Apparatus, method and computer program relating to quality of experience

Abstract

A method includes determining, on a user device, one or more target performance metric values associated with a target quality of experience for an application running on the user device; and causing a request to be sent to the network entity, the request having information about the one or more target performance indicator values.

Description

Technical Field

[0001] The present disclosure relates generally to communication systems, and in particular (but not limited to) to apparatus, methods and computer programs related to quality of experience. Background Art

[0002] A communication system can be viewed as a facility that enables communication between two or more communication devices, provides communication devices with access to a data network, or provides services to communication devices, such as extended reality (XR) services.

[0003] The communication system may be a wireless communication system. Examples of wireless communication systems include mobile systems operating based on radio access technology standards such as those provided by 3GPP (3rd Generation Partnership Project) or ETSI (European Telecommunications Standards Institute), satellite communication systems, and Wi-Fi communication systems. Wireless communication systems operating based on radio access technology have a coverage area that can typically be divided into cells and are therefore often referred to as cellular systems.

[0004] The radio access technology standard specifies what the various entities of the communication system are allowed to do and how it should be implemented. For example, the communication protocols and / or parameters to be used by a communication device for accessing or connecting to the radio access network of a mobile system are defined.

[0005] An example of a standard is the so-called 5G (fifth generation) standard provided by 3GPP. Summary of the invention

[0006] According to one aspect, a method is provided, the method comprising: determining, on a user device, one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user device; and causing a request to be sent to a network entity, the request having information about the one or more target performance indicator values.

[0007] The method may include determining, by the application, a target quality of experience.

[0008] The one or more target performance indicator values ​​include one or more of a target delay value or a target data rate value.

[0009] The target data rate may include a target frame rate value.

[0010] The target delay value may include a target end-to-end delay value.

[0011] The method may include receiving a message from a network entity indicating that support for one or more target performance indicator values ​​is to be provided.

[0012] Determining may include determining one or more target performance indicator values ​​associated with a target quality of experience using a quality of experience model stored on the user equipment.

[0013] A quality of experience model may define the relationship between quality of experience and one or more performance indicators.

[0014] The method may include determining, on a user device, a quality of experience for a running application using a quality of experience model.

[0015] The one or more performance indicators may provide one or more of: an indication of visual quality; a measure of data rate; or an indicator of latency.

[0016] Indicators of delay may include round trip time.

[0017] Indicators of data rate may include one or more of a bit rate and a pixel rate per second.

[0018] The applications may include extended reality applications.

[0019] The method may be performed by a device. The device may be a user equipment or provided in a user equipment. The user equipment may include a user device.

[0020] According to another aspect, a user equipment device is provided, comprising at least one processor and at least one memory, wherein the at least one memory stores instructions that, when executed by the at least one processor, cause the user equipment device to at least: determine one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user equipment device; and cause a request to be sent to a network entity, the request having information about the one or more target performance indicator values.

[0021] The user equipment device may be caused to determine a target quality of experience by an application.

[0022] The one or more target performance indicator values ​​include one or more of a target delay value or a target data rate value.

[0023] The target data rate may include a target frame rate value.

[0024] The target delay value may include a target end-to-end delay value.

[0025] The user equipment device may be caused to receive a message from a network entity indicating that support for one or more target performance indicator values ​​is to be provided.

[0026] Determining may include determining one or more target performance indicator values ​​associated with a target quality of experience using a quality of experience model stored on the user equipment.

[0027] A quality of experience model may define the relationship between quality of experience and one or more performance indicators.

[0028] The user equipment device may be caused to determine a quality of experience for a running application using a quality of experience model.

[0029] The one or more performance indicators may provide one or more of: an indication of visual quality; a measure of data rate; or an indicator of latency.

[0030] Indicators of delay may include round trip time.

[0031] Indicators of data rate may include one or more of a bit rate and a pixel rate per second.

[0032] The applications may include extended reality applications.

[0033] The user equipment device may include user equipment.

[0034] According to another aspect, a user equipment device is provided, comprising: a component for determining one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user equipment device; and a component for sending a request to a network entity, the request having information about the one or more target performance indicator values.

[0035] The user equipment device may include means for determining a target quality of experience by an application.

[0036] The one or more target performance indicator values ​​include one or more of a target delay value or a target data rate value.

[0037] The target data rate may include a target frame rate value.

[0038] The target delay value may include a target end-to-end delay value.

[0039] The user equipment device may include means for receiving a message from a network entity indicating that support for one or more target performance indicator values ​​is to be provided.

[0040] The determining component may use a quality of experience model stored on the user equipment to determine one or more target performance indicator values ​​associated with the target quality of experience.

[0041] A quality of experience model may define the relationship between quality of experience and one or more performance indicators.

[0042] The user equipment apparatus may include means for determining a quality of experience for a running application using a quality of experience model.

[0043] The one or more performance indicators may provide one or more of: an indication of visual quality; a measure of data rate; or an indicator of latency.

[0044] Indicators of delay may include round trip time.

[0045] Indicators of data rate may include one or more of a bit rate and a pixel rate per second.

[0046] The applications may include extended reality applications.

[0047] The user equipment device may include user equipment.

[0048] According to another aspect, a method is provided, the method comprising: receiving a request from a user device at a network entity, the request having information about one or more target performance indicator values, wherein the one or more target performance indicator values ​​are associated with a target quality of experience for an application running on the user device; and requesting resources associated with the target performance indicator values ​​for the application running on the user device.

[0049] The method may include determining resources to be requested using a quality of experience model.

[0050] The requested resources may include one or more of desired levels of throughput and latency.

[0051] The method may include determining a target delay in dependence on a processing time in at least one of the network entity or the user equipment.

[0052] The request may include causing the request to be sent to a 5G core entity.

[0053] The method may include receiving a response to the request for a resource, the response indicating authorization for the requested resource.

[0054] A request for resources may include a request for resources associated with a given 5QI.

[0055] The method may comprise causing an indication of authorization for the requested resource to be sent to the user equipment.

[0056] The method may include receiving a request from a user equipment, the request being for a quality of experience model, and in response to the request causing the quality of experience model to be sent to the user equipment.

[0057] The applications may include extended reality applications.

[0058] The method may be executed by a device. The device may be a server or provided in a server.

[0059] According to another aspect, a network entity device is provided, comprising: a component for receiving a request from a user device, the request having information about one or more target performance indicator values, wherein the one or more target performance indicator values ​​are associated with a target quality of experience for an application running on the user device; and a component for requesting resources associated with the target performance indicator values ​​for the application running on the user device.

[0060] The network entity apparatus may include means for determining resources to be requested using a quality of experience model.

[0061] The requested resources may include one or more of desired levels of throughput and latency.

[0062] The network entity apparatus may include means for determining a target delay dependent on a processing time in at least one of the network entity or the user equipment.

[0063] The component for requesting resources can send a request to the 5G core entity.

[0064] The network entity apparatus may include means for receiving a response to the request for a resource, the response indicating authorization for the requested resource.

[0065] The request for resources may include a request for resources associated with a given 5QI.

[0066] The network entity apparatus may include means for causing an indication of authorization for the requested resources to be sent to the user equipment.

[0067] The network entity apparatus may include means for receiving a request from a user equipment, the request being for a quality of experience model, and means for causing the quality of experience model to be sent to the user equipment in response to the request.

[0068] The applications may include extended reality applications.

[0069] The network entity device may be a server or provided in a server.

[0070] According to another aspect, a network entity device is provided, which includes at least one processor and at least one memory, wherein the at least one memory stores instructions, which when executed by the at least one processor causes the network entity device to at least perform: receiving a request from a user equipment, the request having information about one or more target performance indicator values, wherein the one or more target performance indicator values ​​are associated with a target experience quality for an application running on the user equipment; and requesting resources associated with the target performance indicator values ​​for the application running on the user equipment.

[0071] The network entity apparatus may be caused to determine the resources to be requested using the quality of experience model.

[0072] The requested resources may include one or more of desired levels of throughput and latency.

[0073] The network entity apparatus may be caused to determine the target delay in dependence on a processing time in at least one of the network entity or the user equipment.

[0074] Requesting a resource may include causing a request to be sent to a 5G core entity.

[0075] The network entity apparatus may be caused to receive a response to the request for a resource, the response indicating that the requested resource is granted.

[0076] The request for resources may include a request for resources associated with a given 5QI.

[0077] The network entity apparatus may be caused to send an indication of authorization of the requested resource to the user equipment.

[0078] The network entity apparatus may be caused to receive a request from a user equipment, the request being for a quality of experience model, and in response to the request, cause the quality of experience model to be sent to the user equipment.

[0079] The applications may include extended reality applications.

[0080] The network entity device may be a server or provided in a server.

[0081] According to a further aspect, there is provided a computer program comprising instructions which, when executed by an apparatus, cause the apparatus to perform any of the methods listed above.

[0082] According to another aspect, there is provided a computer program comprising instructions which, when executed, cause any of the methods listed above to be performed.

[0083] According to an aspect, there is provided a computer program comprising computer executable code which, when executed, causes any of the methods listed above to be performed.

[0084] According to one aspect, a computer readable medium is provided, comprising program instructions stored thereon for executing at least one of the above methods.

[0085] According to one aspect, a non-transitory computer readable medium is provided, comprising program instructions which, when executed by an apparatus, cause the apparatus to perform any of the methods listed above.

[0086] According to one aspect, a non-transitory computer readable medium is provided, comprising program instructions which, when executed, cause any of the methods listed above to be performed.

[0087] According to one aspect, a non-volatile tangible storage medium is provided, comprising program instructions stored thereon for executing at least one of the above methods.

[0088] In the above, a number of different aspects have been described. It should be appreciated that additional aspects may be provided by combining any two or more of the above aspects.

[0089] Various other aspects are also described in the following detailed description and appended claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Some examples will now be described in more detail, by way of illustration only, with reference to the accompanying drawings, in which:

[0091] Figure 1 Some parts of a communication system supporting XR applications are schematically shown;

[0092] Figure 2 A schematic diagram of the device is shown;

[0093] Figure 3 A schematic diagram of a user equipment is shown;

[0094] Figure 4 According to some embodiments Figure 1 Schematic diagram of some entities in;

[0095] Figure 5 According to some embodiments Figure 1 A diagram of an example architecture for some of the entities in ;

[0096] Figure 6 According to some embodiments Figure 1 Example message exchanges between entities in ;

[0097] Figure 7 The process of reporting different key performance indicators is schematically shown;

[0098] Figure 8 A first method of some embodiments is shown; and

[0099] Fig. 9 A second method of some embodiments is shown. DETAILED DESCRIPTION

[0100] Certain embodiments will be explained below with reference to communication devices capable of communicating via a wireless cellular system and a mobile communication system providing services for such communication devices.

[0101] A communication system based on the fifth generation radio access technology (commonly referred to as 5G system (5GS)) may include a (radio) access network ((R)AN), a 5G core network (5GC), one or more application functions (AFs) and one or more data networks (DNs). A user equipment (UE) may access or connect to one or more DNs via the 5GS.

[0102] The 5G(R)AN may include one or more base stations or radio access network (RAN) nodes, such as gNodeB (gNB). A base station or RAN node may include one or more distributed units connected to a central unit.

[0103] 5GC may include various network functions such as access and mobility management function (AMF), session management function (SMF), authentication server function (AUSF), user data management (UDM), user plane function (UPF), network data repository, network exposure function (NEF), service communication proxy (SCP), edge application server discovery function (EASDF), policy control function (PCF), network slice access control function (NSACF), network slice specific authentication and authorization function (NSSAAF) and / or network slice selection function (NSSF).

[0104] Figure 2 An example of an apparatus 200 for a communication system is shown. The apparatus 200 may be provided, for example, in a core network of a communication system, such as a 5G core network. The apparatus 200 may, for example, include or implement one or more network functions of a control plane of a communication system. The apparatus 200 may have at least one processor and at least one memory storing instructions of one or more network functions, which instructions, when executed by at least one of the at least one processor, cause the operation or action of the one or more network functions to be performed. In this example, the apparatus may include at least one random access memory (RAM) 211a and / or at least one read-only memory (ROM) 211b. The apparatus may include at least one processor 212, 213 and / or an input / output interface 214. At least one processor 212, 213 may be coupled to at least one memory, which in this example is a RAM 211a and a ROM 211b. At least one processor 212, 213 may be configured to execute appropriate software code 215. The software code 215 may, for example, allow the apparatus to perform one or more steps of one or more aspects of the present invention.

[0105] Figure 3An example of a communication device 300 is shown. The communication device 300 may be any device capable of or configured to send and receive wireless signals (including radio signals). The communication device may be an XR (extended reality) device, such as a headset, or may be capable of supporting XR applications (e.g., capable of executing or running XR applications). The headset may be a VR headset. Some other examples of XR applications will be discussed later. Other non-limiting examples of the communication device 300 include a mobile station (MS) or mobile device, such as a mobile phone or so-called "smart phone", a computer provided with a wireless interface card or other wireless interface facility (e.g., a USB dongle), a personal data assistant (PDA) or tablet, a machine type communication (MTC) device, a cellular Internet of Things (CIoT) device, or any combination of these, etc.

[0106] The communication device 300 may be a combination of an XR device and a communication device. For example, the communication device may be provided by a combination of a head mounted device (HMD) and a smart phone.

[0107] The communication device 300 may be configured to send or receive wireless signals, such as radio signals, that carry communications. The communications may be one or more of voice, electronic mail (email), text messaging, multimedia, data, machine data, and the like.

[0108] The communication device 300 may be configured to send and / or receive radio signals via a transceiver device 306 over an air or radio interface 307. The transceiver device 306 may include, for example, a radio portion and an associated antenna arrangement. The radio portion may convert baseband signals to radio frequencies and / or vice versa. The antenna arrangement may be arranged internally or externally to the mobile device and may include a single antenna or multiple antennas. The antenna arrangement may be an antenna array including multiple antenna elements.

[0109] The communication device 300 may include at least one processor 301 and / or at least one memory. The at least one memory may be at least one ROM 302a and / or at least one RAM 302b. Other possible components 303 may be provided for software and hardware assistance in performing the tasks it is designed to perform, including controlling access and communication to access networks (such as 5G RAN and other communication devices). At least one processor 301 is coupled to RAM 302b and ROM 302a. At least one processor 301 may be configured to execute instructions of software code 308. The execution of the instructions of software code 308 may, for example, allow the communication device 300 to perform one or more operations. The software code 308 may be stored in ROM 302a. It should be understood that in other embodiments, any other suitable memory may be used alternatively or additionally.

[0110] The at least one processor 301 , the at least one ROM 302a and / or the at least one RAM 302b may be provided on a suitable circuit board, in an integrated circuit and / or in a chipset. This feature is indicated by reference numeral 304 .

[0111] The communication device 300 may optionally have a user interface, such as a keyboard 305, a touch screen or touch pad, a combination thereof, etc. Optionally, the communication device may have one or more of a display, a speaker, and a microphone.

[0112] In the following examples, the term UE or user equipment is used. This term covers any example of the communication device 300 discussed previously and / or any other communication device. The term UE also covers examples where the communication device itself is an XR device or an XR device combined with a smartphone or the like.

[0113] The radio access technology currently standardized by 3GPP is generally referred to as 5G or NR. Other radio access technologies standardized by 3GPP include Long Term Evolution (LTE) or LTE Advanced Pro of Universal Mobile Telecommunications System (UMTS). A communication system (such as a 5G system) typically includes an access network, such as a radio access network operating based on the radio access technology, which includes base stations or radio access network nodes.

[0114] A communication system (such as a 5G system) may alternatively or additionally include other types of access networks, such as a wireless local area network (WLAN) and / or a WiMAX (Worldwide Interoperability for Microwave Access) network, which connects the UE to a data network to provide the UE with access to the data network and / or the core network via a Non-3GPP Interworking Function (N3IWF), a Trusted Non-3GPP Gateway Function (TNGF) or a Wired Access Gateway Function (W-AGF).

[0115] It should be understood that the example embodiments may also be used with standards for future radio access technologies (eg, 6G and beyond).

[0116] The communication system may support services and applications that have relatively high requirements on the communication system bandwidth. An example of such an application is an XR application.

[0117] Reference now Figure 1 , which schematically illustrates certain parts of a communication system that can support XR applications. Figure 1 The communication system shown in may operate based on a 5G radio access technology (eg, may be 5GS as described above). Figure 1 As shown, UE 500 is provided with XR application 400, network as code (NaC) API 406, and QoE (quality of experience) modules 506 and 508. UE can generally be as described in Figure 3 The XR application 400, the NaC API 406, and the QoE modules 506 and 508 will be described in more detail later.

[0118] Figure 1 The communication system (e.g., 5GS) shown includes RAN 100 and a core network (e.g., 5GC), which includes various network functions including UPF 102, NEF 106, and PCF 108. For ease of illustration, other network functions of the core network (e.g., 5GC) are not shown in FIG. Figure 1 Displayed in.

[0119] A QoE server 512 may be provided. The QoE server 512 may be provided in a trusted computing system (e.g., a server) located in the external data network 104, or provided in a multi-access edge computing (MEC) system located at the edge of the communication system in the external data network 104. The trusted computing system may be a computing system in which the UE accesses the communication system (e.g., 5GS) via a 3GPP access and security server. The QoE server 512 will be described in more detail later.

[0120] In the MEC (Multi-Access Edge Computing) system 520, the AI ​​algorithm 402, the NaC API 408 and the QoE module 526 are provided. In some embodiments, the MEC system 520 may be provided in an external data network and connected to the UPF 102 of the core network via the N6 interface of the communication system.

[0121] Figure 1 The communication system (e.g., 5GS) shown may support XR applications or XR services provided to XR users by UE 500. Other embodiments of the communication may support applications or services other than XR applications or XR services (e.g., non-XR services and non-XR applications).

[0122] XR is an umbrella term and includes at least the following types of reality: augmented reality (AR), in which virtual objects are added to the real-world environment; virtual reality (VR), in which visual and audio scenes are combined with real-world locations; and mixed reality (MR), in which touch and interactivity are added to the real-world environment.

[0123] Some embodiments of the communication systems (e.g., 5GS) described herein may additionally or alternatively support non-XR applications or non-XR services. For example, embodiments of the communication system may support non-XR services, wherein a portion of the non-XR services are supported by the MEC system 520 and / or a portion of the non-XR services are supported by one or more network functions of a core network (e.g., 5GC) of the communication system (e.g., 5GS). Non-XR services may be services that require the communication system to have relatively high resource requirements and / or strict latency requirements to support the non-XR services.

[0124] Reference again Figure 1 , a communication system (e.g., 5GS) may be used to provide XR services of an XR service provider to an XR application 400 running on a UE 500. A user (e.g., a human) uses an XR service (e.g., an XR game) provided by an XR application 400 running on a UE 500. As described herein, the UE 500 may be an HMD, or may include a headset, such as an HMD, and a user of the XR service (generally referred to herein as an XR user) may wear the headset and use the headset (e.g., HMD) to use the XR service provided by the XR application 400. The communication system for providing XR services to an XR application 400 running on a UE may be part of a mobile telecommunications network and is referred to as a service network. The communication system (e.g., a core network) of the service network may provide a quality of service flow for traffic of an XR application 400 sent to the communication system of the service network. The XR user may experience the quality of experience. The quality of experience may be considered as the degree of pleasure or annoyance associated with the use of XR. The quality of experience (QoE) associated with the XR service is determined by a QoE model. QoE can be a measure of the pleasure or annoyance associated with the use of the XR service experienced by the XR user. The QoE model can be a parametric model. Given one or more key performance indicators (KPIs) as input to the QoE model, the QoE model outputs QoE.

[0125] Currently, for XR applications 400 running on UE 500, most of the computation is performed on the headset. Some XR applications are based on a 3D gaming paradigm, where immersive content is presented on a headset (e.g., HMD (head mounted display)), and the only communication requirement is to exchange game data between players via a communication system, or to utilize XR services provided by the XR service provider's cloud (e.g., cloud computing system).

[0126] This paradigm is changing as more advanced XR services are developed. While the final rendering of the 3D space may still occur on the HMD, some XR services may require more use of network entities of the radio access network and / or core network of the communication system providing the XR service of the XR service provider for rendering. Some rendering examples are described in 3GPP TS26.918 and 3GPP TS26.928.

[0127] For example, it may be necessary to offload part of the processing related to rendering (referred to as rendering-related processing) to an edge cloud (e.g., a cloud computing system located at the edge of a 5G communication system, such as Figure 1 The MEC 520 of the HMD). Offloading of portions of the rendering related processing is often referred to as "split rendering". Split rendering allows computationally intensive algorithms used in performing rendering related processing to be performed on the edge cloud rather than in the HMD. The HMD may not have sufficient processing power (e.g., it may not have a sufficient processor or a powerful GPU (graphics processing unit) to execute the computationally intensive algorithms used in performing rendering related processing).

[0128] Segmented rendering may require the XR application 400 to transmit complex video scenes remotely to the MEC system 520 via network communication. Complex video scenes may include the capture of 360-degree scenes, real-time capture and transmission of volumetric video-based virtual images and / or digital twins. It may be necessary to combine one or more of the 360-degree scenes, volumetric video-based virtual images and / or digital twins.

[0129] In the example of segmented rendering, the rendering-related processing may include performing semantic segmentation on an image (or multiple images) of a local scene captured by one or more cameras on an HMD mounted at the edge cloud. For example, semantic segmentation may be performed by Figure 1 The AI ​​algorithm (or AI model) in the MEC 520 in the example shown is executed. In mixed reality applications, the local environment is enhanced with virtual objects (augmented reality), or some elements of the local environment are introduced in the virtual experience (augmented virtuality). For example, a player may be able to see his or her own body while immersed in the VE.

[0130] To merge the local environment and the virtual environment (VE), a scene in the local environment is captured as an image (or a sequence of images (e.g., a video)) by one or more cameras of the HMD. The image (or sequence of images) is analyzed using an algorithm running on a computer (or an AI model deployed on a computer). The algorithm determines which pixels in the image (or sequence of images) are to be integrated into the VE based on the analysis. The decision about which pixels are to be integrated into the VE can be made using an algorithm, such as a deep learning algorithm (e.g., semantic segmentation), which receives an image (or a sequence of images (e.g., a video)) from one or more cameras of the HMD and creates a transparency mask for the scene that can be added to the VE. The XR application can be provided on the HMD, and the algorithm can be provided on the HMD. Figure 1 The example shown runs on the MEC system 520.

[0131] For complex XR applications, such as those using segmented rendering, offloading algorithms to the edge cloud (or deploying AI models (e.g., neural network models) on the edge cloud) is to provide sufficient processing power for the execution of the algorithms (or AI models). For example, an image (or image sequence (e.g., video)) may need to be analyzed in real time using a deep learning algorithm (e.g., semantic segmentation) and captured by a camera with a sufficiently high frame rate. Therefore, the image (or image sequence) is provided by the HMD to the serving network. The UE 500 running the XR application 400 (e.g., and the network serving the HMD UE 500 (e.g., HMD)) needs to support uplink traffic peaks of, for example, on the order of gigabits per second and have a round-trip time (RTT) of, for example, a few milliseconds to the MEC system 520 to ensure that the image (or image sequence) is analyzed in real time.

[0132] XR applications (such as XR application 400) that use split rendering rely on the infrastructure of a network including a communication system (such as the 5GS described above). Therefore, when using split rendering, there are one or more constraints that the XR application (e.g., XR application 400) needs to consider. The constraints can be the bandwidth and / or latency of the network, and / or the computing power (or equivalently, energy consumption) of the edge cloud (e.g., MEC system 520).

[0133] Some embodiments of the present disclosure may provide a mechanism for indicating the relationship between the above constraints and their impact on quality of experience (QoE). The mechanism may be used to determine network size, operate and / or monitor the network. Some embodiments may use a QoE model or function to determine QoE.

[0134] QoE modeling can provide a statistical model (commonly referred to as a QoE model) that allows a network including a communication system (such as the above-mentioned 5GS) to be controlled or even designed to support a desired QoE level (e.g., the network can be controlled or designed to ensure that the network has sufficient resources (e.g., bandwidth, latency, etc.) to provide sufficient QoE to XR users). Different types of XR applications may require different QoE models. The QoE model can be provided by a QoE module.

[0135] Some embodiments may make QoE models available to XR applications.

[0136] Some embodiments may allow an XR application to request that a desired QoE be supported by the network.

[0137] XR applications can be supported by specialized network services such as network slicing.

[0138] Some embodiments may be used with one or more of the following:

[0139] XR in progress;

[0140] XR and cloud gaming;

[0141] XR – Edge Cloud – Mobility;

[0142] Enabling mobility for future Metaverse and XR applications; and / or

[0143] Edge cloud and network slicing.

[0144] As described above, split rendering may require coordination between the XR application 400 and the network communicating with the MEC system. The network includes a communication system, and the UE 500 (which may be or include an HMD) hosting the XR application 400 communicates with the MEC system 520 via the communication system (e.g., sending (multiple) images for rendering related processing). This may make it possible for the XR application 400 to provide XR services with sufficient QoE to XR users under different network conditions.

[0145] Some embodiments allow the XR application 400 to communicate with the network. In some embodiments, the XR application 400 can communicate with the communication system service network via an API (application programming interface). The XR application 400 can report the QoE experienced by the XR user while the XR application 400 is running. The XR application 400 can report QoE via the API.

[0146] The XR application 400 may request some KQIs to meet the level of QoE required by the XR application 400. The XR application 400 may request the KQIs via an API.

[0147] In some embodiments, the communication system can be configured to understand the QoE being experienced by the XR user. This can be used for monitoring purposes and / or determining the size of the communication system and / or balancing the resources (e.g., bandwidth, latency) of the network including the communication system for UEs of different XR users.

[0148] As discussed, in some embodiments, a QoE model or function may be used to determine the QoE being experienced by an XR user. The QoE model or function may be adapted to different workloads and / or use cases. The QoE model or function may capture the QoS-to-QoE relationship required by the XR application.

[0149] refer to Figure 4 , which schematically shows an overview of an XR application 400 , an AI algorithm 402 , and a QoE model 404 .

[0150] In this example, semantic segmentation is performed for a frame (e.g., image) received from an XR application 400. Semantic segmentation is the process of assigning a class label to each pixel in a frame (e.g., image) and may be performed using an AI algorithm 402, which may be a deep learning algorithm. Examples of such deep learning algorithms are known and are therefore not described in detail.

[0151] In some embodiments, an API is provided to enable the XR application 400 and the AI ​​algorithm 402 to facilitate communication with each other. The API may be a network as code (NaC) API. The NaC API facilitates network programmability by making one or more APIs available, which may be used by the XR application 400 or other applications (e.g., 5GC) that may require network programmability in the core network.

[0152] Some embodiments may provide a NaC API 406 in a UE including an XR application 400 , and provide a NaC API 408 in a MEC system 520 including an AI algorithm 402 .

[0153] The NaC API may allow the QoE being experienced in the XR application to be reported to the QoE module.

[0154] The NaC API may allow QoS KPIs (Quality of Service Key Performance Indicators) to be reported. These QoS KPIs may be network-related KPIs or stream-related KPIs. These QoS KPIs may be frame size, round-trip time (RTT), etc. The QoS KPIs may be reported by the NaC API 406 and / or by the NaC API 408.

[0155] The API may request targets for one or more parameters. For example, the API may request one or more target key quality indicators (KQIs) from the network's communication system. The API may request the target KQI in a manner understood by the XR application 400. The target KQI may be a target resolution and / or frame rate for a frame (e.g., an image). The target KQI may be requested by the NaC API 406. Using the information provided, the QoE server 512 may be able to do one or more of the following: monitor the level of QoE supplied to the XR service provided by the XR application 400 to the XR user; and / or reserve one or more appropriate QoS parameters (e.g., 5QI (5G QoS identifier)) to satisfy the request made by the XR application 400 (XR application request) to call the API's function.

[0156] A QoE model or function 404 is provided. The QoE model or function 404 will be discussed in more detail later. The QoE model or function 404 may be available at the UE 500 and deployed on a computer or computing system, such as a server (referred to herein as a QoE server). The QoE model or function 404 available at the UE 500 may allow the XR application 400 to request an appropriate KQI for a target QoE value. The QoE model deployed at the QoE server 512 may request associated network resources based on a requested target for one or more parameters to support the target QoE. For example, this may be to provide resources that can at least support a given bit rate. The bit rate may be a guaranteed bit rate. For example, the QoE server 512 may request an associated 5QI based on the requested KQI.

[0157] In some embodiments, the QoE model may be a parameter model. In other embodiments, the QoE model may be an AI / ML model. In other embodiments, the model may be a neural network model.

[0158] A cloud application programming interface or API 410 is provided via which appropriate QoS parameters can be requested.

[0159] Reference now Figure 5 , which shows examples of hardware and software of a UE 500 that provides an XR application 400, a MEC 520 that runs an AI algorithm 402, and a QoE server that supports a QoE model or function.

[0160] In this example, there is a distributed rendering XR system. An XR application 400 is running on a UE 500. The UE 500 may be, for example, an HMD on its own or an HMD operating in conjunction with another communication device.

[0161] The AI ​​algorithm 402 runs on a MEC system 520 located at the edge of the network. For example, the AI ​​algorithm 402 may be provided by a mobile edge computing (MEC) system 502, such as Figure 1 shown.

[0162] UE 500 includes a first module 504. The first module 504 can encode and package the video and / or decode and unpack the video. This allows the frames captured by the camera 501 of the UE and the generated segmentation mask to be exchanged between the XR application 400 and the AI ​​algorithm 402 through a network including the above-mentioned communication system (e.g., 5GS). The XR application 400 can pass the frame captured by the camera 501 to the first module 504 via the second API 505. The first module 504 can pass the semantic mask received from the AI ​​algorithm 402 via the second API 505 to the XR application.

[0163] UE 500 includes a second module 510, which is a UDP / TCP (User Datagram / Transmission Control Protocol) transmission module. The second module 510 processes the data received from the first module 504 into a form suitable for transmission through the network. The data is transmitted to the AI ​​algorithm 502 through the network. The second module 510 processes the data received from the AI ​​algorithm 502 via the network and passes the received data to the first module 504. The received data is semantic mask data.

[0164] In this example, the NaC API included in the UE 500 has a first NaC API 406a and a second NaC API 406b. The first NaC API 406a and the second NaC API 406b may be considered as a part of the NaC API.

[0165] The first NaC API 406a may provide one or more of the following functions:

[0166] a. The first NaC API 406a can report QoE. QoE can be reported as a score. The score can be reported on a scale from a to n. a and n can be integers. By way of example only, the scale can be 1 to 5. The score can be a MOS (mean opinion score) score. The score can correspond to a given time. For example, the score can correspond to the last x seconds, where x is a numerical value. For example, the first NaC API 406a can report QoE by calling the reportQoE (score, time) function.

[0167] b. The first NaC API 406a may request sufficient QoS to support a process performed by the XR application. For example, the process may be a process for split rendering (i.e., a split rendering process). The request may be for sufficient QoS to support the process at a given frame (e.g., image) resolution and / or frame rate (e.g., the number of frames captured by the HMD's camera over a period of time). The request may be a KQI request. The KQI request may be provided using a KQI (resolution, fps (frames per second)) function. The request (e.g., a KQI request) may meet the target QoE required by the XR application 400.

[0168] The second NaC API 406b may provide one or more of the following functions:

[0169] a. The second NaC API 406b may report the sending of a single frame (e.g., image) to the AI ​​algorithm 402 running on the MEC system 520. This is a frame (e.g., image) captured by the camera 501 of the UE 500. The report may include one or more of the following: a timestamp indicating the time when the frame (e.g., image was captured by the camera 510 of the UE 500); the resolution of the frame (e.g., image) in pixels; the size of the frame (e.g., image) in bytes; and the encoding delay overhead added by encoding and packing the frame (i.e., image). The report may be sent in response to calling the reportFrame(resolution, bytes, delay, timestamp) function.

[0170] b. The second NaC API 406b may report the receipt of an individual segmentation mask. The report may include one or more of the following: a timestamp indicating the time the segmentation mask was received; the resolution of the segmentation mask in pixels; the size of the segmentation mask in bytes; the encoding delay overhead added by the decoding and unpacking process for the segmentation mask; and the total (application-level) RTT (i.e., the time difference compared to when the associated frame (i.e., image) from which the segmentation mask was generated was reported). The report may be sent by calling the reportMask(resolution, bytes, delay, RTT, timestamp) function.

[0171] The UE 500 includes a KPI reporting module 506 and a QoE model or function module 508. The KPI reporting module 506 and the QoE model module 508 interact with the XR application 400 via the NaC API 406.

[0172] The KPI reporting module 506 collects information related to the XR application 400, which will be sent to the QoE server 512. The information related to the XR application 400 may be provided to the KPI reporting module 506 via the first NaC API 406a.

[0173] The XR application 400 reports the QoE experienced in the XR application to the KPI reporting module 506 via the NaC API 406 a.

[0174] The QoE model or function 516 provided by the QoE module 508 is used by the XR application 400 to determine the QoE.

[0175] The XR application 400 sends the requested KQI via the first NaC API 406a to the KPI reporting module 506. The requested KQI is determined using a QoE model or function.

[0176] The QoE module 508 provides a QoE model. The model can be updated locally using the KPI information received from the KPI reporting module. The update of the QoE model can be performed in the QoE module 508 and / or by the XR application 400.

[0177] The AI ​​algorithm 402 is provided by the MEC system 520. The UE 500 communicates with an access point or access node, such as a gNB or other base station of an access network of a communication system. The access point communicates with the 5GC, and the 5GC communicates with the MEC system 520. The 5GC establishes a data session between the UE 500 and the UPF of the 5GC so that the UE 500 sends data to the MEC system 520 and receives data from the MEC system 520.

[0178] The MEC system 520 includes a third module 522. The third module 522 may encode and pack and / or decode and unpack a video (e.g., a frame) for a semantic mask received from the XR application 400 of the UE 500. This allows the video (e.g., a frame) captured by the camera 501 of the UE 500 and the semantic mask generated by the AI ​​algorithm 402 running on the MEC system 520 to be exchanged through the communication system of the network. The frame or frames of the video are captured by the camera and provided to the AI ​​algorithm via the XR application 400, the API 505, the second module 510, the network between the UE 500 and the MEC 520, the fourth module 524, the third module 522, and the API 520.

[0179] The AI ​​algorithm 402 receives a frame (e.g., image) captured by the camera 501 of the UE 500 and sent by the XR application 400 from the third API 520. The AI ​​algorithm 402 provides a semantic mask determined by processing the received video (e.g., frame) to the third module 522 via the third API 520. The semantic mask is provided to the XR application by the AI ​​algorithm via the API 520, the third module 522, the fourth module, the network between the MEC 520 and the UE 500, the second module 510, and the API 505.

[0180] The MEC system 520 includes a fourth module 524, which is a UDP / TCP (User Datagram / Transmission Control Protocol) transmission module. The fourth module 524 processes the data received from the third module 522 into a form suitable for transmission through the communication network. The processed data (e.g., semantic mask) is transmitted to the XR application 400 through the communication network. The fourth module 524 processes the data (e.g., semantic mask) received from the communication network and passes the received data to the third module 522. The received data is frame data (commonly referred to as frame data).

[0181] The MEC system 520 includes a NaC API 408. The NaC API 408 of the MEC system 520 reports the time taken to process a single frame (e.g., a single image) end-to-end and return a segmentation mask for the single frame (e.g., a single image). The time taken to process a single frame (e.g., a single image) end-to-end may include encoding and decoding delays. The report may be provided by calling the reportProcess(delay, timestamp) function.

[0182] The MEC system 520 includes a KPI reporting module 526. The KPI reporting module collects information or KPIs such as previously discussed from the AI ​​algorithm and sends it to the QoE server.

[0183] In some embodiments, a QoE server 512 is provided. The QoE server 512 may be provided by an application server or by a dedicated QoE server. In some embodiments, the application server may have access to a QoE model or function, which may be part of or separate from the application server. Hereinafter, the server will be referred to as a QoE server.

[0184] In some embodiments, the MEC system 520 communicates with the QoE server 512 via a network.

[0185] The QoE server 512 is provided with a KPI storage module 514 and a QoE model module 516. The QoE model module 516 contains a QoE model or function. The QoE model or function is updated using the KPI information received from the KPI reporting modules 506 and 526. The KPIs received from the KPI reporting module 506 of the UE 500 and the KPI reporting module 526 of the MEC system 520 can be stored in the KPI storage module 514 of the QoE server 512. Using this QoE model or function, the system is able to process the KQI request from the XR application and convert it into a QoS request for the 5G core (or general transport network).

[0186] The QoE modules 508 and 516 store QoE models or functions associated with the XR applications.

[0187] In this example, UE 500 may communicate with MEC system 520 via a network including a 5G / 5G-advanced communication system. However, in other embodiments, UE 500 may communicate with MEC system 520 via any other suitable communication system supporting QoS policies.

[0188] refer to Figure 6 , which illustrates an example message exchange of some embodiments.

[0189] Upon initialization, the QoE module 508 of the UE 500 acquires a generic QoE model for XR services.

[0190] At S1, the QoE module of the UE 500 sends a request for a QoE model or function to the QoE server 512. The request for a QoE model or function may be sent by the UE 500 calling a REQUEST_QOE_MODEL function, such as Figure 6 shown.

[0191] At S2, the QoE server provides the requested QoE model or function to the UE 500. The QoE model or function is stored in a QoE module at the QoE server.

[0192] The services provided by the XR application start running, and the KPIs are reported and stored in the QoE server 512 .

[0193] At some point, the XR application 400 will require a certain level of QoE and may request a certain level of QoE by calling the REQUEST_KQI function. The XR application 400 will set a target quality level (Q) and will use its QoE model or function to determine, for example, the required values ​​for the bitrate, mask, and / or total end-to-end latency for a frame.

[0194] At S3 , the XR application 400 provides a request for one or more KQIs to the QoE module 508 of the UE 500 .

[0195] At S4, the QoE module 508 of the UE 500 sends a request for one or more KQIs to the QoE server 512. The request for one or more KQIs can be sent to the QoE server 512 via a cloud API. The cloud API can be an HTTP (Hypertext Transfer Protocol) / REST (Representational State Transfer) API. It is the communication between the QoE module in the UE and the QoE server. From the total end-to-end delay, the QoE module in the QoE server 512 can subtract the average processing time in the QoS server and the UE 500 to obtain the target delay for the network (commonly referred to as network delay). The QoE module of the QoE server 512 uses the QoE model or function at the QoE server 512 to request the required level of throughput and delay from the core network (e.g., 5GC) of the communication system.

[0196] From the total end-to-end delay, the QoE module 516 subtracts the average processing time in the MEC system 520 (e.g., the average time required for processing by the AI ​​algorithm 402 running on the MEC system 520) and the average processing time in the UE 500 to obtain the target network delay. Finally, the QoE module requests the desired level of throughput and delay from the network (REQUEST_5QI).

[0197] At S5, the QoE server 512 sends a request for the determined 5QI to the 5GC.

[0198] At S6, the 5GC sends an acknowledgement to the QoE server, indicating that the requested KQI or KQIs have been authorized.

[0199] At S7, the QoE server 512 sends an indication to the QoE module 508 of the UE 500 that the one or more KQIs have been authorized.

[0200] At S8 , the QoE module 512 of the UE 500 sends an indication to the XR application 400 that one or more KQIs have been authorized.

[0201] During the above process, both the general QoE model stored in the QoS server 512 and the local version of the QoE model maintained by the UE 500 may be updated.

[0202] It should be appreciated that any other suitable module or portion of UE 500 may be used to formulate and / or send a request for a QoE model.

[0203] The request for KQI will be based on the stored QoE model. It should be understood that any other suitable module or part of UE 500 can be used to send the request for KQI to the core network (e.g., 5GC) of the communication system.

[0204] It should be appreciated that any other suitable module or portion of the UE 500 may be used to receive the requested KQI for the network and / or provide the information to the XR application.

[0205] Reference for reporting different KPI events Figure 7 is described.

[0206] At T1 , a frame (eg, image) is sent by the XR application 400 running on the UE 500 to the AI ​​algorithm 402 running on the MEC system 520 .

[0207] As shown at T2 , whenever a frame (eg, image) is sent by the XR application 400 , the frame (eg, image) is sent to the KPI reporting module 506 by the UE 500 calling the ReportFrame() function.

[0208] At T3, the KPI reporting module 502 reports the KPI for the frame (eg, image) to the QoE server 512. The KPI may be stored in a KPI storage of the QoE server 512.

[0209] At T4 , the AI ​​algorithm 402 generates a semantic mask for the frame (eg, image) and sends the semantic mask to the XR application 400 .

[0210] At T5, when the semantic mask is received by the XR application 400, the XR application 400 reports the semantic mask to the KPI reporting module 506 in a ReportMask message. In some embodiments, the semantic mask can be reported by the XR application 400 calling the ReportMask() function, such as Figure 6 shown.

[0211] At T6, the AI ​​algorithm 402 sends a report of its processing time (e.g., the time taken to process a frame (or frames) received from the XR application 400) to the KPI reporting module of the MEC system 520. The AI ​​algorithm 402 can report the processing time by calling the ReportProcess(delay, timestamp) function, such as Figure 6 shown.

[0212] At T7, the KPI reporting module 526 of the MEC system 520 reports the processing time reported by the AI ​​algorithm 402 to the QoE server 512. The reported processing time may be stored in the KPI storage 514 of the QoE server 512.

[0213] It will be appreciated that T4 and T5 may typically occur in parallel with T6 and T7.

[0214] As a result of the above-described reporting functionality, network KPIs related to the processing of frames (e.g., images), including compression of frames (e.g., images), transmission of frames to and from UE 500 to MEC system 520 via the network's communication system, and semantic segmentation of frames (e.g., images) performed by AI algorithm 402 may be stored. The network KPI may be one or more of: bandwidth, PPS (packets per second), and / or end-to-end latency (e.g., the sum of all latency involved in processing a frame (e.g., image)).

[0215] The network KPIs may be stored in the KPI storage 514 of the QoE server 512 .

[0216] At T9, when the XR application 400 reports a QoE message (eg Figure 6 When the QoE value is reported to the KPI reporting module 506 in the ReportQoE() message shown in , the KPIs from the time period covered by the ReportQoE() message are used to update the values ​​of the local QoE model stored in the UE 500, as referenced at T11.

[0217] At T10, the KPI reporting module 506 reports the QoE generated by the local QoE model to the QoE server 512. The QoE model in the QoE server 512 is also updated.

[0218] In this example, the KPI reporting module 506 is shown interacting with the XR application 400. In some embodiments, the KPI reporting module 506 may store the KPIs, and one or more reporting functions may be performed by any other suitable module or portion of the UE 500.

[0219] In this way, it is possible to use a combination of XR user-related KPIs (i.e. KPIs for each XR user) and platform-wide or deployment-wide (i.e. KPIs common to all XR users of the communication system) KPIs. It is also possible for a QoE model to have a combination of XR user-related parameters and platform-wide parameters. This provides flexibility.

[0220] Any suitable QoE model may be used.

[0221] In some embodiments, one or more perception parameters of the QoE model are updated and processed on a deployment basis.

[0222] The parameters of the QoE model can be per deployment or per user. Per deployment means that all users in the same deployment share the same values ​​for those parameters. The parameters of each deployment are updated in the model in the QoE server entity. The parameters of each deployment are not updated by the UE. The UE can receive updates for each deployment from the QoE server entity. Per user means that the parameters are updated by the UE to the QoE model running on the UE. Each user can have its own values ​​for these parameters.

[0223] An example of a QoE model is now described.

[0224] The QoE model is a first-order parametric model governed by the following equation:

[0225] Q=M(R)=M(1-I V，f -I V,m -I D )

[0226] in:

[0227] Q is the QoE rating within a defined scale. The defined scale can be from 1 to 5. The defined scale can provide an ACR (Absolute Category Rating).

[0228] M is a function.

[0229] R is the transmission rating on a scale of 0-1, where 0 is the lowest quality and 1 is the highest quality.

[0230] This model implies that the communication system (e.g., 5GS) is configured to have high quality, but will be affected by the following factors:

[0231] The visual quality of the frame (I V,f )

[0232] The visual quality of the mask (I V,m )

[0233] End-to-end delay (I D ).

[0234] Visual quality can be modeled using an exponential rate-distortion relationship

[0235]

[0236] in

[0237] B is the bit rate

[0238] PPS is pixels per second, which is the product of resolution and frame rate.

[0239] α is a parameter of the model (αf is used for frames and αm is used for masks, with different values).

[0240] Over a period of time, the bitrate B is calculated as the number of bits sent during that period (obtained from the field "Bytes" in the report Frame / report Mask call) divided by the period of time, while the frame rate is obtained by dividing the number of calls of the reportFrame and / or reportMask functions by the period of time.

[0241] The effect of delay is modeled using a logistic curve:

[0242]

[0243] in:

[0244] T is the end-to-end delay, and β and θ are parameters. The end-to-end delay is the RTT value from the call to the reportMask function. β and θ are parameters that can be learned during model training.

[0245] So Q can be rewritten as:

[0246]

[0247] α is a parameter that can be learned during model training.

[0248] The function M is the R-to-MOS transformation and has the following format:

[0249] M(R)=Q min +R(Q max -Q min )+aR(Rb)(1-R)

[0250] Where Qmax, Qmin, a, and b are parameters. The values ​​of these parameters (e.g., the values ​​of Qmax, Qmin, a, and b) are learned during model training. These values ​​can be updated during use. Qmax and Qmin are the maximum and minimum expected values ​​of M (i.e., the edges of the MOS rating, usually around 1 and 5). a and b are parameters that modify the shape of the curve (i.e., how it deviates from a linear function).

[0251] The R-to-MOS transformation may be based on the function proposed in the ITU-T E model and may be backward compatible therewith (if Qmin=1, Qmax=4.5, a=7 and b=0.6).

[0252] When an application reports QoE values ​​using ReportQoE(), the KPIs from the period covered by ReportQoE() are used to update the values ​​of the parameter model (i.e., QoE model), whether in a central server or in a local (per UE) model. In this way, a combination of user-related and platform-wide parameters can be used to achieve maximum flexibility.

[0253] In some embodiments, the perception parameters (α, β, and θ) are updated and processed on a per-deployment basis.

[0254] In some embodiments, the parameters of the R-to-MOS function (Qmax, Qmin, a, b) are processed on a per-user basis.

[0255] When RequestKQI() is called from the application, it uses the QoE model to calculate the requested bitrate (B) and end-to-end latency (RTT) from the application's perspective. It then maps this to the network level throughput (B N ) and latency (RTT N ), such that:

[0256] -B N =B

[0257] -RTT N =RTT–delay Frame --delay Mask -delay Process

[0258] Where delay Frame 、delay Mask and delay Process is the average of the "latency" values ​​obtained from the reportFrame, reportMask, and reportProcess calls.

[0259] Before the system can process the Request KQI() message, initial values ​​of the model parameters should be provided to the QoE server.

[0260] In some embodiments, the application may be considered to have knowledge about the user's QoE, including the user's experience at a given time and the user's needs.

[0261] Applications can directly report on QoE levels, rather than in terms of required KPIs.

[0262] Applications can request KQIs in application aspects, and these KQIs are automatically converted into KPIs related to the network (e.g., 5GS) that includes the communication system (generally referred to herein as network KPIs).

[0263] In some embodiments, the perceptual attributes are used to create a QoS-to-QoE model. The QoS-to-QoE model may be applicable to any split rendering use case where image quality and end-to-end latency are relevant parameters.

[0264] These perceptual functions can be converted into user opinion scores using the R-to-MOS function.

[0265] In some embodiments, relatively few parameters are used so that the QoE model can capture the most relevant QoS-to-QoE relationship without overfitting. The QoE model can be trained using relatively few samples. The QoE model can be trained using nonlinear least squares minimization techniques. Thus, a QoE model for each user (or each user group) can be provided.

[0266] Some embodiments may provide a relatively simple QoE model.

[0267] I v and I p It has been simplified to select specific parameters.

[0268] The R-to-MOS equation is described in ITU-T G.107, ITU.

[0269] In some embodiments, one or more of the NaC APIs discussed previously allow for reporting of QoE for XR applications.

[0270] The API allows XR applications to report QoE metrics.The NAC API may be called from the NEF and NRF of a communication system (eg, a core network of the communication system).

[0271] NRF (Network Repository Function): This is used to index all the APIs of the network functions (NFs) that can access the core network (e.g., 5GC) of the communication system. NRF provides information about each NF available in the core network. This information is used by the network functions (e.g., SMF, AMF, PCF) of the core network. NF management, discovery, and authorization are done through NRF.

[0272] NEF (Network Exposure Function): This is available between the 5G Core Network and 3GPP entities that need access to 5GC or application functions. Applications that need access to the internal data of the 5GC need to go through NEF. This is the case for XR applications, for example.

[0273] APIs may be used for service-based interfaces. APIs for some embodiments may define NEF northbound APIs, which are a set of APIs that define related processes and resources for interaction between different core network elements. For example, as defined in TS29.522, each new API has a resource, a method to get the resource (e.g., HTTP method), and what type of data model (data type) is defined for those resources.

[0274] Table 1 below shows an API list for some embodiments of the API. This API list can be used by other network functions and solutions of 5GS (such as network as code)

[0275]

[0276]

[0277] These processes are used by the NF to authorize requests and forward requests for network slice instance management via the NEF.

[0278] To request XR QoE for an XR application, the NF shall send an HTTP POST message to the NEF to the resource "XR Application Instance". The HTTP POST request message may include an XRApplicationtData structure, which may include:

[0279] - application identifier as the "appId" attribute;

[0280] And may include:

[0281] - QoE as the "QoEType" attribute;

[0282] The following describes the structure of resource URIs and HTTP methods used by the "XRApplicationQoE" API.

[0283]

[0284] The data type (datatype) XRApplicationtData is defined as follows.

[0285]

[0286]

[0287] Table 1 XR application QoE data

[0288] The following table provides an overview of the resources and HTTP methods available for the NSIManagement API.

[0289]

[0290] The XR Application QoE resource allows the AF to request QoE for the application.

[0291] Resource URI: {apiRoot} / xrapplicationqoe / v1 / {afId} / qoe

[0292] name Data Types definition afId String Identifier of AF.

[0293] Resource method (GET method)

[0294] The GET method allows reading all active configurations for a given AF. The AF shall initiate an HTTP GET request message and the NEF shall respond to it.

[0295] GET Method

[0296] name Data Types Cardinality describe N / A

[0297] GET request body

[0298] Data Types P Cardinality describe N / A

[0299] GET response body

[0300]

[0301] Resource method (POST method)

[0302] The POST method creates a new resource for a separate XR application QoE for a given AF. The AF shall initiate an HTTP POST request message and the NEF shall respond to it. The NEF shall construct the URI of the created resource.

[0303] POST request body

[0304]

[0305] POST response body

[0306]

[0307] QoE is an end-to-end measurement between the user and the access network, measuring the user's satisfaction with the user's device, while QoS measures different parameters. For example, these parameters may be related to the network status. QoS parameters can be regarded as inherent properties of the network, which are very important to guarantee the user's QoE requirements.

[0308] Quality of Experience (QoE) is the overall acceptability of an application or service as perceived subjectively by end users.

[0309] QoE may include the impact of the complete end-to-end system (client, terminal, network, service infrastructure, etc.) on the level of pleasure or annoyance experienced by XR users of XR services provided by XR applications when using the XR services.

[0310] Overall acceptability may be affected by user expectations (user expectations) and the environment.

[0311] In some embodiments, QoE may be controlled by parameters that are reasonably expected to be under the control of an XR service provider (generally referred to as an XR service provider).

[0312] QoE indicates performance metrics expressed from the perspective of end-service users (e.g., XR users). They may be requested or reported by ordinary users and may be stated without regard to their measurability.

[0313] QoE is used and may be considered as the performance characteristic most relevant to the end-user of the service. QoE may be mapped to the QoS of a data session (eg, a PDU session).

[0314] 3GPP TR 26.944 relates to end-to-end multimedia service performance metrics, such as QoE.

[0315] Some example QoE parameters are:

[0316] Service not connected

[0317] Service Failure

[0318] Service setup time

[0319] Rebuffer

[0320] Image corruption

[0321] Edge Noise

[0322] Fuzziness

[0323] Color reproduction accuracy

[0324] Blockiness

[0325] Discontinuous images with blockiness

[0326] Freeze Image

[0327] Audio Quality

[0328] Audio / Video Sync Error

[0329] A given QoE level may be associated with specific values ​​of one or more of these QoE parameters and / or any other suitable QoE parameters.

[0330] In the foregoing discussion, various modules have been mentioned. A module may be implemented by a suitable circuit system. A module may be implemented by at least one processor and at least one memory. The memory may include computer code stored in at least one memory and executed by at least one processor. In some embodiments, two or more modules may be provided by at least one common processor and at least one memory. In some embodiments, one or more modules may be provided by at least one dedicated processor and at least one memory.

[0331] Previous examples have been based on segmentation rendering scenarios, where frames are captured on the user side and semantic segmentation providing masks is performed on the captured frames at the edge cloud computing system. Masks are applied to the captured frames on the user side.

[0332] However, it should be understood that other embodiments may be used where there is a split in the processing of data such that some data processing is provided on the user side and some data processing is performed on computing resources remote from the user. The computing resources remote from the user may be edge cloud computing resources. The data processing may be split in any suitable manner. Typically, more complex processing may be performed remote from the user.

[0333] In some embodiments, the user side can capture image data. The image data can be in the form of frame data. The frame data can be sent to a computing resource away from the user. The computer resource can process the image data and send the data back to the user side. In the example given, the processing is to provide a semantic mask to be applied to the data. In other embodiments, different processing can be performed. For example, the computing resource away from the user can send back modified frame data. In some embodiments, the user side can be configured to use the received data. For example, the received data can be used to control the image displayed to the user. The user side can use the received data to process the image data to control the image displayed to the user. In another example, the modified frame data can be used to control the image displayed to the user.

[0334] Some embodiments may be applied in any distributed computing system involving image (Iv) and / or delay critical information (Id). Some embodiments may be used where network usage is high. This may be, for example, where high data rates and / or low latency are required. Embodiments may be applied where optimization or improvement at the 5QI level is required.

[0335] Some embodiments may be provided in an XR context without image data. For example, time-critical information may need to be generated in an AI server. For example, animating an artificial avatar included in an XR experience may be time-critical for a smooth interaction or experience by the user, so latency should be low.

[0336] Some embodiments may be used where haptic information needs to be generated to feed a haptic device in a UE. Haptics may require low latency to provide good QoE.

[0337] Some embodiments may be used for non-XR use cases. For example, some embodiments may be used for remote operation of a device. The device may be a vehicle, machinery, etc.

[0338] refer to Figure 8 , which illustrates the methods of some embodiments.

[0339] The method may be executed by a device. The device may be in a user equipment or UE, or may be a user equipment or UE.

[0340] The apparatus may include suitable components such as circuitry for providing the method.

[0341] Alternatively or additionally, the apparatus may include at least one processor and at least one memory storing instructions which, when executed by the at least one processor, cause the apparatus to at least provide the following method.

[0342] Alternatively or additionally, the device may be, for example, Figure 3 The device in question.

[0343] The method may be provided by computer program code or computer executable instructions.

[0344] The method may include: as shown in reference A1, determining, on the user equipment, one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user equipment,

[0345] The method may comprise, as indicated with reference A2, causing a request to be sent to a network entity, the request having information about one or more target performance indicator values.

[0346] It should be understood that Figure 8 The methods outlined in may be modified to include any of the previously described features.

[0347] refer to Fig. 9 , which illustrates the methods of some embodiments.

[0348] The method may be executed by a device. The device may be in a network entity or a server, or may be a network entity or a server.

[0349] The apparatus may include appropriate components such as circuitry for providing the method.

[0350] Alternatively or additionally, the apparatus may include at least one processor and at least one memory storing instructions, which when executed by the at least one processor cause the apparatus to at least provide the following method.

[0351] Alternatively or additionally, the device may be, for example, Figure 2 The device in question.

[0352] The method may be provided by computer program code or computer executable instructions.

[0353] The method may include: as shown in reference B1, receiving a request from a user equipment at a network entity, the request having information about one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user equipment.

[0354] The method may include: as shown in reference B2, requesting resources associated with the target performance indicator value for an application running on the user equipment.

[0355] It should be understood that Fig. 9 The methods outlined in may be modified to include any of the previously described features.

[0356] The computer program code may be downloaded and stored in one or more memories of the relevant apparatus or device.

[0357] Therefore, although certain embodiments are described above by way of example with reference to certain example architectures for wireless networks, technologies and standards, the embodiments may be applied to any other suitable form of communication system other than the communication system shown and described herein. In this example, certain embodiments have been described for a 5G network.

[0358] It should also be noted herein that, although the example embodiments are described above, the disclosed solutions may be varied and modified without departing from the scope of the present invention. As used herein, "at least one of the following: " and "at least one of " and similar expressions, wherein a list of two or more elements is connected by "and" or "or", represent at least any one element, or at least any two or more elements, or at least all elements. In general, various embodiments may be implemented in hardware or dedicated circuit systems, software, logic, or any combination thereof. Certain aspects of the present disclosure may be implemented in hardware, while other aspects may be implemented in firmware or software executable by a controller, microprocessor, or other computing device, but the present disclosure is not limited thereto. Although various aspects of the present disclosure may be illustrated and described in block diagrams, flow charts, or other graphical representations, it is well known that, as non-limiting examples, these boxes, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general hardware or controllers or other computing devices, or some combination thereof.

[0359] As used in this application, the term "circuitry" may refer to one or more or all of the following:

[0360] (a) hardware circuit implementation only (e.g., implementation only in analog and / or digital circuitry) and

[0361] (b) a combination of hardware circuitry and software such as (where applicable):

[0362] (i) a combination of analog and / or digital hardware circuits and software / firmware and

[0363] (ii) any portion of hardware processor(s) with software (including digital signal processor(s), software and memory(s) that work together to enable a device (such as a mobile phone or server) to perform various functions and

[0364] (c) Hardware circuits and / or processor(s), such as microprocessor(s) or portions of microprocessor(s), require software (e.g., firmware) to operate, but the software may not be present when the software is not required for operation.

[0365] This definition of circuitry applies to all uses of the term in this application, including in any claims. As a further example, as used in this application, the term "circuitry" also covers an implementation of only a hardware circuit or processor (or multiple processors) or a portion of a hardware circuit or processor and its (or their) accompanying software and / or firmware. The term "circuitry" also covers, for example (and if applicable to a particular claim element) an integrated circuit, such as a baseband integrated circuit or processor integrated circuit for a mobile device, or a similar integrated circuit in a server, cellular network device, or other computing or network device.

[0366] The embodiments of the present disclosure may be implemented by computer software executable by a data processor (such as a processor entity) of a mobile device, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products) include software routines, applets and / or macros that can be stored in a data storage medium readable by any device, and they include program instructions for performing specific tasks. A computer program product may include one or more computer executable components that are configured to perform an embodiment when the program is run. One or more computer executable components may be at least one software code or a portion thereof.

[0367] In this regard, it should also be noted that any box of the logic flow shown in the figure may represent program steps, or interconnected logic circuits, boxes and functions, or a combination of program steps and logic circuits, boxes and functions. The software may be stored on physical media such as memory chips or memory blocks implemented within a processor, magnetic media (such as hard disks or floppy disks), and optical media (such as, for example, DVDs and their data variants CDs). Physical media are non-transient media.

[0368] The term "non-transitory" as used herein refers to a limitation of the medium itself (ie, tangible, not a signal), not a limitation of data storage persistence (eg, RAM vs. ROM).

[0369] The memory may be of any type suitable for the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and removable memory. The data processor may be of any type suitable for the local technical environment and may include, as non-limiting examples, one or more of the following: a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an FPGA, a gate-level circuit, and a processor based on a multi-core processor architecture.

[0370] Embodiments of the present disclosure may be practiced in various components, such as integrated circuit modules. The design of integrated circuits is generally a highly automated process. Complex and powerful software tools are available to convert a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate.

[0371] The foregoing description has provided a complete and informative description of exemplary embodiments of the present disclosure by way of non-limiting examples. However, various modifications and adjustments may become apparent to those skilled in the relevant art when read in conjunction with the accompanying drawings and the appended claims. In fact, there are additional embodiments, including combinations of one or more embodiments with any other embodiments previously discussed. The scope of protection sought by some embodiments of the present disclosure is set forth in the claims. The embodiments and features (if any) described in this specification that do not fall within the scope of the claims should be interpreted as examples that aid in understanding the various embodiments of the present disclosure. It should be noted that different claims with different claim scopes may be sought in related applications (such as divisional applications or continuation applications).

Claims

1. A method of a user equipment, the method comprising: determining one or more target performance indicator values, the one or more target performance indicator values ​​being associated with a target quality of experience for an application running on the user equipment; as well as A request is sent to a network entity, the request having information about the one or more target performance indicator values.

2. The method according to claim 1, further comprising: The target quality of experience for the application running on the user equipment is determined. 3 . The method according to claim 1 , wherein the one or more target performance indicator values ​​include a target delay value or a target data rate value. The method of claim 3 , wherein the target data rate value comprises a target frame rate value. The method according to claim 3 , wherein the target delay value comprises a target end-to-end delay value.

6. The method according to any one of claims 1 to 5, further comprising: A message is received from the network entity, the message indicating support for the one or more target performance indicator values.

7. The method according to any one of claims 1 to 6, wherein the one or more target performance indicator values ​​associated with the target quality of experience for the extended reality application running on the user device are determined using a quality of experience model stored on the user device.

8. The method of claim 8, wherein the quality of experience model defines a relationship between quality of experience and one or more performance indicators.

9. The method according to claim 7 or 8, further comprising: The target quality of experience for the application is determined using the quality of experience model.

10. The method of any one of claims 1 to 9, wherein the application comprises an extended reality application.

11. A user equipment, comprising: at least one processor; as well as At least one memory storing instructions, wherein when the instructions are executed by the at least one processor, the user equipment performs at least operations, the operations comprising at least: determining one or more target performance indicator values, the one or more target performance indicator values ​​being associated with a target quality of experience for an application running on the user equipment; as well as A request is sent to a network entity, the request having information about the one or more target performance indicator values.

12. The user equipment according to claim 11, wherein the operation further comprises: The target quality of experience for the application running on the user equipment is determined.

13. The user equipment according to claim 11 or 12, wherein the one or more target performance indicator values ​​include a target delay value or a target data rate value.

14. The user equipment of claim 13, wherein the target data rate value comprises a target frame rate value.

15. The user equipment according to claim 13 or 14, wherein the target delay value comprises a target end-to-end delay value.

16. The user equipment according to any one of claims 11 to 15, wherein the operation further comprises: A message is received from the network entity, the message indicating support for the one or more target performance indicator values.

17. A user device according to any one of claims 11 to 16, wherein the one or more target performance indicator values ​​associated with the target quality of experience for an extended reality application running on the user device are determined using a quality of experience model stored on the user device.

18. The user equipment of claim 17, wherein the quality of experience model defines a relationship between quality of experience and one or more target performance indicators.

19. The user equipment according to claim 17 or 18, wherein the operation further comprises: The target quality of experience for the application is determined using the quality of experience model.

20. The user equipment of any one of claims 11 to 19, wherein the application comprises an extended reality application.

21. A method for a network entity of a communication network, the method comprising: receiving a request from a user device, the request having information about one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user device; as well as For the application running on the user equipment, resources associated with the target performance indicator value are requested.

22. The method according to claim 21, further comprising: The resource to be requested is determined using a quality of experience model.

23. A method according to claim 21 or 22, wherein the resources comprise one or more of desired levels of throughput and latency.

24. The method according to any one of claims 21 to 23, wherein the one or more target performance indicator values ​​include a target latency value, and wherein the method further comprises: The target delay is determined depending on a processing time in at least one of the network entity or the user equipment.

25. The method according to any one of claims 21 to 24, wherein the request comprises: For the application running on the user equipment, a request for resources associated with the one or more target performance indicator values ​​is sent to a 5G core entity.

26. The method according to any one of claims 21 to 25, further comprising: A response to the request for a resource is received, the response indicating authorization for the requested resource.

27. The method according to any one of claims 21 to 26, wherein the request comprises: For the application running on the user equipment, a request for resources associated with a given 5QI is sent.

28. The method according to any one of claims 21 to 27, further comprising: An indication of the authorization for the requested resource is sent to the user equipment.

29. The method according to any one of claims 22 to 28, further comprising: A request is received from the user equipment, the request being for the quality of experience model, and in response to the request, the quality of experience model is caused to be sent to the user equipment.

30. The method of any one of claims 21 to 29, wherein the application comprises an extended reality application.

31. A network entity for a communication network, the network entity comprising: At least one processor and at least one memory, wherein the at least one memory stores instructions, and when the instructions are executed by the at least one processor, the network entity performs operations, the operations comprising at least: receiving a request from a user device, the request having information about one or more target performance indicator values ​​associated with a target quality of experience for an application running on the user device; and For the application running on the user equipment, resources associated with the target performance indicator value are requested.

32. The network entity of claim 31 , wherein the operations comprise: The resource to be requested is determined using a quality of experience model.

33. A network entity according to claim 31 or 32, wherein the resources comprise one or more of required levels of throughput and latency.

34. The network entity according to any one of claims 31 to 33, wherein the operations comprise: A target delay is determined depending on a processing time in at least one of the network entity or the user equipment.

35. The network entity according to any one of claims 31 to 34, wherein the request comprises: For the application running on the user equipment, a request for resources associated with the one or more target performance indicator values ​​is sent to a 5G core entity.

36. The network entity according to any one of claims 31 to 35, wherein the operations comprise: A response to the request for a resource is received, the response indicating authorization for the requested resource.

37. The network entity according to any one of claims 31 to 36, wherein the request comprises: For the application running on the user equipment, a request for resources associated with a given 5QI is sent.

38. The network entity according to any one of claims 31 to 37, wherein the operations further comprise: An indication of the authorization for the requested resource is sent to the user equipment.

39. The network entity according to any one of claims 31 to 38, wherein the operations further comprise: A request is received from the user equipment, the request being for the quality of experience model, and in response to the request, the quality of experience model is sent to the user equipment.

40. The network entity of any one of claims 31 to 39, wherein the application comprises an extended reality application.

41. A computer program comprising instructions which, when executed by at least one processor of a user equipment, cause the user equipment to perform the method of any one of claims 1 to 10.

42. A computer program comprising instructions which, when executed by at least one processor of a network entity, cause the network entity to perform the method of any one of claims 21 to 30.

43. A computer-readable medium comprising instructions which, when executed by at least one processor of a user device, cause the user device to perform the method of any one of claims 1 to 10.

44. A computer readable medium comprising instructions which, when executed by at least one processor of a network entity, cause the network entity to perform the method of any one of claims 21 to 30.

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