Method and apparatus for QOS and policy enhancements in a wireless communication system

Abstract

The disclosure relates to a fifth generation (5G) or sixth generation (6G) communication system for supporting a higher data transmission rate. According to an example of the disclosure, there is provided a policy control function (PCF) entity configured to: transmit, to a network data analytics function (NWDAF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); receive, from the NWDAF entity, a first response including the information; determine the QoS and / or policy control for the UE based on the information; and notify the determined QoS and / or policy control for the UE to one or more consumer; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS and / or candidate policy. According to another example, there is provided a network data analytics function (NWDAF) entity configured to: receive, from a policy control function (PCF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); obtain input data based on the first request; and provide, to the PCF entity, a first response including the information; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS parameters and / or candidate policy.

Description

METHOD AND APPARATUS FOR QOS AND POLICY ENHANCEMENTS IN A WIRELESS COMMUNICATION SYSTEM

[0001] The disclosure generally relates to methods, apparatus and / or systems for providing QoS and policy enhancements assisted by NWDAF. In various examples, a PCF is configured to consider a combination of enhanced NWDAF-based analytics in determining a policy such as a PCC rule and / or a QoS rule. In other examples, the PCF is configured to store or update the determined policy at a UDR, where the PCF may later retrieve the policy from the UDR for example during PDU session establishment for a UE. In other examples, a NWDAF is configured to collect new inputs to generate new outputs, such as predictions and / or statistics, to assist the PCF in determining QoS and / or policy control.

[0002] 5G mobile communication technologies define broad frequency bands such that high transmission rates and new services are possible, and can be implemented not only in "Sub 6GHz" bands such as 3.5GHz, but also in "Above 6GHz" bands referred to as mmWave including 28GHz and 39GHz. In addition, it has been considered to implement 6G mobile communication technologies (referred to as Beyond 5G systems) in terahertz (THz) bands (for example, 95GHz to 3THz bands) in order to accomplish transmission rates fifty times faster than 5G mobile communication technologies and ultra-low latencies one-tenth of 5G mobile communication technologies.

[0003] At the beginning of the development of 5G mobile communication technologies, in order to support services and to satisfy performance requirements in connection with enhanced Mobile BroadBand (eMBB), Ultra Reliable Low Latency Communications (URLLC), and massive Machine-Type Communications (mMTC), there has been ongoing standardization regarding beamforming and massive MIMO for mitigating radio-wave path loss and increasing radio-wave transmission distances in mmWave, supporting numerologies (for example, operating multiple subcarrier spacings) for efficiently utilizing mmWave resources and dynamic operation of slot formats, initial access technologies for supporting multi-beam transmission and broadbands, definition and operation of BWP (BandWidth Part), new channel coding methods such as a LDPC (Low Density Parity Check) code for large amount of data transmission and a polar code for highly reliable transmission of control information, L2 pre-processing, and network slicing for providing a dedicated network specialized to a specific service.

[0004] Currently, there are ongoing discussions regarding improvement and performance enhancement of initial 5G mobile communication technologies in view of services to be supported by 5G mobile communication technologies, and there has been physical layer standardization regarding technologies such as V2X (Vehicle-to-everything) for aiding driving determination by autonomous vehicles based on information regarding positions and states of vehicles transmitted by the vehicles and for enhancing user convenience, NR-U (New Radio Unlicensed) aimed at system operations conforming to various regulation-related requirements in unlicensed bands, NR UE Power Saving, Non-Terrestrial Network (NTN) which is UE-satellite direct communication for providing coverage in an area in which communication with terrestrial networks is unavailable, and positioning.

[0005] Moreover, there has been ongoing standardization in air interface architecture / protocol regarding technologies such as Industrial Internet of Things (IIoT) for supporting new services through interworking and convergence with other industries, IAB (Integrated Access and Backhaul) for providing a node for network service area expansion by supporting a wireless backhaul link and an access link in an integrated manner, mobility enhancement including conditional handover and DAPS (Dual Active Protocol Stack) handover, and two-step random access for simplifying random access procedures (2-step RACH for NR). There also has been ongoing standardization in system architecture / service regarding a 5G baseline architecture (for example, service based architecture or service based interface) for combining Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) technologies, and Mobile Edge Computing (MEC) for receiving services based on UE positions.

[0006] As 5G mobile communication systems are commercialized, connected devices that have been exponentially increasing will be connected to communication networks, and it is accordingly expected that enhanced functions and performances of 5G mobile communication systems and integrated operations of connected devices will be necessary. To this end, new research is scheduled in connection with eXtended Reality (XR) for efficiently supporting AR (Augmented Reality), VR (Virtual Reality), MR (Mixed Reality) and the like, 5G performance improvement and complexity reduction by utilizing Artificial Intelligence (AI) and Machine Learning (ML), AI service support, metaverse service support, and drone communication.

[0007] Furthermore, such development of 5G mobile communication systems will serve as a basis for developing not only new waveforms for providing coverage in terahertz bands of 6G mobile communication technologies, multi-antenna transmission technologies such as Full Dimensional MIMO (FD-MIMO), array antennas and large-scale antennas, metamaterial-based lenses and antennas for improving coverage of terahertz band signals, high-dimensional space multiplexing technology using OAM (Orbital Angular Momentum), and RIS (Reconfigurable Intelligent Surface), but also full-duplex technology for increasing frequency efficiency of 6G mobile communication technologies and improving system networks, AI-based communication technology for implementing system optimization by utilizing satellites and AI (Artificial Intelligence) from the design stage and internalizing end-to-end AI support functions, and next-generation distributed computing technology for implementing services at levels of complexity exceeding the limit of UE operation capability by utilizing ultra-high-performance communication and computing resources.

[0008] It is an aim of certain examples of the disclosure to address, solve and / or mitigate, at least partly, at least one of the problems and / or disadvantages associated with the related art, for example at least one of the problems and / or disadvantages described herein. It is an aim of certain examples of the disclosure to provide at least one advantage over the related art, for example at least one of the advantages described herein.

[0009] According to an aspect of the disclosure, there is provided a policy control function (PCF) entity configured to: transmit, to a network data analytics function (NWDAF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); receive, from the NWDAF entity, a first response including the information; determine the QoS and / or policy control for the UE based on the information; and notify the determined QoS and / or policy control for the UE to one or more consumer; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS and / or candidate policy.

[0010] According to various examples, the PCF entity is further configured to: determine the QoS and / or policy control from the one or more set of candidate QoS and / or candidate policy included in the information; or determine the QoS and / or policy control based on PCF internal logic and operator policy.

[0011] According to various examples, the first request comprises an indication of one or more analytics ID indicating analytics for providing assistance information on determining QoS and / or policy control.

[0012] According to various examples, the analytics comprises statistics, predications or output including one or more of: application ID; per application ID level traffic related parameters; QoS sustainability analytics; congestion level in an area within which the UE is or unexpected expected to appear; or resource usage for non- guaranteed bit rate (non-GBR) traffic.

[0013] According to various examples, the per application ID traffic related parameters comprise one or more of: uplink (UL) data rate per application ID; downlink (DL) data rate per application ID; data / traffic volume per application ID; delay per application ID; or traffic requirements per application ID (for example, QoS parameter(s), service mean opinion score (MOS), 5QI, Allocation and Retention Priority (ARP), Reflective QoS Attribute (RQA), Flow Bit Rates / traffic rate, GBR or non-GBR and / or Maximum Packet Loss Rate of said application).

[0014] According to various examples, the statistics, predications or output comprises one or more of: 5G QoS identifier (5QI); QoS key performance indicator (KPI); QoS flow identifier (QFI); UE ID for the UE; applicable area; or applicable time period; and / or wherein the QoS sustainability analytics are provided per-UE per QoS flow level.

[0015] According to various examples, the QoS KPI: is QoS flow Retainability KPI, and / or provides user or service experience satisfaction / level associated to each of the candidate QoS .

[0016] According to various examples, the candidate QoS parameters are associated with a QoS flow.

[0017] According to various examples, the PCF entity is further configured to: identify a trigger for transmitting the first request; and / or wherein the one or more consumer includes session management function (SMF), application function (AF) and / or Unified Data Repository (UDR).

[0018] According to another aspect of the disclosure, there is provided a network data analytics function (NWDAF) entity configured to: receive, from a policy control function (PCF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); obtain input data based on the first request; and provide, to the PCF entity, a first response including the information; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS parameters and / or candidate policy. The information may be obtained by the NWDAF entity based on the input data or at least part thereof.

[0019] According to various examples, the first request comprises an indication of one or more analytics ID indicating analytics for providing assistance information on determining QoS and / or policy control.

[0020] According to various examples, the analytics comprises statistics, predications or output including one or more of: application ID; per application ID level traffic related parameters; QoS sustainability analytics; congestion level in an area within which the UE is or unexpected expected to appear; or resource usage for non- guaranteed bit rate (non-GBR) traffic.

[0021] According to various examples, the per application ID traffic related parameters comprise one or more of: uplink (UL) data rate per application ID; downlink (DL) data rate per application ID; data / traffic volume per application ID; delay per application ID; or traffic requirements per application ID (for example, QoS parameter(s), service mean opinion score (MOS), 5QI, Allocation and Retention Priority (ARP), Reflective QoS Attribute (RQA), Flow Bit Rates / traffic rate, GBR or non-GBR and / or Maximum Packet Loss Rate of said application).

[0022] According to various examples, the statistics, predications or output comprises one or more of: 5G QoS identifier (5QI); QoS key performance indicator (KPI); QoS flow identifier (QFI); UE ID for the UE; applicable area; or applicable time period; and / or wherein the QoS sustainability analytics are provided per-UE per QoS flow level.

[0023] According to various examples, the QoS KPI: is QoS flow Retainability KPI, and / or provides user or service experience satisfaction / level associated to each of the candidate QoS.

[0024] According to various examples, the input data is obtained from one or more of application function (AF), 5G network function (NF) or session management function (SMF); and / or wherein the input data relates to traffic / service requirements associated to an application.

[0025] According to various examples, the input data comprises one or more of: a set of QoS parameters; 5QI; ARP; RQA; flow bit rates / traffic rate; GBR or non-GBR; or maximum packet loss rate of the traffic of the application.

[0026] According to various examples, the NWDAF entity is further configured to derive the information based on the input data and reused input data of analytics existing prior to receiving the first request.

[0027] According to various examples, the reused input data is of any one or more of user data congestion analytics, network performance analytics, UE mobility analytics and abnormal behaviour analytics, UE communication analytics, observed service experience analytics, or QoS sustainability analytics.

[0028] According to another aspect of the disclosure there is provided a method of a policy control function (PCF) entity, the method comprising: transmitting, to a network data analytics function (NWDAF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); receiving, from the NWDAF entity, a first response including the information; determining the QoS and / or policy control for the UE based on the information; and notifying the determined QoS and / or policy control for the UE to one or more consumer; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS and / or candidate policy.

[0029] According to various examples, the method is modified to be in accordance with any one or more of the examples relating to the PCF entity given above.

[0030] According to another aspect of the disclosure there is provided a method of a network data analytics function (NWDAF) entity, the method comprising: receiving, from a policy control function (PCF) entity, a first request for information relating to quality of service (QoS) and / or policy control for a user equipment (UE); obtaining input data based on the first request; and providing, to the PCF entity, a first response including the information; wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS parameters and / or candidate policy. The information may be obtained by the NWDAF entity based on the input data or at least part thereof.

[0031] According to various examples, the method is modified to be in accordance with any one or more of the examples relating to the NWDAF entity given above.

[0032] According to another aspect of the disclosure, there is provided a non-transitory computer-readable storage medium comprising instructions which, when executed by at least one processor of an apparatus, cause the apparatus to perform a method according to any aspect or examples described / indicated above.

[0033] Other aspects, advantages, and salient features of the disclosure will become apparent to those skilled in the art from the following detailed description taken in conjunction with the accompanying drawings.

[0034] Aspects of the disclosure are to address at least the above-mentioned problems and / or disadvantages and to provide at least the advantages described below. Accordingly, an aspect of the disclosure is to provide efficient communication methods in a wireless communication system.

[0035] Embodiments / examples of the disclosure are further described hereinafter with reference to the accompanying drawings, in which:

[0036] Figure 1 is a call flow diagram illustrating a method of NWDAF-assisted policy control and QoS enhancement according to various examples of the disclosure.

[0037] Figure 2 is a call flow diagram illustrating a method of NWDAF-assisted policy control and QoS enhancement according to various examples of the disclosure.

[0038] Figure 3 is a call flow diagram illustrating a method of deploying NWDAF-assisted QoS and policy determination during PDU session establishment according to various examples of the disclosure.

[0039] Figure 4 is a block diagram illustrating an example structure of a network entity in accordance with various examples of the disclosure.

[0040] Figure 5 is a flow diagram illustrating a method in accordance with various examples of the disclosure.

[0041] Figure 6 is a flow diagram illustrating a method in accordance with various examples of the disclosure.

[0042] Figure 7 is a block diagram illustrating an example structure of a user equipment (UE) in accordance with various examples of the disclosure.

[0043] Figure 8 is a block diagram illustrating an example structure of a network entity in accordance with various examples of the disclosure.

[0044] Aspects of the disclosure are to address at least the above-mentioned problems and / or disadvantages and to provide at least the advantages described below. Accordingly, an aspect of the disclosure is to provide a terminal and a communication method thereof in a wireless communication system.

[0045] The content of the following documents is referred to below and / or their content provides background information that the following disclosure should be considered in the context of:

[0046] [1] 3GPP TS 23.501 - System architecture for the 5G System (5GS), Release 18 (e.g. V18.4.0).

[0047] [2] 3GPP TS 23.503 - Policy and charging control framework for the 5G System (5GS); Stage 2, Release 18 (e.g. V18.4.0).

[0048] [3] 3GPP TS 23.288 - Architecture enhancements for 5G System (5GS) to support network data analytics services, Release 18 (e.g. V18.4.0).

[0049] [4] 3GPP TSG SA Meeting #102, SP-231800.

[0050] [5] TR 23.700-84 - Study on Core Network Enhanced Support for Artificial Intelligence (AI) / Machine Learning (ML), Release 19 (e.g. V0.1.0)

[0051] Note: indicated version numbers are provided for illustrative purposes, other (including future) versions of these documents are considered also.

[0052] Wireless or mobile (cellular) communications networks in which a mobile terminal (e.g., user equipment (UE), such as a mobile handset) communicates via a radio link with a network of base stations, or other wireless access points or nodes, have undergone rapid development through a number of generations. The 3rd Generation Partnership Project (3GPP) design, specify and standardise technologies for mobile wireless communication networks. Fourth Generation (4G) and Fifth Generation (5G) systems (5GS) are now widely deployed, while beyond 5G (B5G) and 6G systems are being considered.

[0053] 3GPP standards for 4G systems include an Evolved Packet Core (EPC) and an Enhanced-UTRAN (E-UTRAN: an Enhanced Universal Terrestrial Radio Access Network). The E-UTRAN uses Long Term Evolution (LTE) radio technology. LTE is commonly used to refer to the whole system including both the EPC and the E-UTRAN, and LTE is used in this sense in the remainder of this document. LTE should also be taken to include LTE enhancements such as LTE Advanced and LTE Pro, which offer enhanced data rates compared to LTE.

[0054] In 5G systems a new air interface has been developed, which may be referred to as 5G New Radio (5G NR) or simply NR. NR is designed to support the wide variety of services and use case scenarios envisaged for 5G networks, though builds upon established LTE technologies B5G systems, such as 6G, are currently being considered and developed, and are expected to at least partly build on 5G systems.

[0055] New frameworks and architectures are being developed as part of 5G network (and beyond, such as 6G networks) in order to increase the range of functionality and use cases available through 5G networks.

[0056] QoS (Quality of Service) and PCC (Policy and Charging Control) rules

[0057] As defined in TS 23.501 [1], the QoS parameters of 5GS include:

[0058] 5QI (5G QoS Identifier).

[0059] ARP (Allocation and Retention Priority): priority level, the pre-emption capability and the pre-emption vulnerability.

[0060] RQA (Reflective QoS Attribute): The RQA is an optional parameter which indicates that certain traffic (not necessarily all) carried on this QoS Flow is subject to Reflective QoS

[0061] QoS Parameter Notification control: indicates whether notifications are requested from the NG-RAN when the "GFBR can no longer (or can again) be guaranteed" for a QoS Flow during the lifetime of the QoS Flow. Notification control may be used for a GBR (Guaranteed Bit Rate) QoS Flow if the application traffic is able to adapt to the change in the QoS (e.g. if the AF is capable to trigger rate adaptation).

[0062] Flow Bit Rates

[0063] Guaranteed Flow Bit Rate (GFBR) - UL and DL;

[0064] Maximum Flow Bit Rate (MFBR) -- UL and DL.

[0065] Aggregate Bit Rates:

[0066] per Session Aggregate Maximum Bit Rate (Session-AMBR): The Session-AMBR limits the aggregate bit rate that can be expected to be provided across all Non-GBR QoS Flows for a specific PDU Session

[0067] per UE Aggregate Maximum Bit Rate (UE-AMBR): aggregate bit rate that can be expected to be provided across all Non-GBR QoS Flows of a UE

[0068] per UE per Slice-Maximum Bit Rate (UE-Slice-MBR): aggregate bit rate that can be expected to be provided across all GBR and Non-GBR QoS Flows corresponding to PDU (Protocol Data Unit) Sessions of the UE for the same slice (S-NSSAI) which have an active user plane.

[0069] Default values: For each PDU Session Setup, the SMF retrieves the subscribed Session-AMBR values as well as the subscribed default values for the 5QI and the ARP and optionally, the 5QI Priority Level, from the UDM. The subscribed default 5QI value shall be a Non-GBR 5QI from the standardized value range.

[0070] Maximum Packet Loss Rate: maximum rate for lost packets of the QoS Flow that can be tolerated in the uplink and downlink direction. This is provided to the QoS Flow if it is compliant to the GFBR

[0071] Within the 5GS, a QoS Flow associated with the default QoS rule is required to be established for a PDU Session and remains established throughout the lifetime of the PDU Session. This QoS Flow should be a Non-GBR QoS Flow.

[0072] The PCC rules / decision is defined in TS 23.503 [2]:

[0073] PCC decision: A PCF decision for policy and charging control provided to the SMF (consisting of PCC rules and PDU Session related attributes), a PCF decision for access and mobility related policy control provided to the AMF, a PCF decision for UE policy information provided to the UE or a PCF decision for service related policy (e.g. background data transfer policy) provided to the AF.

[0074] QoS control refers to the authorization and enforcement of the maximum QoS that is authorized for a service data flow, for a QoS Flow or for the PDU Session. A service data flow may be either of IP type or of Ethernet type. PDU Sessions may be of IP type or Ethernet type or unstructured.

[0075] The authorized QoS for a service data flow template shall include a 5QI and the ARP and may include a 5QI Priority Level.

[0076] For a 5QI of GBR or Delay-critical GBR resource type, the authorized QoS shall also include the MBR (Maximum Bit Rate), GBR and may include the QoS Notification Control parameter (for notifications when authorized GFBR can no longer (or can again) be fulfilled).

[0077] For 5QI of Non-GBR resource type, the authorized QoS may include the MBR and the Reflective QoS Control parameter.

[0078] The 5QI value can be standardized (i.e. referring to QoS characteristics as defined in clause 5.7.3 of TS 23.501), pre-configured (i.e. referring to QoS characteristics configured in the RAN) or dynamically assigned.

[0079] QoS control also refers to the authorization and enforcement of the Session-AMBR, default 5QI / ARP combination and 5QI Priority Level, if applicable. The PCF may provide the Authorized Session-AMBR, the Authorized default 5QI and ARP combination and the 5QI Priority Level as part of the PDU Session information for the PDU Session to the SMF. The Authorized Session-AMBR, Authorized default 5QI / ARP and if available, 5QI Priority Level values take precedence over other values locally configured or received at the SMF.

[0080] The PCC rules are determined by PCF. The PCF may take the information collected by multiple data sources to make the PCC decision, as specified in clause 6.2.1.2 of TS 23.503 [2]:

[0081] The PCF shall accept input for PCC decision-making from the SMF, the AMF, the CHF, the NWDAF if present, the UDR and if the AF is involved, from the AF, as well as the PCF may use its own predefined information.

[0082] The AMF may provide information related to the UE as defined in clauses 5.2.5.2 and 5.2.5.6 of TS 23.502, for example in the following services:

[0083] Npcf_AMPolicyControl service.

[0084] Npcf_UEPolicyControl Service.

[0085] The SMF may provide information related to the PDU Session as defined in clause 5.2.5.4 of TS 23.502, for example: Default 5QI and default ARP etc. and the parameters in the following services:

[0086] Npcf_SMPolicyControl service of TS 23.502.

[0087] Npcf_SMPolicyControl_Create service operation:

[0088] Inputs, Optional: - subscribed default QoS information

[0089] Outputs, Optional: Policy information for the PDU Session as defined in TS 23.503

[0020] and Policy Control Request Trigger(s) of SM Policy Association as defined in clause 6.1.3.5 of TS 23.503

[0020] .

[0090] At PDU Session establishment the NF Service Consumer, e.g. SMF, requests the creation of a corresponding SM Policy Association with the PCF (Npcf_SMPolicyControl_Create) and provides relevant parameters about the PDU Session to the PCF. When the PCF has created the SM Policy Association, the PCF may provide policy information for the PDU Session in the response.

[0091] The UDR may provide the information for a subscriber connecting to a specific DNN and S-NSSAI, as described in the clause 6.2.1.3.

[0092] The AF, if involved, may provide application session related information as defined in clause 5.2.5.3 of TS 23.502 directly or via NEF, e.g. based on SIP and SDP, for example: Npcf_PolicyAuthorization Service. This service is to authorize an AF request and to create policies as requested by the authorized AF for the PDU Session to which the AF session is bound.

[0093] The NWDAF, if involved, may provide analytics information as described in clause 6.1.1.3. Examples of operator policies including network analytics information as inputs for policy decisions included:

[0094] Based on the "Service Experience" statistics or predictions, the PCF may check the 5QI values assigned to the Application, and may use this as input to calculate and update the authorized QoS for a service data flow template.

[0095] Based on the "User Data Congestion" statistics or predictions including the list of applications contributing the most to the traffic the PCF may perform SM Policy Association modifications to update policies in the SMF for the PDU sessions handling traffic from those applications.

[0096] Examples of operator policies including combination of multiple network analytics as inputs for policy decisions are included: Based on the notification of application(s) in use, provided by "UE Communication" analytics, the PCF may request the "Service Experience" analytics (optionally per RAT Type and / or per Frequency) for each application in use as defined in the list of examples of operator policies that may include network analytics as input for a policy decision.

[0097] NWDAF analytics to support policy decision

[0098] As mentioned above, when making PCC rules or other policy decisions, the PCF may consider the NWDAF analytics as input for decision making. The NWDAF analytics are defined in TS 23.288 [3]. In the above (e.g. the above clause), UE Communication and Service Experience are two analytics used by the PCF to determine the QoS currently.

[0099] UE Communication Analytics is defined in clause 6.7.3 of TS 23.288 [3], and was introduced to support some optimized operations (e.g. customized mobility management, traffic routing handling, RFSP Index Management, QoS improvement or Inactivity Timer optimization) in 5GS. An NWDAF may perform data analytics on UE communication pattern and user plane traffic and provide the analytics results (i.e. UE communication statistics or prediction) to NFs in the 5GC or an AF. An NWDAF supporting UE Communication Analytics collects per-application communication description from AFs. If consumer NF provides an Application ID, the NWDAF only considers the data from AF, SMF and UPF that corresponds to this application ID. NWDAF may also collect data from AMF.

[0100] The output analytics (using some predictions as examples) of the UE Communication Analytics are in Table 1 below (corresponding to Table 6.7.3.3-2: UE Communication Predictions of TS 23.822 [3]). The outputs include the per UE or per UE group parameters, and per application ID level parameters.

[0101] InformationDescriptionUE group ID or UE IDIdentifies a UE or a group of UEs, e.g. internal group ID defined in clause　5.9.7 of TS　23.501　[2] or SUPI (see NOTE).UE communications (1..max) (NOTE　1)List of communication time slots.> Periodic communication indicator (NOTE 1)Identifies whether the UE communicates periodically or not.> Periodic time (NOTE　1)Interval Time of periodic communication (average and variance) if periodic.Example: every hour.> Start time (NOTE　1)Start time predicted (average and variance).> Duration time (NOTE　1)Duration interval time of communication.> Traffic characterizationS-NSSAI, DNN, ports, other useful information.> Traffic volume (NOTE　1)Volume UL / DL (average and variance).> ConfidenceConfidence of the prediction.> RatioPercentage of UEs in the group (in the case of a UE group).Applications (0..max) (NOTE　1)List of application in use.> Application IdIdentification of the application.> Start timeStart time of the application.> Duration timeDuration interval time of the application.> Occurrence probabilityProbability the application will be used by the UE.> Spatial validityArea where the service behaviour applies. If Area of Interest information was provided in the request or subscription, spatial validity may be a subset of the requested Area of Interest. If a Spatial granularity size was provided in the request or subscription, the number of elements of TAs or cells in the area is smaller than or equal to the Spatial granularity size.N4 Session ID (1..max) (NOTE　1) (NOTE　2)Identification of N4 Session.> Inactivity detection timeValue of session inactivity timer (average and variance).> ConfidenceConfidence of the prediction.NOTE　1: Analytics subset that can be used in "list of analytics subsets that are requested" and "Preferred level of accuracy per analytics subset".NOTE　2: This analytics subset shall only be included if the consumer is SMF.

[0102] The Observed Service Experience related network data analytics is specified in clause 6.4 of TS 23.288 [3]. The Observed Service Experience can provide the analytics of user experience, i.e. average of observed Service MoS and / or variance of observed Service MoS indicating service MOS distribution for services such as audio-visual streaming as well as services that are not audio-visual streaming such as V2X and Web Browsing services, analytics, in the form of statistics or predictions, to a service consumer. These analytics may collect or be based on a huge amount of data from different sources and at different levels. The output analytics may be for an application, an network slice and an UE. The outputs of this analytics may be statistics, where an example of statistics are shown in Table 2 below (corresponding to Table 6.4.3-1: Service Experience statistics of TS 23.288 [3]).

[0103] InformationDescriptionSlice instance service experiences (0..max)List of observed service experience information for each Network Slice instance.> S-NSSAIIdentifies the Network Slice> NSI ID (NOTE　2)Identifies the Network Slice instance within the Network Slice.> Network Slice instance service experienceService experience across Applications on a Network Slice instance over the Analytics target period (average, variance).> SUPI list (0..SUPImax) (NOTE　3)List of SUPI(s) for which the slice instance service experience applies.> Ratio (NOTE　3)Estimated percentage of UEs with similar service experience (in the group, or among all UEs).> Spatial validity (NOTE　6)Area where the Network Slice service experience analytics applies.> Validity periodValidity period for the Network Slice service experience analytics as defined in clause　6.1.3.Application service experiences (0..max)List of observed service experience information for each Application.> S-NSSAIIdentifies the Network Slice used to access the Application.> Application IDIdentification of the Application.> Service Experience TypeType of Service Experience analytics, e.g. on voice, video, other.> UE location (NOTE　1, NOTE　5)Indicating the UE location information (e.g. TAI list, gNB ID, or location coordinates, etc) when the UE service is delivered.> UPF Info (NOTE　4)Indicating UPF serving the UE.> DNAIIndicating which DNAI the UE service uses / camps on.> DNNDNN for the PDU Session which contains the QoS flow.> Application Server Instance AddressIdentifies the Application Server Instance (IP address of the Application Server) or FQDN of Application Server.> Service ExperienceService Experience over the Analytics target period (average, variance).> SUPI list (0..SUPImax) (NOTE　3)List of SUPI(s) with the same application service experience.> Ratio (NOTE　3)Estimated percentage of UEs with similar service experience (in the group, or among all UEs).> Spatial validity (NOTE　6)Area where the Application service experience analytics applies.> Validity periodValidity period for the Application service experience analytics as defined in clause　6.1.3.> RAT Type(NOTE　7)Indicating the list of RAT type(s) for which the application service experience analytics applies.> Frequency(NOTE　7)Indicating the list of carrier frequency value(s) of UE's serving cell(s) where the application service experience analytics applies.> SSC ModeSSC Mode selected for the PDU Session used to associate with the application.> PDU Session TypeType of PDU Session used to associate with the application.> Access TypeList of Access Type(s) used for the PDU Session for the application.NOTE　1: This information element is an Analytics subset that can be used in "list of analytics subsets that are requested" and "Preferred level of accuracy per analytics subset".NOTE　2: The NSI ID is an optional parameter. If not provided the Slice instance service experience indicates the service experience for the S-NSSAI.NOTE　3: The SUPI list and Ratio in the service experience information for an application can be omitted, if the corresponding parameter(s) is / are provided and are assigned with the same value(s) in the service experience information for the slice instance which the application belongs to. Otherwise, the SUPI list and Ratio are mandatory to be provided for an application service experience.NOTE　4: If the consumer NF is an AF, the "UPF info" shall not be included.NOTE　5: When possible and applicable to the access type, UE location is provided according to the preferred granularity of location information. UE location shall only be included if the Consumer analytics request is for single UE or a list of UEs. Inclusion of UE location requires user consent.NOTE　6: The Spatial validity is present in the output parameters if the consumer provided the Area of Interest as defined in Table 6.4.1-1.NOTE　7: When "any" value has been provided in the request (e.g. "any" RAT type, "any" frequency, or "any" for all the RAT type and frequency indication), the NWDAF provides an instance of the Application service experience per combination of RAT Type(s) and / or Frequency value(s) having the same Service Experience.

[0104] SA2 Rel-19 New SID on Core Network Enhanced Support for Artificial Intelligence (AI) / Machine Learning (ML) was approved in SP-231800 [4] during SA 102 meeting (Dec, 2023). As it has been documented in the WT#3.1 in SP-231800 [4]:

[0105] -WT3: Study enhancements to support NWDAF-assisted policy control and address network abnormal behaviour

[0106] -WT3.1 - Study whether and what additionally needs to be supported in order to enhance 5GC NF operations (i.e. policy control and QoS) assisted by NWDAF. The work will firstly identify the specific use cases to be considered, in order to identify the appropriate scope. The work will analyse the result impacts on NWDAF (e.g. the need to understand specific NF functionality), and the compatibility of new solutions wrt existing analytics, in order to determine the need and benefits of new solutions.

[0107] The Key issue description of WT3.1 was agreed and documented during SA2 160 adhoc e-meeting. As documented in clause 5.2.3 of TR 23.700-84 [5], Key Issue #3: NWDAF-assisted policy control and QoS enhancement:

[0108] The NWDAF can gather quite a lot of data from 5GC NFs, AF and OAM and thus may further assist the PCF in making PCC decisions (which traditionally determine QoS parameters based on its own data and knowledge as well optional statistics and predictions collected from the NWDAF).

[0109] This Key issue aims to study whether and what additionally needs to be supported in order to enhance 5GC NF operations related to policy control and QoS with the assistance of the NWDAF.

[0110] In this key issue, the following aspects will bestudied:

[0111] Identification of use cases where policy control and QoS can be further enhanced withassistancefrom NWDAF.

[0112] -Whetherand how to introduce new 5GC functionality e.g. of the NWDAF and / or PCF to enhance the policy control and QoS, considering operator's policies.

[0113] -Whether and what additional input information is needed by the NWDAF for providing anassistanceto policy control and QoS, and how to gather it.

[0114] -Whether and what output information, on top of already provided, the NWDAF canprovideto assist with policy control and QoS enhancements.

[0115] -Whetherand how to evaluate the quality of the enhanced NWDAF assistance to policy control and QoS.

[0116] NOTE 1:The study will focus primarily on existing enforcement mechanisms when available and identify new ones only when no existing ones can be used.

[0117] A use case associated to the above KI#3 was agreed in SA2 160 ad-hoc e- meeting, and documented in 5.1.2 of TR 23.700-84 [5].

[0118] UseCase#2: Enhancements to QoS Determination with NWDAF Assistance

[0119] A use case is provided for how the network can benefit from the NWDAF-assistance for QoSdeterminationand setup for the purpose of optimising the overall network performance and signalling based on operator's policy.

[0120] After UE registers with the 5GS, a PDU session set up might be required. Each PDU session is associated with a default QoS rule which provides a default QoS treatment for data flows. Currently the characteristics of the default QoS is determined by the subscribed default values (for parameters such as 5QI, ARP) which the SMF may obtain from the UDM. The default QoS rule might be sufficient for basic browsing or instant messaging over IP, whereas it may not able to satisfy the relatively high service requirements, i.e. of video streaming applications which require better QoS treatment. For example, for V2X and XRM services, the applications may require transmitting traffic with Guaranteed Bit Rate (GBR) or to use certain standardised 5QI values even for non-GBR QoS flows. Therefore, the default QoS requirements may not be able to support such applications.

[0121] When the QoS flows with different requirements from the default flow are required,modificationto the PDU session and thereby to establish a new QoS flow with the required characteristics might be needed. Such modification will result in significant system-wide signalling, including NAS signalling messages between the UE and the 5GC, signalling within 5GC (i.e. signalling between SMF, UPF, PCF), signalling between 5GC and RAN, and also the RRC messages between the RAN and the UE, etc.

[0122] In order to optimise the network performance by determining QoS in a more intelligentmanner, it would be beneficial for the 5GC to leverage NWDAF assistance. For example, when the UE or network trigger PDU session establishment or modification for a new QoS flow with QoS requirements driven by a user or service, it would be beneficial if the QoS characteristics are determined by the network by considering the predictions and measurements of some UE and network related information and also service related information (e.g. service requirements provided by the AF). The information considered by the 5GC could be some patterns in terms of frequency of use of one or more services and the potential QoS requirements to be emerged from the UE subsequently, the QoS sustainability of the UE or of an area the UE belongs to, the corresponding UE locations, the service requirements provided by the AF, etc. Therefore, the PDU session and QoS flow can be established or modified in a more 'future proof' and multiple-service-compatible manner and reduce the potential modifications of the existing QoS flow and the corresponding policy control, e.g. PCC rules.

[0123] Based on this use case, potential enhancements to 5GC functionality e.g. of the NWDAF, PCF, to enhance the policy control and QoS by considering operator's policies, will improve the network performance and UE experience significantly.

[0124] The description of KI#3 in TR　23.700-84 [5] indicates that the following issues should be addressed during R19 AIML_CN study phase:

[0125] -Whether and how to introduce new 5GC functionality e.g. of the NWDAF and / or PCF to enhance the policy control and QoS, considering operator's policies.

[0126] -Whether and what additional input information is needed by the NWDAF for providing an assistance to policy control and QoS, and how to gather it.

[0127] -Whether and what output information, on top of already provided, the NWDAF can provide to assist with policy control and QoS enhancements.

[0128] -Whether and how to evaluate the quality of the enhanced NWDAF assistance to policy control and QoS.

[0129] However, at present there is a lack of solutions for these issues, in particular based on the agreed use case in clause 5.1.2 of TR 23.700-84 [5].

[0130] The following description of examples of the disclosure, with reference to the accompanying drawings, is provided to assist in a comprehensive understanding of certain examples of the disclosure. The description includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made without departing from the scope of the invention or disclosure.

[0131] The same or similar components may be designated by the same or similar reference numerals, although they may be illustrated in different drawings.

[0132] Detailed descriptions of techniques, structures, constructions, functions or processes known in the art may be omitted for clarity and conciseness, and to avoid obscuring the subject matter of the disclosure.

[0133] The terms and words used herein are not limited to the bibliographical or standard meanings, but are merely used to enable a clear and consistent understanding of the disclosure.

[0134] Throughout the description of this specification, the words "comprise", "include" and "contain" and variations of the words, for example "comprising" and "comprises", means "including but not limited to", and is not intended to (and does not) exclude other features, elements, components, integers, steps, processes, operations, functions, characteristics, properties and / or groups thereof.

[0135] Throughout the description of this specification, the singular form, for example "a", "an" and "the", encompasses the plural unless the context otherwise requires. For example, reference to "an object" includes reference to one or more of such objects.

[0136] Throughout the description, the expression "at least one of A, B and / or C" (or the like), the expression "and / or", and the expression "one or more of A, B and / or C" (or the like) should be seen to separately include all possible combinations, for example: A, B, C, A and B, A and C, A and B and C.

[0137] Throughout the description of this specification, language in the general form of "X for Y" (where Y is some action, process, operation, function, activity or step and X is some means for carrying out that action, process, operation, function, activity or step) encompasses means X adapted, configured or arranged specifically, but not necessarily exclusively, to do Y.

[0138] Features, elements, components, integers, steps, processes, operations, functions, characteristics, properties and / or groups thereof described or disclosed in conjunction with a particular aspect, embodiment or example are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith.

[0139] Certain examples of the disclosure relate to methods, apparatus and / or systems for QoS and policy enhancements assisted by NWDAF. In various examples, a PCF is configured to consider a combination of enhanced NWDAF-based analytics in determining a policy, such as a PCC rule and / or a QoS rule. In other examples, the PCF is configured to store or update the determined policy at a UDR, where the PCT may later retrieve the stored or updated policy from the UDR such as triggered by PDU session establishment for a UE. In other examples, a NWDAF is configured to collect new inputs to generate new outputs, such as predictions and / or statistics, to assist the PCF in determining QoS and / or policy control.

[0140] The following examples are applicable to, and use terminology associated with, 3GPP 5G. However, the skilled person will appreciate that the techniques disclosed herein are not limited to these examples or to 3GPP 5G, and may be applied in any suitable system or standard, for example one or more existing and / or future generation wireless communication systems or standards. The skilled person will appreciate that the techniques disclosed herein may be applied in any existing or future releases of 3GPP 5G NR or any other relevant standard. For example, the functionality of the various network entities and other features disclosed herein may be applied to corresponding or equivalent entities or features in other communication systems or standards. Corresponding or equivalent entities or features may be regarded as entities or features that perform the same or similar role, function, operation or purpose within the network. In particular, the following disclosure should be considered at least in relation to 6G also, which is expected to use at least part of the 5G architecture, or equivalent, and to which the disclosure also relates.

[0141] A particular network entity may be implemented as a network element on a dedicated hardware, as a software instance running on a dedicated hardware, and / or as a virtualised function instantiated on an appropriate platform, e.g. on a cloud infrastructure.

[0142] The skilled person will appreciate that the disclosure is not limited to the specific examples disclosed herein. For example:

[0143] The techniques disclosed herein are not limited to 3GPP 5G, B5G or 6G.

[0144] One or more entities in the examples disclosed herein may be replaced with one or more alternative entities performing equivalent or corresponding functions, processes or operations.

[0145] One or more of the messages in the examples disclosed herein may be replaced with one or more alternative messages, signals or other type of information carriers that communicate equivalent or corresponding information.

[0146] One or more further elements, entities and / or messages may be added to the examples disclosed herein.

[0147] One or more non-essential elements, entities and / or messages may be omitted in certain examples.

[0148] The functions, processes or operations of a particular entity in one example may be divided between two or more separate entities in an alternative example.

[0149] The functions, processes or operations of two or more separate entities in one example may be performed by a single entity in an alternative example.

[0150] Information carried by a particular message in one example may be carried by two or more separate messages in an alternative example.

[0151] Information carried by two or more separate messages in one example may be carried by a single message in an alternative example.

[0152] The order in which operations are performed may be modified, if possible, in alternative examples.

[0153] The transmission of information between network entities is not limited to the specific form, type and / or order of messages described in relation to the examples disclosed herein.

[0154] Certain examples of the disclosure may be provided in the form of an apparatus / device / network entity configured to perform one or more defined network functions and / or a method therefor. Such an apparatus / device / network entity may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and / or method steps for implementing the techniques described herein. For example, an operation / function of X may be performed by a module configured to perform X (or an X-module). Certain examples of the disclosure may be provided in the form of a system (e.g., a network) comprising one or more such apparatuses / devices / network entities, and / or a method therefor.

[0155] It will be appreciated that examples of the disclosure may be realized in the form of hardware, software or a combination of hardware and software. Certain examples of the disclosure may provide a computer program comprising instructions or code which, when executed, implement a method, system and / or apparatus in accordance with any aspect, example and / or embodiment disclosed herein. Certain embodiments of the disclosure provide a machine-readable storage storing such a program.

[0156] A network according to one or more of the examples disclosed herein may include one or more of a Network Data Analytics Function (NWDAF) entity, an Access and Mobility Management Function (AMF) entity, a Session Management Function (SMF) entity, a Network Slice Selection Function (NSSF) entity, a Network Repository Function (NRF) entity, Application Function (AF) entity, and an Operation and Maintenance (OAM) entity. The network may include one or more Service Consumers (including one or more of the entities mentioned above and / or one or more other entities) that receive analytics from NWDAF. The skilled person will appreciate that a network may omit one or more of the entities mentioned above and / or may comprise one or more additional entities

[0157] As described above, there is a lack of solutions for the issues documented in the description of KI#3 in TR　23.700-84 [5], in particular based on the agreed use case in clause 5.1.2 of TR 23.700-84 [5]. According to various examples of the disclosure, to solve, address or at least mitigate one or more of these issues, NWDAF analytics are leveraged to support enhanced 5GC NF operations, such as policy control and QoS.

[0158] In particular, various examples disclosed herein introduce enhancements or modifications to an / the NWDAF to assist with the QoS and policy control decision making. For example, the NWDAF disclosed herein provides or obtains enhanced analytics. The PCF considers a combination of the enhanced NWDAF-based analytics and other existing analytics to determine the policies, e.g. PCC rules, QoS. In some examples, a focus is on the use of the enhanced analytics by the PCF, so reference to existing analytics may be omitted. In various examples, the NWDAF may provide the (candidate) QoS parameters / 5QI, the QoS KPI / satisfaction associated with other assistance information to the PCF. Accordingly, the PCF will consider the analytic related to QoS and policy provided by the NWDAF, and optionally other additional information (e.g. information from AMF, SMF, NEF, AF, OAM. RAN node, UE etc.) to determine the QoS and policy to be deployed into 5GS. Based on the above, the PCF is able to (or aims to) generate future-proof and multi-service-compatible QoS for a UE; and therefore, to optimise the UE experience, reduce system-wide signalling and / or improve the overall network performance. Accordingly, reference to a 'future-proof' rule (or similar) herein may be seen to refer to a rule which is obtained or generated using a method according to the disclosure.

[0159] As described in Use Case #2 of TR 23.700-84 [5], each PDU session is associated with a default QoS rule which is normally sufficient for basic browsing or instant messaging over IP in general. For some services that require higher or specific QoS treatments (e.g. V2X, XRM, etc.), modification to the established PDU session might be required, e.g. by establishing new QoS flow or modifying the default QoS rule, which will increase the complex the system and involve significant system-wide signalling. Furthermore, the modification to the PDU session still cannot guarantee that the assigned QoS can satisfy the service requirements. In order to optimise the network performance, it would be beneficial for the 5GC to leverage NWDAF assistance to determine the QoS and policy control in a more 'future proof' and multiple-service-compatible manner.

[0160] In the existing framework, the PCF may determine the PCC rules based on information collected from multiple data sources, e.g. SMF, UPF, AF, etc. The NWDAF analytics can be considered by the PCF to check and improve the UE and network performance, e.g., as captured in clause 6.1.1.3 of TS 23.503 [2], after the 5QI is deployed by 5GS, based on "Service Experience" analytics, the PCF may check whether the 5QI values assigned to the application can satisfy the performance requirements and calculate and update the authorized QoS; the PCF may perform the SM Policy Association modifications to update policies for the PDU sessions handling traffic based on User Data Congestion analytics; and the PCF may also deploy a combination of multiple network analytics as inputs for policy decisions, e.g. the PCF may request the "Service Experience" analytics based on the UE Communication" analytics received previously for a policy decision.

[0161] Currently, the determination of default QoS rule and the SM policy generated during the PDU session establishment barely deploy the assistance of NWDAF analytics. Furthermore, the PCF is not capable to determine whether the assigned 5QI or the QoS rules can satisfy the requirements before they are actually deployed by the system. To avoid necessary PDU session modification, the default QoS can be determined in a more intelligent and sustainable way by considering the aspects that impacts the QoS and policy of the current and also the potential future service(s) of the UE. The PCF may request the leveraged NWDAF analytics of analytic ID(s) to assist with the QoS and policy determination.

[0162] The PCF may request a combination of enhanced existing analytics ID(s) as assistance information to determine QoS and policy, similar to the existing mechanism. In addition, the PCF may also request the NWDAF to provide a list of candidate QoS parameters and policies to choose. The PCF will make the final decision on QoS and policy based on its internal logic and subject to operator policy.

[0163] For example, the QoS and policy might be determined or updated by considering the network congestion level and resource usage condition (e.g. the resource usage of GBR and non-GBR traffic given by Network performance analytics and congestion level given by congestion related analytics) in the area within which the UE may be expected or unexpected to appear (e.g. based on the UE location provided by UE mobility analytics or Unexpected UE location provided by Abnormal behaviour analytics), the statistics and predictions of the traffic patterns of UE services (e.g. introducing new application level ID level inputs and outputs to UE communication analytics), the service experience of a UE associated to different QoS parameters (e.g. given by service experience), and the finer granularity of QoS sustainability associated to different 5QIs, and the candidate QoS profiles, etc.

[0164] According to various examples of the disclosure, in order to determine the QoS and policy in a more intelligent and sustainable way, when authorising the QoS and / or generating or updating the PCC rules, the PCF may consider a combination of several aspects that may impact the QoS and policy of the current service(s) and, optionally, also the potential future service(s). The PCF may consider the statistics and / or predictions of the network congestion level and resource usage condition (e.g. the resource usage of GBR and non-GBR traffic given by Network performance analytics and congestion level given by congestion related analytics) in the area within which the UE may be expected or unexpected to appear (e.g. based on the UE location provided by UE mobility analytics or Unexpected UE location provided by Abnormal behaviour analytics), and / or the statistics and / or predictions of the traffic patterns of UE services (e.g. introducing new application level ID level inputs and outputs to UE communication analytics), the service experience of a UE associated to different QoS parameters (e.g. given by service experience), and the finer granularity of QoS sustainability associated to different 5QIs, etc. Therefore, the PCF will take a combination of analytics into consideration when generating, updating or authorising PCC rules and QoS.

[0165] Note that while examples disclosed herein may refer to QoS and policy (e.g. PCC) together, it should be appreciated that in other examples just the QoS or just the policy may be referred to instead; that is, the examples disclosed herein should be seen to include examples relating to QoS, examples relating to policy, and examples relating to QoS and policy together.

[0166] To assist with QoS and policy control, it is possible to enhance the existing analytics ID and / or introduce new analytics ID according to examples disclosed herein.

[0167] According to various examples of the disclosure, the QoS and the policy can be determined by taking the output(s) of one or more analytics ID into account, at the same time. In an example, one or more set of QoS parameters and policies are generated, e.g. based on the internal logic of PCF or NWDAF. In a case where the one or more set of QoS parameters and policies are generated by NWDAF or other NFs, the NWDAF or other NFs sends the one or more set of QoS parameters and policies to PCF. The final decision of the QoS and the policy (update / modification) of a service / PDU session / QoS flow / UE may be made by PCF. It will be understood that, in other examples, the PCF (as referred to in the previous example) can be replaced by any other 5GC network function (NF) that hosts the functionality of QoS and policy determination / modification / recommendation by considering a one or more output analytics (can be multiple analytics ID or multiple output analytics parameters), e.g. NWDAF, a new NF, NEF, etc.

[0168] In various examples, the 5GC NF (e.g. NWDAF, PCF, NEF, etc.) gathers information to determine one or more set of (candidate) QoS parameters and (candidate) policies to provide to the PCF to choose. The PCF may determine the QoS and policy to be applied to the 5GS from the one or more set of QoS parameters and policies, or the PCF may determine another QoS and / or policy, for example based on PCF internal logic and subject to operator policy.

[0169] Determining one or more set of QoS parameters and policies may be performed (e.g. determined) by the 5GC NF (e.g. NWDAF or PCF) based on information, data and / or outputs of one or more analytics ID(s) collected from different data sources, e.g. other NFs (SMF, UPF, NRF, AMF, GLMC, AF) or OAM, etc.

[0170] For example, if the NWDAF derives the one or more set of (candidate) QoS parameters and (candidate) policies, the NWDAF takes the existing (or stored) but still valid analytics output(s) of one or analytics ID into account. The NWDAF may retrieve the existing (or stored) but still valid analytics output(s) from ADRF which will be used as input data of the NWDAF to derive the prediction and statistics of (candidate) QoS parameters and (candidate) policies and / or the relevant assistance information. The existing (or stored) but still valid analytics outputs may include the output analytics of any one or more of:

[0171] -DN Performance Analytics.

[0172] -User Data Congestion analytics.

[0173] -Observed Service Experience Analytics.

[0174] -Abnormal Behavior Analytics.

[0175] -UE communication analytics.

[0176] -QoS sustainability Analytics.

[0177] -UE mobility Analytics.

[0178] -Slice Load level Analytics.

[0179] -Network Performance Analytics.

[0180] -Observed Service Experience Analytics.

[0181] -NF Load Analytics.

[0182] Alternatively, in other examples the NWDAF may derive the prediction and statistics of (candidate) QoS parameters and (candidate) policies and / or the relevant assistance information by reusing the input information of the above analytics (with enhancements / introducing new input data), and other additional data

[0183] In order to allow the PCF and / or NWDAF to understand the service characteristics and the requirements of the past, on-going and potential future service(s) of a UE, application, service, DN (data network), PDU session and / or QoS flow; and, therefore, support the PCF and / or NWDAF to generate, determine or authorize the future-proof and multi-service-compatible (candidate) QoS and policy, enhancements to the input data and output of the above of the analytics are needed or new analytics ID is needed.

[0184] - E.g. by enhancement of the UE communication analytics or introducing new analytics ID, the service requirements (e.g. 5QI, ARP, RQA, Flow Bit Rates / traffic rate, GBR or non-GBR, and / or Maximum Packet Loss Rate of the application) can be considered as new input information of NWDAF to generate the output analytics that can assist PCF. An example of this is shown in Table 3, given below. It will be appreciated that other examples may comprise part of (e.g. one or more of) the entries shown in Table 3. The statistics and predictions (or output) of QoS and policy assistance information may include the per service level or per application ID level traffic related parameters, e.g. by enhancing the existing UE communication analytics, as shown in Table 4

[0185] -- UL / DL data rate per application ID;

[0186] -- data / traffic volume per application ID;

[0187] -- delay per application ID;

[0188] -- traffic requirements per application ID (e.g. 5QI, ARP, RQA, Flow Bit Rates / traffic rate, GBR or non-GBR, Maximum Packet Loss Rate of the application), etc.

[0189] Table 3 shows examples of input data for output analytics related to QoS and policy assistance information.

[0190] InformationSourceDescriptionTraffic / service requirementsSMF, UPF, AFTraffic / service requirements associated to an application, e.g. 5QI, a set of QoS parameters, ARP, RQA, Flow Bit Rates / traffic rate, GBR or non-GBR, Maximum Packet Loss Rate of the traffic of the application.Resource allocated to a gNB for non-GBR trafficOAMThe overall resource allocated to a gNB for non-GBR trafficRAN UE Throughput per UEOAMTS　28.558The average UE throughput in downlink or uplink, per QoS level and per supported S-NSSAI, as defined in clause　6.3.1.4 of TS　28.558.Delay in RAN per UEOAMTS　28.558The average time it takes for packet transmission over the air-interface in the downlink and uplink direction, per QoS level, per S-NSSAI, as defined in clause　6.3.1.1 of TS　28.558.

[0191] Table 4 shows examples of new statistics and prediction for assisting QoS and policy control decision. It will be appreciated that other examples may comprise part of (e.g. one or more of) the entries shown in Table 4.

[0192] InformationDescriptionApplications (0..max) (NOTE　1) / DN performanceList of application in use.> application IDIdentifying the application providing this information / service> DNAIIdentifier of a user plane access to one or more DN(s) where applications are deployed as defined in TS 23.501 [2].> data rate(average, variance, maximum, peak) UL and / or DL data rate (e.g. flow bit rate) or throughput over the analytics period of an application or at application (ID) level.> data / traffic volume(average, variance, maximum, peak) data / traffic volume of the application over the analytics period or at application (ID) level> data packet delay / latency(average, variance, maximum, peak) data packet delay / latency of the application over the analytics period or at application (ID) level> traffic requirements of the applicatione.g. the QoS parameters, service MOS (Mean Opinion Score (MOS), one or more of the following parameters, e.g. 5QI, ARP, RQA, Flow Bit Rates, GBR or non-GBR, Maximum Packet Loss Rate, QoS parametersList of QoS sustainability Analytics at finer granularity (1..max)List of QoS sustainability Analytics at finer granularity, e.g. per QoS flow, per PDU session or per UE within the interested area. (1...max) can be the number / index of the UE, QoS flow, PDU session, etc.>UE IDIdentifies a UE.>UE locationIndicate the UE location information.>PDU session IDPDU session identifier.>QFIQoS Flow Identifier.>5QI or a set of QoS parameters / QoS profile(candidate) 5G QoS Identifier or a set of QoS parameters / QoS profile of a QoS flow.>Application IDIdentifier of an application.>Applicable Area (NOTE　1)A list of TAIs or Cell IDs or a geographical area in a fine granularity (e.g. smaller than a cell) within the Location information that the analytics applies to. If a Spatial granularity size was provided in the request or subscription, the number of elements of the list is smaller than or equal to the Spatial granularity size.>Applicable Time PeriodThe time period within the Analytics target period that the analytics applies to. If a Temporal granularity size was provided in the request or subscription, the duration of the Applicable Time Period is greater than or equal to the Temporal granularity size.>QoS KPIThe values of QoS KPI could be the MOS, the user or service experience satisfaction / level, or as defined in clause　6.9.1 of TS　23.288. e.g. for a 5QI of GBR resource type, (the Reporting Threshold(s)) refer to the QoS flow Retainability KPI; for a 5QI of non-GBR resource type, (the Reporting Threshold(s)) refer to the RAN UE Throughput KPI and / or delay in RAN KPI as defined in TS 28.554.QoS and / policyThe Candidate or recommended QoS and / or policy derived by the NWDAF.Could be list of / one or more QoS parameter, QoS profiles, AM polices, SM policies, charging rules, UE policies, etc.gNB resource usage for non-GBR trafficUsage of assigned resources for non-GBR traffic (average, peak).

[0193] In order to better maintain the service quality for a UE, the QoS sustainability is an important factor. As defined in TS 23.288 [3], for a 5QI of GBR resource type, the QoS KPI could be the QoS flow Retainability KPI, which reflects how often an end-user abnormally loses a QoS flow during the time the QoS flow is used. If the QoS flow Retainability of a QoS flow associated to a 5QI is not ideal, losing the QoS flow may interrupt the services of a UE. For a 5QI of non-GBR, the QoS KPI refers to the RAN UE Throughput and / or delay in RAN which can reflect the service quality that can be provided by the network in the AOI (area of interest). Therefore, enhancing the outputs of QoS Sustainability analytics to per UE per QoS flow level will help the PCF to understand the whether the 5QI or QoS parameters can be supported for the UE in the AOI stably; and therefore, help the PCF to optimise the 5QI which can provide more sustainable service. The potential enhanced output analytics of the QoS Sustainability analytics may include the statistics and prediction of the per UE per QoS flow level QoS KPI for reporting, as shown in Table 4.

[0194] In various examples, in order to provide assistance information and / or candidate QoS to PCF, the NWDAF reuses the input data of the existing (enhanced) analytics and may request additional input data. The NWDAF may reuse the input data of any one or more of the following analytics IDs:

[0195] - User Data Congestion Analytics.

[0196] - Network Performance Analytics.

[0197] - UE Mobility analytics and Abnormal Behaviour Analytics.

[0198] - UE Communication Analytics.

[0199] - Observed Service Experience Analytics.

[0200] - QoS sustainability Analytics.

[0201] The additional input data may service requirements, e.g. one or more of 5QI or QoS profile, ARP, RQA, Flow Bit Rates / traffic rate, GBR or non-GBR, or Maximum Packet Loss Rate of the application, as shown in Table 3.

[0202] The NWDAF may also take the output of some analytics into account (e.g. as input data) to generate the output analytics of (candidate) QoS and policies and / or the assistance information, e.g. the output analytics of one or more of:

[0203] - User Data Congestion Analytics

[0204] - Network Performance Analytics

[0205] - UE Mobility analytics and Abnormal Behaviour Analytics

[0206] - UE Communication Analytics

[0207] - Observed Service Experience Analytics

[0208] - QoS sustainability Analytics

[0209] In various examples, the NWDAF may trigger to generate the output analytics of the above analytics ID, or fetch the existing but still valid analytics outputs that might be stored, e.g. in ADRF.

[0210] The output of the NWDAF aims help the PCF to understand the service characteristics and the requirements.

[0211] In order to better maintain the service quality for a UE, the QoS sustainability is an important factor. As defined in TS 23.288, for a 5QI of GBR resource type, the QoS KPI could be the QoS flow Retainability KPI which reflects how often an end-user abnormally loses a QoS flow during the time the QoS flow is used. If the QoS flow Retainability of a QoS flow associated to a 5QI is not ideal, losing the QoS flow may interrupt the services of a UE. For a 5QI of non-GBR, the QoS KPI refers to the RAN UE Throughput and / or delay in RAN which can reflect the service quality that can be provided by the network in the AOI. Therefore, the outputs analytics could be enhanced to per UE per QoS flow level which will help the PCF to understand the whether the 5QI or QoS parameters can be supported for the UE in the AOI stably. The candidate QoS candidates could be also provide by the NWDAF to the consumer NF (e.g. PCF). The QoS KPI may also provide the MOS, the user or service experience satisfaction / level associated to the candidate QoS. The potential enhanced output analytics are shown in Table 4.

[0212] Accordingly, Tables 3 and 4 provide examples of the enhanced analytics provided by an NWDAF according to the disclosure, which are then provided to a PCF for use in determining, or generating, QoS and policy with enhancement.

[0213] Figure 1 illustrates (via a call flow diagram) a method of NWDAF-assisted policy control and QoS enhancement.

[0214] The entities in the example of Figure 1 are as follows:

[0215] 100 - UE (User Equipment).

[0216] 200 - SMF (Session Management Function).

[0217] 300 - PCF (Policy Control Function).

[0218] 400 - NWDAF (Network Data Analytics Function).

[0219] 500 - AMF (Access and Mobility Management Function), UPF (User Plane Function), AF (Application Function) and / or other 5GC.

[0220] 600 - UDR (Unified Data Repository).

[0221] 700 - ADRF (Analytics Data Repository Function).

[0222] It will be appreciated that, in more general examples, reference could instead be made to a first entity 100, a second entity 200, a third entity 300, a fourth entity 400, a fifth entity 500, a sixth entity 600 and a seventh entity 700; where each entity is arranged to perform the associated operation(s) indicated below. Furthermore, any one or more of entities in Figure 1 may be combined or co-located. For example, the PCF and the NWDAF can be co-located, in which case an operation which indicates interaction between these two entities is performed internally (for example, not necessitating use of a transmitter / receiver for exchange of data between separate points in the network).

[0223] It will also be understood that various examples relate to individual entities shown in Figure 1. For instance; various examples are directed to the PCF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations; while some other examples are directed to the NWDAF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations. Additionally, yet further examples relate to any combination of the individual entities, and so may include the operations performed by these entities while omitting operations performed by other entities not included in the combination.

[0224] In operation S110, to collect the relevant information to assist with QoS and policy control decision, PCF 300 subscribes to or sends a request to different data sources, e.g. one or more of NWDAF 400, AMF 500, SMF 200, AF 500, etc. In the description of Figure 1, it will be appreciated that references to QoS and policy control together should be understood to not be limiting, where other examples in accordance with Figure 1 relate to either QoS or policy control.

[0225] This procedure / operation may be triggered, e.g. based on a condition being satisfied or detecting a trigger. Some example reasons by which the operation is triggered are as follows: to set up or update the default QoS rule before PDU session was established; triggered by the AF 500 to authorize the QoS and control policy of a service before the service starts; triggered by the PCF itself to check and update the performance of existing or active QoS and control policy that have been determined; etc. It will be appreciated that, more generally, the PCF may subscribe to or send the request based on a predetermined condition being met. As seen from the examples, one trigger is in response to a command or instruction (e.g. authorization) received from another entity in the network.

[0226] The PCF 300 may require the NWDAF 400 to provide the statistics and / or predictions of one or more (enhanced) analytics to assist with QoS and / or policy control decision for a UE, e.g. analytics ID indicates (or is) UE Communication, UE Mobility, Service Experience, QoS Sustainability, Network performance, or indicates (or is) new analytics that can provide assistance information of QoS and policy control decision, etc.

[0227] In operation S120, NWDAF 400 collects input data and generates (or provides, configures etc.) analytics based on PCF request.

[0228] To assist with QoS and policy control, based on the PCF 300 request, the NWDAF 400 may collect the information related to service requirements of multiple applications associated to a UE as input data to generate the UE communication analytics at per application ID level. The statistics and / or predictions of the per application ID level traffic characteristics - e.g. data rate, traffic volume, delay etc. - may help or assist the PCF 300 to determine the traffic patterns of multiple services of a UE when deciding the QoS and policy control. For examples, the collected information (e.g. information related to service requirements) relates to one or more of the information included in Table 3, while the output (e.g. statistics and / or predictions) may relate to one or more of the information included in Table 4.

[0229] In order to generate more sustainability QoS and policy control, the PCF 300 may require the NWDAF 400 to provide the statistics and / or predictions of QoS Sustainability analytics at finer granularity - e.g. per UE per QoS flow level of a 5QI. Based on the QoS KPI provided by the PCF 300 may choose the 5QI or the combination of QoS parameters that can provide the required QoS Sustainability for a UE or a QoS flow.

[0230] In operation S130, the different data sources from S110 send the required data or analytics (for NWDAF 400) to the PCF 300. For example, the different data sources first send the required data or analytics to the NWDAF 400, which processes the received data or analytics (e.g. combine them, or use them to generate output) and forwards / sends the result to the PCF 300. In another example, the PCF 300 receives the required data or analytics from the different data sources, where this may be based on an instruction from the NWDAF 400. More generally, operation S130 may be seen as the PCF 300 receiving the enhanced analytics or data related to such.

[0231] In operation S140, the PCF 300 consolidates all the input data and determines the QoS and / or policy control. The PCF 300 may determine QoS and policy control in a future-proof and multi-service-compatible manner. For example, in determining QoS and policy control in a future-proof and multi-service-compatible manner, the PCF 300 operates according to one of the examples disclosed above; e.g. PCF 300 considers the statistics and / or predictions of the network congestion level and resource usage condition (e.g. the resource usage of GBR and non-GBR traffic given by Network performance analytics and congestion level given by congestion related analytics) in the area within which the UE may be expected or unexpected to appear (e.g. based on the UE location provided by UE mobility analytics or Unexpected UE location provided by Abnormal behaviour analytics), and / or the statistics and / or predictions of the traffic patterns of UE services (e.g. introducing new application level ID level inputs and outputs to UE communication analytics), the service experience of a UE associated to different QoS parameters (e.g. given by service experience), and / or the finer granularity of QoS sustainability associated to different 5QIs, etc

[0232] The PCF 300 may notify (e.g. transmit or communicate) the determined QoS and policy control to the consumer(s) - e.g. other 5GC NFs or AF - based on the trigger of the QoS and policy control procedures. PCF 300 may notify the outcome of the QoS and policy control to SMF 200 to establish SM policy, to the AF 500 for the QoS configuration before the service starts, and / or to UDR 600 to provide or update the default QoS rule (e.g. before PDU session establishment), etc.

[0233] The method of Figure 1 includes an operation of policy and analytics context management, which comprises either or both of operations S150a and S150b. These operations are omitted in some examples of the disclosure, such as examples in which storing output of the PCF 300 and / or NWDAF 400 at the UDR 600 and ADRF 700, respectively, is not required.

[0234] In operation S150a, the PCF 300 determines to store the determined QoS and policy control, and / or update existing QoS and policy control in UDR 600 for future use. In other words, the PCF 300 may store the results of operation S140, such as in the UDR 600, or may use the results of operation S140 to update existing, corresponding information (e.g., an existing QoS, if a QoS is determined in operation S140, and / or existing policy control, if policy control is determined in operation S140) stored at the UDR 600.

[0235] In operation S150b, the NWDAF 400 determines (based on PCF requirement) to store and / or update the analytics context of the above analytics in ADRF 700 for future use (e.g. update existing analytics context). In other words, the NWDAF 400 may store the analytics derived in operation S120 or data related to these analytics, such as at ADRF 700, or may use the derived analytics or related data to update existing, corresponding information at the ADRF 700 (e.g., update corresponding analytics or analytics context stored at the ADRF 700).

[0236] The method may further include an operation of PDU session establishment, which comprises one or more of operations S160a, 160b, S170a, S170b, S180, S190a and S190b). That is, from operations S160a to S190b, the PDU session establishment procedures are used as an example to illustrate the procedures of QoS and / or policy enhancements assisted by NWDAF as disclosed herein. It will therefore be appreciated that operations S160a to S190b can be omitted for various examples of the disclosure, as these operations relate to an example which illustrates use of the NWDAF-assisted enhanced QoS and policy control. It will also be appreciated that operations other than PDU session establishment may make use of QoS and / or policy control determined according to earlier operations S110 to S140 (and optionally S150a and / or S150b).

[0237] In operations S160a and S160b, a UE 100 triggers PDU session establishment to the 5GC. Upon receiving the PDU session establishment request, the SMF 200 triggers SM policy establishment procedures to the PCF 300 to require or request PCC rules.

[0238] In operation S170a, based on the SMF request, the PCF 300 determines to fetch the determined QoS and policy for the UE 100.

[0239] In operation S170b, the PCF 300 determines to update the fetched determined QoS and policy for the UE 100, or the PCF 300 determines to generate new QoS and policies by repeating operations S110 to S140.

[0240] It will be appreciated that it may be the decision of PCF 300 to determine whether to fetch or update the determined QoS and policy, or to generate new QoS and policy, e.g. subject to operator policy.

[0241] In operations S180, S190a and S190b, the PCF 300 notifies the SMF 200 of the determined QoS and policy for the UE 100. The SMF 200 establish the SM policy and PDU session based on the information derived from PCF notification. The SMF 200 establishes two QoS flows during the PDU session establishment, e.g. one QoS flow is with default QoS rule, another QoS flow associated to the future-proof QoS rule(s) to provide multi-service-compatible QoS configuration. The SMF 200 notifies the UE 100 about the PDU session successfully establishment.

[0242] In an example, the operations of Figure 1 can be labelled as follows:

[0243] S110 - 1. PCF subscribes to different data sources to collect data to assist with QoS and policy decision.

[0244] S120 - 2. NWDAF collects input data and generates (enhanced) analytics based on PCF request.

[0245] S130 - 3. Different data sources send required data or analytics to PCF to assist with QoS and policy decision.

[0246] S140 - 4. PCF determines PCC rules, including QoS related information.

[0247] S150a - 5a. PCF stores or updates the generated QoS and policy in UDR (e.g. as part of policy and analytics context management procedure).

[0248] S150b - 5b. NWDAF stores or updates the analytics context in ADRF (e.g. as part of policy and analytics context management procedure).

[0249] S160a - 6a. PDU establishment (e.g. as part of PDU session establishment procedures).

[0250] S160b - 6b. Request for PCC rules (e.g. as part of PDU session establishment procedures).

[0251] S170a - 7a. PCF fetch the determined PCC rules from UDR (e.g. as part of PDU session establishment procedures).

[0252] S170b - 7b. The PCT may determine to update the determined or generate new QoS and policy by repeating steps 1-4 (e.g. as part of PDU session establishment procedures).

[0253] S180 - 8. PCC rules provided with determines 5QI(s) or QoS parameters (e.g. as part of PDU session establishment procedures).

[0254] S190a - 9a. SMF establishes QoS rule (e.g. as part of PDU session establishment procedures).

[0255] S190b - 9b. PDU session Establishment Accept (e.g. as part of PDU session establishment procedures).

[0256] For various examples in accordance with the disclosure, a PCF is configured to consider a combination of NWDAF analytics, including new or enhanced analytics from NWDAF, to generate future-proof and multi-service-compatible QoS and policy. Also, the PCF is configured to store, update and / or fetch the determined (or generated) QoS and policy from UDR, including default QoS rules.

[0257] For various examples in accordance with the disclosure, a NWDAF is configured to collect new inputs to generate assistance information of QoS and policy control. Also, the NWDAF is configured to generate new outputs to assist with PCF for QoS and policy control determination, including predictions and / or statistics. Further, the NWDAF is configured to expose, or provide, the new output analytics to consumers.

[0258] For various examples in accordance with the disclosure, a UDR is configured to store, update, and / or notify QoS and policy decision based on a request from a PCF.

[0259] Figure 2 illustrates (via a call flow diagram) another example of a method of NWDAF-assisted policy control and QoS enhancement.

[0260] The entities in the example of Figure 2 are as follows:

[0261] 100 - UE (User Equipment).

[0262] 200 - SMF (Session Management Function).

[0263] 300 - PCF (Policy Control Function).

[0264] 400 - NWDAF (Network Data Analytics Function).

[0265] 500 - AMF (Access and Mobility Management Function), UPF (User Plane Function), AF (Application Function) and / or other 5GC.

[0266] 600 - UDR (Unified Data Repository).

[0267] 700 - ADRF (Analytics Data Repository Function).

[0268] 800 - AF (Application Function).

[0269] It will be appreciated that, in more general examples, reference could instead be made to a first entity 100, a second entity 200, a third entity 300, a fourth entity 400, a fifth entity 500, a sixth entity 600, a seventh entity 700 and an eighth entity 800; where each entity is arranged to perform the associated operation(s) indicated below. Furthermore, any one or more of entities in Figure 2 may be combined or co-located. For example, the PCF and the NWDAF can be co-located, in which case an operation which indicates interaction between these two entities is performed internally (for example, not necessitating use of a transmitter / receiver for exchange of data between separate points in the network).

[0270] It will also be understood that various examples relate to individual entities shown in Figure 2. For instance; various examples are directed to the PCF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations; while some other examples are directed to the NWDAF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations. Additionally, yet further examples relate to any combination of the individual entities, and so may include the operations performed by these entities while omitting operations performed by other entities not included in the combination.

[0271] In operation S210, to collect the relevant information to assist with QoS and policy control decision, PCF 300 subscribes to or sends a request to different data sources, e.g. one or more of NWDAF 400, AMF 500, SMF 200, AF 500, 800, etc. In the description of Figure 2, it will be appreciated that references to QoS and policy control together should be understood to not be limiting, where other examples in accordance with Figure 2 relate to either QoS or policy control.

[0272] This procedure / operation may be triggered, e.g. based on a condition being satisfied or detecting a trigger. Some example reasons by which the operation is triggered are as follows: to set up or update the default QoS rule before PDU session was established; triggered by the AF 500, 800 to authorize the QoS and control policy of a service before the service starts; triggered by the PCF 300 itself to check and update the performance of existing or active QoS and control policy that have been determined; etc. It will be appreciated that, more generally, the PCF 300 may subscribe to or send the request based on a predetermined condition being met. As seen from the examples, one trigger is in response to a command or instruction (e.g. authorization) received from another entity in the network.

[0273] The PCF 300 may require the NWDAF 400 to provide the statistics and / or predictions of one or more (enhanced) analytics to assist with QoS and / or policy control decision for a UE, e.g. analytics ID indicates (or is) UE Communication, UE Mobility, Service Experience, QoS Sustainability, Network performance, or indicates (or is) new analytics that can provide assistance information of QoS and policy control decision, etc.

[0274] It is possible to enhance the existing analytics ID and / or introduce new analytics ID to assist with QoS and policy control.

[0275] In operation S220, NWDAF 400 collects input data and generates (or provides, configures etc.) analytics based on PCF request, to derive the output analytics that can assist with QoS and policy control.

[0276] To derive the output analytics that can assist with QoS and policy control, based on the PCF 300 request, the NWDAF 400 may collect the input data of one or more (e.g. all) of User Data Congestion Analytics, Network Performance Analytics, UE Mobility analytics and Abnormal Behaviour Analytics, UE Communication Analytics, Observed Service Experience Analytics, QoS sustainability Analytics, etc., and (optionally) additional input data, e.g. one or more (e.g. all) of service requirements related data that includes 5QI or QoS profile, ARP, RQA, Flow Bit Rates / traffic rate, GBR or non-GBR, or Maximum Packet Loss Rate of the application.

[0277] For example, the information related to service requirements of multiple applications associated to a UE is used as input data to generate the UE communication analytics at per application ID level. The statistics and prediction of the per application ID level traffic characteristics, e.g. data rate, traffic volume, delay etc., help the PCF 300 to determine the traffic patterns of multiple services of a UE when deciding the QoS and policy control. Furthermore, in order to generate more sustainability QoS and policy control, the PCF 300 may require the NWDAF 400 to provide the statistics and prediction of QoS Sustainability analytics at finer granularity, e.g. per UE per QoS flow level of a 5QI. Based on the QoS KPI provided by the NWDAF 400, the PCF 300 may choose the 5QI or the combination of QoS parameters that can provide the required QoS Sustainability for a UE or a QoS flow.

[0278] In operation S230, the different data sources from operation S210 send the required data or analytics (for NWDAF 400) to the PCF 300.

[0279] In operation S240, the PCF 300 consolidates all the collected data (e.g. the input data) and determine the QoS and / or policy control. The PCF 300 may determine the QoS and / or policy control in a future-proof and multi-service-compatible manor, for example based on its internal logic and subject to operator policy. The PCF determines PCC rules including QoS related information.

[0280] For example, based on the trigger of the QoS and policy control procedures in operation S210, the PCF 300 notifies the determined QoS and policy control to its consumers to store or update the QoS and policy. For example, the PCF 300 notifies the QoS and policy control to SMF 200 to establish or modify SM policy, to the AF 500, 800 for the QoS configuration before the service starts, or to UDR 600 to provide or update the default QoS rule before PDU session establishment, etc.

[0281] Operation S250 relates to policy and analytics context management, and comprises either or both of operations S250a and S250b. These operations are omitted in some examples of the disclosure, such as examples in which storing output of the PCF 300 and / or NWDAF 400 at the UDR 600 and ADRF 700, respectively, is not required.

[0282] In operation S250a, the PCF 300 determines to store the determined QoS and policy control or update the existing ones in UDR 600 for future use. In various examples, this operation is similar to operation S150a of FIG. 1.

[0283] In operation S250b, the NWDAF 400 determines (based on PCF requirement) to store or update the analytics context of the analytics derived in operation S220 in ADRF 700 for future use. In various examples, this operation is similar to operation S150b of FIG. 1.

[0284] In operation S260, the PCF 300 notifies the QoS and policy to other 5GC NF (e.g. SMF 200, AMF 100) or the AF 500, 800. The PCF send the QoS and policy for policy establishment or modification.

[0285] In an example, the operations of Figure 2 can be labelled as follows:

[0286] S210 - 1. PCF subscribes to different data sources to collect data to assist with QoS and policy decision.

[0287] S220 - 2. NWDAF collects input data and generates (enhanced) analytics based on PCF request.

[0288] S230 - 3. Different data sources send required data or analytics to PCF to assist with QoS and policy decision.

[0289] S240 - 4. PCF determines PCC rules, including QoS related information.

[0290] S250 - 5. Policy and analytics context management.

[0291] 250a - 5a. PCF store or update the generated QoS and policy in UDR.

[0292] S250b - 5b. NWDAF stores or updates the analytics context in ADRF.

[0293] S260 - 6. PCF sends the QoS and policy for policy establishment or modification.

[0294] Figure 3 illustrates (via a call flow diagram) an example of a method of deploying NWDAF-assisted QoS and policy determination during PDU session establishment.

[0295] The entities in the example of Figure 3 are as follows:

[0296] 100 - UE (User Equipment).

[0297] 200 - SMF (Session Management Function).

[0298] 300 - PCF (Policy Control Function).

[0299] 400 - NWDAF (Network Data Analytics Function).

[0300] 500 - AMF (Access and Mobility Management Function), UPF (User Plane Function), AF (Application Function) and / or other 5GC.

[0301] 600 - UDR (Unified Data Repository).

[0302] 700 - ADRF (Analytics Data Repository Function).

[0303] It will be appreciated that, in more general examples, reference could instead be made to a first entity 100, a second entity 200, a third entity 300, a fourth entity 400, a fifth entity 500, a sixth entity 600 and a seventh entity 700; where each entity is arranged to perform the associated operation(s) indicated below. Furthermore, any one or more of entities in Figure 3 may be combined or co-located. For example, the PCF and the NWDAF can be co-located, in which case an operation which indicates interaction between these two entities is performed internally (for example, not necessitating use of a transmitter / receiver for exchange of data between separate points in the network).

[0304] It will also be understood that various examples relate to individual entities shown in Figure 3. For instance; various examples are directed to the PCF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations; while some other examples are directed to the NWDAF, in which case such examples can focus on operations in which the PCF is involved and omit any other operations. Additionally, yet further examples relate to any combination of the individual entities, and so may include the operations performed by these entities while omitting operations performed by other entities not included in the combination.

[0305] In the example of Figure 3, PDU session establishment procedures are used as an example to illustrate the procedures of how the 5GC may deploy the NWDAF assistance with QoS and policy determination as disclosed herein.

[0306] In operation S310a, UE 100 triggers PDU session establishment to the 5GC. Upon receiving the PDU session establishment request, in operation S310b the SMF 200 triggers SM policy establishment procedures to the PCF 300 to require PCC rules.

[0307] Relating to operations S320a, S320b, the PCF 300 determines the QoS and policy for the SM policy establishment request by deploying NWDAF assistance. For example, based on the SMF request: in operation S320a the PCF 300 determines to fetch the determined QoS and policy (if available) for the UE, if operation S250 or operation S250a in FIG. 2 is already performed; and / or, in operation S320b, the PCF 300 determines to update the fetched stored QoS and policy or generate new QoS and policy for PDU session of the UE, by repeating operations S210 to S240 in FIG. 2.

[0308] It will be understood that, in various examples, it is the decision of PCF 300 to determine whether to fetch or update the determined QoS and policy, or to generate new QoS and policy, e.g. subject to operator policy.

[0309] In operation S330, the PCF 300 notifies or informs the SMF 200 of the determined QoS and policy for PDU session of the UE 100.

[0310] In operation S340a, the SMF 200 establishes the SM policy and PDU session based on the information indicated by PCF notification, and in operation S340b the SMF 200 sends PUD Session Establishment Accept message to the UE 100. The SMF 200 may establish two QoS flows during the PDU session establishment, e.g. one QoS flow is with default QoS rule and another QoS flow associated to the future-proof QoS rules to provide multi-service-compatible QoS configuration. The SMF 200 may notify the UE 100 about the PDU session being successfully established.

[0311] In an example, the operations of Figure 3 can be labelled as follows:

[0312] S310a - 1a. PDU establishment.

[0313] S310b - 1b. Request for PCC rules.

[0314] S320a - 2a. PCF fetch the determined PCC rules from UDR.

[0315] S320b - 2b. the PCF may determine to update the determined or generate new QoS and policy by repeating s210- s240 (of Figure 2).

[0316] S330 - 3. PCC rules provided with determined 5QI(s) or QoS parameters.

[0317] S340a - 4a. SMF establishes QoS rule.

[0318] S340b - 4b. PDU session Establishment Accept.

[0319] Impacts on services, entities and interfaces

[0320] PCF: Consider a combination of NWDAF analytics, including new or enhanced analytics from NWDAF to generate future-proof and multi-service-compatible QoS and policy; Store, update and fetch the determined QoS and policy from UDR, including the default QoS rules.

[0321] NWDAF: Collect new inputs to generate assistance information of QoS and policy control; Generate new outputs to assist with PCF for QoS and policy control determination, including predictions and statistics; Expose the new output analytics to consumers.

[0322] UDR: Store, update, and notify QoS and policy decision based on PCF request.

[0323] Figure 4 is a block diagram of an exemplary apparatus, or network entity, that may be used in examples of the disclosure. The skilled person will appreciate said entity may be implemented, for example, as a network element on a dedicated hardware, as a software instance running on a dedicated hardware, and / or as a virtualised function instantiated on an appropriate platform, e.g. on a cloud infrastructure.

[0324] The entity 1000 comprises a processor (or controller) 1001, a transmitter 1003 and a receiver 1005. The receiver 1005 is configured for receiving one or more messages from one or more other network entities, for example as described above. The transmitter 1003 is configured for transmitting one or more messages to one or more other network entities, for example as described above. The processor 1001 is configured for performing one or more operations, for example according to the operations as described above.

[0325] Figure 5 illustrates a method according to an example of the disclosure. The method is performed by a network entity such as a PCF entity.

[0326] In operation 510, the PCF entity transmits, to a NWDAF entity, a first request relating to QoS and / or policy control for a UE. The first request may be for information relating to QoS and / or policy control for the UE.

[0327] In operation 520, the PCF entity receives, from the NWDAF entity, a first response including information (this may be the requested information), wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS and / or candidate policy.

[0328] In operation 530, the PCF entity determines the QoS and / or policy control for the UE based on the information.

[0329] In optional operation 540, the PCF entity notifies the determined QoS and / or policy control for the UE to one or more consumer.

[0330] Figure 6 illustrates a method according to an example of the disclosure. The method is performed by a network entity such as a NWDAF entity.

[0331] In operation 610, the NWDAF entity receives, from a PCF entity, a first request relating to QoS and / or policy control for a UE. The first request may be for information relating to QoS and / or policy control for the UE.

[0332] In operation 620, the NWDAF entity obtains input data based on the first request.

[0333] In operation 630, the NWDAF entity provides to the PCF entity, a first response including information (this may be the requested information), wherein the information includes: analytics relating to one or more of network congestion level, resource usage condition, traffic patterns of UE services, service experience associated to different QoS parameters, or QoS sustainability associated to different 5QIs; and / or one or more set of candidate QoS parameters and / or candidate policy. The information may be obtained, by the NWDAF entity, based on the obtained input data or at least a part thereof.

[0334] Figure 7 is a block diagram illustrating an example structure of a user equipment (UE) in accordance with various examples of the disclosure.

[0335] As shown in FIG. 7, the UE according to an embodiment may include a transceiver 710, a memory 720, and a processor 730. The transceiver 710, the memory 720, and the processor 730 of the UE may operate according to a communication method of the UE described above. However, the components of the UE are not limited thereto. For example, the UE may include more or fewer components than those described above. In addition, the processor 730, the transceiver 710, and the memory 720 may be implemented as a single chip. Also, the processor 730 may include at least one processor. Furthermore, the UE of FIG. 10 corresponds to the UE of the embodiments of the disclosure.

[0336] The transceiver 710 collectively refers to a UE receiver and a UE transmitter, and may transmit / receive a signal to / from a base station or a network entity. The signal transmitted or received to or from the base station or a network entity may include control information and data. The transceiver 710 may include a RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and a RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver 710 and components of the transceiver 710 are not limited to the RF transmitter and the RF receiver.

[0337] Also, the transceiver 710 may receive and output, to the processor 730, a signal through a wireless channel, and transmit a signal output from the processor 730 through the wireless channel.

[0338] The memory 720 may store a program and data required for operations of the UE. Also, the memory 720 may store control information or data included in a signal obtained by the UE. The memory 720 may be a storage medium, such as read-only memory (ROM), random access memory (RAM), a hard disk, a CD-ROM, and a DVD, or a combination of storage media.

[0339] The processor 730 may control a series of processes such that the UE operates as described above. For example, the transceiver 710 may receive a data signal including a control signal transmitted by the base station or the network entity, and the processor 730 may determine a result of receiving the control signal and the data signal transmitted by the base station or the network entity.

[0340] Figure 8 is a block diagram illustrating an example structure of a network entity in accordance with various examples of the disclosure.

[0341] Referring to FIG. 8, the network entity includes a transceiver (810), a memory (820), and a processor (830). The transceiver (810), the memory (820), and the processor (830) of the network entity may operate according to a communication method of the network entity described above. However, the components of the terminal are not limited thereto. For example, the network entity may include fewer or a greater number of components than those described above. However, the components of the network entity are not limited thereto. For example, the network entity may include more or fewer components than those described above. In addition, the processor (830), the transceiver (810), and the memory (820) may be implemented as a single chip. Also, the processor (830) may include at least one processor. Furthermore, the network entity of FIG. 8 corresponds to the network apparatus of the embodiments of the disclosure.

[0342] The network entity includes at least one entity of a core network. For example, the network entity includes an AMF, a session management function (SMF), a policy control function (PCF), a network repository function (NRF), a user plane function (UPF), a network slicing selection function (NSSF), an authentication server function (AUSF), a UDM and a network exposure function (NEF), but the network entity is not limited thereto.

[0343] The transceiver (810) collectively refers to a network entity receiver and a network entity transmitter, and may transmit / receive a signal to / from a base station or a UE. The signal transmitted or received to or from the base station or the UE may include control information and data. In this regard, the transceiver (810) may include an RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and an RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver (810) and components of the transceiver (810) are not limited to the RF transmitter and the RF receiver.

[0344] The transceiver (810) may receive and output, to the processor (830), a signal through a wireless channel, and transmit a signal output from the processor (830) through the wireless channel.

[0345] The memory (820) may store a program and data required for operations of the network entity. Also, the memory (820) may store control information or data included in a signal obtained by the network entity. The memory (820) may be a storage medium, such as a ROM, a RAM, a hard disk, a CD-ROM, and a DVD, or a combination of storage media.

[0346] The processor (830) may control a series of processes such that the network entity operates as described above. For example, the transceiver (810) may receive a data signal including a control signal, and the processor (830) may determine a result of receiving the data signal.

[0347] Enhancements to analytics IDs to support QoS and policy enhancement are described as below.

[0348] The PCF may request one or more analytics from the NWDAF that are used within the same analytics target period, i.e. Observed service experience, QoS sustainability, Network Performance analytics, analytics of the duration and usage of the established QoS Flows.

[0349] In order to provide richer information to the PCF to assist the QoS and policy determination and modification, the QoS sustainability and Network Performance analytics could be enhanced.

[0350] Currently, the Network Performance analytics may provide the statistics and predictions of the gNB resource usage, including the overall resource usage and the resource usage of GBR and Delay-critical GBR traffic. However, the resource usage of non-GBR traffic is not provided. For PCF QoS and policy determination and modification, understanding the resource usage of all types of traffic will help the PCF with deciding the resource type of a QoS flow for a service. Therefore, the Network Performance analytics is enhanced to provide the statistics and predictions of the gNB resource usage for non-GBR traffic.

[0351] To maintain the service quality, the abnormal QoS change may be prevented by the PCF by choosing proper QoS and policy. The likelihood of a QoS abnormal change may be provided by QoS Sustainability analytics ID.

[0352] However, the existing QoS Sustainability analytics ID can only provide the result based on the QoS KPI in a certain area. In order to support the decision making for the future-proof QoS and policy, finer granularity of the QoS change in forms of statistics and predictions are needed (e.g. UE level). Using the finer granularity of the QoS Sustainability analytics, the PCF can understand the UE level QoS sustainability and optimise the QoS and policy to avoid abnormal QoS change.

[0353] Statistics and predictions of gNB resource usage for non-GBR traffic are introduced as new outputs of Network Performance analytics.

[0354] New inputs and outputs are introduced to QoS Sustainability analytics to support finer granularity analytics.

[0355] Editorial changes.

[0356] PCF is not able to determine the optimised QoS and policy for a service flow that can fulfil the service requirements.

[0357] [Output analytics]

[0358] The NWDAF may be able to provide both statistics and predictions on Network Performance. Network performance statistics are defined in Table 5.

[0359] InformationDescriptionList of network performance information (1..max)Observed statistics during the Analytics target period.> Area subsetList of TAs or Cell IDs within the requested area of interest as defined in clause　6.6.1. If a Spatial granularity size was provided in the request or subscription, the number of elements of the list is smaller than or equal to the Spatial granularity size.> Analytics target period subsetTime window within the requested Analytics target period as defined in clause　6.6.1. If a Temporal granularity size was provided in the request or subscription, the duration of the Analytics target period subset is greater than or equal to the Temporal granularity size.> gNB status information (NOTE　1)Average ratio of gNBs that have been up and running during the entire Analytics target period in the area subset.> gNB resource usage (NOTE　1) (NOTE　2)Usage of assigned resources (average, peak).> gNB resource usage for GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for GBR traffic (average, peak).> gNB resource usage for Delay-critical GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for Delay-critical GBR traffic (average, peak).> gNB resource usage for non-GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for non-GBR traffic (average, peak).> Number of UEs (NOTE　1)Average number of UEs observed in the area subset.> Communication performance (NOTE　1)Average ratio of successful setup of PDU Sessions.> Mobility performance (NOTE　1)Average ratio of successful handover.NOTE　1: Analytics subset that can be used in "list of analytics subsets that are requested" and "Preferred level of accuracy per analytics subset".NOTE　2: The average and peak usage of uplink and downlink traffic are provided as percentage.NOTE　3 The resource usage (average, peak) for GBR and Delay-critical GBR traffic types can be computed using the sub-counters of their corresponding 5QI measurements, as defined in clause　5.1.1.2 of TS　28.552　[8].

[0360] Network performance predictions are defined in Table 6

[0361] InformationDescriptionList of network performance information (1..max)Predicted analytics during the Analytics target period> Area subsetList of TAs or Cell IDs within the requested area of interest as defined in clause　6.6.1. If a Spatial granularity size was provided in the request or subscription, the number of elements of the list is smaller than or equal to the Spatial granularity size.> Analytics target period subsetTime window within the requested Analytics target period as defined in clause　6.6.1. If a Temporal granularity size was provided in the request or subscription, the duration of the Analytics target period subset is greater than or equal to the Temporal granularity size.> gNB status information (NOTE　1)Average ratio of gNBs that will be up and running during the entire Analytics target period in the area subset.> gNB resource usage (NOTE　1) (NOTE　2)Usage of assigned resources (average, peak)> gNB resource usage for GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for GBR traffic (average, peak).> gNB resource usage for Delay-critical GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for Delay-critical GBR traffic (average, peak).> gNB resource usage for non-GBR traffic (NOTE　1) (NOTE　2) (NOTE　3)Usage of assigned resources for non-GBR traffic (average, peak).> Number of UEs (NOTE　1)Average number of UEs predicted in the area subset.> Communication performance (NOTE　1)Average ratio of successful setup of PDU Sessions.> Mobility performance (NOTE　1)Average ratio of successful handover.> ConfidenceConfidence of this prediction.NOTE　1: Analytics subset that can be used in "list of analytics subsets that are requested" and "Preferred level of accuracy per analytics subset".NOTE　2: The average and peak usage of uplink and downlink traffic are provided as percentage.NOTE　3: The resource usage (average, peak) for GBR and Delay-critical GBR traffic types can be computed using the sub-counters of their corresponding 5QI measurements, as defined in clauses 5.1.1.2 of TS　28.552　[8].

[0362] NOTE 1: The predictions are provided with a Validity Period.

[0363] NOTE 2: The analytics on number of UEs are related to the information retrieved from the AMFs.

[0364] The number of network performance information entries is limited by the maximum number of objects provided as part of Analytics Reporting Information.

[0365] The NWDAF provides Network Performance Analytics to a consumer at the time requested by the consumer in the Analytics target period:

[0366] - Analytics ID set to "Network Performance".

[0367] - Notification Target Address including the address of the consumer.

[0368] - Notification Correlation ID, for the consumer to correlate notifications from NWDAF if subscription applies.

[0369] - Analytics specific parameters at the time indicated in the Analytics target period.

[0370] [General]

[0371] The consumer of QoS Sustainability analytics may request the NWDAF analytics information regarding the QoS change statistics for an Analytics target period in the past in a certain area or the likelihood of a QoS change for an Analytics target period in the future in a certain area. The consumer can request either to subscribe to notifications (i.e. a Subscribe-Notify model) or to a single notification (i.e. a Request-Response model).

[0372] The service consumer may be a NF (e.g. AF, PCF).

[0373] The request includes the following parameters:

[0374] - Analytics ID = "QoS Sustainability";

[0375] - Target of Analytics Reporting as defined in clause 6.1.3;

[0376] - Analytics Filter Information:

[0377] -- QoS requirements (mandatory):

[0378] -- 5QI (standardized or pre-configured) and applicable additional QoS parameters and the corresponding values (conditional, i.e. it is needed for GBR 5QIs to know the GFBR); or

[0379] -- the QoS Characteristics attributes including Resource Type, PDB, PER and their values;

[0380] - -- Location information (mandatory): an Area Of Interest or a path of interest. The location information could reflect a list of waypoints:

[0381] -- if the location information is an Area Of Interest, the area can be either described in a coarse granularity as list of TAIs or Cell IDs, or in a fine granularity as geographical area (that can be smaller than a cell), or both (coarse and fine granularity); if both granularities are provided, the NWDAF understands that the area of interest is the intersection between the fine granularity location and the list of TAIs or Cell IDs.

[0382] -- if the location information is a path of interest, the area can be either described in a coarse granularity as list of TAIs or Cell IDs, or in a fine granularity as a list of waypoints (expressed as longitude and latitude in geographical coordinates) and combined with a radius value, or both (coarse and fine granularity); if both granularities are provided, the NWDAF understands that the path of interest is the intersection between the fine granularity location and the list of TAIs or Cell IDs.

[0383] -- Threshold linear distance: The distance travelled by the UE before reporting subsequent location as described in TS 23.273

[0039] .

[0384] NOTE 1: Threshold linear distance is used by the NWDAF when requesting location of the UE from the GMLC using LCS.

[0385] NOTE 2: In this Release, the consumer of the "QoS Sustainability" Analytics ID will provide location information in the area of interest format (TAIs or Cell IDs or geographical area) which is understandable by NWDAF.

[0386] NOTE 3: When location information is described as an area of interest in a fine granularity (i.e. as geographical area that can be smaller than a cell) the Cell ID(s) can already be determined by the NEF based on its local configuration and provided to the NWDAF in addition. This addresses the scenario when Cell ID(s) cannot be determined by the NWDAF based on its local configuration. Alternatively, the NWDAF can also be configured with the Cell ID(s) corresponding to an area of interest in a fine granularity.

[0387] -- S-NSSAI (optional);

[0388] - Optional maximum number of objects;

[0389] - Optional UE Device and Context Information: which may contain one or more of the following:

[0390] -- Speed range, which is a range of UE speeds for which analytics is requested, where the speed range is indicated as a range of Velocity Estimate, as in clause 6.1.6.2.17 of TS 29.572

[0037] ;

[0391] -- Device information, which may contain one of the following:

[0392] -- List of equipment types, according to clause 8.0 of GSMA TS.06

[0038] .

[0393] - Analytics target period: relative time interval, either in the past or in the future, that indicates the time period for which the QoS Sustainability analytics is requested;

[0394] - Optionally, Spatial granularity size and Temporal granularity size;

[0395] - Reporting Threshold(s), which apply only for subscriptions and indicate conditions on the level to be reached for the reporting of the analytics, i.e. to discretize the output analytics and to trigger the notification when the threshold(s) provided in the analytics subscription are crossed by the expected QoS KPIs.

[0396] -- A matching direction may be provided such as crossed (default value), below, or above.

[0397] -- An acceptable deviation from the threshold level in the non-critical direction (i.e. in which the QoS is improving) may be set to limit the amount of signalling.

[0398] -- The level(s) relate to value(s) of the QoS KPIs, for the relevant 5QI:

[0399] -- for a 5QI of GBR resource type, the Reporting Threshold(s) refer to the QoS flow Retainability KPI as defined in clause 6.5.1 of TS 28.554

[0010] ;

[0400] -- for a 5QI of non-GBR resource type, the Reporting Threshold(s) refer to the RAN UE Throughput KPI and / or delay in RAN KPI as defined in TS 28.554

[0010] and TS 28.558

[0050] .

[0401] - In a subscription, the Notification Correlation Id and the Notification Target Address.

[0402] To derive the QoS Sustainability analytics when the location information is an area of interest with coarse granularity (i.e. TAIs or Cell IDs):

[0403] - The NWDAF collects the corresponding statistics information on the QoS KPI for the relevant 5QI of interests from the OAM, i.e. the QoS flow Retainability or the RAN UE Throughput or delay in RAN as defined in TS 28.554

[0010] and average GTP metrics as defined in TS 28.552 [8].

[0404] To derive the QoS Sustainability analytics when the location information is an area of interest with fine granularity (i.e. geographical area that can be smaller than a cell):

[0405] - The NWDAF derives the UE list for the area of interest with fine granularity by two steps, firstly based on an initial selection of the UE list in the corresponding coarse area from AMF, secondly based on finer granularity location data using LCS as described in clause 6.2.12, e.g. NWDAF can collect finer granularity location data of a UE using LCS and identify whether this UE is inside of the area of interest with fine granularity area, input data as defined in Table 8.

[0406] - The NWDAF can then collect the corresponding UE level information on the QoS KPI for the relevant 5QI of interests from the 5GC NF / OAM, i.e. input data as defined in Table 8.

[0407] - NWDAF derives QoS sustainability statistics or predictions for the area of interest with fine granularity by averaging these input data for all the UEs that are in the UE list.

[0408] To improve QoS Sustainability analytics, the NWDAF may additionally collect GTP metrics defined in Table 9.

[0409] If the Analytics target period refers to the past:

[0410] - The NWDAF verifies whether the triggering conditions for the notification of QoS change statistics are met and if so, generates for the consumer one or more notifications.

[0411] - The analytics feedback contains the information on the location and the time for the QoS change statistics and the Reporting Threshold(s) that were crossed.

[0412] If the Analytics target period is in the future:

[0413] - The NWDAF detects the need for notification about a potential QoS change based on comparing the expected values for the KPI of the target 5QI against the Reporting Threshold(s) provided by the consumer in any cell in the requested area for the requested Analytics target period. The expected KPI values are derived from the statistics for the 5QI obtained from OAM. OAM information may also include planned or unplanned outages detection and other information that is not in scope for 3GPP to discuss in detail.

[0414] - The analytics feedback contains the information on the location and the time when a potential QoS change may occur and what Reporting Threshold(s) may be crossed.

[0415] [Input data]

[0416] To derive the QoS Sustainability analytics for a path of interest or for an area of interest with coarse granularity (i.e. TAIs or Cell IDs), the input data is listed in Table 7(Data collection for "QoS Sustainability" analytics).

[0417] InformationSourceDescriptionRAN UE ThroughputOAM TS　28.554

[0010] Average UE bitrate in the cell (Payload data volume on RLC level per elapsed time unit on the air interface, for transfers restricted by the air interface), per timeslot, per cell, per 5QI and per S-NSSAI.RAN UE Throughput per UEOAMTS　28.558

[0050] The average UE throughput in downlink or uplink, per QoS level and per supported S-NSSAI, as defined in clause　6.3.1.4 of TS　28.558.QoS flow RetainabilityOAM TS　28.554

[0010] Number of abnormally released QoS flows during the time the QoS Flows were used per timeslot, per cell, per UE, per 5QI and per S-NSSAI.Delay in RANOAM TS　28.554

[0010] Average Uplink and downlink packet transmission delay through RAN part to the UE, per timeslot, per cell, per 5QI and per S-NSSAI.Delay in RAN per UEOAMTS　28.558

[0050] The average time it takes for packet transmission over the air-interface in the downlink and uplink direction, per QoS level, per S-NSSAI, as defined in clause　6.3.1.1 of TS　28.558.

[0418] NOTE 1: The timeslot is the time interval split according to the time unit of the OAM statistics defined by operator.

[0419] To derive the QoS Sustainability analytics for an area of interest with fine granularity (i.e. geographical area that can be smaller than a cell), additional input data is listed in Table 8(UE level data collection for "QoS Sustainability" analytics with fine granularity).

[0420] InformationSourceDescriptionTimestampLCS (NOTE　1)A time stamp associated with the collected information.UE IDLCS, AMF (NOTE　1)(list of) SUPI(s).Finer granularity location dataLCS (NOTE　1)UE position in the area of interest.SpeedLCS (NOTE　1)Current UE speed.SMF infoAMFSMF address for the SMF serving the UEUPF infoSMFAddress for the UPF serving the UE.5QISMF5G QoS Identifier.PEIUDMPermanent Equipment Identifier, as described in clause　5.9.3 of 1　23.501　[2].Equipment typeGSMA IMEI database or OAMEquipment Type such as smartphone, tablet, dongle, etc. as described in GSMA　TS.06

[0038] .NOTE　1: The procedure to collect location data using LCS is described in clause　6.2.12

[0421] NOTE 2: How to use the input data from GSMA for QoS Sustainability analytics is up to NWDAF implementation.

[0422] Additionally, the NWDAF collects the following input (Table 9:Data collection for QoS Sustainability analytics at GTP level) according to measurements defined in clause 5.33.3 QoS Monitoring to Assist URLLC Service of TS 23.501 [2] and IP-layer section capacity definition from ITU-T Y.1540

[0040] between UE, NG-RAN and UPF at GTP level. The UL / DL available GTP capacity between UPF and UE will also be used as inputs for the QoS Sustainability analytics. The NWDAF calculates this value by implementation, e.g. by subtracting the UL / DL traffic volume from the maximum value of the GTP capacity.

[0423] InformationSourceDescriptionUL / DL packet delay GTPOAM TS　28.552　[8] (NOTE)UL / DL packet delay measurement round trip on GTP path on N3 for non-GBR traffic.UL / DL capacity GTP between UPF and NG-RANOAMTS　28.552　[8]TS　28.554

[0010] Maximum achievable UL / DL capacity measurement from UPF to NG-RAN based on GTP path. The capacity measurement corresponds to the IP-layer section capacity definition from ITU-T　Y.1540

[0040] . It also corresponds to the descriptions in clause　5.1 (DL GTP Capacity) and clause　5.4 (UL GTP Capacity) of TS　28.552　[8] and clause　6.3 of TS　28.554

[0010] .UL / DL capacity GTP between UPF and UEOAMTS　28.552　[8]TS　28.554

[0010] Maximum achievable UL / DL capacity measurement from UE to UPF based on GTP path. The capacity measurement corresponds to the IP-layer section capacity definition from ITU-T　Y.1540

[0040] . It also corresponds to the descriptions in clause　5.4 of TS　28.552　[8] and clause　6.3 of TS　28.554

[0010] .NOTE: Refer to clause　5.1 of TS　28.552　[8] for the performance measurement in NG-RAN and clause　5.4 of TS　28.552　[8] for the performance measurement in UPF. In addition, Annex　A of TS　28.552　[8] describes various performance measurements, especially, clause　A.61 "Monitoring of one way delay between PSA UPF and NG-RAN" indicates that the measurements on the one way DL and UL delay between PSA UPF and NG-RAN can be used to evaluate and optimize the DL and UL user plane delay performance between 5GC and NG-RAN.

[0424] [Output analytics]

[0425] The NWDAF outputs the QoS Sustainability analytics. Depending on the Analytics target period, the output consists of statistics or predictions. The detailed information provided by the NWDAF is defined in Table 10("QoS Sustainability" statistics) for statistics and Table 11("QoS Sustainability" predictions) for predictions.

[0426] InformationDescriptionList of QoS sustainability Analytics (1..max)>Applicable Area (NOTE　1)A list of TAIs or Cell IDs or a geographical area in a fine granularity (e.g. smaller than a cell) within the Location information that the analytics applies to. If a Spatial granularity size was provided in the request or subscription, the number of elements of the list is smaller than or equal to the Spatial granularity size.>Applicable Time PeriodThe time period within the Analytics target period that the analytics applies to. If a Temporal granularity size was provided in the request or subscription, the duration of the Applicable Time Period is greater than or equal to the Temporal granularity size.>Crossed Reporting Threshold(s)The Reporting Threshold(s) that are met or exceeded or crossed by the statistics value or the expected value of the QoS KPI.UE QoS sustainability Analytics (1..max)List of UE QoS sustainability statistics one or list of UE(s).Max. is the number of UEs, if applicable.>UE IDIdentifies the UE for which the statistic applies, e.g. SUPIs.>UE locationIndicate the UE location information.>Applicable Area (NOTE　1)Area where the UE QoS sustainability statistics applies. If Area of Interest information was provided in the request or subscription, spatial validity may be a subset of the requested Area of Interest.>Applicable Time PeriodThe validity period of the UE QoS sustainability statistics. The time period within the Analytics target period that the analytics applies to. If a Temporal granularity size was provided in the request or subscription, the duration of the Applicable Time Period is greater than or equal to the Temporal granularity size.>Crossed Reporting Threshold(s)The Reporting Threshold(s) that are met or exceeded or crossed by the statistics value or the expected value of the QoS KPI.NOTE　1: The Applicable Area may be described as geographical area in a fine granularity (e.g. smaller than a cell) within the Location information when the location information is an area of interest with finer granularity or a path of interest expressed with a list of waypoints and a radius value. How to determine the geographical area is up to NWDAF implementation.

[0427] InformationDescriptionList of QoS sustainability Analytics (1..max)>Applicable Area (NOTE　1)A list of TAIs or Cell IDs or a geographical area in a fine granularity (e.g. smaller than a cell) within the Location information that the analytics applies to. If a Spatial granularity size was provided in the request or subscription, the number of elements of the list is smaller than or equal to the Spatial granularity size.>Applicable Time PeriodThe time period within the Analytics target period that the analytics applies to. If a Temporal granularity size was provided in the request or subscription, the duration of the Applicable Time Period is greater than or equal to the Temporal granularity size.>Crossed Reporting Threshold(s)The Reporting Threshold(s) that are met or exceeded or crossed by the statistics value or the expected value of the QoS KPI.>ConfidenceConfidence of the prediction.UE QoS sustainability Analytics (1..max)List of UE QoS sustainability prediction of one or list of UE(s).Max. is the number of UEs, if applicable.>UE IDIdentifies the UE for which the prediction applies, e.g. SUPIs.>UE locationIndicate the UE location information.>Applicable Area (NOTE　1)Area where the UE QoS sustainability prediction applies. If Area of Interest information was provided in the request or subscription, spatial validity may be a subset of the requested Area of Interest.>Applicable Time PeriodThe validity period of the UE QoS sustainability prediction. The time period within the Analytics target period that the analytics applies to. If a Temporal granularity size was provided in the request or subscription, the duration of the Applicable Time Period is greater than or equal to the Temporal granularity size.>Crossed Reporting Threshold(s)The Reporting Threshold(s) that are met or exceeded or crossed by the statistics value or the expected value of the QoS KPI.>ConfidenceConfidence of the prediction.NOTE　1: The Applicable Area may be described as geographical area in a fine granularity (e.g. smaller than a cell) within the Location information when the location information is an area of interest with finer granularity or a path of interest expressed with a list of waypoints and a radius value. How to determine the geographical area is up to NWDAF implementation.

[0428] NOTE 1: The meaning of Confidence is based on the SLA, i.e. the consumer has to understand the meaning of the different values of Confidence.

[0429] NOTE 2: The Analytics can contain multiple sets of the above information if the location information reflected a list of waypoints.

[0430] The number of QoS sustainability analytics entries is limited by the maximum number of objects provided as part of Analytics Reporting Information.

[0431] It will be appreciated that, in each example / embodiment / aspect etc. described above, one or more features or operations may be omitted, modified or moved (e.g., to change the order of the features or the operations), if desired and appropriate. Additionally, one or more features or operations from any example / embodiment may be combined with features or operations from any other example / embodiment. In particular, regardless of whether or not a pointer towards a combination of features / examples is found herein, the disclosure should be considered to include all combinations of two or more of the embodiments, examples etc. disclosed herein, and all combinations of two or more of the features disclosed herein.

[0432] The techniques described herein may be implemented using any suitably configured apparatus and / or system. Such an apparatus and / or system may be configured to perform a method according to any aspect, embodiment or example disclosed herein. Such an apparatus may comprise one or more elements, for example one or more of receivers, transmitters, transceivers, processors, controllers, modules, units, and the like, each element configured to perform one or more corresponding processes, operations and / or method steps for implementing the techniques described herein. For example, an operation / function of X may be performed by a module configured to perform X (or an X-module). The one or more elements may be implemented in the form of hardware, software, or any combination of hardware and software.

[0433] It will be appreciated that examples of the disclosure may be implemented in the form of hardware, software or any combination of hardware and software. Any such software may be stored in the form of volatile or non-volatile storage, for example a storage device like a ROM, whether erasable or rewritable or not, or in the form of memory such as, for example, RAM, memory chips, device or integrated circuits or on an optically or magnetically readable medium such as, for example, a CD, DVD, magnetic disk or magnetic tape or the like.

[0434] It will be appreciated that the storage devices and storage media are embodiments of machine-readable storage that are suitable for storing a program or programs comprising instructions that, when executed, implement certain examples of the disclosure. Accordingly, certain examples provide a program comprising code for implementing a method, apparatus or system according to any example, embodiment and / or aspect disclosed herein, and / or a machine-readable storage storing such a program. Still further, such programs may be conveyed electronically via any medium, for example a communication signal carried over a wired or wireless connection.

[0435] While the disclosure has been shown, illustrated and described with reference to certain examples, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the disclosure.

[0436] The reader's attention is directed to all papers and documents which are filed concurrently with or previous to this specification in connection with this application and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference.

[0437] Acronyms and definitions

[0438] 3GPP: 3rd Generation Partnership Project

[0439] 5G: 5th Generation

[0440] 5GC: 5G Core

[0441] 5QI: 5G QoS Identifier

[0442] 5GS: 5G System

[0443] 5GSM: 5G System Session Management

[0444] 5GMM: 5G System Mobility Management

[0445] AF: Application Function

[0446] AI: Artificial Intelligence

[0447] AIML: Artificial Intelligence / Machine Learning

[0448] AM: Acknowledged Mode

[0449] AMF: Access and Mobility Management Function

[0450] ARP: Allocation and Retention Priority

[0451] AS: Application Server

[0452] ASP: Application Service Provider

[0453] ATSSS: Access Traffic Steering Switching & Splitting

[0454] AUSF : Authentication Server Function

[0455] CDRX: Connected Mode Discontinuous Reception

[0456] CSI: Channel Status Information

[0457] DCAF: Data Collection Application Function

[0458] DNAI: Data Network Access Identifier

[0459] DNN: Data Network Name

[0460] DNS: Domain Name Server

[0461] DRB: Data Radio Bearer

[0462] eNB: Evolved Node B

[0463] EPS: Evolved Packet System

[0464] FQDN: Fully Qualified Domain Name

[0465] GBR: Guaranteed Bit Rate

[0466] GFBR: Guaranteed Flow Bit Rate

[0467] GMLC: Gateway Mobile Location Centre

[0468] gNB: Next generation Node B

[0469] GPSI: Generic Public Subscription Identifier

[0470] IAB: Integrated Access and Backhaul

[0471] IIoT: Industrial Internet of Things

[0472] IMEI: International Mobile Equipment Identities

[0473] IP: Internet Protocol

[0474] I-SMF: Intermediate SMF

[0475] LMF: Location Management Function

[0476] MA-PDU: Multiple Access PDU

[0477] ML: Machine Learning

[0478] MME: Mobility Management Entity

[0479] MN: Master Node

[0480] MNO: Mobile Network Operator

[0481] MPTCP: MultiPath TCP

[0482] MT: Mobile Termination

[0483] NAS: Non-Access Stratum

[0484] NEF: Network Exposure Function

[0485] NRF: Network Repository Function

[0486] NG-RAN: Next Generation Radio Access Network

[0487] NG-eNB: Next Generation eNB

[0488] NSA: Non-Standalone

[0489] NSSF: Network Slice Selection Function

[0490] NW: Network

[0491] NWDAF: Network Data Analytics Function

[0492] OAM: Operations and Management

[0493] OS: Operating System

[0494] PCF: Policy Control Function

[0495] PCC: Policy and Charging Control

[0496] PCO: Protocol Configuration Options

[0497] PDR: Packet Detection Rule

[0498] PDU: Protocol Data Unit

[0499] PMF: Performance Measurement Function

[0500] PRU: Positioning Reference Unit

[0501] PSA: PDU session anchor

[0502] QFI: QoS Flow Identifier (ID)

[0503] QoE: Quality of Experience

[0504] QoS: Quality of Service

[0505] RACH: Random Access Channel

[0506] RAN: Radio Access Network

[0507] RAT: Radio Access Technology

[0508] RLC-AM: Radio Link Control Acknowledge Mode

[0509] RLC-UM: Radio Link Control Unacknowledge Mode

[0510] RSD: Route Selection Descriptor

[0511] SA: Standalone

[0512] SBA: Service-Based Architecture

[0513] SBI: Service-Based Interface

[0514] SCEF: Service Capability Exposure Function

[0515] SCP: Service-Based Communication Proxy

[0516] SCTP: Stream Control Transmission Protocol

[0517] SDAP: Service Data Adaptation Protocol

[0518] SDU: Service Data Unit

[0519] SIM: Subscriber Identity Module

[0520] SLA: Service Level Agreement

[0521] SM: Session Management

[0522] SMF: Session Management Function

[0523] SN: Secondary Node

[0524] S-NSSAI: Single Network Slice Selection Assistance Information

[0525] SSC: Session and Service Continuity

[0526] SUPI: Subscription Permanent Identifier

[0527] TAI: Tracking Area Identity

[0528] TE: Terminal Equipment

[0529] TM: Transparent Mode

[0530] TS: Technical Specification

[0531] UDM: Unified Data Manager

[0532] UDR: Unified Data Repository

[0533] UE: User Equipment

[0534] UL: Uplink

[0535] UM: Unacknowledged Mode

[0536] UP: User Plane

[0537] UPF: User Plane Function

[0538] URLLC: Ultra-Reliable and Low-Latency Communication

[0539] URSP: UE Route Selection Policy

[0540] V2X: Vehicle-to-everything

[0541] XRM: Extended Reality and Media

Claims

1.A method performed by a network data analytics function (NWDAF) entity in a wireless communication system, the method comprising:receiving, from a policy control function (PCF) entity, a first message for requesting for quality of service (QoS) and policy assistance analytics;obtaining input data from at least one NF entity;transmitting, to the PCF entity, a second message including output data for the QoS and policy assistance analytics which is generated based on the input data.2.The method of claim 1, wherein the input data includes at least one of a QoS parameter set, or a QoS profile.3.The method of claim 2, wherein the output data includes at least one of an application identifier (ID), or at least one QoS parameter.4.The method of claim 3, wherein the at least one QoS parameter includes at least one of a 5G QoS identifier (5QI), an allocation and retention priority (ARP), flow bit rates, a maximum packet loss rate, a guaranteed bit rate (GBR) QoS flow, or a non-GBR QoS flow.5.The method of claim 1, wherein input data for observed service experience analytics is reused for the QoS and policy assistance analytics.6.A method performed by a policy control function (PCF) entity in a wireless communication system, the method comprising:transmitting, to a network data analytics function (NWDAF) entity, a first message for requesting for quality of service (QoS) and policy assistance analytics;receiving, from the NWDAF entity, a second message including output data for the QoS and policy assistance analytics which is based on the input data.7.The method of claim 6, wherein the input data includes at least one of a QoS parameter set, or a QoS profile.8.The method of claim 7, wherein the output data includes at least one of an application identifier (ID), or at least one QoS parameter, andwherein the at least one QoS parameter includes at least one of a 5G QoS identifier (5QI), an allocation and retention priority (ARP), flow bit rates, a maximum packet loss rate, a guaranteed bit rate (GBR) QoS flow, or a non-GBR QoS flow.9.A network data analytics function (NWDAF) entity in a wireless communication system, the NWDAF entity comprising:a transceiver; anda controller coupled with the transceiver and configured to:receive, from a policy control function (PCF) entity, a first message for requesting for quality of service (QoS) and policy assistance analytics,obtain input data from at least one NF entity,transmit, to the PCF entity, a second message including output data for the QoS and policy assistance analytics which is generated based on the input data.10.The NWDAF entity of claim 9, wherein the input data includes at least one of a QoS parameter set, or a QoS profile.11.The NWDAF entity of claim 10, wherein the output data includes at least one of an application identifier (ID), or at least one QoS parameter.12.The NWDAF entity of claim 11, wherein the at least one QoS parameter includes at least one of a 5G QoS identifier (5QI), an allocation and retention priority (ARP), flow bit rates, a maximum packet loss rate, a guaranteed bit rate (GBR) QoS flow, or a non-GBR QoS flow.13.The NWDAF entity of claim 9, wherein input data for observed service experience analytics is reused for the QoS and policy assistance analytics.14.A policy control function (PCF) entity in a wireless communication system, the PCF entity comprising:a transceiver; anda controller coupled with the transceiver and configured to:transmit, to a network data analytics function (NWDAF) entity, a first message for requesting for quality of service (QoS) and policy assistance analytics;receive, from the NWDAF entity, a second message including output data for the QoS and policy assistance analytics which is based on the input data.15.The PCF entity of claim 14, wherein the input data includes at least one of a QoS parameter set, or a QoS profile,wherein the output data includes at least one of an application identifier (ID), or at least one QoS parameter, andwherein the at least one QoS parameter includes at least one of a 5G QoS identifier (5QI), an allocation and retention priority (ARP), flow bit rates, a maximum packet loss rate, a guaranteed bit rate (GBR) QoS flow, or a non-GBR QoS flow.

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