NWDAF XR Analytics

Abstract

An apparatus includes means for receiving, from a network function consumer, a request for analytics related to at least one extended reality feature 510; means for determining the analytics related t

Description

TECHNICAL FIELD

[0001] The examples and non-limiting example embodiments relate generally to communications and, more particularly, to NWDAF XR analytics. BACKGROUND

[0002] It is known for a communication device in a communication network to provide functionality for extended reality. SUMMARY

[0003] In accordance with an aspect, an apparatus includes means for receiving, from a network function consumer, a request for analytics related to at least one extended reality feature; means for determining the analytics related to the at least one extended reality feature; and means for transmitting, to the network function consumer, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0004] In accordance with an aspect, an apparatus includes means for transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; and means for receiving, from the network data analytics function, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0005] In accordance with an aspect, an apparatus includes means for receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and means for transmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended 1 reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

[0006] In accordance with an aspect, an apparatus includes means for receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; and means for transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

[0007] In accordance with an aspect, an apparatus includes means for implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated; means for implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated; means for transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; and means for transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The foregoing aspects and other features are explained in the following description, taken in connection with the accompanying drawings.

[0009] FIG. 1 is an example architecture configured to implement the examples described herein.

[0010] FIG. 2 shows a procedure for determining the service experience and service experience improvement with an XR feature.

[0011] FIG. 3 is a block diagram of one possible and non-limiting system in which the example embodiments may be practiced.

[0012] FIG. 4 shows a representation of an example of non-volatile memory media used to store instructions that implement the examples described herein.

[0013] FIG. 5 is an example method, based on the examples described herein.

[0014] FIG 6 is an example method, based on the examples described herein.

[0015] FIG 7 is an example method, based on the examples described herein.

[0016] FIG. 8 is an example method, based on the examples described herein.

[0017] FIG. 9 is an example method, based on the examples described herein. DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0018] The examples described herein relate to both the planned Release 19 (Rei-19) extended reality and media services (XRM) and enablers for network analytics phase 4 (e\APh4) studies planned for Rei. 19. Specifically, the examples described herein extend network data analytics function (NWDAF) Analytics to assess the effectiveness of extended reality (XR) features defined in Rei. 18 and potentially enhanced in Rei. 19, and new features introduced in Rei. 19 and subsequent third generation partnership project (3GPP) releases.

[0019] FIG. 1 is an example architecture configured to implement the examples described herein. XR Analytics 30 are determined by an NWDAF 230 in the 5GC, not necessarily in the RAN 60. The NWDAF 230 and NFs (e.g. NF 260, SMF 42, AMF 44, AF 250, PCF 220, etc.) from which the NWDAF 230 obtains data (e.g. via link 65) to determine analytics could be implemented in standalone computing hardware (HW), or more likely be implemented and / or instantiated as virtualized functions in a data center I cloud 50. The dashed block shown to represent the data center or cloud 50 indicates that the NWDAF 230 and NFs (260, 42, 44, 250, 220) being implemented within the data center or cloud 50 is optional. The role for the RAN 60 comprising RAN node 170 is that OA&M data from the RAN 60 (transmitted via link368) may be used as a data source for analytics generated by XR analytics 30.

[0020] The architecture 10 comprises at least one processor 70 (e.g. an FPGA and / or CPU), one or more memories 80 including computer program code 90, the computer program code 90 having instructions to carry out the methods described herein, wherein the at least one 3 memory 80 and the computer program code 90 are configured to, with the at least one processor 70, cause the NWDAF 230 and NFs (260, 42, 44, 250, 220) to implement circuitry, a process, component, module, or function to implement the examples described herein. The memory 80 may be a non-transitory memory, a transitory memory, a volatile memory (e.g. RAM), or a non-volatile memory (e.g. ROM). UE 110, via link 71, is configured to provide data to the functions in the data center or cloud 50, including NWDAF 230.

[0021] NWDAF 230 may implement the messages and signaling as described herein, such as that described with reference to FIG. 2. The configurations of the RAN node 170 and UE are described in more detail with reference to FIG. 3.

[0022] The Network Data Analytics Function (NWDAF) 230 is a 5GC network function comprised of one or more of a Model Training Logical Function (MTLF) and Analytics Logical Function (AnLF). Any 5GC NF may request Analytics (statistics and / or predictions) from an NWDAF containing an AnLF. 3GPP TS23.288 defines the analytics that may be provided by an NWDAF. Examples are Slice Load Level, Observed Service Experience, NF load, Network Performance, UE Mobility, UE Communication, User Data Congestion and QoS Sustainability analytics. For each of the analytics, 3GPP defines what the consumer of the analytics requests, the input data used to determine the analytics, the analytics output and procedure(s). It also defines ways to collect data (i.e. directly from a data source, using a DCCF, or using a DCCF and MFAF) and the source of the data for determining analytics (e.g. from NFs, OA&M, UEs via an AF, an ADRF or the RAN). 3GPP however does not define the internal NWDAF AI / ML processing needed to determine the analytics.

[0023] The XR features relevant to the examples described herein are described in TS23.501 clause 5.37 and include PDU Set Handling, L4SECN marking by the RAN orUPF, Policy control enhancements to support XR multi-modal services and UE power savings management. They are summarized below.

[0024] PDU Set Handling

[0025] In Rei. 18 (see TS 23.501), mechanisms for PDU Set handling were specified, where a PDU Set is one or more PDUs carrying the payload of one unit of information generated at the application level (e.g., a video frame or video slice for XR Services). For downlink XR traffic, detection of PDU Sets and determination of PDU Set related parameters is done by the PSA UPF. The UPF subsequently provides PDU Set information to the RAN via 4 parameters in an extension header of each packet sent in the GTP tunnel between the UPF and the NG-RAN. In doing so, the RAN becomes aware of application layer characteristics and can adapt its processing and packet handling accordingly. In Rei. 18, PDU Set handling is performed in the NG-RAN according to the information received in the GTP-U header extension and new QoS parameters that are applicable to the group of PDUs that form a PDU Set. These parameters are PDU Set Error Rate (PSER), PDU Set Delay Budget (PSDB) and a PDU Set Integrated Handling Indicator (PSIHI). The PSIHI indicates whether all PDUs in a PDU Set are needed by the application for it to process the application layer information at all. PDU Set handling is also supported in the UE for uplink PDUs. The UE identifies PDUs that belong to a PDU Set and adapts its processing accordingly.

[0026] L4S Marking

[0027] Low latency, low loss and scalable throughput (L4S) marking of ECN bits to indicate congestion in the 5GS was specified in Rei. 18 in 3GPP TS23.501: L4S is described in IETF RFC 9330

[159] , IETF RFC 9331

[160] and IETF RFC 9332

[161] , The 5GS exposes congestion information by marking ECN bits in the IP header of the user plane IP packets sent between the UE and the application server. This may trigger application layer rate adaptation by hosts that support L4S.

[0028] In the 5GS, ECN marking for L4S is enabled on a per QoS Flow basis in the uplink and / or downlink direction and may be used for GBR and non-GBR QoS Flows. ECN marking for the L4S in the IP header is supported in either the NG-RAN or in the PSA UPF.

[0029] QoS parameters determine the QoS provided by the 5GS and include parameters such as packet error rate, packet delay budget, Guaranteed Flow bit rate, etc. A QoS Flow is the finest granularity for QoS forwarding treatment in the 5G System. QoE is the quality of experience experienced by the subscriber. QoE may or may not be correlated with QoS attributes. L4S marking is the same as ECN marking for L4S.

[0030] PCC Enhancements for Multi-modal services

[0031] Multi-modal services consist of several data flows (named as multi-modal flows) that are related to each other and may come from different sources. Each data flow (single-modal data) may be seen as one type of data (for example audio, video, positioning, haptic data) associated with the same communication service. These data flows are expected to be closely related and to require strong application coordination for correct delivery of the multimodal application data. To enable this the application (AF) may provide, at the same time, service requirements for each media that comprise the multi-modal service, a Multi-modal Service ID to identify related media components and QoS monitoring requirements for multiple IP data flows associated to a multi-modal service.

[0032] Accordingly, the AF provides QoS monitoring requirements for multiple IP data flows associated to a multi-modal service to the 5GS. The 5GS provides QoS monitoring as defined in TS 23.501 clause 5.45. The QoS monitoring provided by the 5GS includes monitoring UL and DL packet delay, round trip delay, congestion and data rate packet delay variation.

[0033] The PCF may use this information (PCC enhancements and multi-modal services information) to derive PCC rules and apply QoS policies for data flows that are part of a specific multi-modal application.

[0034] UE Power Saving Management

[0035] The 5G core (5GC) may provide the RAN with traffic assistance information to aid the RAN in configuring UE connected mode DRX in order to save UE power. The assistance information consists of UL and / or DL media Periodicity and N6 Jitter Information associated with the DL Periodicity. Both are provided via the 5GC control plane (SMF to RAN). The assistance information also comprises End of Data Burst indications which the UPF may insert in the GTP-U header of DL UP PDUs. The RAN may determine the end of a data burst by examining the GTP-U header information sent by the UPF.

[0036] Described herein are new analytics or enhancements to existing analytics to determine the effectiveness of XRM features that were first defined in 3GPP Rei. 18 and may be enhanced in Rei. 19, and new features introduced in Rei. 19 and subsequent 3GPP releases. Currently there is no mechanism to determine the effectiveness of XRM features besides monitoring of KPIs which include simple metrics like congestion information (i.e. a percentage of congestion level), data rate information for UL and DL and round-trip delay for the same UE / PDU Session, etc.

[0037] Release 18 XRM has introduced a number of features to bring application awareness to the 5GS. As described previously, those features include PDU Set Handling, L4S ECN marking by the RAN or UPF, Policy control enhancements to support XR multi-modal services and UE Power Savings management. The objective of these features is to improve the subscriber QoE, QoS and increase capacity utilization for a given QoS / QoE. However, there is currently no mechanism to determine whether these enhancements actually improve the user experience (e.g. does PDU Set handling or L4S actually have a positive overall effect on subscriber QoE?). The examples described herein solve that problem. In particular, 3GPP does not provide a means to assess XR feature effectiveness in improving subscriber QoE. QoS may be a factor in the QoE. The QoE is the quality of experience of the subscriber, and may be measured using MoS (mean opinion score) or similar measures.

[0038] The examples described herein introduce new “XR Feature” NWDAF Analytics that assess the benefit provided by individual features or combinations of features introduced for XR. The benefits are determined by comparing analytics when the feature(s) are activated (on) to the same analytics when the same feature(s) are de-activated. For example, a first set of the analytics determined during a period of time when the one or more features are activated are compared to a second set of analytics determined during a period of time when the one or more features are deactivated. The analytics may for example, include one or more of “XR Feature Service Experience analytics” and / or “XR Feature QoS Sustainability analytics” and / or “XR Feature Congestion analytics”.

[0039] “XR Feature Service Experience analytics” provide statistics and predictions of QoE (i.e. service experience). The QoE with the XR feature(s) “on” is compared with the QoE when the XR feature(s) “off’.

[0040] “XR Feature QoS Sustainability analytics” indicate the degree to which the required QoS can be maintained. The QoS sustainability when XR features or combinations of XR features are “on” is compared with the QoS sustainability when the XR features or combinations of XR features are “off’.

[0041] ‘‘XR Feature Congestion analytics” indicate the user plane congestion for applications. The congestion analytics when XR features or combinations of XR features are “on” is compared with the congestion analytics when the XR features or combinations of XR features are “off’.

[0042] Note these analytics may be used to assess capacity improvement by comparing the capacity at which equivalent analytics are obtained with the features on and off. 7

[0043] The items described previously, namely L4S, UE Power Saving Management, and PDU Set Handling are the features. The XR Feature Service Experience Analytics evaluate the effect these features have on the subscriber Service Experience. Similarly the XR feature sustainability analytics assess whether the feature improves the sustainability of QoS, etc. QoS and PCC rules in the PCF may be assumed to be constant when assessing whether an XR feature is beneficial.

[0044] XR Feature analytics may be based on enhancements to different existing analytics such as “Observed Service Experience”, “QoS Sustainability”, “User Data Congestion” and “Redundant Transmission Experience related” analytics or may be defined separately using one or more new Analytics ID (e.g. a new Analytics ID for XR Feature Service Experience” analytics).” New Analytics ID(s) may be introduced in 3GPP TS 23.288 (there are currently approx. 19 NWDAF analytics IDs to which this would be added). In either case, the following standardized analytics outputs may be provided (and specified in TS 23.288). These new analytics directly correspond to the enhancements for high data rate low latency services, XR, and interactive media services defined for Rei. 18 in TS 23.501, clause 5.37.

[0045] Analytics Outputs from NWDAF (1-2):

[0046] 1. Service Experience, QoS Sustainability, Congestion analytics and / or capacity Improvement with one or more of the following XR Features: PDU Set Handling, L4S feature where L4S marking is performed in the RAN, L4S feature where L4S marking is performed in the UPF, Congestion information exposed towards the AF via exposure interface, Enhancements for multi-modal services (enabling the same QoS) in terms of synchronized delivery of services, Use of Assistance parameters (jitter and EoDB) provided for improved UE power savings (DRX), Use of Policy control based on round-trip latency requirement, UL PDB or DL PDB individually, AF Packet Delay Variation (jitter) requirement for UL, DL or RT (i.e. consistent support of low latency requirement) and monitoring results

[0047] 2. Service Experience, QoS Sustainability, Congestion analytics and / or capacity Improvement depending on the access technology used for XR access.

[0048] The analytics outputs described with reference to Analytics Outputs from NWDAF assess the effectiveness of the features. That includes improving QoE. The output of Service Experience analytics is an MoS score that directly assesses QoE.

[0049] The analytics may be provided for one application, a specified set of application(s) or for all applications. The analytics may also be provided with combinations of XR features. For example, one or more of Service Experience, QoS sustainability and capacity improvement with both PDU Set Handling and with L4S (simultaneously) may be provided.

[0050] The consumer of the analytics may indicate in the request or subscription, one or more of the following (1-6):

[0051] 1. XR Feature(s) - one or more of PDU Set Handling, L4S, Enhancements for Multi- Modal Services, UE Power Savings Management and Policy Control based on round-trip latency, etc. for which the service experience and / or service experience improvement is to be determined.

[0052] 2. ‘‘Feature off / on” or “Feature Improvement” for the indicated feature(s). This determines whether Feature “off’ and Feature “on” analytics, or only the “Improvement” (i.e. delta between “off” and “on”) are to be provided.

[0053] 3. Number of UE(s).

[0054] 4. Target of Analytics Reporting - The target for analytics reporting may be one or more of (i-iii): i) The UEs or a group of UEs or “any UE” for which analytics are reported when the specified XR feature(s) are active, ii) The UEs or a group of UEs “any UE” for which analytics are reported when the specified XR feature(s) are not active, iii) The UEs, group of UEs or “any UE” to be considered for analytics.

[0055] 5. The Application type or group of applications, per DNN / S-NSSAI, for a given access (3GPP access, non-3GPP) for which the analytics are to be determined, meaning that the performance of the XR features can be assessed for a specific network (DNN - for example internet, enterprise, etc.) and network slice - for example URLLC, eMBB, gaming, etc.

[0056] Note: the 5GS may determine which if any of the specified XR features are active for the UE(s) by querying the PCF or SMF.

[0057] 6. XR feature specific parameters as described herein.

[0058] New functionality provided by 5GS NFs for Data Collection includes (1-3):

[0059] 1 The UE IDs for which a feature (e g. PDU Set Handling) is active is provided by one or more of the PCF 220, SMF 42 or UE 110.

[0060] 2. The time period when a feature is active may be provided by the PCF 220, SMF 42 or UE 110.

[0061] 3. Additional data specific the XR Feature(s) - see clause 7 for examples.

[0062] Note these are in addition to existing parameters specified by the consumer and data obtained by the NWDAF for Analytics - see TS23.288 clause 6.

[0063] A procedure illustrating the methods described herein based on assessing XR Feature Service Experience is shown in FIG. 2. In particular, FIG. 2 shows a procedure for determining the Service Experience and Service Experience Improvement with an XR feature. The diagram is based on TS23.288 figure 6.4.4-1 “Procedure for NWDAF providing Service Experience for an Application” which is modified accordingly. Similar procedures may be modified for other XR Feature analytics.

[0064] This procedure allows the consumer to request analytics that assess the effect of one or more of the XR features (see list described previously) on subscriber QoE, this may include for example (1-5): 1) PDU Set Handling, 2) L4S feature where L4S marking is performed by the RAN and / or UPF, 3) Enhancements for XR multi-modal services, 4) Improved UE Power Savings (DRX), 5) etc. (see list described previously). QoS is one of the factors that may influence QoE. Observed Service Experience analytics measure QoE.

[0065] The consumer may include a list of Application IDs for which the service experience or service experience improvements are requested, or indicate “any” application ID. The consumer may further request that the Target of Analytics Reporting be one or more UEs, a group of UEs or "any UE".

[0066] FIG. 2 shows an example signaling exchange between the NF (consumer) 210, the PCF 220, the NWDAF 230, NEF 240, AF 250, and NF (network data provider) 260. The procedure shown in FIG. 2 is described as follows:

[0067] 1 (201). Consumer NF 210 sends an Analytics request / subscribe (Analytics ID = XR Feature Service Experience, XR Feature(s) (e.g. PDU Set handling, L4S, etc.), Application ID(s), Service Experience or Service Experience Improvement indicator and UEs, group of UEs or “any UE”) to NWDAF 230.

[0068] Thus as shown in FIG. 2, at 201 the NF consumer 210 transmits to the NWDAF 230 an NnwdafAnalyticsInfoRequest message or anNnwdafAnalyticsSubscriptionSubscribe message, where Analytics ID = XR Feature Service Experience and new parameters are transmitted with the message.

[0069] 2a-b (202-a, 202-b). At 202-a, the NWDAF 230 subscribes / queries the PCF 220 to determine the UE-IDs for which the App-IDs are in use and the XR Feature Status. At 202-b, at least one of two lists are provided by the PCF 220 to the NWDAF 230: The list of UE-IDs for which the XR Feature(s) are active for an App. ID and a list of UE-IDs for which the XR Feature(s) are not active for an App. ID.

[0070] Thus as shown in FIG. 2, at 202-a the NWDAF 230 transmits to the PCF 220 an NpcfPolicy Authorization subscribe message or an Npcf EventExposure subscribe message, where event ID = XR Feature and an App-ID is optionally provided in the message. At 202-b, the PCF 220 transmits to the NWDAF 230 an Npcfjol icy Control Notify message or an Npcf_EventExposure notify message, where UE-IDs, one or more App-IDs, and one or more XR features are provided in the message.

[0071] 3a (203-a-l, 203-a-2). At 203-a-l, NWDAF 230 subscribes for the service data from AF 250 in the Table 6.4.2-1 of TS 23.288 by invoking NnefEventExposure Subscribe or NafJiventExposure^Subscribe service (Event ID = XR Feature Service Experience information, Application ID, Event Filter information), Target of Event Reporting = UEs for which XR feature is active and / or UEs for which XR feature is not active.

[0072] Thus as shown in FIG. 2, at 203-a-l, the NWDAF 230 transmits to the NEF 240 and the AF 250 an NafEventExposureSubscribe message, where EventID=XR Feature Service Experience Information. At 203-a-2, the AF 250 and NEF 240 transmit a response to the NWDAF 230 in response to the message transmitted at 203-a-l. The response may be one or more notifications comprising data to determine Service Experience analytics with or without the XR feature active.

[0073] 3b (203-b-l, 203-b-2). NWDAF subscribes to the network data from 5GC NF(s) in the Table 6.4.2-2 ofTS23.288 by invoking NnfEventExposurejSub scribe service operation.

[0074] Thus as shown in FIG. 2, at 203-b-l the NWDAF 230 transmits to the NF (network data provider) 260 an NnfEventExposureSubscribe message having an EventID. At 203-b-2, the NF (network data provider) 260 transmits to the NWDAF 230 an Nnf_EventExposure_Notify message comprising data to determine Service Experience analytics with or without the XR feature active.

[0075] 3c (203-c). With these data, the NWDAF 230 estimates the Service experience for the XR feature (either the Service experiences with the XR feature on and the service experience with the XR feature off, or the difference between the service experiences). Thus as shown in FIG. 2, at 203-c the NWDAF 230 derives requested analytics for an XR feature.

[0076] 4 (204). The NWDAF 230 provides the data analytics, i.e. the observed XR Feature Service Experience (which can be a range of values) to the consumer NF 210 by means of either an NnwdafAnalyticsInfoRequest response message or an Nnwdaf AnalyticsSubscription Notify message, depending on the service used in step 1 (201), indicating how well the used QoS Parameters satisfy the Service MoS agreed between the MNO and the end user or between the MNO and the external ASP.

[0077] Thus as shown in FIG. 2, at 204 the NWDAF 230 transmits to the NF (consumer) 210 an NnwdafAnalyticsInfoRequest Response message or an Nnwdaf AnalyticsSubscription Notify message, where the message has the estimated service experience with the one or more XR features and the service experience improvement with the one or more XR features.

[0078] Additional feature specific “Analytics Filter” information provided by the consumer to the NWDAF 230 (for example via interface 65) or input data that may be used to determine the analytics for the above service experience and characteristics may include (1-6):

[0079] 1) PDU Set Handling, which may include (a-e): a. Protocol description, b. PSDB, PSER values used for the PDU Set, c. QoS flows enabled for PDU Set Handling, d. PSDB and PSER monitoring information (indicating when the PSDB and PSER is not met, also when the PSDB / PSER is met, need to understand the actual delay incurred for the PDU Set), e. Number of UE(s) served using PDU Set vs PDU based handling (may be application specific).

[0080] 2) L4S handling, which may include (a-e): a. QoS Flows enabled for L4S marking, b. UL and / or DL congestion information based on L4S marking (as per TS23.501 5.37.4), c. Time taken for the application to adapt data rate based on L4S marking for UL and DL, d. Latency achieved with L4S activated and L4S not activated, e. L4S marking performed in the RAN or UPF.

[0081] 3) Multi-modal Handling, which may include (a-c): a. Single UE or multiple UE multi-modal handling, b. QoS Flows enabled for multi-modal services, c. Multi-Modal Service ID(s).

[0082] 4) Power savings enhancements (including UE power savings management), which may include (a-c): a. QoS Flows that receive EoDB indication, b. QoS Flows that receive Periodicity and N6 jitter, c. Periodicity and jitter information.

[0083] 5) Round trip delay, UL PDB, DL PDB, which may include (a-d): a. QoS Flows that receive round-trip latency requirement, b. Round-trip Requirements, c. Assigned UL and DL PDBs, d. QoS performance information.

[0084] 6) Use of Packet Delay Variation (jitter) requirements, which may include AF requirements for Jitter and jitter monitoring results.

[0085] The examples described herein may be applicable to solutions for 3GPP XR, and may be a standardized feature for Rei. 19 or in a subsequent 3GPP release. Use of the feature can be implemented via use of the new NWDAF analytics by a consumer.

[0086] The signaling shown in FIG. 2 are messages in the sense that they are sent from a consumer to a producer. The signaling and messages shown in FIG. 2 may also be referred to as service operations.

[0087] Turning to FIG. 3, this figure shows a block diagram of one possible and nonlimiting example of a configuration in 5G, 6G, and beyond. A user equipment (UE) 110, radio access network (RAN) node 170, and network element(s) 190 are illustrated. In the example of FIG. 3, the user equipment (UE) 110 is in wireless communication with a wireless network 100. A UE is a wireless device that can access the wireless network 100. The UE 110 includes one or more processors 120, one or more memories 125, and one or more transceivers 130 interconnected through one or more buses 127. Each of the one or more transceivers 130 includes a receiver, Rx, 132 and a transmitter, Tx, 133. The one or more buses 127 may be address, data, or control buses, and may include any interconnection mechanism, such as a series of lines on a motherboard or integrated circuit, fiber optics or other optical communication equipment, and the like. The one or more transceivers 130 are connected to one or more antennas 128. The one or more memories 125 include computer program code 123. The UE 110 includes a module 140, comprising one of or both parts 140-1 and / or 140-2, which may be implemented in a number of ways. The module 140 may be implemented in hardware as module 140-1, such as being implemented as part of the one or more processors 120. The module 140-1 may be implemented also as an integrated circuit or through other hardware such as a programmable gate array. In another example, the module 140 may be implemented as module 140-2, which is implemented as computer program code 123 and is executed by the one or more processors 120. For instance, the one or more memories 125 and the computer program code 123 may be configured to, with the one or more processors 120, cause the user equipment 110 to perform one or more of the operations as described herein. The UE 110 communicates with RAN node 170 via a wireless link 111.

[0088] The RAN node 170 in this example is a base station that provides access for wireless devices such as the UE 110 to the wireless network 100. The RAN node 170 may be, for example, a base station for 5G, also called New Radio (NR) or a base station for 6G. In 5G and 6G, the RAN node 170 may be a NG-RAN node, which is defined as either a gNB or an ng-eNB. A gNB is a node providing NR user plane and control plane protocol terminations towards the UE, and connected via the NG interface (such as connection 131) to a 5GC (such as, for example, the network element(s) 190). The ng-eNB is a node providing E-UTRA user plane and control plane protocol terminations towards the UE, and connected via the NG interface (such as connection 131) to the 5GC or 6G core network. The NG-RAN node may include multiple gNBs, which may also include a central unit (CU) (gNB-CU) 196 and distributed unit(s) (DUs) (gNB-DUs), of which DU 195 is shown. Note that the DU 195 may include or be coupled to and control a radio unit (RU). The gNB-CU 196 is a logical node hosting radio resource control (RRC), SDAP and PDCP protocols of the gNB or RRC and PDCP protocols of the en-gNB that control the operation of one or more gNB-DUs. The gNB-CU 196 terminates the Fl interface connected with the gNB-DU 195. The Fl interface is illustrated as reference 198, although reference 198 also illustrates a link between remote elements of the RAN node 170 and centralized elements of the RAN node 170, such as between the gNB-CU 196 and the gNB-DU 195. The gNB-DU 195 is a logical node hosting RLC, MAC and PHY layers of the gNB or en-gNB, and its operation is partly controlled by gNB-CU 196. One gNB-CU 196 supports one or multiple cells. One cell may be supported with one gNB-DU 195, or one cell may be supported / shared with multiple DUs under RAN sharing. The gNB-DU 195 terminates the Fl interface 198 connected with the gNB-CU 196. Note that the DU 195 is considered to include the transceiver 160, e.g., as part of a RU, but some examples of this may have the transceiver 160 as part of a separate RU, e.g., under control of and connected to the DU 195.

[0089] The RAN node 170 includes one or more processors 152, one or more memories 155, one or more network interfaces (N / W I / F(s)) 161, and one or more transceivers 160 interconnected through one or more buses 157. Each of the one or more transceivers 160 includes a receiver, Rx, 162 and a transmitter, Tx, 163. The one or more transceivers 160 are connected to one or more antennas 158. The one or more memories 155 include computer program code 153. The CU 196 may include the processor(s) 152, one or more memories 155, and network interfaces 161. Note that the DU 195 may also contain its own memory / memories and processor(s), and / or other hardware, but these are not shown.

[0090] The RAN node 170 includes a module 150, comprising one of or both parts 150-1 and / or 150-2, which may be implemented in a number of ways. The module 150 may be implemented in hardware as module 150-1, such as being implemented as part of the one or more processors 152. The module 150-1 may be implemented also as an integrated circuit or through other hardware such as a programmable gate array. In another example, the module 150 may be implemented as module 150-2, which is implemented as computer program code 153 and is executed by the one or more processors 152. For instance, the one or more memories 155 and the computer program code 153 are configured to, with the one or more processors 152, cause the RAN node 170 to perform one or more of the operations as described herein. Note that the functionality of the module 150 may be distributed, such as being distributed between the DU 195 and the CU 196, or be implemented solely in the DU 195.

[0091] The one or more network interfaces 161 communicate over a network such as via the links 176 and 131. Two or more gNBs 170 may communicate using, e.g., link 176. The link 176 may be wired or wireless or both and may implement, for example, an Xn interface for 5G, or other suitable interface for other standards.

[0092] The one or more buses 157 may be address, data, or control buses, and may include any interconnection mechanism, such as a series of lines on a motherboard or integrated circuit, fiber optics or other optical communication equipment, wireless channels, and the like. For example, the one or more transceivers 160 may be implemented as a remote radio head (RRH) 195 or a distributed unit (DU) 195 for gNB implementation for 5G, with the other elements of the RAN node 170 possibly being physically in a different location from the RRH / DU 195, and the one or more buses 157 could be implemented in part as, for example, fiber optic cable or other suitable network connection to connect the other elements (e.g., a central unit (CU), gNB-CU 196) of the RAN node 170 to the RRH / DU 195. Reference 198 also indicates those suitable network link(s).

[0093] A RAN node / gNB can comprise one or more TRPs to which the methods described herein may be applied. FIG. 3 shows that the RAN node 170 comprises TRP 51 and TRP 52, in addition to the TRP represented by transceiver 160. Similar to transceiver 160, TRP 51 and TRP 52 may each include a transmitter and a receiver. The RAN node 170 may host or comprise other TRPs not shown in FIG. 3.

[0094] A relay node in NR is called an integrated access and backhaul node. A mobile termination part of the 1AB node facilitates the backhaul (parent link) connection. In other words, the mobile termination part comprises the functionality which carries UE functionalities. The distributed unit part of the IAB node facilitates the so called access link (child link) connections (i.e. for access link UEs, and backhaul for other IAB nodes, in the case of multi-hop IAB). In other words, the distributed unit part is responsible for certain base station functionalities. The IAB scenario may follow the so called split architecture, where the central unit hosts the higher layer protocols to the UE and terminates the control plane and user plane interfaces to the 5G core network.

[0095] It is noted that the description herein indicates that “cells” perform functions, but it should be clear that equipment which forms the cell may perform the functions. The cell makes up part of a base station. That is, there can be multiple cells per base station. For example, there could be three cells for a single carrier frequency and associated bandwidth, each cell covering one-third of a 360 degree area so that the single base station’s coverage area covers an approximate oval or circle. Furthermore, each cell can correspond to a single carrier and a base station may use multiple carriers. So if there are three 120 degree cells per carrier and two carriers, then the base station has a total of 6 cells.

[0096] The wireless network 100 may include a network element or elements 190 that may include core network functionality, and which provides connectivity via a link or links 181 with a further network, such as a telephone network and / or a data communications network (e.g., the Internet). Such core network functionality for 5G may include location management functions (LMF(s)) and / or access and mobility management function(s) (AMF(S)) and / or user plane functions (UPF(s)) and / or session management function(s) (SMF(s)) and / or network data analytics functions (NWDAF(s)) and / or MME (mobility management entity ) / SGW (serving gateway) functionality. Such core network functionality may include SON (self-organizing / optimizing network) functionality. These are merely example functions that may be supported by the network element(s) 190, and note that both 5G and 6G functions might be supported. The RAN node 170 is coupled via a link 131 to the network element 190. The link 131 may be implemented as, e.g., an NG interface for 5G, or other suitable interface for other standards. The network element 190 includes one or more processors 175, one or more memories 171, and one or more network interfaces (N / W I / F(s)) 180, interconnected through one or more buses 185. The one or more memories 171 include computer program code 173. Computer program code 173 may include SON and / or MRO functionality 172.

[0097] The wireless network 100 may implement network virtualization, which is the process of combining hardware and software network resources and network functionality into a single, software-based administrative entity, or a virtual network. Network virtualization involves platform virtualization, often combined with resource virtualization. Network virtualization is categorized as either external, combining many networks, or parts of networks, into a virtual unit, or internal, providing network-like functionality to software containers on a single system. Note that the virtualized entities that result from the network virtualization are still implemented, at some level, using hardware such as processors 152 or 175 and memories 155 and 171, and also such virtualized entities create technical effects.

[0098] The computer readable memories 125, 155, and 171 may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, non-transitory memory, transitory memory, fixed memory and removable memory. The computer readable memories 125, 155, and 171 may be means for performing storage functions. The processors 120, 152, and 175 may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on a multi-core processor architecture, as nonlimiting examples. The processors 120, 152, and 175 may be means for performing functions, such as controlling the UE 110, RAN node 170, network element(s) 190, and other functions as described herein.

[0099] In general, the various example embodiments of the user equipment 110 can include, but are not limited to, cellular telephones such as smart phones, tablets, personal digital assistants (PDAs) having wireless communication capabilities, portable computers having wireless communication capabilities, image capture devices such as digital cameras having wireless communication capabilities, gaming devices having wireless communication capabilities, music storage and playback devices having wireless communication capabilities, internet appliances including those permitting wireless internet access and browsing, tablets with wireless communication capabilities, head mounted displays such as those that implement virtual / augmented / mixed reality, as well as portable units or terminals that incorporate combinations of such functions. The UE 110 can also be a vehicle such as a car, or a UE mounted in a vehicle, a UAV such as e.g. a drone, or a UE mounted in a UAV. The user equipment 110 may be terminal device, such as mobile phone, mobile device, sensor device etc., the terminal device being a device used by the user or not used by the user.

[0100] UE 110, RAN node 170, and / or network element(s) 190, (and associated memories, computer program code and modules) may be configured to implement (e.g. in part) the methods described herein. Thus, computer program code 123, module 140-1, module 140-2, and other elements / features shown in FIG. 3 of UE 110 may implement user equipment related aspects of the examples described herein. Similarly, computer program code 153, module 150-1, module 150-2, and other elements / features shown in FIG. 3 of RAN node 170 may implement gNB / TRP related aspects of the examples described herein. Computer program code 173 and other elements / features shown in FIG. 3 of network element(s) 190 may be configured to implement network element related aspects of the examples described herein.

[0101] FIG. 4 shows a schematic representation of non-volatile memory media 400a (e.g. computer / compact disc (CD) or digital versatile disc (DVD)) and 400b (e.g. universal serial bus (USB) memory stick) and 400c (e.g. cloud storage for downloading instructions and / or 18 parameters 402 or receiving emailed instructions and / or parameters 402) storing instructions and / or parameters 402 which when executed by a processor allows the processor to perform one or more of the steps of the methods described herein. Instructions and / or parameters 402 may represent a non-transitory computer readable medium.

[0102] FIG. 5 is an example method 500, based on the example embodiments described herein. At 510, the method includes receiving, from a network function consumer, a request for analytics related to at least one extended reality feature. At 520, the method includes determining the analytics related to the at least one extended reality feature. At 530, the method includes transmitting, to the network function consumer, the analytics related to the at least one extended reality feature. At 540, the method includes wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated. Method 500 may be performed with NWDAF 230.

[0103] FIG. 6 is an example method 600, based on the example embodiments described herein. At 610, the method includes transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature. At 620, the method includes receiving, from the network data analytics function, the analytics related to the at least one extended reality feature. At 630, the method includes wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated. Method 600 may be performed with NF (consumer) 210.

[0104] FIG. 7 is an example method 700, based on the example embodiments described herein. At 710, the method includes receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated. At 720, the method includes transmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated. At 730, the method includes wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature. Method 700 may be performed with NEF 240 or 19 AF 250.

[0105] FIG. 8 is an example method 800, based on the example embodiments described herein. At 810, the method includes receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated. At 820, the method includes transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated. At 830, the method includes wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature. Method 800 may be performed with PCF 220 or SMF 42.

[0106] FIG. 9 is an example method 900, based on the example embodiments described herein. At 910, the method includes implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated. At 920, the method includes implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated. At 930, the method includes transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated. At 940, the method includes transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated. Method 900 may be performed with UE 110.

[0107] The following examples are provided and described herein.

[0108] Example 1. An apparatus including: means for receiving, from a network function consumer, a request for analytics related to at least one extended reality feature; means for determining the analytics related to the at least one extended reality feature; and means for transmitting, to the network function consumer, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0109] Example 2. The apparatus of example 1, further including: means for determining the analytics related to the at least one extended reality feature by comparing the analytics determined when the at least one extended reality feature is activated, and the analytics determined when the at least one extended reality feature is deactivated.

[0110] Example 3. The apparatus of any of examples 1 to 2, further including: means for determining the analytics related to the at least one extended reality feature by comparing the analytics determined when the at least one extended reality feature is activated during a time period, and the analytics determined when the at least one extended reality feature is deactivated during the time period.

[0111] Example 4. The apparatus of any of examples 1 to 3, wherein the at least one extended reality feature is related to one or more of: protocol data unit set handling, or low latency, low loss and scalable throughput, or congestion information exposed towards an application function via an exposure interface, or multi-modal services, or user equipment power savings management, or policy control based on a round-trip latency requirement, or an application function packet delay requirement.

[0112] Example 5. The apparatus of any of examples 1 to 4, wherein the extended reality feature service experience analytics comprise one or more of: extended reality feature service experience analytics comprising statistics or predictions of quality of experience, or extended reality feature quality of service sustainability analytics that indicate a degree to which a quality of service can be maintained, or extended reality feature congestion analytics that indicate user plane congestion for applications, or an enhancement to existing analytics.

[0113] Example 6. The apparatus of any of examples 1 to 5, further including: means for transmitting, to a policy control function or session management function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated; and means for receiving, from the policy control function or session management function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the analytics related to the at least one extended reality feature are determined based on at least one or more of: the list of user 21 equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated.

[0114] Example 7. The apparatus of any of examples 1 to 6, further including: means for transmitting, to a policy control function or session management function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated for an application identifier; and means for receiving, from the policy control function or session management function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier; wherein the analytics related to the at least one extended reality feature are determined based on at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier.

[0115] Example 8. The apparatus of example 6 or 7, wherein: the request is transmitted to the policy control function using an Npcf service or to the session management function using an Nsmf service; and the one or more lists are received from the policy control function using the Npcf service or from the session management function using the Nsmf service.

[0116] Example 9. The apparatus of example 6 or 7, wherein the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is supplemented with information related to a time when the at least one extended reality feature is activated or deactivated for at least one user equipment.

[0117] Example 10. The apparatus of any of examples 1 to 9, further including: means for transmitting, to a network exposure function or application function, a request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated; and means for receiving, from the network exposure function or application function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the analytics related to the at least one extended reality feature are determined based on the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated.

[0118] Example 11. The apparatus of example 10, wherein: the request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted to the network exposure function using an Nnef service or to the application function using an Naf service; and the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is received from the network exposure function using the Nnef service or from the application function using the Naf service.

[0119] Example 12. The apparatus of any of examples 1 to 11, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises a request for a subscription for the analytics related to the at least one extended reality feature.

[0120] Example 13. The apparatus of any of examples 1 to 12, wherein the analytics related to the at least one extended reality feature are determined based on at least one target user equipment.

[0121] Example 14. The apparatus of example 13, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises the at the least one target user equipment.

[0122] Example 15. The apparatus of any of examples 13 to 14, wherein the at least one target user equipment comprises one or more of: at least one specified user equipment, a specified group of user equipments, or any user equipment, or at least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is activated, or at least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is deactivated.

[0123] Example 16. The apparatus of any of examples 1 to 15, wherein the analytics related to the at least one extended reality feature are determined based on an application type or a group of applications.

[0124] Example 17. The apparatus of example 16, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises the application type or the group of applications.

[0125] Example 18. The apparatus of any of examples 16 to 17, wherein the analytics related to the at least one extended reality feature are determined based on the application type or the group of applications per data network name or per single network slice selection assistance information for a given access.

[0126] Example 19. The apparatus of example 18, wherein the given access comprises third generation partnership project (3GPP) access or non-3GPP access.

[0127] Example 20. The apparatus of any of examples 1 to 19, wherein: the request for analytics related to at least one extended reality feature is received from the network function consumer using an Nnwdaf service; and the analytics related to the at least one extended reality feature are transmitted to the network function consumer using the Nnwdaf service.

[0128] Example 21. An apparatus including: means for transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; and means for receiving, from the network data analytics function, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0129] Example 22. The apparatus of example 21, wherein the analytics related to the at least one extended reality feature are based on a comparison of the analytics determined when the at least one extended reality feature is activated, and the analytics determined when the at least one extended reality feature is deactivated.

[0130] Example 23. The apparatus of any of examples 21 to 22, wherein the analytics related to the at least one extended reality feature are based on a comparison of the analytics determined when the at least one extended reality feature is activated during a time period, and the analytics determined when the at least one extended reality feature is deactivated during the time period.

[0131] Example 24. The apparatus of any of examples 21 to 23, wherein the at least one extended reality feature is related to one or more of: protocol data unit set handling, or low latency, low loss and scalable throughput, or congestion information exposed towards an application function via an exposure interface, or multi-modal services, or user equipment power savings management, or policy control based on a round-trip latency requirement, or an application function packet delay requirement.

[0132] Example 25. The apparatus of any of examples 21 to 24, wherein the analytics related to the at least one extended reality feature comprise one or more of: extended reality feature service experience analytics comprising statistics or predictions of quality of experience, or extended reality feature quality of service sustainability analytics that indicate a degree to which a quality of service can be maintained, or extended reality feature congestion analytics that indicate user plane congestion for applications, or an enhancement to existing analytics.

[0133] Example 26. The apparatus of any of examples 21 to 25, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises a request for a subscription for the analytics related to the at least one extended reality feature.

[0134] Example 27. The apparatus of any of examples 21 to 26, wherein the analytics related to the at least one extended reality feature are based on at least one target user equipment.

[0135] Example 28. The apparatus of example 27, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises the at least one target user equipment.

[0136] Example 29. The apparatus of any of examples 27 to 28, wherein the at least one target user equipment comprises one or more of: at least one specified user equipment, a specified group of user equipments, or any user equipment, or at least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is activated, or at least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is deactivated.

[0137] Example 30. The apparatus of any of examples 21 to 29, wherein the analytics related to the at least one extended reality feature are based on an application type or a group of applications.

[0138] Example 31. The apparatus of example 30, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises the application type or the group of applications.

[0139] Example 32. The apparatus of any of examples 30 to 31, wherein the analytics related to the at least one extended reality feature are based on the application type or the group of applications per data network name or per single network slice selection assistance information for a given access.

[0140] Example 33. The apparatus of example 32, wherein the given access comprises third generation partnership project (3GPP) access or non-3GPP access.

[0141] Example 34. The apparatus of any of examples 21 to 33, wherein: the request for analytics related to at least one extended reality feature is transmitted to the network data analytics function using an Nnwdaf service; and the analytics related to the at least one extended reality feature are received from the network data analytics function using the Nnwdaf service.

[0142] Example 35. An apparatus including: means for receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and means for transmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

[0143] Example 36. The apparatus of example 35, further including: means for forwarding, to an application function, the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and means for receiving, from the application function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated.

[0144] Example 37. The apparatus of any of examples 35 to 36, further including: means for receiving, from a network exposure function, the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; wherein the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated is received indirectly from the network data analytics function via the network exposure function; and means for transmitting, to the network exposure function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted indirectly to the network data analytics function via the network exposure function.

[0145] Example 38. The apparatus of any of examples 35 to 37, wherein: the request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated is received from the network data analytics function using an Naf service; and the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted to the network data analytics function using the Naf service.

[0146] Example 39. An apparatus including: means for receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; and means for transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

[0147] Example 40. The apparatus of example 39, further including: means for receiving, from the network data analytics function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated for an application identifier; and means for transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated 27 for an application identifier, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier; wherein the list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier, is configured to be used to generate the analytics related to the at least one extended reality feature.

[0148] Example 41. The apparatus of example 39 or 40, wherein: the request is received from the network data analytics function using an Npcf service or an Nsmf service; and the one or more lists are transmitted to the network data analytics function using an Npcf service or an Nsmf service.

[0149] Example 42. The apparatus of example 39 or 40, wherein the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is supplemented with information related to a time when the at least one extended reality feature is activated or deactivated for at least one user equipment.

[0150] Example 43. An apparatus including: means for implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated; means for implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated; means for transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; and means for transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

[0151] Example 44. The apparatus of example 43, wherein the data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated, and the data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated are configured to be used with the network data analytics function to generate analytics determined when the at least one extended reality feature of the at least one extended reality application is activated, or analytics determined when the at least one extended reality feature of the at least one extended reality application is deactivated.

[0152] Example 45. The apparatus of any of examples 43 to 44, further including: means for transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated during a first time period; and means for transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated during a second time period.

[0153] Example 46. The apparatus of any of examples 43 to 45, further including: maintaining an application identifier associated with the at least one extended reality application; wherein the application identifier associated with the at least one extended reality application is configured to be used with the network data analytics function to generate analytics determined when the at least one extended reality feature of the at least one extended reality application is activated, or analytics determined when the at least one extended reality feature of the at least one extended reality application is deactivated.

[0154] Example 47. The apparatus of any of examples 43 to 46, wherein a user equipment comprises the apparatus.

[0155] Example 48. An apparatus including: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: receive, from a network function consumer, a request for analytics related to at least one extended reality feature; determine the analytics related to the at least one extended reality feature; and transmit, to the network function consumer, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0156] Example 49. An apparatus including: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: transmit, to a network data analytics function, a request for analytics related to at least one extended reality feature; and receive, from the network data analytics function, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined 29 when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0157] Example 50. An apparatus including: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: receive, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and transmit, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

[0158] Example 51. An apparatus including: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: receive, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; and transmit, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

[0159] Example 52. An apparatus including: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: implement at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated; implement the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated; transmit, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; and transmit, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

[0160] Example 53. A method including: receiving, from a network function consumer, a request for analytics related to at least one extended reality feature; determining the analytics related to the at least one extended reality feature; and transmitting, to the network function consumer, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0161] Example 54. A method including: transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; and receiving, from the network data analytics function, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0162] Example 55. A method including: receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and transmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

[0163] Example 56. A method including: receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; and transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature

[0164] Example 57. A method including: implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated; implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated; transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; and transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

[0165] Example 58. A computer readable medium including instructions stored thereon for performing at least the following: receiving, from a network function consumer, a request for analytics related to at least one extended reality feature; determining the analytics related to the at least one extended reality feature; and transmitting, to the network function consumer, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0166] Example 59. A computer readable medium including instructions stored thereon for performing at least the following: transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; and receiving, from the network data analytics function, the analytics related to the at least one extended reality feature; wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

[0167] Example 60. A computer readable medium including instructions stored thereon for performing at least the following: receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; and transmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated; wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

[0168] Example 61. A computer readable medium including instructions stored thereon for performing at least the following: receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; and transmitting, to the network data analytics function, at least one or more of a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated; wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

[0169] Example 62. A computer readable medium including instructions stored thereon for performing at least the following: at least one processor; and implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated; implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated; transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; and transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

[0170] References to a ‘computer’, ‘processor’, etc. should be understood to encompass not only computers having different architectures such as single / multi-processor architectures and sequential or parallel architectures but also specialized circuits such as field-programmable gate arrays (FPGAs), application specific circuits (ASICs), signal processing devices and other processing circuitry. References to computer program, instructions, code etc. should be understood to encompass software for a programmable processor or firmware such as, for example, the programmable content of a hardware device whether instructions for a processor, or configuration settings for a fixed-function device, gate array or programmable logic device etc.

[0171] The memories as described herein may be implemented using any suitable data storage technology, such as semiconductor based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, non-transitory memory, transitory memory, fixed memory and removable memory. The memories may comprise a 33 database for storing data.

[0172] As used herein, the term ‘circuitry’ may refer to the following: (a) hardware circuit implementations, such as implementations in analog and / or digital circuitry, and (b) combinations of circuits and software (and / or firmware), such as (as applicable): (i) a combination of processor(s) or (ii) portions of processor(s) / software including digital signal processor(s), software, and memories that work together to cause an apparatus to perform various functions, and (c) circuits, such as a microprocessor(s) or a portion of a microprocessors), that require software or firmware for operation, even if the software or firmware is not physically present. As a further example, as used herein, the term ‘circuitry’ would also cover an implementation of merely a processor (or multiple processors) or a portion of a processor and its (or their) accompanying software and / or firmware. The term ‘circuitry’ would also cover, for example and if applicable to the particular element, a baseband integrated circuit or applications processor integrated circuit for a mobile phone or a similar integrated circuit in a server, a cellular network device, or another network device.

[0173] It should be understood that the foregoing description is only illustrative. Various alternatives and modifications may be devised by those skilled in the art. For example, features recited in the various dependent claims could be combined with each other in any suitable combination(s). In addition, features from different example embodiments described above could be selectively combined into a new example embodiment. Accordingly, this description is intended to embrace all such alternatives, modifications and variances which fall within the scope of the appended claims.

[0174] The following acronyms and abbreviations that may be found in the specification and / or the drawing figures are given as follows (the abbreviations and acronyms may be appended / combined with each other or with other characters using e.g. a dash, hyphen, slash, letter, or number, and may be case insensitive): 3 GPP third generation partnership project 5G fifth generation 5GC 5G core network 5GS 5G System 6G sixth generation ADRF analytics and data repository function AF AI AMF AnLF application function artificial intelligence access and mobility management function analytics logical function application-specific integrated circuit ASP application service provider CD compact / computer disc CPU central processing unit CU central unit or centralized unit 10 DCCF data collection coordination function DL downlink DNN data network name DRX discontinuous reception DSP digital signal processor 15 DU distributed unit DVD digital versatile disc ECN explicit congestion notification eMBB enhanced mobile broadband eNA_Ph4 enablers for network analytics phase 4 20 EN-DC E-UTRAN new radio - dual connectivity en-gNB node providing NR user plane and control plane protocol terminations towards the UE, and acting as a secondary node in EN- DC EoDB end of data burst 25 E-UTRA evolved UMTS terrestrial radio access E-UTRAN E-UTRA network Fl interface between the CU and the DU FPGA field-programmable gate array GBR guaranteed bit rate 30 gNB base station for 5G / NR, i.e., a node providing NR user plane and control plane protocol terminations towards the UE, and connected via the NG interface to the 5GC GPRS general packet radio services GTP GPRS tunnelling protocol GTP-U GTP user data tunnelling HW hardware KPI key performance indicator IAB integrated access and backhaul ID identifier IETF Internet Engineering Task Force I / F interface I / O input / output IP internet protocol L4S low latency, low loss and scalable throughput LMF location management function MAC medium access control MFAF messaging framework adapter function ML machine learning MME mobility management entity MoS mean opinion score MNO mobile network operator MRO mobility robustness optimization MTLF model training logical function N6 interface providing connectivity between the user plane function (UPF) and any other external (or internal) networks or service platforms Naf service based interface for an AF NCE network control element NEF network exposure function NF network function ng or NG ng-eNB NG-RAN new generation new generation eNB new generation radio access network Nnef service based interface for an NEF Nnf interface defined for the NWDAF to request subscription to data delivery for a particular context, to cancel subscription to data delivery and to request a specific report of data for a particular context Nnwdaf Npcf NR service based interface exhibited by the NWDAF service based interface exhibited by PCF new radio Nsmf service based interface exhibited by SMF 5 N / W network NWDAF network data analytics function OAM, OA&M operations, administration and maintenance PCC policy and charging control PCF policy control function 10 PDA personal digital assistant PDB packet delay budget PDCP packet data convergence protocol PDU protocol data unit PHY physical layer 15 PSA PDU session anchor PSDB PDU set delay budget PSER PDU set error rate PSIHI PDU set integrated handling indicator QoE quality of experience 20 QoS quality of service RAM random access memory RAN radio access network Rei release RFC request for comments 25 RLC radio link control ROM read-only memory RRC radio resource control RU radio unit RT round trip 30 Rx receive, or receiver, or reception SA system aspects (for example SA2) SDAP service data adaptation protocol SGW serving gateway SMF session management function S-NSSAI single - network slice selection assistance information SON self-organizing / optimizing network TRP transmission and reception point TS technical specification 5 Tx transmit, or transmitter, or transmission UAV unmanned aerial vehicle UE user equipment (e.g., a wireless, typically mobile device) UI user interface UE uplink 10 UMTS Universal Mobile Telecommunications System UP user plane UPF user plane function URLLC ultra reliable and low latency communications USB universal serial bus 15 UTRAN UMTS terrestrial radio access network Xn network interface between NG-RAN nodes XR extended reality XRM extended reality and media services

Claims

What is claimed is:

1. An apparatus comprising:means for receiving, from a network function consumer, a request for analytics related to at least one extended reality feature;means for determining the analytics related to the at least one extended reality feature; andmeans for transmitting, to the network function consumer, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

2. The apparatus of claim 1, further comprising:means for determining the analytics related to the at least one extended reality feature by comparing the analytics determined when the at least one extended reality feature is activated, and the analytics determined when the at least one extended reality feature is deactivated.

3. The apparatus of any of claims 1 to 2, further comprising:means for determining the analytics related to the at least one extended reality feature by comparing the analytics determined when the at least one extended reality feature is activated during a time period, and the analytics determined when the at least one extended reality feature is deactivated during the time period.

4. The apparatus of any of claims 1 to 3, wherein the at least one extended reality feature is related to one or more of:protocol data unit set handling, orlow latency, low loss and scalable throughput, orcongestion information exposed towards an application function via an exposure interface, ormulti-modal services, oruser equipment power savings management, orpolicy control based on a round-trip latency requirement, oran application function packet delay requirement.

5. The apparatus of any of claims 1 to 4, wherein the extended reality feature service experience analytics comprise one or more of:extended reality feature service experience analytics comprising statistics or predictions of quality of experience, orextended reality feature quality of service sustainability analytics that indicate a degree to which a quality of service can be maintained, orextended reality feature congestion analytics that indicate user plane congestion for applications, oran enhancement to existing analytics.

6. The apparatus of any of claims 1 to 5, further comprising:means for transmitting, to a policy control function or session management function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated; andmeans for receiving, from the policy control function or session management function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers forwhich the at least one extended reality feature is deactivated;wherein the analytics related to the at least one extended reality feature are determined based on at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated.

7. The apparatus of any of claims 1 to 6, further comprising:means for transmitting, to a policy control function or session management function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated for an application identifier; andmeans for receiving, from the policy control function or session management function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier;wherein the analytics related to the at least one extended reality feature are determined based on at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier.

8. The apparatus of claim 6 or 7, wherein:the request is transmitted to the policy control function using an Npcf service or to the session management function using an Nsmf service; andthe one or more lists are received from the policy control function using the Npcf service or from the session management function using the Nsmf service.

9. The apparatus of claim 6 or 7, wherein the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, issupplemented with information related to a time when the at least one extended reality feature is activated or deactivated for at least one user equipment.

10. The apparatus of any of claims 1 to 9, further comprising:means for transmitting, to a network exposure function or application function, a request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated; andmeans for receiving, from the network exposure function or application function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the analytics related to the at least one extended reality feature are determined based on the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated.

11. The apparatus of claim 10, wherein:the request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted to the network exposure function using an Nnef service or to the application function using an Naf service; andthe data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is received from the network exposure function using the Nnef service or from the application function using the Naf service.

12. The apparatus of any of claims 1 to 11, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises a request for a subscription for the analytics related to the at least one extended reality feature.

13. The apparatus of any of claims 1 to 12, wherein the analytics related to the at least one extended reality feature are determined based on at least one target user equipment.

14. The apparatus of claim 13, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises the at the least one target user equipment.

15. The apparatus of any of claims 13 to 14, wherein the at least one target user equipment comprises one or more of:at least one specified user equipment, a specified group of user equipments, or any user equipment, orat least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is activated, orat least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is deactivated.

16. The apparatus of any of claims 1 to 15, wherein the analytics related to the at least one extended reality feature are determined based on an application type or a group of applications.

17. The apparatus of claim 16, wherein the request for analytics related to the at least one extended reality feature received from the network function consumer comprises the application type or the group of applications.

18. The apparatus of any of claims 16 to 17, wherein the analytics related to the at least one extended reality feature are determined based on the application type or the group of applications per data network name or per single network slice selection assistance information for a given access.

19. The apparatus of claim 18, wherein the given access comprises third generation partnership project (3GPP) access or non-3GPP access.

20. The apparatus of any of claims 1 to 19, wherein:the request for analytics related to at least one extended reality feature is received from the network function consumer using an Nnwdaf service; andthe analytics related to the at least one extended reality feature are transmitted to the network function consumer using the Nnwdaf service.

21. An apparatus comprising:means for transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; andmeans for receiving, from the network data analytics function, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

22. The apparatus of claim 21, wherein the analytics related to the at least one extended reality feature are based on a comparison of the analytics determined when the at least one extended reality feature is activated, and the analytics determined when the at least one extended reality feature is deactivated.

23. The apparatus of any of claims 21 to 22, wherein the analytics related to the at least one extended reality feature are based on a comparison of the analytics determined when the at least one extended reality feature is activated during a time period, and the analytics determined when the at least one extended reality feature is deactivated during the time period.

24. The apparatus of any of claims 21 to 23, wherein the at least one extended reality feature is related to one or more of:protocol data unit set handling, orlow latency, low loss and scalable throughput, orcongestion information exposed towards an application function via an exposure interface, ormulti-modal services, oruser equipment power savings management, orpolicy control based on a round-trip latency requirement, oran application function packet delay requirement.

25. The apparatus of any of claims 21 to 24, wherein the analytics related to the at least one extended reality feature comprise one or more of:extended reality feature service experience analytics comprising statistics or predictions of quality of experience, orextended reality feature quality of service sustainability analytics that indicate a degree to which a quality of service can be maintained, orextended reality feature congestion analytics that indicate user plane congestion for applications, oran enhancement to existing analytics.

26. The apparatus of any of claims 21 to 25, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises a request for a subscription for the analytics related to the at least one extended reality feature.

27. The apparatus of any of claims 21 to 26, wherein the analytics related to the at least one extended reality feature are based on at least one target user equipment.

28. The apparatus of claim 27, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises the at least one target user equipment.

29. The apparatus of any of claims 27 to 28, wherein the at least one target user equipment comprises one or more of:at least one specified user equipment, a specified group of user equipments, orany user equipment, orat least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is activated, orat least one specified user equipment, a specified group of user equipments, or any user equipment for which the at least one extended reality feature is deactivated.

30. The apparatus of any of claims 21 to 29, wherein the analytics related to the at least one extended reality feature are based on an application type or a group of applications.

31. The apparatus of claim 30, wherein the request for analytics related to the at least one extended reality feature transmitted to the network data analytics function comprises the application type or the group of applications.

32. The apparatus of any of claims 30 to 31, wherein the analytics related to the at least one extended reality feature are based on the application type or the group of applications per data network name or per single network slice selection assistance information for a given access.

33. The apparatus of claim 32, wherein the given access comprises third generation partnership project (3GPP) access or non-3GPP access.

34. The apparatus of any of claims 21 to 33, wherein:the request for analytics related to at least one extended reality feature is transmitted to the network data analytics function using an Nnwdaf service; andthe analytics related to the at least one extended reality feature are received from the network data analytics function using the Nnwdaf service.

35. An apparatus comprising:means for receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; andmeans for transmitting, to the network data analytics function, the data related 46to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

36. The apparatus of claim 35, further comprising:means for forwarding, to an application function, the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; andmeans for receiving, from the application function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated.

37. The apparatus of any of claims 35 to 36, further comprising:means for receiving, from a network exposure function, the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated;wherein the request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated is received indirectly from the network data analytics function via the network exposure function; andmeans for transmitting, to the network exposure function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted indirectly to the network data analytics function via the network exposure function.

38. The apparatus of any of claims 35 to 37, wherein:the request for data related to at least one user equipment for which the at least one extended reality feature is activated or deactivated is received from the network data analytics function using an Naf service; andthe data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is transmitted to the network data analytics function using the Naf service.

39. An apparatus comprising:means for receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; andmeans for transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated;wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

40. The apparatus of claim 39, further comprising:means for receiving, from the network data analytics function, a request for user equipment identifiers for which the at least one extended reality feature is activated or deactivated for an application identifier; andmeans for transmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier;wherein the list of user equipment identifiers for which the at least one extended reality feature is activated for an application identifier, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated for an application identifier, is configured to be used to generate the analytics related to the at least one extended reality feature.

41. The apparatus of claim 39 or 40, wherein:the request is received from the network data analytics function using an Npcf service or an Nsmf service; andthe one or more lists are transmitted to the network data analytics function using an Npcf service or an Nsmf service.

42. The apparatus of claim 39 or 40, wherein the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is supplemented with information related to a time when the at least one extended reality feature is activated or deactivated for at least one user equipment.

43. An apparatus comprising:means for implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated;means for implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated;means for transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; andmeans for transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

44. The apparatus of claim 43, wherein the data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated, and the data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated are configured to be used with the network data analytics function to generate analytics determined when the at least one extended reality feature of the at least one extended reality application is activated, or analytics determined when the at least one extended reality feature of the at least one extended reality application is deactivated.

45. The apparatus of any of claims 43 to 44, further comprising:means for transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated during a first time period; andmeans for transmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated during a second time period.

46. The apparatus of any of claims 43 to 45, further comprising:maintaining an application identifier associated with the at least one extended reality application;wherein the application identifier associated with the at least one extended reality application is configured to be used with the network data analytics function to generate analytics determined when the at least one extended reality feature of the at least one extended reality application is activated, or analytics determined when the at least one extended reality feature of the at least one extended reality application is deactivated.

47. The apparatus of any of claims 43 to 46, wherein a user equipment comprises the apparatus.

48. An apparatus comprising:at least one processor; andat least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:receive, from a network function consumer, a request for analytics related to at least one extended reality feature;determine the analytics related to the at least one extended reality feature; andtransmit, to the network function consumer, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

49. An apparatus comprising:at least one processor; andat least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:transmit, to a network data analytics function, a request for analytics related to at least one extended reality feature; andreceive, from the network data analytics function, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

50. An apparatus comprising:at least one processor; andat least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:receive, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; andtransmit, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

51. An apparatus comprising:at least one processor; andat least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:receive, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; andtransmit, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated;wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality52feature.

52. An apparatus comprising:at least one processor; andat least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:implement at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated;implement the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated;transmit, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; andtransmit, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

53. A method comprising:receiving, from a network function consumer, a request for analytics related to at least one extended reality feature;determining the analytics related to the at least one extended reality feature; andtransmitting, to the network function consumer, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

54. A method comprising:transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; andreceiving, from the network data analytics function, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

55. A method comprising:receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; andtransmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

56. A method comprising:receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; andtransmitting, to the network data analytics function, at least one or more of: a list of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated;wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

57. A method comprising:implementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated;implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated;transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; andtransmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.

58. A computer readable medium comprising instructions stored thereon for performing at least the following:receiving, from a network function consumer, a request for analytics related to at least one extended reality feature;determining the analytics related to the at least one extended reality feature; andtransmitting, to the network function consumer, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

59. A computer readable medium comprising instructions stored thereon for performing at least the following:transmitting, to a network data analytics function, a request for analytics related to at least one extended reality feature; andreceiving, from the network data analytics function, the analytics related to the at least one extended reality feature;wherein the analytics related to the at least one extended reality feature are based on at least one of: analytics determined when the at least one extended reality feature is activated, or analytics determined when the at least one extended reality feature is deactivated.

60. A computer readable medium comprising instructions stored thereon for performing at least the following:receiving, from a network data analytics function, a request for data related to at least one user equipment for which at least one extended reality feature is activated or deactivated; andtransmitting, to the network data analytics function, the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated;wherein the data related to the at least one user equipment for which the at least one extended reality feature is activated or deactivated is configured to be used to generate analytics related to the at least one extended reality feature.

61. A computer readable medium comprising instructions stored thereon for performing at least the following:receiving, from a network data analytics function, a request for user equipment identifiers for which at least one extended reality feature is activated or deactivated; andtransmitting, to the network data analytics function, at least one or more of: alist of user equipment identifiers for which the at least one extended reality feature is activated, or a list of user equipment identifiers for which the at least one extended reality feature is deactivated;wherein the at least one or more of: the list of user equipment identifiers for which the at least one extended reality feature is activated, or the list of user equipment identifiers for which the at least one extended reality feature is deactivated, is configured to be used to generate analytics related to the at least one extended reality feature.

62. A computer readable medium comprising instructions stored thereon for performing at least the following: at least one processor; andimplementing at least one extended reality application when at least one extended reality feature of the at least one extended reality application is activated;implementing the at least one extended reality application when the at least one extended reality feature of the at least one extended reality application is deactivated;transmitting, to a network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is activated; andtransmitting, to the network data analytics function, data associated with implementing the at least one extended reality application when the at least one extended reality feature is deactivated.Application No: GB2319466.5 Examiner:Contract Unit ExaminerClaims searched: 1-62Date of search: 12 August 2024Patents Act 1977: Search Report under Section 17Documents considered to be relevant:Category Relevant to claims Identity of document and passage or figure of particular relevance X Y Y A A X: 1-5, 9, 12, 15-26, 30-34, 36, 38, 42-49, 52-54, 57-59, 62; Y: 6-8, 10, 11, 13, 14, 27-29, 35, 37, 39-41, 50, 51,55, 56, 60, 61 6-8, 10, H, 13, 14, 27-29, 35, 37, 39-41, 50, 51,55, 56, 60, 61 3 GPP DRAFT, vol 3 GPP SA 2, 2022, VIVIAN CHONG ET AL, "KI#2, New Sol; NWDAF assisted KR service detection" URL: https: / / www.3gpp.org / ftp / tsg sa / WG2 Arch / TSGR2 152E Electronic 2022-08 / Docs / S2-2206408.zip page 1 - page 4 3GPP DRAFT, 2023, "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Architecture enhancements for 5G system (5GS) to support network data analytics services (Release 18)" URL: https: / / ftp.3gpp.org / tsg sa / WG2 Arch / Latest SA2 Specs / DRAFT INT ERIM / Archive / 23288-i40 CRs Implemented Plen Revs rl.zip section 6.4 3GPP STANDARD, 2022, "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Study on XR (Extended Reality) and media services (Release 18)", pages 1-266 URL: https: / / ftp.3gpp.Org / Specs / archive / 23_series / 23.700-60 / 23700-60-iOO.zip page 20 - page 52 3GPP DRAFT, 2023, "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; System architecture for the 5G System (5GS); Stage 2 (Release 18)" URL: https: / / www.3gpp.org / ftp / tsg sa / WG2 Arch / Latest SA2 Specs / DRAFT INTERIM / Archive / 23501 -i40 CRs Implemented Plen Revs.zip section 5.37Categories:___________________________________________________________________________________X Document indicating lack of novelty or inventive A Document indicating technological background and / or state step of the art.Y Document indicating lack of inventive step if combined with one or more other documents of same category. P Document published on or after the declared priority date but before the filing date of this invention. & Member of the same patent family E Patent document published on or after, but with priority date earlier than, the filing date of this application.Field of Search:Search of GB. EP, WO &US patent documents classified in the following areas of the UKCX :Worldwide search of patent documents classified in the following areas of the IPC____________H04L; H04W_____________________________________________The following online and other databases have been used in the preparation of this search reportInternational Classification:Subclass Subgroup Valid From H04W 0024 / 08 01 / 01 / 2009 H04L 0041 / 14 01 / 01 / 2022

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