First network node, method performed by a first network node, second network node, and method performed by a second network node.

Abstract

There is provided a method performed by a first network node for enabling performance analytics of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The method comprises: receiving a requirement for performance analytics for the application session; identifying at least one device to serve as data collection entity for collecting data required for the performance analytics; and sending a data collection requirement to the identified data collection entity, the data collection requirement including a request for performance data related to the at least one tethered connection within the application session. The method further comprises: receiving, from the data collection entity, performance data measured in accordance with the data collection requirement; deriving performance analytics based on the performance data and the data collection requirement; and sending the derived performance analytics.

Description

1 / 72 First network node, method performed by a first network node, second network node, and method performed by a second node. NETWORK Field

[001] The subject matter disclosed here refers, in general, to the field of enabling performance analysis of a tethered connection in a wireless communication network. This document defines a first network node, a method on a first network node, a second network node, a method on a second network node, a third network node, and a method on a third network node. Introduction

[002] In many interactive and immersive applications with challenging latency, rate, and reliability requirements, the application experience is delivered via a tethered connection, where an endpoint Personal IoT Network Element (PINE) device is connected to a gateway device, which in turn is connected to a 3GPP access network (e.g., 4G, 5G, or similar) for internet connectivity. Examples of this application experience delivery include, for example, AR / VR experiences where the PINE is a head-mounted device (HMD) in the form of AR / VR glasses and the gateway is a mobile phone or, alternatively, a 3GPP user equipment (UE). E2E connectivity between a client and an application server therefore relies on at least three heterogeneous network segments: the tethered link, the 3GPP connectivity, and the data network (DN) link. The tethered link and DN are outside the scope of 3GPP.The tethered connection between the PIN and the gateway typically relies on Wi-Fi, Bluetooth, or unlicensed spectrum radio access technologies. This connection affects E2E QoS, and in fact, both tethered and DN links contribute to reducing the effectiveness of the rules. Petition 870260036934, dated 04 / 20 / 2026, page 10 / 169 2 / 72 QoS policies employed in the 3GPP network. SUMMARY

[003] Thus, it would be useful for 3GPP networks to monitor and ingest link metrics relating to the performance of out-of-scope network segments (e.g., tie link, DN link) in a heterogeneous E2E network path. A 3GPP network can also perform analyses of these link metrics and derive statistical characterizations of expected performance. Furthermore, this 3GPP network can adapt 3GPP QoS rules and policies and compensate for the degradation effects of out-of-scope network segments (e.g., additional latency, etc.) and perfectly meet the requirements of E2E applications for an enhanced user experience.

[004] Procedures are disclosed here for enabling performance analysis of a tethered connection in a wireless communication network. These procedures can be implemented by a first network node, a method on a first network node, a second network node, a method on a second network node, a third network node, and a method on a third network node.

[005] Thus, a first network node is provided to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The first network node comprises a processor and processor-coupled memory, the processor being configured to cause the first network node to: receive a requirement for performance analysis for the application session; identify at least one device to serve as a data collection entity to collect data necessary for the performance analysis; and send a data collection requirement to the identified data collection entity, the data collection requirement including a data request. Petition 870260036934, dated 04 / 20 / 2026, page 11 / 169 3 / 72 of performance related to at least one tied connection within the application session. The processor is further configured to make the first network node: receive, from the data collection entity, measured performance data according to the data collection requirement; derive performance analysis based on the performance data and the data collection requirement; and send the derived performance analysis.

[006] A method is further provided, implemented by a first network node, to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The method comprises: receiving a requirement for performance analysis for the application session; identifying at least one device to serve as a data collection entity to collect the data necessary for the performance analysis; and sending a data collection requirement to the identified data collection entity, the data collection requirement including a request for performance data relating to at least one tethered connection within the application session.The method also includes: receiving, from the data collection entity, measured performance data in accordance with the data collection requirement; deriving the performance analysis based on the performance data and the data collection requirement; and sending the derived performance analysis.

[007] A second network node is further provided to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The second network node comprises a processor and processor-coupled memory. The processor is configured to cause the second network node to: receive a data collection request from a first network node; determine Petition 870260036934, dated 04 / 20 / 2026, page 12 / 169 4 / 72 at least one data source based on the data collection requirement; collect performance data from at least one data source, with the collection based on the data collection requirement; send the collected performance data to the first network node.

[008] A method is further provided, implemented by a second network node, to enable performance analysis of a tethered connection wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The method comprises receiving a data collection requirement from a first network node; determining at least one data source based on the data collection requirement; collecting performance data from at least one data source, collecting it based on the data collection requirement; and sending the collected performance data to the first network node.

[009] A third network node is further provided to enable performance analysis of a tied connection within an application session, wherein the application session includes communication via at least one tied connection. The third network node comprises a processor and processor-coupled memory. The processor is configured to cause the third network node to: send a performance analysis request for the application session to a first network node, the performance analysis request including a request for performance data relating to at least one tied connection within the application session; and receive performance analyses from the first network node.

[010] A method implemented by a third network node is also provided to enable performance analysis of a tied connection within an application session, wherein the application session includes communication via at least one tied connection. The method comprises sending an analysis request. Petition 870260036934, dated 04 / 20 / 2026, page 13 / 169 5 / 72 of performance for the application session for a first network node, where the performance analysis requirement includes a request for performance data related to at least one bound connection within the application session; and the receipt of performance analyses from the first network node. BRIEF DESCRIPTION OF THE DRAWINGS

[011] In order to describe the manner in which the advantages and resources of disclosure can be obtained, a description of disclosure is presented by reference to certain apparatus and methods illustrated in the accompanying drawings. Each of these drawings describes only certain aspects of disclosure and, therefore, should not be considered as limiting its scope. The drawings may have been simplified for clarity and are not necessarily drawn to scale.

[012] Methods and devices for enabling performance analysis of a tethered connection in a wireless communication network will now be described, by way of example only, with reference to the attached drawings, in which: Figure 1 describes a wireless communication system to enable performance analysis of a tethered connection in a wireless communication network; Figure 2 depicts a user equipment device that can be used to implement the methods described here; Figure 3 describes in more detail the network node that can be used to implement the methods described here; Figure 4 illustrates an overview of a core network XRM architecture handling data packets; Figure 5 depicts an implementation of an initial tethering approach using tethered autonomous eyeglasses; Figure 6 illustrates an AR glasses implementation where a tethered XR link exposes an XR runtime to the 5G device as an XR runtime API; Figure 7 illustrates an implementation of AR glasses in which Petition 870260036934, dated 04 / 20 / 2026, page 14 / 169 6 / 72 Exposure of the XR runtime via the tether link as a source and receiver of medium buffering is supported by a virtualized edge network XR runtime instance; Figure 8 illustrates an E2E path and subsequent path delays; Figure 9 illustrates an example of a wireless communication system; Figure 10 illustrates a generic DCAF architecture represented in a simplified format; Figure 11 describes an application data analytics enablement architecture in the non-itinerant case; Figure 12 illustrates a generic functional model for ADAE by reusing the 3GPP network data analysis model; Figure 13 illustrates an architecture where analysis is required for the ADAE-C interface and the VAL client resides in a different UE that is not networked; Figure 14 illustrates a procedure for analyzing the connectivity performance of a tethered VAL; Figure 15 illustrates a method implemented by a first network node to enable performance analysis of a tethered connection, where an application session comprises an end-to-end communication session; Figure 16 illustrates a method implemented by a second network node to enable performance analysis of a tethered connection where an application session comprises an end-to-end communication session; and Figure 17 illustrates a method implemented by a third network node to enable performance analysis of a tethered connection within an application session. DETAILED DESCRIPTION

[013] As will be appreciated by one skilled in the art, aspects of this disclosure can be incorporated as a system, Petition 870260036934, dated 04 / 20 / 2026, page 15 / 169 7 / 72 device, method or program product. Consequently, arrangements described in this document may be implemented in an entirely hardware form, an entirely software form (including firmware, resident software, microcode, etc.) or a form combining software and hardware aspects.

[014] For example, the disclosed methods and apparatus may be implemented as a hardware circuit comprising customized very large-scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. The disclosed methods and apparatus may also be implemented in programmable hardware devices such as field-programmable gate arrays, programmable array logic, programmable logic devices, or the like. As another example, the disclosed methods and apparatus may include one or more physical or logical blocks of executable code that may, for example, be organized as an object, procedure, or function.

[015] Furthermore, methods and apparatus may take the form of a program product embedded in one or more computer-readable storage devices that store machine-readable code, computer-readable code and / or program code, hereinafter referred to as code. Storage devices may be tangible, non-transient and / or non-transmissionable. Storage devices may not incorporate signals. In certain arrangements, storage devices employ only signals to access the code.

[016] Any combination of one or more computer-readable media may be used. The computer-readable medium may be a computer-readable storage medium. The computer-readable storage medium may be a storage device that stores the code. The device of Petition 870260036934, dated 04 / 20 / 2026, page 16 / 169 8 / 72 storage may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical or semiconductor system, apparatus or device, or any suitable combination thereof.

[017] More specific examples (a non-exhaustive list) of storage devices would include the following: an electrical connection having one or more wires, a portable computer floppy disk, a hard disk drive, random access memory (RAM), read-only memory (ROM), programmable erasable read-only memory (EPROM or Flash memory), a portable compact disc (CD-ROM) read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain, or store, a program for use by or in connection with an instruction-executing system, apparatus, or device.

[018] Reference throughout this descriptive report to an example of a specific method or device, or similar language, means that a specific feature, structure, or characteristic described in connection with that example is included in at least one implementation of the method and device described herein. Thus, reference to features of an example of a specific method or device, or similar language, may, but does not necessarily, refer to the same example, but means one or more, but not all, examples, unless expressly specified otherwise. The terms including, comprising, having, and variations thereof, mean including, but not limited to, unless expressly specified otherwise. An enumerated list of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise. Petition 870260036934, dated 04 / 20 / 2026, p. 17 / 169 9 / 72 form. The terms a, an and the also refer to “one or more”, unless expressly specified otherwise.

[019] As used in this document, a list with an and / or conjunction includes any single item in the list or a combination of items in the list. For example, a list of A, B, and / or C includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B, and C. As used in this document, a list using the terminology one or more of includes any single item in the list or a combination of items in the list. For example, one or more of A, B, and C includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B, and C. As used in this document, a list using the terminology one of includes one, and only one, of any single item in the list. For example, one of A, B, and C includes only A, only B, or only C, and excludes combinations of A, B, and C.As used in this document, a selected member of the group consisting of A, B, and C includes one and only one of A, B, or C and excludes combinations of A, B, and C. As used in this document, a selected member of the group consisting of A, B, and C and combinations thereof includes only A, only B, only C, a combination of A and B, a combination of B and C, a combination of A and C, or a combination of A, B, and C.

[020] Furthermore, the resources, structures, or features described in this document may be combined in any suitable manner. In the following description, various specific details are provided, such as programming examples, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a complete understanding of the disclosure. One skilled in the relevant art will recognize, however, that the disclosed methods and apparatus may be practiced without or Petition 870260036934, dated 04 / 20 / 2026, page 18 / 169 10 / 72 more specific details, or with other methods, components, materials, and so on. In other cases, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.

[021] Aspects of the disclosed method and apparatus are described below with reference to schematic flowchart diagrams and / or schematic block diagrams of methods, apparatus, systems, and program products. It will be understood that each block of the schematic flowchart diagrams and / or schematic block diagrams, and combinations of blocks in the schematic flowchart diagrams and / or schematic block diagrams, can be implemented by code. This code can be supplied to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which are executed by means of the computer processor or other programmable data processing apparatus, create means to implement the functions / acts specified in the schematic flowchart diagrams and / or schematic block diagrams.

[022] The code can also be stored on a storage device that can direct a computer, other programmable data processing device, or other devices to operate in a particular way, so that the instructions stored on the storage device produce a manufactured article including instructions that implement the function / act specified in the schematic flowchart diagrams and / or schematic block diagrams.

[023] The code can also be loaded into a computer, other programmable data processing device, or other devices to cause a series of operational steps to be performed on the computer, other programmable device, or other devices to produce a process implemented by Petition 870260036934, dated 04 / 20 / 2026, page 19 / 169 11 / 72 computer so that the code that is executed on the computer or other programmable device provides processes to implement the functions / actions specified in the schematic flowchart and / or schematic block diagram.

[024] The schematic flowchart diagrams and / or schematic block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of devices, systems, methods, and program products. In this respect, each block in the schematic flowchart diagrams and / or schematic block diagrams may represent a module, segment, or portion of code, which includes one or more executable instructions of the code to implement the specified logical function(s).

[025] It should also be noted that, in some alternative implementations, the functions indicated in the block may occur out of the order shown in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order, depending on the functionality involved. Other steps and methods may be devised that are equivalent in function, logic, or effect to one or more blocks, or parts thereof, of the illustrated Figures.

[026] The description of the elements in each figure may refer to elements in the preceding figures. Similar numbers refer to similar elements in all figures.

[027] Figure 1 illustrates one embodiment of a wireless communication system 100 to allow performance analysis of a tethered connection in a wireless communication network. In one embodiment, the wireless communication system 100 includes 102 remote units and 104 network units. Although a specific number of 102 remote units and 104 network units is represented in Figure 1, a technician in the field will recognize that any number of 102 remote units and 104 network units can be represented. Petition 870260036934, dated 04 / 20 / 2026, page 20 / 169 12 / 72 included in the 100 wireless communication system. The wireless communication system may comprise a wireless communication network and at least one wireless communication device. The wireless communication device is typically a 3GPP User Equipment (UE). The wireless communication network may comprise at least one network node. The network node may be a network unit.

[028] In one embodiment, remote units 102 may include computing devices such as desktop computers, laptop computers, personal digital assistants (PDAs), tablet computers, smartphones, smart televisions (e.g., Internet-connected televisions), set-top boxes, game consoles, security systems (including security cameras), vehicle onboard computers, network devices (e.g., routers, switches, modems), aerial vehicles, drones, or the like. In some embodiments, remote units 102 include wearable devices such as smartwatches, fitness trackers, head-mounted optical displays, or the like. Furthermore, remote units 102 may be referred to as subscriber units, mobiles, mobile stations, users, terminals, mobile terminals, fixed terminals, subscriber stations, UE, user terminals, a device, or by other terminology used in the art.Remote units 102 can communicate directly with one or more network units 104 via UL communication signals. In certain embodiments, remote units 102 can communicate directly with other remote units 102 via side-link communication.

[029] 104 network units can be distributed in a geographic region. In certain embodiments, a 104 network unit may also be referred to as an access point, an access terminal, a base, a base station, a Node-B, an eNB, a gNB, a Home Node-B, a relay node, a device, Petition 870260036934, dated 04 / 20 / 2026, p. 21 / 169 13 / 72 a core network, an air server, a radio access node, an AP, NR, a network entity, an Access and Mobility Management Function (AMF), a Unified Data Management Function (UDM), a Unified Data Repository (UDR), a UDM / UDR, a Policy Control Function (PCF), a Radio Access Network (RAN), a Network Slice Selection Function (NSSF), an operation, administration and management (OAM), a session management function (SMF), a user plane function (UPF), an application function, an authentication server function (AUSF), security anchor functionality (SEAF), a non-trusted 3GPP gateway function (TNGF), an application function, a service enabler architecture layer function (SEAL), a vertical application enabler server, an edge enabler server, an edge configuration server, a mobile edge computing platform function,A mobile edge computing application, an application data analytics enabler server, a SEAL data delivery server, a middleware entity, a network slice capacity management server, or by any other terminology used in the art. Network units 104 are generally part of a radio access network that includes one or more controllers communicatively coupled to one or more corresponding network units 104. The radio access network is generally communicatively coupled to one or more core networks, which may be coupled to other networks such as the Internet and public switched telephone networks, among other networks. These and other elements of radio access and core networks are not illustrated, but are generally well known to those skilled in the art.

[030] In one implementation, the wireless communication system 100 is compatible with the New Radio (NR) protocols standardized in 3GPP, where the network unit 104 transmits Petition 870260036934, dated 04 / 20 / 2026, page 22 / 169 14 / 72 using an Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme on the downlink (DL), and the remote units 102 transmit on the uplink (UL) using a Single Carrier Frequency Division Multiple Access (SC-FDMA) scheme or an OFDM scheme. More generally, however, the wireless communication system 100 may implement some other open or proprietary communication protocol, for example, WiMAX, IEEE 802.11 variants, GSM, GPRS, UMTS, LTE variants, CDMA2000, Bluetooth®, ZigBee, Sigfox, LoraWAN, among other protocols. This disclosure is not intended to be limited to the implementation of any specific wireless communication system architecture or protocol.

[031] Network units 104 can serve a number of remote units 102 within a service area, for example, a cell or a cell sector, by means of a wireless communication link. Network units 104 transmit DL communication signals to serve remote units 102 in the time, frequency and / or spatial domain.

[032] Figure 2 depicts a User Equipment Appliance 200 that can be used to implement the methods described in this document. The User Equipment Appliance 200 is used to implement one or more of the solutions described in this document. The User Equipment Appliance 200 conforms to one or more of the User Equipment Appliances described in this document. In particular, the User Equipment Appliance 200 may comprise a Remote Unit 102, a UE 435, 904, a 5G Device 530, 630, 730, or a VAL UE 1110, 1310, as described herein. The User Equipment Appliance 200 may comprise a second network node, as described herein. The User Equipment Appliance 200 may include an Application Data Analysis Enablement Client (ADAEC) 1114, 1314, 1414, as described herein. User equipment 200 includes a processor 205, a memory 210, an input device 215, Petition 870260036934, dated 04 / 20 / 2026, page 23 / 169 15 / 72 a 220 output device and a 225 transceiver.

[033] Input device 215 and output device 220 may be combined into a single device, such as a touch screen. In some implementations, the user equipment device 200 does not include any input device 215 and / or output device 220. The user equipment device 200 may include one or more of: the processor 205, the memory 210 and the transceiver 225, and may not include the input device 215 and / or the output device 220.

[034] As represented, the 225 transceiver includes at least one 230 transmitter and at least one 235 receiver. The 225 transceiver can communicate with one or more cells (or wireless coverage areas) supported by one or more base units. The 225 transceiver can be operable in unlicensed spectrum. In addition, the 225 transceiver can include multiple UE panels supporting one or more beams. Furthermore, the 225 transceiver can support at least one 240 network interface and / or 245 application interface. The 245 application interface(s) can support one or more APIs. The 240 network interface(s) can support 3GPP reference points such as Uu, N1, PC5, etc. Other 240 network interfaces may be supported, as understood by a person skilled in the art.

[035] Processor 205 may include any known controller capable of executing computer-readable instructions and / or capable of performing logical operations. For example, processor 205 may be a microcontroller, a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processing unit, a field-programmable gate array (FPGA), or a similar programmable controller. Processor 205 may execute instructions stored in memory 210 to perform the methods and routines described in this document. Petition 870260036934, dated 04 / 20 / 2026, page 24 / 169 16 / 72 Processor 205 is communicatively coupled to memory 210, input device 215, output device 220, and transceiver 225.

[036] Processor 205 can control user equipment device 200 to implement the user equipment device behaviors described in this document. Processor 205 may include an application processor (also known as a “main processor”) that manages application domain and operating system (“OS”) functions and a baseband processor (also known as a “baseband radio processor”) that manages radio functions.

[037] Memory 210 may be a computer-readable storage medium. Memory 210 may include volatile storage media. For example, memory 210 may include RAM, including dynamic RAM (“DRAM”), synchronous dynamic RAM (“SDRAM”), and / or static RAM (“SRAM”). Memory 210 may include non-volatile storage media. For example, memory 210 may include a hard disk drive, flash memory, or any other suitable non-volatile computer storage device. Memory 210 may include both volatile and non-volatile computer storage media.

[038] Memory 210 can store data related to implementing a traffic category field as described in this document. Memory 210 can also store program code and related data, such as an operating system or other controller algorithms operating on device 200.

[039] Input device 215 may include any known computer input device, including a touch panel, a button, a keyboard, a pen, a microphone, or the like. Input device 215 may be integrated into output device 220, for example, as a touch screen or similar touch-sensitive display. Input device 215 may include a touch-sensitive display. Petition 870260036934, dated 04 / 20 / 2026, page 25 / 169 17 / 72 touch so that text can be entered using a virtual keyboard displayed on the touch screen and / or by handwriting on the touch screen. Input device 215 may include two or more different devices, such as a keyboard and a touch panel.

[040] Output device 220 may be designed to emit visual, auditory, and / or haptic signals. Output device 220 may include an electronically controllable display or display device capable of emitting visual data to a user. For example, output device 220 may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic LED (OLED) display, a projector, or a similar display device capable of emitting images, text, or the like to a user. As another non-limiting example, output device 220 may include a separate wearable display, but communicatively coupled to the rest of the user equipment 200, such as a smartwatch, smart glasses, a heads-up display, or the like.In addition, a 220V output device can be a component of a smartphone, a personal digital assistant, a television, a desktop computer, a notebook computer (laptop), a personal computer, a vehicle dashboard, or similar devices.

[041] Output device 220 may include one or more loudspeakers to produce sound. For example, output device 220 may produce an audible alert or notification (e.g., a beep or buzzer). Output device 220 may include one or more haptic devices to produce vibrations, movement, or other haptic feedback. All or parts of output device 220 may be integrated with input device 215. For example, input device 215 and output device 220 may form a touch screen. Petition 870260036934, dated 04 / 20 / 2026, page 26 / 169 18 / 72 or similar touch-sensitive display. Output device 220 may be located near input device 215.

[042] Transceiver 225 communicates with one or more network functions of a mobile communication network by means of one or more access networks. Transceiver 225 operates under the control of processor 205 to transmit messages, data and other signals and also to receive messages, data and other signals. For example, processor 205 can selectively activate transceiver 225 (or parts thereof) at specific times to send and receive messages.

[043] The transceiver 225 includes at least one transmitter 230 and at least one receiver 235. One or more transmitter(s) 230 may be used to provide uplink communication signals to a base unit of a wireless communication network. Similarly, one or more receiver(s) 235 may be used to receive downlink communication signals from the base unit. Although only one transmitter 230 and one receiver 235 are illustrated, the user equipment apparatus 200 may have any suitable number of transmitters 230 and receivers 235. Furthermore, the transmitter(s) 230 and receiver(s) 235 may be of any suitable type of transmitters and receivers.The 225 transceiver may include a first transmitter / receiver pair used to communicate with a mobile communication network over licensed radio spectrum and a second transmitter / receiver pair used to communicate with a mobile communication network over unlicensed radio spectrum.

[044] The first transmitter / receiver pair can be used to communicate with a mobile communication network over licensed radio spectrum and the second transmitter / receiver pair used to communicate with a mobile communication network over unlicensed radio spectrum can be combined into a single transceiver unit, for example, a single chip performing functions for Petition 870260036934, dated 04 / 20 / 2026, page 27 / 169 19 / 72 Use with licensed and unlicensed radio spectrum. The first transmitter / receiver pair and the second transmitter / receiver pair may share one or more hardware components. For example, certain transceivers 225, transmitters 230 and receivers 235 may be implemented as physically separate components that access a shared hardware and / or software resource, such as, for example, the network interface 240.

[045] One or more transmitters 230 and / or one or more receivers 235 may be implemented and / or integrated into a single hardware component, such as a multitransceiver chip, a system-on-a-chip, an Application-Specific Integrated Circuit (ASIC), or other type of hardware component. One or more transmitters 230 and / or one or more receivers 235 may be implemented and / or integrated into a multichip module. Other components, such as the network interface 240 or other hardware components / circuits, may be integrated into any number of transmitters 230 and / or receivers 235 on a single chip. The transmitters 230 and receivers 235 may be logically configured as a transceiver 225 using one or more common control signals or as modular transmitters 230 and receivers 235 implemented on the same hardware chip or in a multichip module.

[046] Figure 3 describes in more detail the network node 300 that can be used to implement the methods described in this document. The network node 300 can be an implementation of an entity in the wireless communication network, for example, in one or more of the wireless communication networks described in this document. The network node 300 can comprise a network unit 104, a RAN 430, and a 5G core 1120. The network node 300 can comprise a first network node, as described herein. The network node 300 can include an Application Data Analysis Enablement Server (ADAES) 1164, 1264, 1364, and 1464, as described Petition 870260036934, dated 04 / 20 / 2026, page 28 / 169 20 / 72 here. Network node 300 may comprise a third network node, as described here. Network node 300 may include an application layer - Analysis and Data Repository Function (A-ADRF) 1224, as described here. Network node 300 includes a processor 305, a memory 310, an input device 315, an output device 320, and a transceiver 325.

[047] Input device 315 and output device 320 can be combined into a single device, such as a touch screen. In some implementations, network node 300 does not include any input device 315 and / or output device 320. Network node 300 may include one or more of the following: processor 305, memory 310, and transceiver 325, and may not include input device 315 and / or output device 320.

[048] As represented, the transceiver 325 includes at least one transmitter 330 and at least one receiver 335. Here, the transceiver 325 communicates with one or more remote units 200. In addition, the transceiver 325 may support at least one network interface 340 and / or application interface 345. The application interface(s) 345 may support one or more APIs. The network interface(s) 340 may support 3GPP reference points such as Uu, N1, N2, and N3. Other network interfaces 340 may be supported, as understood by those skilled in the art.

[049] Processor 305 may include any known controller capable of performing computer-readable instructions and / or capable of performing logical operations. For example, processor 305 may be a microcontroller, a microprocessor, a CPU, a GPU, an auxiliary processing unit, an FPGA, or a similar programmable controller. Processor 305 may execute instructions stored in memory 310 to perform the methods and routines described in this document. Processor 305 is communicatively coupled to memory 310, to Petition 870260036934, dated 04 / 20 / 2026, page 29 / 169 21 / 72 input device 315, to output device 320 and to transceiver 325.

[050] Memory 310 may be a computer-readable storage medium. Memory 310 may include volatile computer storage media. For example, memory 310 may include RAM, including dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), and / or static RAM (SRAM). Memory 310 may include non-volatile computer storage media. For example, memory 310 may include a hard disk drive, flash memory, or any other suitable non-volatile computer storage device. Memory 310 may include both volatile and non-volatile computer storage media.

[051] Memory 310 can store data related to establishing a multipath unicast link and / or mobile operation. For example, memory 310 can store parameters, configurations, resource assignments, policies, and the like, as described in this document. Memory 310 can also store program code and related data, such as an operating system or other controller algorithms operating on network node 300.

[052] Input device 315 may include any known computer input device, including a touch panel, a button, a keyboard, a pen, a microphone, or the like. Input device 315 may be integrated with output device 320, for example, as a touch screen or similar touch-sensitive display. Input device 315 may include a touch-sensitive display so that text can be entered using a virtual keyboard displayed on the touch-sensitive display and / or by handwriting on the touch-sensitive display. Input device 315 may include two or more different devices, such as a keyboard and a touch panel.

[053] The 320 output device can be designed for Petition 870260036934, dated 04 / 20 / 2026, page 30 / 169 22 / 72 to emit visual, auditory, and / or haptic signals. The output device 320 may include an electronically controllable display or display device capable of emitting visual data to a user. For example, the output device 320 may include, but is not limited to, an LCD display, an LED display, an OLED display, a projector, or a similar display device capable of emitting images, text, or the like to a user. As another non-limiting example, the output device 320 may include a separate wearable display, but communicatively coupled to the rest of the network node 300, such as a smartwatch, smart glasses, a heads-up display, or the like. Furthermore, the output device 320 may be a component of a smartphone, a personal digital assistant, a television, a desktop computer, a notebook computer (laptop), a personal computer, a vehicle dashboard, or the like.

[054] Output device 320 may include one or more loudspeakers to produce sound. For example, output device 320 may produce an audible alert or notification (e.g., a beep or buzzer). Output device 320 may include one or more haptic devices to produce vibrations, movement, or other haptic feedback. All or parts of output device 320 may be integrated into input device 315. For example, input device 315 and output device 320 may form a touch-sensitive screen or similar touch-sensitive display. Output device 320 may be located near input device 315.

[055] Transceiver 325 includes at least one transmitter 330 and at least one receiver 335. The transmitter(s) 330 may be used to communicate with the UE, as described in this document. Similarly, one or more receiver(s) 335 may be used to communicate with network functions in the PLMN and / or RAN, as described in this document. Although only one Petition 870260036934, dated 04 / 20 / 2026, page 31 / 169 23 / 72 transmitter 330 and receiver 335 are illustrated, the network node 300 can have any suitable number of transmitters 330 and receivers 335. Furthermore, the transmitter(s) 330 and receiver(s) 335 can be of any suitable type of transmitters and receivers.

[056] In many interactive and immersive applications with challenging latency, rate, and reliability requirements, the application experience is delivered via a tethered connection, where an endpoint Personal IoT Network Element (PINE) device is connected to a gateway device, which in turn is connected to a 3GPP access network (e.g., 4G, 5G, or similar) for internet connectivity. Examples of this application experience delivery include, for example, AR / VR experiences where the PINE is a head-mounted device (HMD) in the form of AR / VR glasses and the gateway is a mobile phone or, alternatively, a 3GPP user equipment (UE). E2E connectivity between a client and an application server therefore relies on at least three heterogeneous network segments: the tethered link, the 3GPP connectivity, and the data network (DN) link. The tethered link and DN are outside the scope of 3GPP.The tethered connection between the PIN and the gateway typically relies on Wi-Fi, Bluetooth, or unlicensed spectrum radio access technologies. This connection affects E2E QoS, and in fact, both tethered and DN links contribute to reducing the effectiveness of QoS rules and policies employed in the 3GPP network.

[057] Thus, it is extremely important that 3GPP networks monitor and ingest link metrics relating to the performance of out-of-scope network segments (e.g., tie link, DN link) in a heterogeneous E2E network path. A 3GPP network can also perform analyses of these link metrics and derive statistical characterizations of performance. Petition 870260036934, dated 04 / 20 / 2026, page 32 / 169 24 / 72 expected. Furthermore, this 3GPP network can adapt 3GPP QoS rules and policies and compensate for the degradation effects of out-of-scope network segments (e.g., additional latency, etc.) and perfectly meet the requirements of E2E applications for an enhanced user experience.

[058] There is a need for a solution that facilitates efficient monitoring, in the 5G system (including the enabling layer), of the delay components for the end-to-end application service, assuming that the end UE device is decoupled from the running application (which may be deployed on a tethered UE), and how to ensure that the service KPI is met, considering different technologies and connection links used throughout the e2e service (which is not under the control of the 5G system). Each connection link generates a component of the total E2E delay.

[059] The core network handles packets, which can be Protocol Data Units (PDUs) and which can be grouped into sets of PDUs, as shown in Figure 4, which illustrates an overview of a core network (CN) XRM architecture handling data packets. Figure 4 shows a system 400 comprising an Extended Reality Medium Application Function (XRM AF) 410, a Policy and Control Function (PCF) 415, a Session Management Function (SMF) 420, an Access and Mobility Function (AMF) 425, a Radio Access Network (RAN) 430, a User Equipment (UE) 435, a User Plane Function (UPF) 440, and an Application Service Provider 410. The Application Service Provider 410 comprises an Application Function (AF) 412 and an Application Server 414. The UE 435 may comprise a remote unit 102 or a user equipment appliance 200, as described herein.A RAN 430 can comprise a base unit 104 and a network node 300, as described herein. The 400 system operation will now be described in the example of downlink traffic; a process. Petition 870260036934, dated 04 / 20 / 2026, page 33 / 169 25 / 72 similar can operate for uplink traffic.

[060] In 480, AF 412 sets PDU requirements.

[061] In 481, Application Function 412 provides QoS requirements for packets for PCF 415 and information to identify the application (i.e., 5 tuples or application id). QoS requirements can be expressed in terms of delay budget, Packet Delay Budget (PDF) or, alternatively, PDU Set Delay Budget (PSDB), error rate, Packet Error Rate (PER) or, alternatively, PDU Set Error Rate (PSER).

[062] In 482, PCF 415 determines the QoS rules for the application and the specific QoS requirements for the PDU. The QoS rules can use a 5G QoS identifier (5QI) for application traffic. PCF 415 makes this determination by assigning a 5QI to the application PDU traffic. PCF 415 sends the QoS rules to SMF 420 as a 5-tuple PDU QoS Requirement. PCF 415 can include Policy and Charge Control (PCC) rules in the communication with SMF 420 based on the importance of a set of PDUs. The PCC rules can be derived from information received from AF 412 or based on a carrier configuration.

[063] In 483, SMF 420 establishes a QoS flow according to the QoS rules of PCF 415 and configures the UPF to route application packets to a QoS flow. SMF 420 also provides the QoS profile containing the PDU set QoS requirements for RAN 430 via AMF 425. AMF 425 can provide the QoS profile containing the PDU-defined QoS requirements for RAN 430 in an N2 Session Management (SM) container. Additionally, AMF 425 can provide the QoS rules for UE 435 in an N1 SM container.

[064] In 484, UPF 440 determines and routes the application's PDUs (i.e., a 5-tuple) to a corresponding QoS flow, according to the N4 rules received from SMF 420. Petition 870260036934, dated 04 / 20 / 2026, page 34 / 169 26 / 72

[065] In 485, RAN 430 receives QFIs, QoS profiles of QoS flows from SMF 420 via AMF 425 during PDU session establishment / modification, identifies packets belonging to an application's PDU session in a QoS flow, and handles the packets on RBs according to the QoS requirements provided by SMF 420. RAN 430 inspects the GTP-U headers and ensures that PDUs are handled according to the QoS profile determined by the SM container. This may include transmitting some packets on a radio carrier that carries QoS flow 1. This may also include sending other packets on a different radio carrier that carries QoS flow 2.

[066] The general steps described above, relating to QoS flow manipulation, RB flow mapping to QoS and application flow, and PDU session manipulation, are applicable to both UL and DL directions. That is, while the example above refers to downlink (DL) traffic, reciprocal processing is applicable to uplink (UL) traffic, where the packet inspection function of UPF 440 is assumed by UE 435. The low-level signaling mechanism associated with passing information from UE to RAN from UL is in accordance with the specifications and implementations of RAN signaling procedures.

[067] Here, Extended Reality (XR) is used as an umbrella term for different types of realities, of which Virtual Reality, Augmented Reality and Mixed Reality are examples.

[068] Virtual Reality (VR) is a rendered version of a delivered visual and audio scene. The rendering in this case is designed to mimic the visual and auditory sensory stimuli of the real world as naturally as possible for an observer or user as they move within the boundaries defined by the application. Virtual reality generally, but not Petition 870260036934, dated 04 / 20 / 2026, page 35 / 169 27 / 72 necessarily requires the user to wear a head-mounted display (HMD) to completely replace the user's field of vision with a simulated visual component, and to wear headphones to provide the user with accompanying audio. Some form of head and user movement tracking in VR is also generally necessary to allow the simulated visual and audio components to update, ensuring that, from the user's perspective, items and sound sources remain consistent with the user's movements. In some cases, additional means of implementation for interacting with the virtual reality simulation may be provided, but are not strictly necessary.

[069] Augmented reality (AR) is when a user receives additional information or artificially generated items or content superimposed on their current environment. This additional information or content will generally be visual and / or audible, and the observation of the current environment can be direct, without intermediate detection, processing, and rendering, or indirect, where the perception of the environment is relayed through sensors and can be enhanced or processed.

[070] Mixed Reality (MR) is an advanced form of AR in which some virtual elements are inserted into the physical scene in order to give the illusion that these elements are part of the real scene.

[071] XR refers to all combined real and virtual environments and human-machine interactions generated by computer and wearable technology. It includes representative forms such as AR, MR, and VR and the areas interpolated between them. Levels of virtuality range from partially sensory inputs to fully immersive VR. In some circles, a fundamental aspect of XR is considered the extension of human experiences, especially related to the senses of existence (represented by VR) and the acquisition of cognition (represented by VR). Petition 870260036934, dated 04 / 20 / 2026, page 36 / 169 28 / 72 by AR).

[072] In 3GPP version 17, 3GPP Working Group SA4 analyzed the Medium Transport Protocol and the XR traffic model in Technical Report TR 26.926 (v1.1.0) entitled Traffic Models and Quality Assessment Methods for Medium and XR Services in 5G Systems and defined the QoS requirements in terms of delay budget, data rate and error rate needed for a satisfactory application-level experience. This led to 4 additional 5G QoS Identifiers (5QIs) for 5G System XR QoS flows (5GS). These 5QIs are defined in 3GPP TS 23.501 (v17.5.0), Table 5.7.4-1, presented as 5 critical GBR QIs for delay, rated from 87 to 90. The latter are applicable to XR video streams and control metadata necessary to deliver immersive and interactive XR experiences.

[073] XR video traffic consists primarily of multiple high-resolution DL / UL video streams (e.g., typically dual-eye buffered at at least 1080p), frames per second (e.g., more than 60 fps), and high bandwidth (e.g., typically at least 20-30 Mbps), which need to be transmitted over the network with minimal latency (typically limited to 15-20 ms) to maintain a low end-to-end application round-trip interaction latency. These latter requirements are of fundamental importance given the XR application's reliance on cloud / edge processing (e.g., content download, viewport generation and configuration, viewport update, viewport rendering, media encoding / transcoding, etc.).

[074] Tied and Heterogeneous Links can be used for Medium Applications. In Version 17, 3GPP studied support for XR glasses for 5G and later versions, based on a common client architecture, based on three main components: a time Petition 870260036934, dated 04 / 20 / 2026, page 37 / 169 29 / 72 of XR execution, a Scene Manager, and a Medium Access Function (MAF). Of the three components of general relevance to communication aspects, the MAF stands out.

[075] 3GPP Technical Report TR 26.998 (v18.0.0 - Dec. 2022) describes support for 5G Glass-type AR / MR devices and defines the Medium Access Function (MAF) as supporting UE AR to access and transmit the medium. To that end, a MAF includes: • Codecs: used to compress and decompress the media. In many cases, not just a single codec instance is needed per media type, but several. • Content Delivery Protocols: Container format and protocol for delivering content between the UE and the network according to an application's requirements. This includes timing, synchronization, reliability, protocol-level reporting (e.g., RTP reporting), and other features. • 5G Connectivity: a modem and 5G System functionalities that allow the UE to connect to a 5G network and gain access to the features and services offered by the 5G System. • Media Session Handler: A generic function on the device to configure 5G System capabilities and support 5GS integration. This can configure edge functionalities, provide QoS support, support reporting functionalities, etc. • Content protection and decryption: This function handles content protection against playback on unauthorized devices.

[076] Some examples of MAF implementations are: • A 5GMSd client that includes a Medium Session Handler and a Medium Player, as defined in TS 26.501 and TS 26.512. • A 5GMSu client that includes a Medium Session Handler and a Medium Player, as defined in TS 26.501 and TS 26.512. Petition 870260036934, dated 04 / 20 / 2026, page 38 / 169 30 / 72 • A real-time communication client that includes an uplink or downlink, or both, to support more latency-critical communication services, such as for XR applications.

[077] In Version 18, 3GPP is studying in more detail the tethering aspects for XR glasses-type devices, where two different tethering approaches are established as: • Tethered standalone glasses: In this case, the glasses run an XR application that uses the capabilities of the glasses to create a service. The glasses are tethered to a 5G device or similar mobile access technology (e.g., a cell phone) and potentially use the phone's resources (e.g., the Medium Session Handler) to support the application. • Tethered display glasses: In this case, the glasses are tethered to a 5G device or similar mobile access technology (e.g., a mobile phone) that includes the XR application and functions, i.e., at least the MAF and / or a lightweight instance of the scene manager. The 5G device runs the application that uses the capabilities of the 5G device to run an XR experience. The glasses are connected to the 5G device and incorporate at least one lightweight XR runtime, which is exposed to the 5G device via a specific XR runtime API through an XR tethered link or via a wireless link that exposes media buffers.

[078] An implementation describing the first tethering approach as tethered autonomous glasses is shown in Figure 5. An AR glasses device 510 is tethered to a 5G device 530. The AR glasses device 510 comprises an XR runtime 512, an XR runtime API 514, an AR / MR application 516, a wireless connection module 518, and a Medium Access Function 552. A pair of speakers 521, an eye display buffer 522, sensors 523, and at least one Petition 870260036934, dated 04 / 20 / 2026, page 39 / 169 31 / 72 cameras 524 provide input to the XR runtime 512, which comprises visual, tactile, and audio composition. The XR runtime API 514 provides an interface between the XR runtime 512 and each of the uplink media management modules 520 and a presentation engine 526. The presentation engine 526 comprises a visual renderer and an audio renderer and interfaces with a scene manager 527. The media access function 552 comprises metadata codecs, video codecs, and audio codecs, and a MAF API 554. The AR / MR application 516 interfaces with each of the XR runtime APIs 514, the scene manager 527, and the MAF API 554.

[079] A tether connection is provided between the AR glasses device 510 and the 5G device 530 by the respective wireless connectivity modules 518, 538. The MAF 552 passes compressed medium to and from the tether connection via the wireless connectivity module 518. The 5G device 530 likely comprises a smartphone and includes a 5G system module 535. Phone-based processing functions are performed by a processor 531. The phone-based processing functions comprise an API 533 that is capable of passing configuration information to the AR / MR application 516 via the tether connection.

[080] Figure 6 illustrates an implementation of AR glasses in which a tethered XR link exposes an XR runtime to the 5G device as an XR runtime API. An AR glasses device 610 is tethered to a 5G device 630. The augmented reality (AR) glasses device 610 comprises XR runtime core functions 612. A pair of speakers 621, an eye display buffer 622, sensors 623, and at least one camera 624 provide input to the XR runtime core functions 612, which comprise visual, tactile, and audio composition. A Petition 870260036934, dated 04 / 20 / 2026, page 40 / 169 32 / 72 glasses with XR 611 link function operates as an interface between the XR 612 runtime core functions and a 618 wireless connection module of the augmented reality (AR) glasses device 610.

[081] A tether connection is provided between the AR glasses device 610 and the 5G device 630 by the respective wireless connectivity modules 618, 638. The 5G device 630 comprises an XR link function device 613 that provides an interface between the wireless connectivity module 638 and the XR runtime API 614. The 5G device 630 further comprises an augmented reality / MRI application 616 and a medium access function 652. The XR runtime API 614 provides an interface between the XR link function device 613 and each of the uplink medium management modules 620 and a presentation engine 626. The presentation engine 626 comprises a visual renderer and an audio renderer and interfaces with a scene manager 627. The medium access function 652 comprises metadata codecs, video codecs, and audio codecs, and a MAF API 654.The AR / MR application 616 interfaces with each of the XR runtime APIs 614, the scene manager 627, and the MAF API 654. The 5G device 630 likely comprises a smartphone and includes a 5G system module 635. The MAF 652 passes compressed media to and from the 5G system module 635.

[082] Figure 7 illustrates an implementation of AR glasses in which the exposure of the XR runtime via the tethering link as a source and receiver of the medium buffer is supported by a virtualized edge network XR runtime instance. An AR glasses device 710 is tethered to a 5G device 730; the 5G device 730 is connected to an edge network 750 via a 5G connection. The augmented reality (AR) glasses device 710 comprises Petition 870260036934, dated 04 / 20 / 2026, page 41 / 169 33 / 72 core runtime functions of XR 712. A pair of speakers 721, an eye display buffer 722, sensors 723 and at least one camera 724 provide input to the core runtime functions of XR 712. An XR runtime API 714 provides an interface to a basic AR / MR application 716.

[083] A tether connection is provided between the AR glasses device 710 and the 5G device 730 by the respective wireless connectivity modules 718, 738. The main XR runtime functions 712 of the AR glasses device 510 exchange data with the 5G device 730 via the tether connection. The 5G device 730 likely comprises a smartphone and includes a 5G system module 735. The 5G device 730 comprises a Media Access Function 732. The MAF 752 passes compressed media to and from the 5G system module 735.

[084] Edge network 750 comprises medium access functions 754, an XR runtime 756, an XR scene manager 758, and an AR / MR application 760. The AR / MR application 760 interacts with the medium access functions 752 via a MAF API 754 and with the XR scene manager 758 via an XR scene API 759. An XR runtime API 757 provides an interface between the XR runtime 756 and the XR scene manager 758.

[085] All three tethering architectures in Figures 5, 6, and 7 can be supported by edge-split rendering to reduce complexity, processing requirements, power consumption, and heat dissipation in XR glasses. To this end, some key issues identified in the Version 18 3GPP tethering study are related to monitoring and reporting tethering link and DN link latencies and, respectively, to E2E QoS delay budget management. Petition 870260036934, dated 04 / 20 / 2026, page 42 / 169 34 / 72

[086] The latency monitoring and reporting solution presented here is therefore relevant because in an E2E connection including a tethering link (e.g., Wi-Fi link or Bluetooth link), a 5G network, and the Internet, the Wi-Fi segment and the Internet segment typically cannot guarantee latency. Low E2E latency is required by XR applications to provide a good quality of experience (QoE) to the end user. Such QoE can make the experience seem more immersive to the user and also make it more interactive. To achieve the low E2E latency required by XR applications, one approach is to make the latency on the 5G network very conservative, so that the end-to-end latency is below a target value.This, however, comes at a cost, because only a finite amount of bandwidth is available in the wireless communication system, and provisioning unnecessarily low latency in the 5G network requires excessive allocation of radio resources. This excessive allocation of radio resources might support a more robust modulation and coding scheme (MCS), but it would require many other traffic flows to be deprived of bandwidth resources.

[087] Thus, the solution presented here is to dynamically adjust the delay in the 5G network according to the total delay incurred in other parts of the E2E path. This requires a measurement of the non-5G delay in the total E2E connection between the tethered headset and the application server. The delay in a Wi-Fi link can change over time depending on interference generated by other nearby Wi-Fi networks operating in the same frequency band. Similarly, the delay between the UPF and the application server (AS) depends on the location of the selected UPF, the selected edge / AS, and the network congestion level. Therefore, measurements can be used to estimate these time-varying delays in the non-5G segments.

[088] Thus, an efficient implementation is provided for the Petition 870260036934, dated 04 / 20 / 2026, page 43 / 169 35 / 72 determination of delays in non-5G segments of the E2E path between a glasses endpoint and an AS or, alternatively, an edge AS (EAS) for split rendering.

[089] Figure 8 illustrates an E2E path and subsequent path delays. In this example, the E2E path comprises augmented reality glasses 805, a phone 835, a gNB 830, a UPF 840, and an Edge Application Server 814. The delay notation illustrated in Figure 8 is defined as follows. • De2e: denotes the delay of E2E in one direction, i.e., UL or DL. • D$gs: denotes the 5GS delay from the PSA UPF to the UE, which is measurable through core network QoS monitoring procedures described in 3GPP TS 23.501 and RAN Layer 2 measurement procedures described in TS 38.314; this can be measured based on the average performance of DRBs and QoS flows, but also per QoS flow and per DRB per UE. For the latter, the QoS monitoring procedure per QoS flow per UE is applied, leveraging the GTP-U headers to carry the timestamps required for the PSA UPF to NG-RAN measurements, while the delay between NG-RAN and UE is measured on average per DRB per UE in accordance with the RAN Layer 2 procedures in the PDCP layer. • Dn,l: denotes the delay of the tethering link (e.g., Wi-Fi, Bluetooth). • Dn2: denotes the DN link latency (e.g., connection between PSA UPF and AS, or alternatively, EAS). • Dn: denotes the total non-5G / non-3GPP E2E delay accumulated on the tethered link and DN link segments as Dn = Dn,1 + Dn,2.

[090] Therefore, it is useful to determine, in order to allow fine-grained control of QoS rules, that the delay budget and the requirements of an application, i.e., De2e,max, are Petition 870260036934, dated 04 / 20 / 2026, page 44 / 169 36 / 72 attended, that is, De2e = D5GS + Dn <De2e,max.

[091] Delay measurement can be performed segment by segment, where the delays detailed above are determined individually, and due to interest in determining the delays Dn,± and Dn,2.

[092] For delay measurement, the measured delay can be representative of the delay experienced by data packets passing between the augmented reality glasses 805 and the edge application server 814. Delay measurements based on out-of-band delay measurement messages, such as the ping message (ICMP Echo and Echo Reply, according to RFC 792), may be easy to collect, but may not accurately reflect the delay experienced by data packets. The latter is a consequence of two facts: i).The ICMP delay measurement message uses a different protocol number (e.g., 1 for ping) than the protocol number of an XR traffic data packet (e.g., 17 if the data packets are sent with RTP / UDP), and this results in different 5 tuples (src addr, dst addr, src port, dst port, protocol ID) and, consequently, different QoS treatments on 5GS communication links; ii) the packet size of an ICMP delay measurement is usually much smaller than that of a data packet (a few tens of bytes), resulting in different transmission delays.

[093] An alternative approach to delay measurement is represented by bandwidth delay measurements performed on the RTP / UDP stack, WebRTC stack, RTP / QUIC stack, WebRTC / QUIC stack, or similar real-time communication protocols. In some implementations, RTP header extensions are used, such as the WebRTC / RTP abs-sendtime header extension (http: / / www.webrtc.org / experiments / rtp-hdrext / abs-sendtime), and time synchronization with respect to an NTP server to measure the delay at the receiver or, alternatively, at a node. Petition 870260036934, dated 04 / 20 / 2026, p. 45 / 169 37 / 72 of network along a network path, from the absolute time of sending an RTP packet or, alternatively, of RTP packets containing an ADU. In another implementation, leveraging on top of RTCP sender / receiver reports can be used in conjunction with RTP / RTCP multiplexing, as per RFC 5761, for unicast sessions. In this case, the RTP timestamps, along with the RTCP sender / report timestamps and receive times, can be used to calculate an average round-trip time (RTT) and provide an estimate for the latter, for the UL, or alternatively, for the DL direction.

[094] In the case of in-band delay measurement, the measurement structure requires an E2E measurement approach coupled with the 5GS measurement procedure for the determination of De2e, D5GS, and finally, the measurement of interest, i.e., Dn. This is due to the strategy of leveraging RTP traffic originating from the application source.

[095] 3GPP also defined, in standard TS 23.288 v17.2.0, an architecture to support the provision of network analytics. In the architecture, NWDAF provides analytics outputs to one or more Analytics Consumer NFs based on Data Collected from one or more Data Producer NFs. The Analytics Consumer NF can be one or more AF, OAM, and 5G Core NFs (e.g., SMF, AMF, PCF).

[096] Figure 9 illustrates an example of a 900 wireless communication system. The 900 system comprises a UE 904, an NWDAF Analysis Logic Function (ANLF) 910, an NWDAF Model Training Logic Function (MTLF) 912, a plurality of Data Producer Network Functions, in this example an Application Function (AF) 920, a 5G Network Function 922 and an Operations, Administration and Maintenance (OAM) Function 924. The 900 wireless communication system also comprises a plurality of Analysis Consumer Network Functions which, in this example, Petition 870260036934, dated 04 / 20 / 2026, page 46 / 169 38 / 72 include an Application Function 930, a 5G Network Function 932, and an OAM 934. In the current 3GPP architecture, NWDAFs 910, 912 (defined in 3GPP Technical Specification 23.288 v17.2.0) provide analytics output to one or more of the Consumer Analytics NFs 930, 932, and 934 based on data collected from one or more of the Producer Data NFs 920, 922, and 924. The analytics output can be derived by NWDAFs 910 and 912 using Analytics Sharing and / or Federated Learning. UE 904 can be incorporated as a remote unit 102, a user appliance 200, or alternatively, a tethered UE 1110, as described herein. The NWDAF1 910 and NWDAF 2 912 can be incorporated as a network unit 104 and a network node 300, as described herein.

[097] A list of potential Consumer Analysis NFs for each analysis output provided by NWDAF is described in Table 1 below. NWDAF Analytical Output Example of Consumer NF Slice Load Level Analysis PCF, NSSF Observed Service Experience PCF, OAM NF Load Analysis All Core NFs 5G, OAM Network Performance Analysis PCF, NEF, AF or OAM UE Mobility Analysis AMF, SMF UE Communication Analysis AMF, SMF, PCF Expected UE Behavior Analysis AMF, UDM, AF or OAM Abnormal Behavior Analysis AMF, SMF, PCF User Data Congestion Analysis NEF, AF QoS Sustainability Analysis AF Table 1: Example of Consumer Invoices for Analysis

[098] To support XR services and applications, the Petition 870260036934, dated 04 / 20 / 2026, page 47 / 169 39 / 72 The following analyses are relevant to this disclosure. Such analyses may be beneficial to mobile XR users or XR service providers who need to deploy the XR service in a specific area and time (e.g., for an event) and require statistics / forecasts on QoS / network performance and availability. • QoS Sustainability Analysis provides information on QoS change statistics for a target analysis period in the past in a given area, or the probability of a QoS change for a target analysis period in the future in a given area. • Network Performance Analysis: provides statistics or forecasts on gNB status information, gNB resource usage, communication performance, and mobility performance in an area of ​​interest. • User Data Congestion Analysis: Analysis related to User Data Congestion may relate to congestion experienced during the transfer of user data in the control plane or the user plane, or both. • DN Performance Analysis: provides statistics or forecasts on DN performance indicators for a specific edge computing application for a UE, group of UEs in a specific service PSA UPF, DN application identifier, or EAS.

[099] In Version 17, the framework for UE data collection and event exposure reporting (EVEX) was completed. It provides the architecture and protocols to enable UE and AS data collection and event exposure associated with NF consumers through the generic architecture and procedures described by NWDAF.

[100] To this end, the high-level procedures by which data are collected by an NWDAF are explored from Petition 870260036934, dated 04 / 20 / 2026, page 48 / 169 40 / 72 of EU applications via an intermediary AF as a data provider. This is done by a Data Collection AF (DCAF), registered with the NRF and connected as an event provider to the NWDAF. The DCAF relies on three potential Data Collection Clients: • A Direct Data Collection Client that operates directly at the EU endpoint and collects data relevant to the operation and application logic, communicating directly with a DCAF instance; • an Indirect Data Collection Client that operates within an ASP backend with which the UE application instance communicates the collected data; the Indirect Data Collection Client collects the UE application data and relays it to a DCAF instance; and / or • an AS / EAS that communicates with the DCAF as part of an ASP infrastructure, or through NEF interfaces in distributed / separate domain deployments.

[101] DCAF and, subsequently, Data Collection Clients can therefore be provisioned by the Application Service Provider via a provisioning AF with a configuration intended to perform data collection directly from a UE or group of UEs serving the application or, alternatively, from the AS / EAS serving application content to the UE or group of UEs. The configuration further comprises a Data Access Profile provisioned by the application provider. The Data Access Profile contains information about the data parameters to be collected (e.g., an Event ID), filtering metadata to be applied to the collected data (e.g., location filters, time sampling restrictions, UE / application identifier filters, etc.) and reporting procedures. The Data Access Profile can also define the processing to be performed by DCAF on the collected data for Petition 870260036934, dated 04 / 20 / 2026, page 49 / 169 41 / 72 generation and exposure of events to additional NF or, alternatively, AF.

[102] DCAF is therefore connected as an NF data producer, or alternatively, event producer, to an NWDAF instance that is an event consumer. Other event consumers can be attached via the NWDAF service-based architecture. For example, other event consumers can be other NFs, such as PCF, SMF, UPF or similar, or other AFs, such as the application provider AF.

[103] Figure 10 illustrates a generic DCAF architecture represented in simplified form. DCAF registration and NRF provisioning AF connections have been omitted for brevity. A wireless communication device 1035 comprises a Direct Data Collection Client (DDCC) 1036 that reports to a Data Collection Application Function (DCAF) 1022. The DCAF 1022 receives UE reporting data also from an Application Server 1024 and exposes an event to a NWDAF 1032 and to an event-consuming application function 1016 in an ASP 1010. The NWDAF 1032 exposes network data analytics to any network function 1042 that wishes to consume data analytics.Thus, DCAF 1022 collects data through a configured data collection session (i.e., through a Data Access Profile that acquires data via RESTful APIs served by authenticated HTTPS connections) with Direct Data Collection Client 1036 and AS 1024, which may be an Edge AS. The collected data is processed in DCAF 1022 to generate and expose an event that is subsequently consumed by NWDAF 1032 for analysis. NWDAF 1032, in turn, performs analysis of the collected events and sends the results to other NF / AF 1042 consumers.

[104] The Data Access Profile is defined in TS 26.531 v17.0.0 “Data Collection and Reporting; Overview and Architecture”. Several restrictions are available in Petition 870260036934, dated 04 / 20 / 2026, page 50 / 169 42 / 72 dimensions of time, user, and location. • Time-related restrictions: determine the granularity of access to UE data along the time axis. The finest granularity allows access to events as they occur over time (without restrictions). The coarsest level of access aggregates all event data along the time axis to produce a single aggregated value, considering an aggregation window. • User restrictions: allow the provisioning AF to restrict access to event-related UE data based on groups. Finer granularity allows the event consumer to access events related to individual users or, alternatively, UEs. Coarser granularity access exposes event data collected and aggregated based on user groups, as defined by an application (e.g., UEs running a specific application version). The coarsest granularity access exposes the aggregated data to all users. • Location-based restrictions: allow the provisioning AF to restrict access to EU data-related events based on the geographic location of the data collection client during the event. The finest granularity allows the event consumer to access events individually, regardless of location. Coarser-grained access exposes aggregated collected event data based on a geographic area. The coarsest level of access aggregates all event data by location to produce a single aggregated value for all locations.

[105] The basic set of aggregation filters for DCAF is currently defined in 3GPP TS 26.532 v17.1.0 “Data Collection and Reporting. Protocols and Formats”, in particular in Table 4.5.2-1. The basic DCAF aggregation filters based on the reporting period are therefore as follows: • None: no aggregation applied, all records of Petition 870260036934, dated 04 / 20 / 2026, page 51 / 169 43 / 72 reported data points are presented as individual events. • Count: number of reported data records exposed to event consumers • Average: the average of the values ​​in the reported data records exposed to event consumers. • Maximum: The maximum value observed in the reported data records is exposed to event consumers. • Minimum: The minimum value observed in the reported data records is exposed to event consumers. • Sum: The sum of the values ​​in the reported data records is exposed to event consumers.

[106] In 3GPP, a framework for the Service Enablement Application Layer (SEAL) in support of Vertical Application Layers (VAL) has been developed over the last few versions. Thus, this SEAL is organized as a generic SEAL service functional model, instantiated by specific SEAL service functional models, such as: • Location management; • Group management; • Configuration management; • Identity management; • Key management; • Network resource management • Data delivery, and • Application Data Analytics Enablement (ADAE)

[107] The generic functional model for SEAL is organized into generic functional entities based on client-server architecture to describe a functional architecture that addresses the application layer support aspects for vertical applications both on the network (based on Uu connectivity) and off the network (based on PC5 connectivity).

[108] The ADAE layer is a new SEAL service specified in Petition 870260036934, dated 04 / 20 / 2026, page 52 / 169 44 / 72 3GPP TS 23.436 v0.3.0 “Procedures for Application Data Analysis Enablement Service”. Figure 11 is a reproduction of Figure 5.2.2-1 from TS 23.436 and describes the application data analysis enablement architecture 1100 in the non-roaming case, using the reference point representation showing how various entities interact with each other.

[109] The 1100 architecture comprises a UE VAL 1110 that communicates via a 3GPP 1150 network system with a VAL 1162 server and an Application Data Analysis Enablement (ADAES) server 1164. The UE VAL 1110 comprises a VAL 1112 client and an Application Data Analysis Enablement (ADAEC) client 1114. The communication protocols between components of the 1100 architecture are illustrated in the figure. The 1100 architecture can be considered as comprising a VAL side and a SEAL side. The VAL side is illustrated in the upper part of Figure 11, and the SEAL side is illustrated in the lower part of Figure 11.

[110] In operation, the application data analytics enablement client communicates with the application data analytics enablement server via the ADAE-UU reference point. The application data analytics enablement client provides support for application data analytics enablement functions for the VAL client(s) over the ADAE C reference point. The VAL server(s) communicate(s) with the application data analytics enablement server via the ADAE-S reference point. The application data analytics enablement server, acting as AF, can communicate with the 5G Core Network functions (over the N33 reference point for NEF and the N6 reference point for UPF) and OAM (over the ADAE-OAM interface).

[111] In the ADAE framework, A-DCCF and A-ADRF can be defined as functionalities within the ADAE architecture and can offer the following functionalities: Petition 870260036934, dated 04 / 20 / 2026, p. 53 / 169 45 / 72 • Application Layer - The Data Collection and Coordination Function (A-DCCF) coordinates the collection and distribution of data requested by the consumer (ADAE server). Data Collection Coordination is supported by an A-DCCF. The ADAE server can send data requests to the A-DCCF instead of directly to the Data Sources. The A-DCCF can also perform data processing / abstraction and data preparation based on the VPL server requirements. The A-DCCF can be within the ADAE framework or in certain implementations as external data coordination functionality (e.g., SEAL entity, core entity). • Application Layer - The Analysis and Data Repository Function (A-ADRF) stores historical data and / or analyses, i.e., data and / or analyses relating to a previous period obtained by the consumer (e.g., ADAE server). After the consumer obtains the data and / or analyses, it can store them in an A-ADRF. Whether the consumer contacts the A-ADRF directly or through the A-DCCF is based on configuration.

[112] Figure 12 illustrates a generic functional model 1200 for ADAE by reusing the 3GPP network data analysis model. An application layer - Data Analysis and Repository Function (A-ADRF) 1224 stores analyses and collected data in an associated storage component. The architecture 1200 further comprises at least one data source 1230, an application layer - Data Collection and Coordination Function (A-DCCF) 1240, an ADAE server 1264 and an analysis consumer 1262. A data network 1240 (which may be an edge data network) comprises the A-ADRF 1240, at least one data source 1230, the A-DCCF 1240 and the ADAE server 1264.

[113] In this model, A-DCCF 1240 is used to retrieve data from or insert it into an application-level entity (e.g., A-ADRF 1224, Data Source 1230). This A-DCCF 1240 coordinates the Petition 870260036934, dated 04 / 20 / 2026, page 54 / 169 46 / 72 collects and distributes data requested by the ADAE 1264 server (via ADCCF-1, ADAE-X). The ADAE 1264 server can also interact directly with the Data Sources via ADAE-Y.

[114] In addition, the Application Layer - Data Analysis and Repository Function (A-ADRF) 1224 can be used to store historical data and / or analyses, i.e., data and / or analyses relating to past periods obtained by the ADAE server 1264 (via AADRF-1) or other NFs / NWDAF. The ADAE server 1264 can also retrieve historical data from ADRF 1224. The configuration determines whether the ADAE server 1264 contacts ADRF directly or uses A-DCCF 1240.

[115] Data Sources 1230 can be 5GS data sources (5GC, OAM) or enablement layer data sources (SEAL, EEL) or external data sources on the DN side (VAL / EAS server) and VAL UEs. A-DCCF 1240 and A-ADRF 1224 can only be used to interact with certain data sources (e.g., 5GC, OAM) based on the configuration, and can be hidden from the VAL layer.

[116] A mechanism is presented here for analyzing the application layer segment delay within an end-to-end application service segment (e.g., XR service) and, in particular, the link between the Application Client on the Tied Device and the 3GPP UE (in particular, a 5G UE). Based on this analysis, the mechanism includes the derivation of application layer statistics or forecasts for the segment of interest and the optional recommendation of an action for the consumer (e.g., VAL server or VAL client, NF such as NWDAF, DCAF). The steps of this solution are defined in the numbered paragraphs below.

[117] 1. A consumer subscribes to the application service enabler (ADAES or, generally, a SEAL / EES server) for a segment-related monitoring or analytics event. Petition 870260036934, dated 04 / 20 / 2026, page 55 / 169 47 / 72 interest (e.g., Link X: tethered device 5G device).

[118] 2. The application service enabler sends the requirement to the 5G device and, in particular, to a client application on the 5G device (i.e., service enabler client, or ADAEC, or SEAL client) and configures the device to collect or calculate the data and report certain criteria (e.g., providing predefined thresholds to trigger an action).

[119] 3. The 5G device begins collecting data from one or more application clients (via request / response or subscription / notification) on one or more tethered devices. This collection may include at least one of the following: • Alt1: requests the end-to-end delay from the app client after measurements. The enabling client can identify the segments between the 5G device and the application service enabler; therefore, it can calculate the remaining delay contribution. • Alt2: By knowing the relative location of the tethered UE and the technology used, it can accurately estimate the maximum and minimum latency, NLOS and LOS data. • Alt3: If one or more tethered UE Apps interact with the 5G device, the 5G device may capture when the link delay exceeds the packet delay budget and for how long (e.g., for Link X, the PDB might be 5 ms and the XR message arrives at the 5G device in 7 ms). • Alt4: The 5G device (using the analytics enabler) performs local analytics based on tethered EU location and technology, as well as environment and time of day. These analyses may be AI / ML based.

[120] 4. The 5G device sends the collected data (measurements or analyses) in the form of a report to the enabler of Petition 870260036934, dated 04 / 20 / 2026, page 56 / 169 48 / 72 application service for one or more tethered devices. This report can be provided once, regularly, or based on an event (e.g., delay drift).

[121] 5. The application service enabler derives analytics based on the data. These analytics can take the following forms: • Statistics or forecasts for a given time horizon regarding the delay of the segment of interest by link or by tethered EU or by 5G device. • Statistics or forecasts for end-to-end delay considering 3GPP and non-3GPP link inputs. • Whether the delay of the segment of interest can be sustained for a given session or time period.

[122] 6. Based on the analyses, the service enabler can also recommend a proactive action regarding the VAL customer or the 5G network. Such action can be based on certain policies (triggering event - action pair) or the service enabler may have the necessary logic to translate the predictive event into a VAL service action. • Regarding the VAL server, the action may involve adapting the service mode / level (e.g., video resolution, automation level) so that the application can handle potentially high delays. This may also include additional adaptations, such as changing traffic schedules or different retransmission policies (from the application layer). • Towards 5GC, such action could be updating the QoS requirements / profile per network session to compensate for potential high delays due to high delays in the segment of interest (UE tied to the 5G device). An additional action could be requesting an update to the UP path (to perform traffic routing) or a possible slice change (which could offer lower delays).

[123] 7. The service enabler sends the analysis output. Petition 870260036934, dated 04 / 20 / 2026, page 57 / 169 49 / 72 based on the consumer subscription.

[124] Figure 13 illustrates a 1300 architecture that provides a mechanism for the case where analysis is required for the ADAE-C interface and the VAL client resides in a different UE that is not networked. These cases may exist for: • Lashing into XR scenarios. • Industrial scenarios where the VAL customer resides in a local cloud and the UE is a low-capacity node (e.g., a field device or slave). In this scenario, the interaction between the slave / field device and the local cloud can be done via another wireless technology (e.g., Wi-Fi). • For restricted devices (e.g., sensors) that may not run applications on the same entity, but on another entity (e.g., UE GW for a group of devices), the interaction between the GW and the UE VAL may be via non-3GPP wireless means.

[125] The 1300 architecture comprises a UE VAL 1310 that communicates via a 3GPP network system 1350 with a VAL server 1362 and an Application Data Analysis Enablement (ADAES) server 1364. The UE VAL 1310 comprises a VAL client 1312 and an Application Data Analysis Enablement (ADAEC) client 1314. The UE VAL 1310 is tied to the tethered device 1320 by a non-3GPP access link. The non-3GPP access link may include Bluetooth or Wi-Fi. The tethered device 1320 comprises a VAL client 1322. The communication protocols between components of the 1300 architecture are illustrated in the figure. The 1300 architecture can be considered as comprising a VAL side and a SEAL side. The VAL side is illustrated at the top of Figure 13, and the SEAL side is illustrated at the bottom of Figure 13.

[126] A prerequisite for the operation of the 1300 architecture is that the ADAEC 1314 is connected to the ADAES 1364. The steps for this solution are defined in the numbered paragraphs below.

[127] Step 1: The VAL 1362 server sends a request Petition 870260036934, dated 04 / 20 / 2026, page 58 / 169 50 / 72 subscription to ADAES 1364 for ADAEC / VAL-X 1314 performance analysis. In this request, the VAL 1362 server indicates the service ID / application ID, the VAL UE ID and address, the identity (or information) of the tied device, the connectivity type for ADAE-C 1314 and also for VAL-X (e.g., Wi-Fi), optionally, the location of the tied device (if assumed to be fixed), the type of analysis (e.g., delay sustainability or predicted delay or delay statistics), the service area, the validity period, and possibly the preferred confidence level (in the case of prediction).

[128] It may be possible that the UE is not indicated and the subscription is for all UEs in a given service area (e.g., XR users).

[129] Step 2: ADAES 1364 authorizes the request and sends a signature response as a positive or negative result.

[130] Step 3: ADAES 1364 finds the VAL UEs that need to provide reports, as well as the data sources needed for data collection. Data sources may be: • A-ADRF which can maintain historical data / analysis related to ADAE-C / VAL-X interface delay for the provided UE or for the provided service and area / time. • VAL 1322 client of the tied device 1320 that can provide QoS (delay) data for the link or end-to-end. • VAL UE 1310 client (VAL 1312) that supports connectivity.

[131] Step 4: ADAES 1364 sends a request to ADAEC 1314 for performance data for ADAE-C and / or VAL-X, indicating the reporting configuration parameters (frequency, intervals, etc.), triggering criteria for the reports (e.g., upper tolerable delay limits), required processing (abstraction, analysis / statistics), the data sources needed to provide data, and validity. Petition 870260036934, dated 04 / 20 / 2026, page 59 / 169 51 / 72 time frame for the request.

[132] Step 5: ADAEC 1314 identifies whether it is possible to collect the requested data and, if feasible, responds to ADAES 1364 with a positive or negative confirmation.

[133] Step 6: ADAEC 1314 starts collecting data from the data sources. In the case of A-ADRF, ADAEC subscribes directly to A-ADRF or via ADAES.

[134] Step 7: Based on the report configuration and data requirements, ADAEC provides the data / analyses related to ADAE-C and / or VAL-X performance to ADAES. This data may be the expected / actual / predicted / statistical delay for the link / segment of interest or the deviation / delta from the upper limit.

[135] Step 8: The ADAES 1364, upon receiving the data, derives analyses on the predicted performance of VAL-X / ADAE-C. To do this, the ADAES 1364 can optionally obtain supplementary data on the location of the VAL UE 1310 and the tethered device 1320 to help predict the delay more accurately.

[136] Step 9: ADAES 1364 can also provide a recommendation on proactive action based on the analysis. This requires that ADAES 1364 has the logic for such translation, or it can use another SEAL service (or input from the VAL server) to identify the best action based on the predictive trigger.

[137] Step 10. ADAES 1364 sends an analysis notification and, optionally, a proactive adaptation to a network entity and / or an application entity.

[138] Integrating analytics related to application Data Network performance within the SEAL plan may be desirable. Such integration could support the implementation of immersive and / or vertically interactive surface media applications, such as XR applications, experienced by end users via tethered UEs, for example, as a Petition 870260036934, dated 04 / 20 / 2026, pp. 60 / 169 52 / 72 combination of an HMD and a 5G or similar device.

[139] In this way, the QoS delay characteristics at the application layer, end-to-end, across all network segments, can be monitored and controlled to provide reliable support and experience to vertical over-the-top immersive and interactive media applications, experienced in tethered UEs. In these arrangements, the SEAL ADAE service can monitor VAL connectivity across all network segments: • Regarding the DN link segment, that is, from the VAL server to the 5GS PSA UPF; • On the 5GS link segment, i.e., from the 5GS PSA UPF to the tied UE (i.e., the 5G device); and / or • On the UE tie-in link segment, i.e., from the 5G device that provides 5G DN connectivity to the tied end-user device where the VAL application experience is consumed.

[140] ADAE may require further enhancements to its support for application performance analysis, whereby simultaneous monitoring, analysis and forecasting of the data connectivity pipeline is performed both from a connected UE, or alternatively, from a VAL client perspective, and from an AS / EAS, or alternatively, from a VAL server perspective.

[141] A tethered UE DCAF implementation can be provisioned to expose events of at least one of the following types: E2eDelayExperience, TetheredLinkDelayExperience, and DnDelayExperience are attached as a Data Source to the SEAL ADAE functional architecture. The new events exposed to ADAE are therefore based on the De2e,Dnil,Dn,2 delay measurements collected by the tethered UE Direct Data Collection Client, or alternatively, VAL client, and by the AS / EAS, or alternatively, VAL server. As such, ADAE acts as a consuming AF exposed to the DCAF event outputs. This Petition 870260036934, dated 04 / 20 / 2026, page 61 / 169 The 53 / 72 EU-specific ADAE data source therefore complements the other ADAE data sources, namely the VAL server, 5GS data sources and the enablement layer data sources (e.g. SEAL, Edge Enablement Layer (EEL)).

[142] The UE-bound Direct Data Collection Client can be instantiated and deployed by an ADAE Client (ADAEC) colocated within the UE device bound with the MAF or, alternatively, the MSH.

[143] An ADAE connected to tethered DCAF can extend its application performance analysis support to additionally include tethered UE analytics, as a tethered VAL client. These analyses can be extended to include online analytics for real-time analysis and forecasting for the VAL server to consume. This ADAE functionality can be identified by the tethered VAL connectivity performance analysis ID.

[144] The VAL server that consumes VAL connectivity performance analyses connected to ADAE can adapt its behavior (e.g., adapting the application layer configuration, reducing the source encoding rate, changing the video encoding configuration in terms of FPS, Q parameter, number of slices, number of layers, number of eye buffers, or similarly changing the audio encoding configuration to a lower encoding quality, AS / EAS load balancing, etc.) or request network resource management for the SEAL NRM instance to adapt the QoS handling based on the ASP application requirements.

[145] In the first case, an example might include the VAL server reducing the FPS of video traffic associated with an XR application from 120 FPS to 60 FPS when ADAES predicts an increase in E2E latency by monitoring either Petition 870260036934, dated 04 / 20 / 2026, page 62 / 169 54 / 72 of the events exposed by the EU tied through the corresponding ADAEC.

[146] In the latter case, an implementation may include the VAL server instructing the 5GS network provider to adapt the 5GS QoS delay budget and reduce it from a previous PDB configuration of ücl to a lower PDB configuration of Dc,2, such that Dc,2+Dn,i +Dn,2 <De2e,max, onde o De2e,maxé o limite máximo de atraso E2E tolerado pela aplicação de ASP e pelo servidor de VAL. Nesse caso, a solicitação de servidor de VAL à camada de SEAL para adaptação dos parâmetros de orçamento de atraso de QoS sobre o 5GS é baseada na interação do servidor de VAL com o servidor de NRM, por meio da qual o servidor de VAL realiza uma solicitação de adaptação de recursos de rede ao servidor de NRM para reduzir o orçamento de atraso de QoS dentro dos limites permitidos por um SLA entre o ASP e uma operadora de rede móvel ou provedor de serviços 5GS.In one example, such a request might contain the identity of the VAL server requester, a list of one or more bound UE VAL IDs, and a resource adaptation requirement indicating the VAL service requirement for the new QoS delay budget (e.g., 10 ms as PDB or, alternatively, PSDB) for the QoS flows related to the VAL service flows of interest. The NRM will perform the adaptation procedure, provided the VAL server is authorized to request such a change, and will report the update status (i.e., successful, including the changed parameters, or failure and an appropriate failure code).

[147] The procedure associated with the ADAE analysis for UE connectivity performance and tied application is described below, as illustrated in Figure 14, through which the connection between an ADAEC and an ADAES is established.

[148] Figure 14 illustrates a connectivity performance analysis procedure for VAL Amarrada 1400. The procedure Petition 870260036934, dated 04 / 20 / 2026, page 63 / 169 55 / 72 1400 is implemented by a tethered UE VAL 1410, a 5G System 1450, an ADAES 1464, and a VAL server 1462. The tethered UE VAL 1410 comprises a VAL client 1412 and an ADAEC 1414.

[149] Procedure 1400 starts on 1471, when the consumer of the ADAES analysis service, for example, the VAL server 1462, sends a subscription request to ADAES 1464 and provides the analysis event ID, for example, tied VAL connectivity performance, the target tied UE VAL ID or group of tied UE IDs, the VAL session / service IDs associated with the tied UE VAL ID, the time validity and area of ​​the request, the confidence level required for any predictions, and the exposure level to provide UE-to-UE analysis. Such a request may also include whether analysis notification will be periodic or based on expected application ASP QoS performance, with performance thresholds being additionally provided in the request (e.g., Maximum Tied Link Delay = 15 ms).

[150] In 1472, ADAES 1464 sends a signature response as an ACK to the consumer (the VAL Server 1462).

[151] In 1473, ADAES 1464 maps the analytical ID (i.e., tethered VAL connectivity performance) to a list of data collection event identifiers and, optionally, a list of data producer IDs. This mapping can be pre-configured by ADAES 1464 itself based on the preferred ASP event types, or VAL type, or alternatively, it can be pre-configured by an MNO via OAM. Additionally, ADAES 1646 determines, based on the configured tethered UE VAL ID and VAL session / service IDs, the ADAES 1414 instance authorized to perform tethered link-related data collection and reporting. Tethered link-related data collection and reporting are based on EVEX procedures involving tethered UE DCAF reporting mechanisms. Petition 870260036934, dated 04 / 20 / 2026, pp. 64 / 169 56 / 72

[152] On 1474, ADAES 1464 sends a tethered VAL connectivity performance analysis request to the determined tethered ADAEC 1414 VAL, with the analytical event ID and the required report configuration (e.g., periodic, based on maximum delay threshold, etc.). This request also includes additional application QoS attributes to be further analyzed based on other metrics (tethered link delay, E2E delay, 5GS PER, 5GS PDB / PSDB, etc.). An application session is then initiated between the tethered UE 1410 VAL and the VAL 1462 server.

[153] The next steps can occur asynchronously and in parallel, given the 5GC service-based architecture and event reporting for data collection that is configured. Therefore, the order of events presented below is just an example of implementation.

[154] In 1475a, ADAEC 1414 starts collecting data from tethered UE VAL 1410 based on the request. Collection and reporting are based on EVEX UE data collection procedures associated with mapped Event IDs from tethered UE link performance. In these cases, events such as and can collect various tethered link delay-related events, for example, Event ID = TetheredLinkDelayExperience. This data can therefore be about delay measurements, throughput (e.g., maximum WiFi capacity), QoE measurements, etc. Data can be collected in part by ADAEC 1414 from the VAL 1412 client application, as well as based on EVEX data collection and reporting procedures (e.g., as for TetheredLinkDelayExperience).

[155] In 1475b, ADAES 1464 can optionally collect more data on DN performance analysis by consuming NWDAF events, including metrics on average / maximum packet delay between the VAL server and the service PSA UPF, QoS monitoring analyses over the 5GS, including Petition 870260036934, dated 04 / 20 / 2026, pp. 65 / 169 57 / 72 service experience reviews etc.

[156] In addition, in 1475c, ADAES 1464 can optionally collect data on DN performance analysis by consuming NWDAF events, including metrics on average / maximum packet delay E2E between the VAL server and the tethered UE VAL 1410, as well as other E2E metrics related to QoS monitoring analysis (e.g., aggregated PER E2E, etc.).

[157] In 1476a, ADAEC 1414 detects an application QoS change. Such a change may be, for example, a change in QoS attribute requirements, by detecting an event where the maximum latency limit (e.g., on tethered or E2E link) accepted by the ASP is exceeded, while the detection mechanism is performed over a given time horizon based on the analysis signature request.

[158] In 1476b, ADAES 1464 detects or predicts an application QoS change. Such a change may be, for example, a change in QoS attribute requirements, detecting or alternatively predicting (based on collected metrics) an event where the maximum latency limit (e.g., on the tethered link, DN link, or E2E connectivity) accepted by the ASP is exceeded, while the detection mechanism is performed over a given time horizon based on the analysis subscription request.

[159] In 1477, ADAEC 1414 sends the analysis to ADAES 1464 in a tethered VAL connectivity performance analysis response message.

[160] In 1478, ADAES 1464 sends the derived analysis notification to the consumer (e.g., VAL 1462 server or any other authorized NF / AF consumer).

[161] Thus, a first network node is provided to enable performance analysis of a tethered connection, where an application session comprises a communication session. Petition 870260036934, dated 04 / 20 / 2026, pp. 66 / 169 58 / 72 end-to-end, wherein the end-to-end communication session includes the tethered connection. The first network node comprises a processor and processor-coupled memory, the processor being configured to cause the first network node to: receive a performance analysis requirement for the application session; identify at least one device to serve as a data collection entity to collect data necessary for the performance analysis; and send a data collection requirement to the identified data collection entity, wherein the data collection requirement includes a request for performance data related to at least one tethered connection within the application session.The processor is further configured to make the first network node: receive, from the data collection entity, measured performance data according to the data collection requirement; derive performance analysis based on the performance data and the data collection requirement; and send the derived performance analysis.

[162] A first network node can therefore derive performance analyses that include the performance of a tethered connection. These performance analyses are necessary to properly understand end-to-end quality of service. A measure of end-to-end quality of service may include end-to-end latency. The end-to-end communication session may include a connection between a user device and an application server.

[163] The tethered connection is therefore an integral part of an end-to-end communication session. The end-to-end communication session is included in an application session.

[164] The first network node can be an application data analytics enablement server (ADAES).

[165] The application session may include communication between a wireless communication device and an application server. The application session may comprise a plurality of links Petition 870260036934, dated 04 / 20 / 2026, pp. 67 / 169 59 / 72 that are communicated by a plurality of access technologies. The wireless communication device may comprise a tethered device and a tethering device. The tethering device may be arranged to communicate with the tethered device by means of at least one tethered connection. The tethered connection may comprise a connection using Wi-Fi or Bluetooth, for example.

[166] Receiving a requirement for performance analysis includes receiving a subscription request from an analysis consumer.

[167] Derived performance analyses can be sent to the analytics consumer in response to the need for performance analyses. Derived performance analyses can be sent to the analytics consumer.

[168] The requirement for performance analysis may comprise at least one of the following: an analysis event identity; at least one target UE VAL identity; a group identifier consisting of one or more tethering device identities and one or more tethered device identities; information about the access capability and / or technology for the tethering connection; positioning information associated with a target UE VAL identity; a VAL service identity associated with a target UE VAL identity; a VAL service identity associated with a target UE VAL identity; a time period for which measurements should be collected; a definition of an area for which measurements should be collected; the required confidence level of any derived performance analysis; and a level of exposure to provide analyses related to the tethered connection.The target VAL UE identity may include the identity of a tethered device and / or a tethering device. The derived performance analysis may comprise at least one prediction.

[169] The processor can also be configured to do with Petition 870260036934, dated 04 / 20 / 2026, pp. 68 / 169 60 / 72 that the first network node selects at least one data source for data collection by the data collection entity.

[170] Performance data may include historical data and / or real-time data. Real-time data is measurement data that is reported as it is collected.

[171] The data collection requirement may include a subscription to at least one data source.

[172] The application session may comprise at least one of: an extended reality session, a mobile metaverse session and / or an artificial intelligence application session.

[173] Performance analysis may comprise at least one of the following: statistics or forecasts for tethered connection communication delay; statistics or forecasts for end-to-end delay, considering the tethered connection as well as other segments in the end-to-end communication session; and / or identifying whether the quality of service for the tethered connection is sustainable for a given session or time period. Performance analysis may be related to a specific time period. The specific time period may be defined. For example, the specific time period may be defined by a consumer. The consumer may comprise an application server or a network unit.

[174] Performance analysis can be sent to an application server or to a network drive.

[175] Figure 15 illustrates a method 1500 performed by a first network node to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The method 1500 comprises: receiving 1510 a requirement for performance analysis for the application session; identifying 1520 at least one device to serve as a data collection entity. Petition 870260036934, dated 04 / 20 / 2026, pp. 69 / 169 61 / 72 to collect the data necessary for performance analysis; and send 1530 a data collection requirement to the identified data collection entity, the data collection requirement including a request for performance data related to at least one bound connection within the application session. Method 1500 further comprises: receiving 1540, from the data collection entity, performance data measured in accordance with the data collection requirement; deriving 1550 performance analyses based on the performance data and the data collection requirement; and sending 1560 the derived performance analyses.

[176] In certain embodiments, the 1500 method can be performed by a processor that executes program code, for example, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliary processing unit, an FPGA or similar.

[177] A first network node can therefore derive performance analyses that include the performance of a tethered connection. These performance analyses are necessary to properly understand end-to-end quality of service. A measure of end-to-end quality of service may include end-to-end latency. The end-to-end communication session may include a connection between a user device and an application server.

[178] The first network node can be an application data analytics enablement server (ADAES).

[179] The application session may include communication between a wireless communication device and an application server. The application session may comprise a plurality of links that are communicated by a plurality of access technologies. The wireless communication device may comprise a tethered device and a tethering device. The tethering device may be arranged to communicate with the tethered device via at least one connection. Petition 870260036934, dated 04 / 20 / 2026, page 70 / 169 62 / 72 tethered. A tethered connection can include a connection using Wi-Fi or Bluetooth, for example.

[180] Receiving a requirement for performance analysis includes receiving a subscription request from an analysis consumer.

[181] Derived performance analyses can be sent to the analytics consumer in response to the need for performance analyses. Derived performance analyses can be sent to the analytics consumer.

[182] The requirement for performance analysis may comprise at least one of the following: an analysis event identity; at least one target UE VAL identity; a group identifier consisting of one or more tethering device identities and one or more tethered device identities; information about the access capability and / or technology for the tethering connection; positioning information associated with a target UE VAL identity; a VAL service identity associated with a target UE VAL identity; a VAL service identity associated with a target UE VAL identity; a time period for which measurements should be collected; a definition of an area for which measurements should be collected; the required confidence level of any derived performance analysis; and a level of exposure to provide analyses related to the tethered connection.The target VAL UE identity may include the identity of a tethered device and / or a tethering device. The derived performance analysis may comprise at least one prediction.

[183] ​​The method may also include selecting at least one data source for data collection by the data collection entity.

[184] Performance data may include historical data and / or real-time data. Real-time data is measurement data that is reported as it is collected. Petition 870260036934, dated 04 / 20 / 2026, page 71 / 169 63 / 72

[185] The data collection requirement may include a subscription to at least one data source.

[186] The application session may comprise at least one of: an extended reality session, a mobile metaverse session and / or an artificial intelligence application session.

[187] Performance analysis may comprise at least one of the following: statistics or forecasts for tethered connection communication delay; statistics or forecasts for end-to-end delay, considering the tethered connection as well as other segments in the end-to-end communication session; and / or identifying whether the tethered connection quality of service is sustainable for a given session or time period. Performance analysis may be related to a specific time period. The specific time period may be defined. For example, the specific time period may be defined by a consumer. The consumer may comprise an application server or a network unit.

[188] Performance analysis can be sent to an application server or to a network drive.

[189] A second network node is further provided to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The second network node comprises a processor and processor-coupled memory. The processor is configured to cause the second network node to: receive a data collection requirement from a first network node; determine at least one data source based on the data collection requirement; collect performance data from at least one data source, with the collection based on the data collection requirement; send the collected performance data to the first network node. Petition 870260036934, dated 04 / 20 / 2026, page 72 / 169 64 / 72

[190] A second network node can therefore derive performance analyses that include the performance of a tethered connection. These performance analyses are necessary to properly understand end-to-end quality of service. A measure of end-to-end quality of service may include end-to-end latency.

[191] The second network node may comprise an Application Data Analytics Enablement Client (ADAEC). The first network node may comprise an Application Data Analytics Enablement Server (ADAES).

[192] The processor can be further configured to have the second network node process the collected performance data before sending it to the first network node. The second network node may include collecting performance data from at least one data source, processing the collected performance data, and then sending the collected and processed performance data to the first network node.

[193] The processor can be further configured to have the second network node determine whether the collected performance data is sufficient to meet the data collection requirement; and, if the collected performance data is not sufficient to meet the data collection requirement, to request supplementary data. The supplementary data can be collected from at least one data source or form an additional data source.

[194] Performance data may include an indication of a communication delay on the tethered connection.

[195] Performance data collection may comprise at least one of the following: requesting end-to-end delay measurements from an application client; estimating a maximum and minimum latency considering line-of-sight and no line-of-sight and using the relative location of the tethered connection endpoints; capturing when a delay occurs for the connection Petition 870260036934, dated 04 / 20 / 2026, page 73 / 169 65 / 72 tethered devices exceed a packet delay budget; and / or perform local analyses based on the location of a tethered device, the communication technology used for the tethering connection, as well as the local environment and time of day.

[196] When performance data collection involves requesting end-to-end delay measurements from an application client, the second network node can identify segments in the application session and calculate a remaining delay contribution.

[197] Estimating a maximum and minimum latency, considering line of sight and no line of sight, and using the relative location of the tethered connection endpoints, can be based on the communication technology used for the tethered connection.

[198] In which capturing when a delay for the tethered connection exceeds a packet delay budget comprises, if one or more applications use the tethered connection, the tethering device determines how long the tethered connection exceeds a packet delay budget (PDB).

[199] Local analysis can be based on AI / ML.

[200] Figure 16 illustrates a method 1600 performed by a second network node to enable performance analysis of a tethered connection, wherein an application session comprises an end-to-end communication session, and wherein the end-to-end communication session includes the tethered connection. The method 1600 comprises receiving 1610 a data collection requirement from a first network node; determining 1620 at least one data source based on the data collection requirement; collecting 1630 performance data from at least one data source, collecting it based on the data collection requirement; and sending 1640 the collected performance data to the first network node.

[201] In certain modalities, the 1600 method can be performed Petition 870260036934, dated 04 / 20 / 2026, page 74 / 169 66 / 72 by a processor that executes program code, for example, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliary processing unit, an FPGA or similar.

[202] A second network node can therefore derive performance analyses that include the performance of a tethered connection. These performance analyses are necessary to properly understand end-to-end quality of service. A measure of end-to-end quality of service may include end-to-end latency.

[203] The second network node may comprise an Application Data Analytics Enablement Client (ADAEC). The first network node may comprise an Application Data Analytics Enablement Server (ADAES).

[204] The method may also comprise processing the collected performance data before sending it to the first network node. The method may comprise collecting performance data from at least one data source, processing the collected performance data, and then sending the collected and processed performance data to the first network node.

[205] The method may further comprise: determining whether the performance data collected is sufficient to satisfy the data collection requirement; and, if the performance data collected is not sufficient to satisfy the data collection requirement, requesting supplementary data. Supplementary data may be collected from at least one data source or form an additional data source.

[206] Performance data may include an indication of a communication delay on the tethered connection.

[207] Performance data collection may comprise at least one of the following: requesting end-to-end delay measurements from an application client; estimating a maximum and minimum latency considering line of sight and no line of sight; and using the relative location of the endpoints of Petition 870260036934, dated 04 / 20 / 2026, page 75 / 169 67 / 72 tethered connection; capture when a delay for the tethered connection exceeds a packet delay budget; and / or perform local analytics based on the location of a tethered device, the communication technology used for the tethering connection, as well as the local environment and time of day.

[208] When performance data collection involves requesting end-to-end delay measurements from an application client, the second network node can identify segments in the application session and calculate a remaining delay contribution.

[209] Estimating a maximum and minimum latency, considering line of sight and absence of line of sight, and using the relative location of the tethered connection endpoints, can be based on the communication technology used for the tethered connection.

[210] In which capturing when a delay for the tethered connection exceeds a packet delay budget comprises, if one or more applications use the tethered connection, the tethering device determines how long the tethered connection exceeds a packet delay budget (PDB).

[211] Local analyses can be based on AI / ML.

[212] A third network node is further provided to enable performance analysis of a tied connection within an application session, wherein the application session includes communication via at least one tied connection. The third network node comprises a processor and processor-coupled memory. The processor is configured to cause the third network node to: send a performance analysis request for the application session to a first network node, the performance analysis request including a request for performance data relating to at least one tied connection within the application session; and receive performance analyses from the first network node. Petition 870260036934, dated 04 / 20 / 2026, pp. 76 / 169 68 / 72

[213] Figure 17 illustrates a 1700 method performed by a third network node to enable performance analysis of a tied connection within an application session, wherein the application session includes communication through at least one tied connection. The 1700 method comprises sending a performance analysis request for the application session to a first network node, including a request for performance data relating to at least one tied connection within the application session; and receiving a performance analysis from the first network node.

[214] In certain embodiments, the 1700 method can be performed by a processor that executes program code, for example, a microcontroller, a microprocessor, a CPU, a GPU, an auxiliary processing unit, an FPGA or similar.

[215] A third network node can therefore derive performance analyses that include the performance of a tethered connection. These performance analyses are necessary to properly understand end-to-end quality of service. A measure of end-to-end quality of service may include end-to-end latency.

[216] The third network node may comprise an Application-Analysis Function and Data Repository (A-ADRF) layer. The first network node may be an Application Data Analysis Enablement Server (ADAES).

[217] The application session may include communication between a wireless communication device and an application server. The application session may comprise a plurality of links that are communicated by a plurality of access technologies. The wireless communication device may comprise a tethered device and a tethering device. The tethering device may be arranged to communicate with the tethered device via at least one tethered connection. The tethered connection may comprise a connection using Petition 870260036934, dated 04 / 20 / 2026, page 77 / 169 69 / 72 Wi-Fi or Bluetooth, for example.

[218] This disclosure set introduces the following innovative elements: A method for providing performance monitoring and analysis on a 5GS entity for interfaces that are supported by non-3GPP connectivity. A method for introducing ADAE service functionality for VAL tethered connectivity performance analysis, which exposes to VAL server analysis related to the performance of a tethered UE VAL and enables the application to adapt its behavior in terms of source encoding configuration, QoS, and EAS / AS load balancing.

[219] A method is provided here (which can be implemented in an ADAES) for enabling performance analysis for a tied link within an application session. The method comprises: obtaining a requirement for performance analysis for the application session, wherein the application session comprises a plurality of links that are communicated by a plurality of access technologies; identifying at least one device to serve as a data collection entity for the data needed for performance analysis; sending a data collection requirement to the identified data collection entity; receiving performance data based on the data collection requirement, the performance data relating to the tied link within the application session; deriving analyses based on the requirement; and sending the derived analyses.

[220] Meeting the requirement may involve: receiving a subscription request from a consumer; and sending a subscription response.

[221] The method may also involve selecting at least one data source for collection.

[222] Performance data may include historical data or real-time data.

[223] The data collection requirement may include a Petition 870260036934, dated 04 / 20 / 2026, pp. 78 / 169 70 / 72 signature of at least one data source.

[224] The application session can be at least an XR session, a mobile metaverse session, or an AI application session.

[225] The tethered link can be communicated by means of technologies such as Wi-Fi, Bluetooth, etc.

[226] A method is further provided (which can be implemented in an ADAEC) to support the enabling of performance analysis for a tied link within an application session, the method comprising: receiving a data collection requirement from an analysis enabling entity; determining at least one data source based on the requirement; collecting performance data based on the requirement from the determined data sources; sending the collected performance data to the analysis enabling entity; processing the data before sending; requesting / receiving supplementary data (location, etc.) if data is insufficient; the performance data is the tied link delay; determining the mechanism for estimating the tied link delay;

[227] It should be noted that the methods and apparatus mentioned above illustrate, rather than limit, the invention, and that those skilled in the art will be able to design many alternative arrangements without departing from the scope of the appended claims. The word comprising does not exclude the presence of elements or steps other than those listed in a claim, one or an does not exclude a plurality, and a single processor or other unit may perform the functions of several units recited in the claims. Any reference signs in the claims should not be interpreted as limiting their scope.

[228] Furthermore, although examples have been given in the context of particular communication patterns, these examples are not intended to be the limit of the communication patterns to which Petition 870260036934, dated 04 / 20 / 2026, p. 79 / 169 71 / 72 The method and apparatus disclosed may be applied. For example, although specific examples have been given in the context of 3GPP, the principles disclosed in this document may also be applied to other wireless communication systems and, indeed, to any communication system that uses routing rules. The method can also be incorporated into a set of instructions, stored on a computer-readable medium, which, when loaded into a computer processor, Digital Signal Processor (DSP), or similar, causes the processor to perform the methods described above.

[229] The methods and apparatus described can be practiced in other specific forms. The methods and apparatus described should be considered, in all respects, only as illustrative and not restrictive. The scope of the invention is therefore indicated by the appended claims and not by the preceding description. All alterations that fall within the meaning and scope of equivalence of the claims should be included in their scope.

[230] The following abbreviations are relevant in the field covered in this document: 3GPP, 3rd generation partnership project; 5G, fifth generation; 5GS, 5G system; 5QI, 5G QoS identifier; A-ADRF, application layer analytics data repository function; ADAEC, application data analytics enablement client; ADAES, application data analytics enablement server; A-DCCF, application layer data collection and coordination function; AF, application function; AMF, access and mobility function; AR, augmented reality; AS, application server; ASP, application service provider; DCAF, data collection AF; DL, downlink; EAS, edge application server; NAL, network abstraction layer; NRM, network resource management; PCF, policy control function; PDU, packet data unit; PPS, packet set Petition 870260036934, dated 04 / 20 / 2026, page 80 / 169 72 / 72 image parameters; PSA UPF, PDU session anchor UPF; PSB, PDU set limit; PSI, PDU set importance; QoE, Quality of Experience; QoS, Quality of Service; RAN, Radio Access Network; RTCP, Real-Time Control Protocol; RTP, Real-Time Protocol; SDAP, Service Data Adaptation Protocol; SEAL, Service Enablement Application Layer; SMF, Session Management Function; SRTCP, Secure Real-Time Control Protocol; SRTP, Secure Real-Time Protocol; UE, User Equipment; UL, Uplink; UPF, User Plane Function; VAL, Vertical Application Layer; VCL, Video Coding Layer; VMAF, Video Multi-Method Evaluation Function; VPS, Video Parameter Set; VR, Virtual Reality; XR, Extended Reality; XR AS, XR Application Server; and XRM, XR Medium. Petition 870260036934, dated 04 / 20 / 2026, page 81 / 169

Claims

1 / 6 CLAIMS 1.First network node, characterized in that it comprises: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the first network node to: receive a requirement for performance analysis of an application session comprising an end-to-end communication session that includes a tethered connection; identify at least one device to serve as a data collection entity to collect data for performance analysis; send a data collection requirement to the data collection entity, the data collection requirement including a request for performance data relating to the tethered connection within the application session; receive, from the data collection entity, the performance data measured in accordance with the data collection requirement; derive performance analyses based on the performance data and the data collection requirement; and send the derived performance analyses.

2. First network node, according to claim 1, characterized in that to receive the requirement for performance analysis, at least one processor must be configured to cause the first network node to receive a subscription request from an analysis consumer.

3. First network node, according to claim 1, characterized in that the requirement for performance analysis comprises at least one of: an analytical event identity; at least one target vertical application layer (VAL) user equipment (UE) identity; Petition 870260036934, dated 20 / 04 / 2026, p.82 / 169 2 / 6 a group identifier consisting of one or more tethering device identities and one or more tethered device identities; information about one or more access capabilities or technologies for the tethered connection; positioning information associated with a target UE VAL identity; a VAL session identity associated with the target UE VAL identity; a VAL service identity associated with the target UE VAL identity; a time period for which measurements are collected; a definition of an area for which measurements are collected; a confidence level of any derived performance analysis; or an exposure level to provide analyses related to the tethered connection.

4. First network node, according to claim 1, characterized in that at least one processor is further configured to cause the first network node to select at least one data source for data collection by the data collection entity.

5. First network node, according to claim 1, characterized in that the performance data comprises one or more historical data or real-time data.

6. First network node, according to claim 1, characterized in that the data collection requirement comprises a subscription to at least one data source.

7. First network node, according to claim 1, characterized in that the application session comprises at least one of an extended reality session, a mobile metaverse session, or an artificial intelligence application session.

8. First network node, according to claim 1, characterized in that the performance analysis comprises at least one of: statistics or predictions for a tethered connection communication delay; statistics or predictions for an end-to-end delay, considering the tethered connection as well as other segments in the end-to-end communication session; or a determination of whether a quality of service for the tethered connection is sustainable for a given session or time period.

9. First network node, according to claim 1, characterized in that performance analyses are sent to an application server or to a network unit.

10. Method performed by a first network node, characterized in that the method comprises: receiving a requirement for performance analysis of an application session comprising an end-to-end communication session that includes a tethered connection; identifying at least one device to serve as a data collection entity to collect data for performance analysis; sending a data collection requirement to the data collection entity, the data collection requirement including a request for performance data relating to the tethered connection within the application session; receiving, from the data collection entity, the performance data measured in accordance with the data collection requirement; deriving performance analyses based on the performance data and the data collection requirement; and sending the derived performance analyses.

11. Method, according to claim 10, characterized in that receiving the requirement for performance analysis comprises receiving a subscription request from an analysis consumer.

12. Method according to claim 10, characterized in that it further comprises: selecting at least one data source for data collection by the data collection entity.

13. Method according to claim 10, characterized in that the data collection requirement comprises a subscription from at least one data source.

14. A method according to claim 10, characterized in that the performance analysis comprises at least one of: statistics or forecasts for a tethered connection communication delay; statistics or forecasts for an end-to-end delay, considering the tethered connection as well as other segments in the end-to-end communication session; or a determination of whether a quality of service for the tethered connection is sustainable for a given session or time period.

15. Second network node, characterized in that it comprises: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the second network node to: receive a data collection requirement from a first network node, the data collection requirement for performance analysis of an application session comprising an end-to-end communication session that includes a tethered connection; Petition 870260036934, dated 04 / 20 / 2026, p. 85 / 169 5 / 6 determine at least one data source based on the data collection requirement; collect performance data from at least one data source based on the data collection requirement; and send the collected performance data to the first network node.

16. Second network node, according to claim 15, characterized in that at least one processor is further configured to cause the second network node to process the collected performance data before sending it to the first network node.

17. Second network node, according to claim 15, characterized in that at least one processor is further configured to cause the second network node to: determine whether the collected performance data is sufficient to satisfy the data collection requirement; and if the collected performance data is not sufficient to satisfy the data collection requirement, request supplementary data.

18. Second network node, according to claim 15, characterized in that the performance data comprises an indication of a communication delay in the tethered connection.

19. Second network node, according to claim 15, characterized in that collecting performance data comprises at least one processor being configured to cause the second network node to perform at least one of the following: requesting end-to-end delay after measurements from an application client; estimating a maximum latency and a minimum latency given line of sight and no line of sight and using a relative location of tethered connection endpoints; capturing when a delay for the tethered connection exceeds a packet delay budget; or performing local analyses based on a tethered device location, a communication technology used for the tethered connection, and a local environment and time of day.

20. A method implemented by a second network node, characterized in that the method comprises: receiving a data collection requirement from a first network node, the data collection requirement being for performance analysis of an application session comprising an end-to-end communication session that includes a tethered connection; determining at least one data source based on the data collection requirement; collecting performance data from at least one data source based on the data collection requirement; and sending the collected performance data to the first network node. Petition 870260036934, dated 04 / 20 / 2026, p. 87 / 169

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