers only the data from the AF, SMF, and UPF that corresponds to the application ID.

Consumers in this analysis exhibit one or more of the following non-limiting examples of needs:

- The target of the analysis report, which can be one UE or a group of UEs.
- Analysis filter information, optionally including one or more of the following non-limiting examples:

oS-NSSAI,
oDNN,
o Application ID,
o Area of interest.

- A time period to be analyzed indicating the time period for which statistics and/or forecasts are required.
- Preferred analytical accuracy level (e.g. low/high).
- Maximum number of entities.
- In the case of a subscription, it contains the notification correlation ID and the notification target address.

a) Input Data: <Table 1> shows the current input data specifications in [2] for UE communication analysis. Embodiments of the present invention use one or more portions of such information. Those skilled in the art will understand that the exact form of input data and/or source of such information are not necessarily limited to the embodiments shown in <Table 1>. <Table 1> shows service data in 5GC related to UE communication.

In an embodiment of the present invention, one or more input data portions shown in <Table 2> are used in addition to one or more input data portions according to <Table 1>, for example. In one embodiment, some or all of the input data according to <Table 2> is collected as part of the UE communication service data or as a separate entry for each PDU session. Those skilled in the art will appreciate that the exact format of the input data or the source of such information is not necessarily limited to the embodiment shown in <Table 2>. <Table 2> shows an example of additional service data in 5GC related to UE communication.

b) Output Analysis: Table 3 shows the current output analysis specifications in [2] for UE communication analysis. Statistics do not require a "confidence" item, but predictions do. Embodiments of the present invention generate one or more output analysis portions according to Table 3. Those skilled in the art will understand that the exact form of the output analysis is not necessarily limited to the embodiment shown in Table 3. Table 3 shows UE communication output analysis.

In one embodiment of the present invention, for example, one or more items shown in Table 4 are generated in addition to one or more items of the output analysis according to Table 3. Those skilled in the art will appreciate that the exact form of the output analysis is not necessarily limited to the embodiment shown in Table 4. Table 4 shows an example of additional output analysis data for UE communications.

≪Network Performance Analysis≫

In an embodiment of the present invention, network performance analysis by the NWDAF is used to optimize user plane performance (in addition to or instead of UE communication and/or other analysis). For example, the SMF uses network performance analysis, in addition to UE communication analysis, to derive timer values that optimize not only the performance of individual UEs but also the performance of the entire network, and in particular the RAN, as a whole.

a) Input Data: Table 5 shows the current input data specifications in [2] for UE communication analysis. Embodiments of the present invention use one or more portions of such information. Those skilled in the art will appreciate that the exact form of input data and/or source of such information are not necessarily limited to the embodiments shown in Table 5. Table 5 shows input data for network performance analysis.

b) Output Analysis: Table 6 shows the current output analysis specifications in [2] for network performance analysis. Statistics do not require a "confidence" item, but predictions are. Embodiments of the present invention generate one or more output analysis portions according to Table 6. Those skilled in the art will understand that the exact form of the output analysis is not necessarily limited to the embodiment shown in Table 6. Table 6 shows the network performance output analysis.

In an embodiment of the present invention, in addition to one or more output analysis portions according to Table 6, for example, one or more output analysis portions as shown in Table 7 are generated. Those skilled in the art will appreciate that the exact form of the output analysis is not necessarily limited to the embodiment shown in Table 7. For example, one embodiment generates the output analysis shown below in bold italics: Table 7 shows an example of an additional network performance output analysis.

Figures 3a and 3b show procedures for supporting NWDAF-based user plane optimization according to various embodiments of the present invention.

A procedure for supporting NWDAF-based user plane optimization is shown in Figures 3a and 3b. Various operations of the above procedure are described below. In various examples, certain operations (e.g., operations indicated by dotted arrows/boxes) are omitted. For simplicity, Figures 3a and 3b show two alternative sets of operations (Alt1 and Alt2). In various examples, one or the other of these alternatives is used. Those skilled in the art will understand that the present invention is not limited to the embodiments of Figures 3a and 3b.

Referring to Figures 3a and 3b, in operation 300, a PDU session is established across the UE, RAN, AMF, SMF, and UPF. Data transfer requires activation of the user plane connection. During the procedure, the user plane connection is deactivated when the inactivity timer expires and is activated when new data traffic is available.

In operation 301, an SMF (e.g., SMF210) subscribes to UE communication analysis in an NWDAF (e.g., NWDAF200).

In operation 302, [optional] the SMF subscribes to network performance analysis in the NWDAF.

Input Data Collection: Two alternatives are possible for collecting data related to an N4 session.

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

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

In operation 303a, the NWDAF requests N4 session-related input data from the SMF as defined in Table 2. This may include other UE communication data with the SMF as the source NF, as specified in TS 23.288 [2] and Table 2.

In operation 303b, the SMF requests an N4 session report from the UPF.

In operation 303c, the UPF provides the requested N4 session report to the SMF, for example in accordance with clause 4.4.2.2 of TS 23.502 [4].

In operation 303d, the SMF provides the requested N4 session-related input data to the NWDAF.

Alternative 2: UPF-based N4 session data collection

In operation 304, [optional] the NWDAF collects N4 session-related input data directly from the UPF via an implementation-specific mechanism.

In operation 305, the NWDAF collects the remaining input data necessary to generate the requested analysis, for example, according to TS 23.288 [2].

In operation 306, the NWDAF provides UE communication analysis to the SMF, for example, as defined in TS 23.288 [2] and Table 4.

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

In operation 308, while the SMF continues to activate and deactivate PDU sessions, the SMF also processes the received analysis provided by the NWDAF.

In operation 309, based on its analysis against the NWDAF analysis, the SMF decides to update the user plane inactivity timer for the specific PDU session associated with the N4 session.

In operation 310, the SMF triggers an N4 session modification procedure, for example according to clause 4.4.1.3 of TS 23.502 [4], to inform the UPF of the update of the inactivity timer.

An embodiment of the present invention provides a method for setting inactivity timer values for transitioning between states of data sessions in a network including a first entity and a second entity that provides network analysis, the method performed by the second entity comprising: obtaining, by the second entity, input data including communication description information for at least one user equipment (UE); and providing, by the second entity, to the first entity, output analysis generated based on the input data and including a UE communication analysis for each data session, the output analysis being used to determine whether to update the inactivity timer value for the data session.

An embodiment of the present invention provides a method for setting inactivity timer values for transitions between states of data sessions in a network including a first entity and a second entity that provides network analysis, the method being performed by the first entity and comprising the steps of: sending, by the first entity, input data including communication description information for at least one user equipment (UE) to the second entity; receiving, by the first entity, from the second entity, output analysis generated based on the input data and including UE communication analysis for each data session; and determining transitions between states of the data sessions using inactivity timer values for the data sessions updated based on the output analysis.

An embodiment of the present invention provides an apparatus for setting inactivity timer values for transitioning between states of data sessions in a network including a first entity and a second entity that provides network analysis. The apparatus of the second entity includes a transceiver and a processor coupled to the transceiver, the processor configured to perform the following steps: obtaining input data including communication description information for 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 and including a UE communication analysis for each data session; the output analysis being used to determine whether to update the inactivity timer value for the data session.

An embodiment of the present invention provides an apparatus for setting inactivity timer values for transitions between states of data sessions in a network including a first entity and a second entity that provides network analysis. The apparatus of the first entity includes a transceiver and a processor coupled to the transceiver, and the processor is configured to perform the following steps: sending input data to the second entity, the input data including communication description information for at least one user equipment (UE); receiving output analysis from the second entity, the output analysis being generated based on the input data and including UE communication analysis for each data session; and determining transitions between states of the data sessions using inactivity timer values for the data sessions updated based on the output analysis.

An embodiment of the present invention provides a method for a second entity (e.g., an NWDAF) providing network analysis in a network including a first entity (e.g., an SMF) and a second entity, the method comprising: obtaining input data including communication description information; determining an output analysis including a communication analysis of a user equipment (UE) for each data session based on the input data; and providing the output analysis to the first entity. Based on the output analysis, the first entity determines whether to update a timer value for the data session, i.e., a timer (e.g., an inactivity timer) for transitions between states (e.g., active/inactive states) of the data session (e.g., a PDU session).

One embodiment of the present invention provides a second entity (e.g., NWDAF) for providing network analysis in a network including a first entity (e.g., SMF) and a second entity, the second entity being configured to obtain input data including communication description information, determine an output analysis including a communication analysis of a user equipment (UE) for each data session based on the input data, and provide the output analysis to the first entity. Based on the output analysis, the first entity determines whether to update a timer value for the data session, i.e., a timer (e.g., an inactivity timer) for transitions between states (e.g., active/inactive states) of the data session (e.g., PDU session).

An embodiment of the present invention provides a method for setting a timer (e.g., an inactivity timer) value for transitions between states (e.g., active/inactive states) of data sessions (e.g., PDU sessions) in a network including a first entity (e.g., an SMF) and a second entity (e.g., an NWDAF) that provides network analysis, the method comprising the steps of: obtaining input data including communication description information by the second entity; determining, by the second entity, an output analysis including a communication analysis of a user equipment (UE) for each data session based on the input data and providing the output analysis to the first entity; and determining, by the first entity, whether to update the timer value of the data session based on the output analysis.

In one embodiment, the method further includes receiving, by the second entity, a request (e.g., a subscription) for output analysis from the first entity.

In one embodiment, the request includes one or more of a request for analysis of a specific UE or group of UEs and an analysis filter.

In one embodiment, the analysis filter specifies in its filter criteria: information specifying one or more S-NSSAIs; information specifying one or more DNNs; one or more application IDs; information indicating one or more areas of interest; information specifying an analysis period representing the period for which statistics and/or predictions are requested; information indicating the preferred level of analysis accuracy (e.g., low/high); information specifying the maximum number of entities; and, at the time of subscription, one or more of a notification correlation ID and a notification target address.

In one embodiment, the operation of obtaining input data includes sending, by the second entity, a request for session parameters (e.g., N4 session parameters) to the first entity; sending, by the first entity, a request for a session report (e.g., N4 session report) to a third entity (e.g., UPF); receiving, by the first entity, the session parameters from the third entity; and sending, by the first entity, the session parameters to the second entity.

In one embodiment, the act of obtaining input data includes performing a procedure with a third entity (e.g., a UPF) to obtain session parameters (e.g., N4 session parameters) directly from the third entity.

In one embodiment, the input data further includes 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).

In one embodiment, the input data acquisition operation is performed continuously.

In one embodiment, the method further includes, if it is determined that the timer value should be updated, initiating a procedure (e.g., an N4 session modification procedure) for updating the timer value.

In one embodiment, the method further includes transitioning between states of the data connection based on corresponding timer values (and optionally traffic).

In one embodiment, the input data includes one or more pieces of information specified in Table 1.

In one embodiment, the input data includes one or more of the following: identification of one or more PDU sessions (e.g., obtained from the SMF), identification of an N4 session (e.g., obtained from the SMF and/or UPF), a value of a session inactivity timer (e.g., obtained from the SMF and/or UPF), information indicating the state (e.g., activated or deactivated) of one or more PDU sessions (e.g., obtained from the SMF), and one or more UE states (e.g., obtained from the AMF) over the entire period under analysis.

In one embodiment, the UE communication analysis includes one or more pieces of information specified in Table 3.

In one embodiment, the UE communication analysis includes one or more of the following: identification of one or more PDU sessions, identification of the N4 session, and the value (e.g., mean or variance) of the session inactivity timer.

In one embodiment, the output analysis further includes network performance analysis.

In one embodiment, the input data includes one or more pieces of information specified in Table 5.

In one embodiment, the network performance analysis includes one or more pieces of information specified in Table 6.

In one embodiment, the network performance analysis includes one or more of the average usage of allocated resources (e.g., spectrum, CPU, memory, and/or disk) and the average amount of network outage for an area subset during the analyzed period.

In one embodiment, the input data includes 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.

Embodiments of the present invention provide a network including a first entity (e.g., an SMF) and a second entity (e.g., an NWDAF), the network being configured to operate in accordance with the methods disclosed herein.

Embodiments of the present invention provide a first entity (e.g., an SMF) or a second entity (e.g., an NWDAF) configured to operate on a network, according to the preceding examples.

An embodiment of the present invention provides 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.

An embodiment of the present invention provides a computer- or processor-readable data carrier having stored thereon a computer program according to the preceding examples.

In an embodiment of the present invention, an inactivity timer value is set for activation and deactivation of data sessions related to multi-services within the network.

In an embodiment of the present invention, the input data includes UE communication data, cell load measured over multiple active data sessions, and UE type.

In an embodiment of the present invention, the UE communication data includes at least one of start and end timestamps, uplink and downlink data rates, and traffic volume.

Figure 4 is a block diagram of an example of a network entity used in an embodiment of the present invention. For example, a UE, an AMF, an SMF, a UPF, an NWDAF, an AF, and/or other NFs may be provided in the form of the network entities shown in Figure 4. Those skilled in the art will understand that the network entities shown in Figure 4 may be embodied, for example, as network elements on dedicated hardware, software instances running on dedicated hardware, or virtualized functions embodied on a suitable platform, for example, a cloud infrastructure.

Referring to FIG. 4, entity 400 includes at least one of a processor (or controller) 401, a transmitter 403, and a receiver 405. The receiver 405 is configured to receive one or more messages or signals wirelessly or via a wired connection from one or more other network entities. The transmitter 403 is configured to transmit one or more messages or signals wirelessly or via a wired connection to one or more other network entities. The processor 401 is configured to perform one or more operations and/or functions as described above. For example, the processor 401 is configured to perform operations of a UE, an AMF, an SMF, a UPF, an NWDAF, an AF, and/or other NFs.

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

It will be understood that embodiments of the present invention 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, whether erasable or rewritable, such as read-only memory (ROM), random-access memory (RAM), memory chips, devices, or integrated circuits, or on optically or magnetically readable media, such as compact discs (CDs), digital versatile discs (DVDs), magnetic disks, or magnetic tapes.

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

While the present invention has been shown and described with reference to various embodiments, those skilled in the art will recognize that various changes in form and detail may be made without departing from the scope and spirit of the invention, including as defined by the claims and their equivalents.

100, 200 NWDAF: Network Data Analysis Function 102 Analysis Consumer 104 5GC NF: 5G Core Network Network Function 106 AF: Application Function 108 OAM: Operation and Maintenance 202 OAM, [NG-RAN: Next Generation - Radio Access Network]
204 UPF: User Plane Function, AF
206 AMF: Access and Mobility Management Function, [UE: User Equipment]
208 UPF: User Plane Function 210 SMF: Session Management Function 220 Cell Load Information 222 UE Communication Data 224 UE Information 226 Data Analysis, UE Communication Analysis 228 Inactivity Timer Value of PDU Session 400 Entity 401 Processor 403 Transmitter 405 Receiver

Claims (12)

1. A method performed by a session management function (SMF) and a network data analytics function (NWDAF) for configuring an inactivity timer value associated with a protocol data unit (PDU) session in a network including the NWDAF, the NWDAF comprising:
receiving first input data from the SMF, the first input data including an N4 session ID for identifying an N4 session between the SMF and a User Plane Function (UPF), a session inactivity timer value, and a PDU session status indicating whether the state of the PDU session is active or inactive, for a PDU session ID for identifying a Protocol Data Unit (PDU) session associated with a User Equipment (UE);
receiving second input data from an Access Mobility Management Function (AMF), the second input data including a UE connection management (CM) state of the UE;
and sending an output analysis to the SMF based on at least one of the first input data and the second input data, the output analysis including a UE communication analysis provided by the NWDAF;
The UE communication analysis includes the N4 session ID and the value of the session inactivity timer, and is used to determine the value of the session inactivity timer for the PDU session. 2. The method of claim 1, further comprising receiving the N4 session ID and the value of the session inactivity timer from the UPF . receiving a request for the output analysis from the SMF;
the output analysis request includes an analysis filter;
The analysis filter includes information specifying one or more single network slice selection assistance information (S-NSSAI), information indicating one or more areas of interest, information specifying an analysis period representing a period for which statistics and/or predictions are requested, information indicating a preferred analysis accuracy level, information specifying a maximum number of objects, and, at the time of subscription, one or more of a notification correlation ID and a notification target address. The method of claim 1, wherein the analysis filter specifies one or more of the following filter criteria . 1. A method performed by a session management function (SMF) for configuring an inactivity timer value associated with a protocol data unit (PDU) session in a network including the SMF and a network data analytics function (NWDAF) for providing network data analysis, the method comprising:
Sending first input data to the NWDAF, the first input data including an N4 session ID for identifying an N4 session between the SMF and a User Plane Function (UPF), a session inactivity timer value, and a PDU session status indicating whether the state of the PDU session is active or inactive, for a PDU session ID for identifying a Protocol Data Unit (PDU) session associated with a User Equipment (UE) ;
receiving an output analysis from the NWDAF, the output analysis including a UE communication analysis provided by the NWDAF, based on at least one of the first input data and second input data provided to the NWDAF from an Access Mobility Management Function (AMF), the second input data including a UE connection management (CM) state of the UE ;
determining to update a value of the session inactivity timer for the PDU session based on the output analysis;
Informing the UPF of the updated value and determining a transition between states of the PDU session using the updated value of the session inactivity timer by the UPF ;
The method , wherein the UE communication analysis includes the N4 session ID and the value of the session inactivity timer . 5. The method of claim 4 , wherein at least one of the N4 session ID or the session inactivity detection time is received from the UPF . receiving from the NWDAF a request for session parameters related to a session between the SMF and the UPF;
sending a request for a session report to the UPF;
receiving the session parameters from the UPF;
and transmitting the session parameters to the NWDAF . further comprising sending a request for the output analysis to the NWDAF;
the output analysis request includes an analysis filter;
The analysis filter includes information specifying one or more single network slice selection assistance information (S-NSSAI), information indicating one or more areas of interest, information specifying an analysis period representing a period for which statistics and/or predictions are requested, information indicating a preferred analysis accuracy level, information specifying a maximum number of objects, and, at the time of subscription, specifying one or more of a notification correlation ID and a notification target address as filter criteria. The method of claim 4, wherein the analysis filter specifies one or more of the following as filter criteria: information specifying one or more areas of interest, information specifying one or more areas of interest, information specifying a period for which statistics and/or predictions are requested, information indicating a preferred analysis accuracy level, information specifying a maximum number of objects, and, at the time of subscription, a notification correlation ID and a notification target address. 1. An apparatus for configuring an inactivity timer value associated with a protocol data unit (PDU) session in a network, the apparatus comprising : a session management function (SMF) and a network data analytics function (NWDAF) for providing network data analysis ;
A transceiver;
a processor coupled to the transceiver,
The processor:
Receive first input data from the SMF, including an N4 session ID for identifying an N4 session between the SMF and a User Plane Function (UPF), a session inactivity timer value, and a PDU session status indicating whether the state of the PDU session is active or inactive, for a PDU session ID for identifying a Protocol Data Unit (PDU) session associated with a user equipment (UE);
receiving second input data from an Access Mobility Management Function (AMF), the second input data including a UE connection management (CM) state of the UE;
configured to send an output analysis to the SMF based on at least one of the first input data and the second input data, the output analysis including a UE communication analysis provided by the NWDAF ;
The UE communication analysis includes the N4 session ID and the value of the session inactivity timer, and is used to determine the value of the session inactivity timer for the PDU session. 10. The apparatus of claim 8 , wherein the processor is further configured to receive the N4 session ID and the value of the session inactivity timer from the UPF . The processor is further configured to receive a request for the output analysis from the SMF;
the output analysis request includes an analysis filter;
The analysis filter includes information specifying one or more single network slice selection assistance information (S-NSSAI), information indicating one or more areas of interest, information specifying an analysis period representing a period for which statistics and/or predictions are requested, information indicating a preferred analysis accuracy level, information specifying a maximum number of objects, and, at the time of subscription, specifying one or more of a notification correlation ID and a notification target address as filter criteria . The device of claim 8 , 1. An apparatus for configuring an inactivity timer value associated with a protocol data unit (PDU) session in a network , the apparatus comprising: a session management function (SMF) that configures an inactivity timer value associated with a PDU session in a network; and a network data analytics function (NWDAF) that provides network data analysis, the apparatus comprising:
A transceiver;
a processor coupled to the transceiver,
The processor:
Send first input data to the NWDAF, the first input data including an N4 session ID for identifying an N4 session between the SMF and a user plane function (UPF), a session inactivity timer value, and a PDU session status indicating whether the state of the PDU session is active or inactive, for a PDU session ID for identifying a protocol data unit (PDU) session associated with a user equipment (UE) ;
receiving an output analysis from the NWDAF, the output analysis including a UE communication analysis provided by the NWDAF, based on at least one of the first input data and second input data provided to the NWDAF from an Access Mobility Management Function (AMF), the second input data including a UE connection management (CM) state of the UE ;
determining to update the value of the session inactivity timer for the PDU session based on the output analysis ;
The updated value is notified to the UPF, and the UPF is configured to determine a transition between states of the PDU session using the updated value of the session inactivity timer ;
The apparatus , wherein the UE communication analysis includes the N4 session ID and the value of the session inactivity timer . 12. The apparatus of claim 11 , wherein at least one of the N4 session ID or the session inactivity detection time is received from the UPF .