Predicted extended reality user behavior proactive signaling

Abstract

An extended reality processing unit can receive a user characteristic report configuration from a radio access network node including a user characteristic indication indicating a user characteristic corresponding to use of an extended reality device during an extended reality session, which can be potentially predicted by the processing unit. The node can request via the configuration message that the processing unit report a prediction of the user characteristic associated with the session to the node. The request message can include a reporting criterion. Based on traffic corresponding to the session, the processing unit can predict a value indicating one or more user characteristics associated with the session. Upon determining that the predicted value satisfies the reporting criterion, the processing unit can transmit the predicted value to the node. The node can adjust a resource allocation available for delivery of traffic associated with the session based on the reported predicted value.

Description

Cross Reference to Related Applications

[0001] This application claims priority to U.S. nonprovisional patent application No. 18 / 521,831, filed November 28, 2023, entitled "PROACTIVE SIGNALING OF PREDICTED EXTENDED REALITY USER BEHAVIOR", the entire contents of which are incorporated herein by reference. Background Technology

[0002] The term “New Radio” (NR), associated with fifth-generation mobile wireless communication systems (“5G”), refers to the technical aspects used in a radio access network (“RAN”) that encompass multiple Quality of Service (QoS) categories, including Ultra-Reliable and Low-Latency Communication (“URLLC”), Enhanced Mobile Broadband (“eMBB”), and Massive Machine-Type Communication (“mMTC”). The URLLC QoS category is associated with stringent latency requirements (e.g., low latency or low signal / message delay) and high reliability of radio performance, while traditional eMBB use cases can be associated with high-capacity wireless communication, which allows for less stringent latency requirements (e.g., higher latency than URLLC) and less reliable radio performance compared to URLLC. Performance requirements for mMTC can be lower than those for eMBB use cases. Some use cases involving mobile devices or mobile user equipment (such as smartphones, wireless tablets, smartwatches, etc.) can impose varying loads or demands on given RAN resources. RAN nodes can activate network power-saving modes to reduce power consumption. Summary of the Invention

[0003] The following is a simplified overview of the disclosed subject matter to provide a basic understanding of some embodiments in various examples. This invention is not a broad overview of all embodiments. It is neither intended to identify key or essential elements of the various embodiments nor to define the scope of the various embodiments. Its sole purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that follows.

[0004] In an example embodiment, a method may include: a user equipment including a processor facilitating the reception of a user characteristic report configuration from a radio access network node, the configuration including at least one user characteristic indication indicating at least one user characteristic; and the user equipment facilitating the reception of a user characteristic report request from the radio access network node, the request including at least one of the at least one user characteristic indicated by the at least one user characteristic indication. The method may further include: the user equipment determining at least one user action indication indicating at least one user action corresponding to at least one of the at least one user characteristic indicated by the user characteristic report request. The user action indication may be determined based on user actions during an XR session, wherein a user operates an XR device, and the user action indication may include a prediction or predicted value indicating a future user action corresponding to at least one of the at least one user characteristic indicated by the user characteristic report request. In response to receiving a user characteristic report request, the method may further include the user equipment facilitating the transmission of a user characteristic report including at least one user action indication to the radio access network node.

[0005] At least one user action indication can be used by a radio access network node to schedule resources adapted to the delivery of services corresponding to at least one user action.

[0006] In an embodiment, a user characteristic report request may include at least one confidence level indication indicating at least one confidence level criterion corresponding to at least one user characteristic indication. The method may further include: a user equipment determining at least one user characteristic based on the satisfaction of at least one confidence level criterion to obtain at least one determined user characteristic. Transmission of the user characteristic report is based on at least one determined user characteristic satisfying at least one confidence level criterion corresponding to at least one user characteristic. The user characteristic report request may include at least one configured user characteristic indication duration indication indicating at least one configured user characteristic indication validity period length, during which at least one confidence level criterion will be valid with respect to at least one determined user characteristic. The user characteristic report may also include at least one actual user characteristic indication duration indication indicating at least one user characteristic indication validity period, specifying at least one user characteristic indication validity period during which at least one confidence level criterion is valid with respect to at least one determined user characteristic. The at least one user characteristic indication validity period indicated in the user characteristic report may be less than the at least one configured user characteristic indication validity period length. In an embodiment, the at least one user characteristic indication validity period indicated in the user characteristic report may be greater than the at least one configured user characteristic indication validity period length.

[0007] In one embodiment, the user characteristic report configuration can be generated by an extended reality (XR) server. Alternatively, in another embodiment, the user characteristic report configuration can be generated by a radio access network node based on information received from the user equipment.

[0008] In an embodiment, the method may further include: facilitating the transmission by the user equipment to a radio access network node of at least one user characteristic capability indication, indicating at least one user characteristic capability, to a radio access network node, regarding at least one characteristic of the user equipment reporting the at least one user characteristic indication requested via a user characteristic reporting request. The user equipment may include a digital twin module to facilitate the determination of at least one user characteristic capability. The user equipment may be communicatively coupled to the digital twin module to facilitate the determination of at least one user characteristic capability.

[0009] In one embodiment, the extended reality (XR) device may include a user device.

[0010] In one embodiment, the user equipment may be a component of an extended reality (XR) processing unit that is communicatively coupled to an XR device.

[0011] In an embodiment, at least one user characteristic corresponds to at least one action result caused by the execution of at least one action relating to the use of the extended reality (XR) user interface. The at least one action result may include at least one of the following: a specified pose orientation, horizontal orientation, target acceleration, target velocity, specified user hand orientation, blinking, target blink rate, or specified orientation in three-dimensional space.

[0012] In an embodiment, determining at least one user action indication may include receiving at least one user action indication from an extended reality (XR) device.

[0013] In another example embodiment, an extended reality (XR) processing unit may include: a processor configured to process executable instructions that, when executed by the processor, facilitate the execution of operations including: receiving a user characteristic report configuration from a radio network node, including at least one user characteristic indication indicating at least one user characteristic; and receiving a user characteristic report request from the radio network node, including at least one characteristic of at least one user characteristic indicated by the at least one user characteristic indication and at least one confidence level indication indicating at least one confidence level criterion corresponding to the at least one user characteristic indication. The user characteristic report request may be received in the form of a configuration message, and the at least one confidence level indication may be configured to the XR processing unit for use in triggering a report of a predicted user action when the confidence level corresponding to a prediction of a predicted user action by the XR processing unit satisfies the at least one confidence level indication. These operations may further include: determining at least one user action prediction indication indicating at least one predicted user action, the at least one predicted user action corresponding to at least one characteristic of at least one user characteristic indicated by the user characteristic report request. In response to receiving a user characteristic report request and based on at least one user action prediction indication that at least one confidence level criterion corresponding to at least one characteristic is met, a user characteristic report including at least one user action indication is transmitted.

[0014] These operations may include: transmitting at least one user characteristic capability indication to a radio network node, indicating at least one user characteristic capability, to determine at least one user action prediction indication with respect to the user equipment. In an embodiment, the at least one user action prediction indication may be determined by a digital twin module.

[0015] In another example embodiment, a non-transitory machine-readable medium may include executable instructions that, when executed by a processor of an extended reality (XR) processing unit, facilitate the execution of operations including: receiving a user characteristic report configuration from a radio network node, including at least one user characteristic indication indicating at least one user characteristic; and receiving a user characteristic report request from the radio network node, including at least one of the at least one user characteristic indications, wherein the user characteristic report request includes at least one confidence level indication indicating at least one confidence level criterion corresponding to the at least one user characteristic indication. These operations may further include: receiving from an XR device at least one user action indication indicating at least one user action corresponding to at least one user characteristic indicated by the user characteristic report request. Based on the at least one user action indication, these operations may further include: determining at least one user characteristic prediction that satisfies at least one confidence level criterion to obtain a user characteristic prediction satisfaction result. In response to receiving the user characteristic report request, these operations may further include: transmitting a user characteristic report including the user characteristic prediction satisfaction result to the radio network node.

[0016] In an embodiment, the user characteristic report may further include: at least one actual user characteristic indication duration indication indicating at least one valid period of user characteristic prediction, during which at least one confidence level criterion is valid regarding the user characteristic prediction satisfaction result.

[0017] In embodiments, these operations may further include: transmitting to a radio network node at least one user characteristic capability indication indicating at least one user characteristic capability, in order to report to the XR processing unit, with regard to the XR device, at least one of the at least one user characteristic indications indicated by the user characteristic reporting configuration, at least one user characteristic indication. Attached Figure Description

[0018] Figure 1 The diagram illustrates the environment of a wireless communication system.

[0019] Figure 2 An example virtual reality device is illustrated.

[0020] Figure 3 The illustration shows an example environment with an IoT device attached to a user device, which manages the business flows associated with that IoT device.

[0021] Figure 4 The illustration shows a sample user feature report configuration.

[0022] Figure 5 The illustration shows a sample user feature report request.

[0023] Figure 6 The illustration shows a sample user characteristic report.

[0024] Figure 7 The illustration shows an example embodiment of directing a user characteristic capability indicator to an extended reality processing unit.

[0025] Figure 8 The illustration shows an example embodiment of directing user characteristic capability indicators to a wireless access network node.

[0026] Figure 9 The illustration shows a timing diagram of an example embodiment of providing user characteristic reports to radio access network nodes.

[0027] Figure 10 The illustration shows a flowchart of an example embodiment of a method for providing user characteristic reports that can be used to schedule radio resources to radio access network nodes.

[0028] Figure 11 A block diagram illustrating an example method embodiment is shown.

[0029] Figure 12 The diagram illustrates a block diagram of an example extended reality processing unit.

[0030] Figure 13 A block diagram illustrating an example of a non-transitory machine-readable medium embodiment is shown.

[0031] Figure 14 The illustration shows an example computer environment.

[0032] Figure 15 The diagram illustrates a block diagram of an example wireless user equipment.

[0033] Figure 16 The illustration shows data from an example XR device that can be used to facilitate the prediction of user behavior characteristics by utilizing a digital twin module. Detailed Implementation

[0034] As will be readily understood by those skilled in the art as a preliminary observation, this embodiment has broad applicability and utility. In addition to those described herein, numerous methods, embodiments, and adaptations, as well as many variations, modifications, and equivalent arrangements, will be apparent from or reasonably suggested by the spirit or scope of the various embodiments of this application.

[0035] Therefore, although this application has been described in detail herein with reference to various embodiments, it will be understood that this disclosure illustrates one or more concepts expressed by various exemplary embodiments and is made solely for the purpose of providing a complete and feasible disclosure. The following disclosure is not intended to limit this application, nor should it be construed as limiting this application or otherwise excluding any such other embodiments, adaptations, variations, modifications, and equivalent arrangements, and the embodiments described herein are limited only by the appended claims and their equivalents.

[0036] As used in this disclosure, in some embodiments, the terms "component," "system," etc., are intended to refer to or include computer-related entities or entities associated with operating means having one or more specific functions, wherein the entity may be hardware, a combination of hardware and software, software, or software in execution. As an example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable file, a thread in execution, computer-executable instructions, a program, and / or a computer. By way of illustration and not limitation, both an application running on a server and the server itself can be components.

[0037] One or more components may reside within a process and / or execution thread, and components may be located on a single computer and / or distributed across two or more computers. Furthermore, these components may be executed from various computer-readable media containing various data structures. Components may communicate via local and / or remote processes, such as based on signals having one or more data packets (e.g., data from a component that interacts with another component in a local system, a distributed system, and / or with other systems across a network such as the Internet). As another example, a component may be a device having a specific function provided by mechanical parts operated by electrical or electronic circuitry, operated by a software or firmware application executed by a processor, wherein the processor may be internal or external to the device and executes at least a portion of the software or firmware application. As yet another example, a component may be a device providing a specific function through an electronic component without mechanical parts, the electronic component including a processor therein to execute software or firmware that at least partially endows the electronic component with the function. Although the various components have been illustrated as separate components, it should be understood that multiple components can be implemented as a single component, or a single component can be implemented as multiple components, without departing from the example embodiments.

[0038] As used herein, the term "facilitate" refers to, in relation to the nature of a complex computing environment, in the context of a system, device, or component "facilitating" one or more actions or operations, in which multiple components and / or devices may be involved in some computational operation. Non-limiting examples of actions that may or may not involve multiple components and / or devices include: transmitting or receiving data, establishing connections between devices, determining intermediate results toward obtaining a result, and so on. In this regard, a computing device or component can facilitate an operation by playing any role in accomplishing the operation. Therefore, when describing the operation of a component herein, it will be understood that, where an operation is described as being facilitated by a component, the operation may optionally be accomplished in cooperation with one or more other computing devices or components, such as, but not limited to, sensors, antennas, audio and / or visual output devices, other devices, etc.

[0039] Furthermore, various embodiments can be implemented as methods, apparatus, or articles of art using standard programming and / or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. As used herein, the term "article of art" is intended to cover a computer program accessible from any computer-readable (or machine-readable) device or computer-readable (or machine-readable) storage / communication medium. For example, computer-readable storage media may include, but is not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic stripes), optical discs (e.g., compact discs (CDs), digital versatile discs (DVDs)), smart cards, and flash memory devices (e.g., cards, sticks, key drives). Of course, those skilled in the art will recognize that many modifications can be made to this configuration without departing from the scope or spirit of the various embodiments.

[0040] As an example use case illustrating the exemplary embodiments disclosed herein, virtual reality (“VR”) applications and VR variants (e.g., mixed reality and augmented reality) may perform optimally at certain times when using NR radio resources associated with URLLC, while at other times, lower performance levels may be sufficient. Virtual reality smart glasses devices can consume NR radio resources at a given broadband data rate with more stringent radio latency and reliability standards to provide a satisfactory end-user experience.

[0041] 5G systems should support Extended Reality (“XR”) services. XR services can be referred to as Reality of Everything services. XR services can include VR applications, which are widely adopted XR applications that provide immersive environments that stimulate the end-user's senses, allowing him or her to be “tricked” into experiencing a different environment than their actual surroundings. XR services can include Augmented Reality (“AR”) applications that enhance the real-world environment by providing additional virtual-world elements through the user's senses, focusing on real-world elements in the user's actual surroundings. XR services can include Mixed Reality (“MR”) applications that help merge or integrate the virtual and real worlds, allowing the end-user of the XR service to interact with elements of both their real and virtual environments simultaneously. As used herein, the term “XR” can refer to VR, AR, or MR.

[0042] Different XR use cases can be associated with certain radio performance objectives. Unlike URLLC or eMBB, a common thread in XR use cases is that achieving a satisfactory end-user experience typically requires high-capacity links with stringent radio and reliability levels. For example, some XR applications require 100Mbps links with allowable radio latency of a few milliseconds, compared to a 5Mbps URLLC link with a 1ms radio budget. Therefore, 5G radio design and associated procedures can be adapted to new XR QoS categories and associated performance objectives.

[0043] XR services can be facilitated by services with certain characteristics associated with XR services. For example, XR services can often be periodic, with packet sizes and arrival rates varying over time. Furthermore, different packet traffic flows within a single XR communication session can differently impact the end-user experience. For instance, smart glasses streaming 180-degree high-resolution frames can utilize a large portion of the broadband service capacity to satisfy the user experience. However, frames presented to the user's directional orientation (e.g., forward direction) are most important for a satisfactory user experience, while frames presented to the user's peripheral vision have a smaller impact on the user experience, and therefore can be associated with lower QoS requirements for transport traffic packets compared to QoS requirements for directional traffic flows. Therefore, prioritizing certain flows or packets within an XR session over others can help efficiently utilize the communication system's capacity for service delivery. Additionally, due to the limited form factor of devices, XR-enabled devices (e.g., smart glasses, projection wearables, etc.) may be more power-constrained than traditional mobile phones. Therefore, techniques to maximize power-saving operations at XR-enabled devices are desirable. Therefore, user equipment devices accessing XR services or XR sessions can be associated with one or more specific QoS parameter standards to meet the performance objectives of the XR service. The measured service values ​​or metrics can correspond to QoS or be analyzed with respect to one or more parameter standards, such as, for example, data rate, end-to-end latency, or reliability.

[0044] High-capacity services, such as virtual reality applications, can even pose performance challenges to 5G NR capabilities. Therefore, while 5G NR systems can facilitate and support higher performance capabilities, the radio interface should still be optimized to support the extremely high capacity and low latency requirements of XR applications and XR data services.

[0045] Multimodal XR applications can integrate different technologies to provide a versatile and comprehensive user experience. For example, a multimodal XR application can use VR to immerse the user in a virtual training environment and then seamlessly switch to AR or MR to provide real-time feedback or overlay guidance information corresponding to physical objects that may appear in the environment viewed by the XR user. This feedback or guidance information can be related to static objects or can be information that does not change frequently and can be referred to as stable information.

[0046] The advantage of multimodal XR applications lies in their adaptability to different contexts and user preferences. XR devices can provide varying levels of immersion and interactivity, allowing users to choose the most appropriate engagement mode based on their needs or the specific task at hand. Additionally, multimodal XR enables collaborative experiences, allowing users in different physical locations to interact within the same virtual space.

[0047] Multimodal XR applications extend beyond entertainment and gaming, with widespread adoption in fields such as healthcare, education, engineering, and marketing. Healthcare practitioners can use multimodal XR to simulate complex surgeries, educators can create interactive and immersive learning experiences, and architects can visualize and modify architectural designs in real time.

[0048] Now turn to the attached diagram. Figure 1 Examples of a wireless communication system 100 supporting blind decoding of PDCCH candidate or search space according to one or more exemplary embodiments of the present disclosure are shown. The wireless communication system 100 may include one or more base stations 105, one or more user equipment (“UE”) devices 115, and a core network 130. In some examples, the wireless communication system 100 may include a long-range wireless communication network, including, for example, a Long Term Evolution (LTE) network, an Advanced LTE (LTE-A) network, an LTE-A Pro network, or a New Radio (NR) network. In some examples, the wireless communication system 100 may support enhanced broadband communication, ultra-reliable (e.g., mission-critical) communication, low-latency communication, communication with low-cost and low-complexity devices, or any combination thereof. As shown in the figures, examples of UE 115 may include smartphones, laptop computers, tablet computers, automobiles or other vehicles, or drones or other aircraft. Another example of a UE may be a virtual reality / extended reality device 117, such as smart glasses, virtual reality headsets, augmented reality headsets, and other similar devices that can provide the wearer with images, video, audio, touch, taste, or smell. A UE (such as XR device 117) can transmit or receive radio signals with RAN base station 105 via long-range radio link 125, or the UE / XR device can receive and transmit radio signals via short-range radio link 137, which may include a radio link with UE device 115, such as a Bluetooth link, a Wi-Fi link, etc. A UE (such as device 117) can communicate simultaneously via multiple radio links, such as via link 125 with base station 105 and via short-range radio links. XR device 117 can also communicate with a wireless UE via cable or other wired connection. XR device 117 can offload processing functionality or functionality related to communication with the RAN to user equipment 115, which may be referred to as intermediate user equipment or XR processing unit. The XR processing unit or RAN, or components thereof, may be referenced from [reference needed]. Figure 14 This is achieved through one or more computer components as described.

[0049] Continue to Figure 1In this discussion, base stations 105, which may be referred to as radio access network nodes or units, can be distributed throughout a geographical area to form a wireless communication system 100, and can be devices of different forms or with different capabilities. Base stations 105 and UEs 115 can communicate wirelessly via one or more communication links 125. Each base station 105 can provide a coverage area 110, within which UEs 115 and base stations 105 can establish one or more communication links 125. Coverage area 110 can be an example of a geographical area over which base stations 105 and UEs 115 can support signal communication according to one or more radio access technologies.

[0050] UE 115 can be distributed throughout the entire coverage area 110 of the wireless communication system 100, and each UE 115 can be stationary or mobile at different times, or both. UE 115 can be devices of different forms or with different capabilities. Figure 1 The diagram illustrates some example UE 115s. The UE 115 described herein can communicate with various types of devices, such as other UE 115s, base station 105, or network devices (e.g., core network nodes, relay devices, integrated access and backhaul (IAB) nodes, or other network devices). Figure 1 As shown in the image.

[0051] Base station 105 may communicate with core network 130, communicate with each other, or both. For example, base station 105 may interface with core network 130 via one or more backhaul links 120 (e.g., via S1, N2, N3, or other interfaces). Base station 105 may communicate directly (e.g., directly between base stations 105) or indirectly (e.g., via core network 130) or both via backhaul links 120 (e.g., via X2, Xn, or other interfaces). In some examples, backhaul link 120 may include one or more radio links.

[0052] One or more base stations in the base station 105 described herein may include, or may be referred to by those skilled in the art as, base station, radio base station, access point, radio transceiver, NodeB, eNodeB (eNB), next-generation NodeB or gigabit NodeB (any of which may be referred to as bNodeB or gNB), home NodeB, home eNodeB or other suitable terms.

[0053] UE 115 may include or be referred to as a mobile device, wireless device, remote device, handheld device, or subscriber device, or some other suitable term, wherein "device" may also be referred to as a unit, station, terminal, or client, etc. UE 115 may also include or be referred to as a personal electronic device, such as a cellular phone, personal digital assistant (PDA), tablet computer, laptop computer, personal computer, or router. In some examples, UE 115 may include or be referred to as a wireless local loop (WLL) station, Internet of Things (IoT) device, Internet of Everything (IoE) device, or machine-type communication (MTC) device, etc., which can be implemented in various objects, such as devices, vehicles, or smart meters, etc.

[0054] like Figure 1 As shown, UE 115 can communicate with various types of devices, such as other UE 115s that can sometimes act as repeaters, as well as base station 105 and network devices including macro eNB or gNB, small cell eNB or gNB, or relay base station.

[0055] UE 115 and base station 105 can wirelessly communicate with each other on one or more carriers via one or more communication links 125. The term "carrier" can refer to a set of radio frequency spectrum resources having a defined physical layer structure for supporting communication link 125. For example, a carrier for communication link 125 may include a portion (e.g., a bandwidth portion (BWP)) of a radio frequency spectrum band operating according to one or more physical layer channels for a given radio access technology (e.g., LTE, LTE-A, LTE-A Pro, NR). Each physical layer channel may carry acquisition signaling (e.g., synchronization signals, system information), control signaling coordinating operation for the carrier, user data, or other signaling. Wireless communication system 100 can use carrier aggregation or multi-carrier operation to support communication with UE 115. Depending on the carrier aggregation configuration, UE 115 can be configured with multiple downlink component carriers and one or more uplink component carriers. Carrier aggregation can be used in conjunction with both frequency division duplex (FDD) and time division duplex (TDD) component carriers.

[0056] In some examples (e.g., in a carrier aggregation configuration), the carrier may also have acquisition signaling or control signaling that coordinates operation against other carriers. The carrier may be associated with a frequency channel (e.g., an Evolved Universal Mobile Telecommunications System Terrestrial Radio Access (E-UTRA) Absolute Radio Frequency Channel Number (EARFCN)) and can be located according to a channel grid for discovery by the UE 115. The carrier may operate in a standalone mode, where initial acquisition and connection can be performed by the UE 115 via the carrier, or the carrier may operate in a non-standalone mode, where connections are anchored using different carriers (e.g., carriers of the same or different radio access technologies).

[0057] The communication link 125 shown in the wireless communication system 100 may include uplink transmission from UE 115 to base station 105 or downlink transmission from base station 105 to UE 115. The carrier may carry downlink or uplink communication (e.g., in FDD mode), or may be configured to carry both downlink and uplink communication (e.g., in TDD mode).

[0058] A carrier can be associated with a specific bandwidth of the radio frequency spectrum, and in some examples, the carrier bandwidth can be referred to as the carrier or the "system bandwidth" of the wireless communication system 100. For example, the carrier bandwidth can be a specific bandwidth (e.g., 1.4, 3, 5, 10, 15, 20, 40, or 80 MHz) of a carrier for a specific wireless access technology. Devices of the wireless communication system 100 (e.g., base station 105, UE 115, or both) can have a hardware configuration that supports communication on a specific carrier bandwidth, or can be configured to support communication on a single carrier bandwidth within a set of carrier bandwidths. In some examples, the wireless communication system 100 may include a base station 105 or UE 115 that supports simultaneous communication via carriers associated with multiple carrier bandwidths. In some examples, each served UE 115 can be configured to operate on a portion (e.g., a subband, BWP) or the entire carrier bandwidth.

[0059] The signal waveform transmitted on a carrier may consist of multiple subcarriers (e.g., using multi-carrier modulation (MCM) techniques, such as orthogonal frequency division multiplexing (OFDM) or discrete Fourier transform extended OFDM (DFT-S-OFDM)). In a system employing MCM, a resource element may consist of a symbol phase (e.g., the duration of a modulation symbol) and a subcarrier, where the symbol phase and subcarrier spacing are inversely related. The number of bits carried by each resource element may depend on the modulation scheme (e.g., the order of the modulation scheme, the coding rate of the modulation scheme, or both). Therefore, the more resource elements the UE 115 receives and the higher the order of the modulation scheme, the higher the data rate that can be used for the UE. Wireless communication resources may refer to a combination of radio frequency spectrum resources, temporal resources (e.g., search space), or spatial resources (e.g., spatial layers or beams), and the use of multiple spatial layers can also improve the data rate or data integrity for communication with the UE 115.

[0060] One or more parameter sets for a carrier can be supported, where the parameter sets may include subcarrier spacing (Δf) and cyclic prefix. A carrier can be divided into one or more BWPs with the same or different parameter sets. In some examples, UE 115 can be configured with multiple BWPs. In some examples, a single BWP for a carrier can be active at a given time, and communication for UE 115 can be limited to one or more active BWPs.

[0061] The time interval for base station 105 or UE 115 can be expressed as a multiple of a basic time unit; for example, the basic time unit can refer to... The sampling phase is in seconds, where Δf max This can represent the maximum supported subcarrier spacing, and N f This can represent the maximum supported Discrete Fourier Transform (DFT) size. The time interval of the communication resources can be organized according to radio frames, each with a specified duration (e.g., 10 milliseconds (ms)). Each radio frame can be identified by a System Frame Number (SFN) (e.g., ranging from 0 to 1023).

[0062] Each frame may include multiple consecutively numbered subframes or time slots, and each subframe or time slot may have the same duration. In some examples, a frame may (e.g., in the time domain) be divided into subframes, and each subframe may also be divided into multiple time slots. Alternatively, each frame may include a variable number of time slots, and the number of time slots may depend on the subcarrier spacing. Each time slot may include multiple symbol phases, for example, depending on the length of the cyclic prefix preceding each symbol phase. In some wireless communication systems 100, time slots may also be divided into multiple micro-time slots containing one or more symbols. In addition to the cyclic prefix, each symbol phase may contain one or more (e.g., N) symbols. f (Sampling phase). The duration of the symbol phase can depend on the subcarrier spacing or the operating frequency band.

[0063] A subframe, time slot, micro-time slot, or symbol can be the smallest scheduling unit of the wireless communication system 100 (e.g., in the time domain) and can be referred to as a transmission time interval (TTI). In some examples, the duration of the TTI (e.g., the number of symbol phases in the TTI) can be variable. Additionally or alternatively, the smallest scheduling unit of the wireless communication system 100 can be dynamically selected (e.g., in a burst of shortened TTIs (sTTIs)).

[0064] Physical channels can be multiplexed on carriers using various techniques. Physical control channels and physical data channels can be multiplexed on downlink carriers, for example, using one or more of the following: Time Division Multiplexing (TDM), Frequency Division Multiplexing (FDM), or Hybrid TDM-FDM. The control region (e.g., control resource set (CORESET)) of the physical control channel can be defined by multiple symbol stages and can be extended across the system bandwidth or a subset of the system bandwidth of the carrier. One or more control regions (e.g., CORESETs) can be configured for a set of UEs 115. For example, one or more UEs in UE 115 can monitor or search for control regions or spaces for control information based on one or more search space sets, and each search space set can include one or more control channel candidates in one or more aggregation levels arranged in a cascaded manner. The aggregation level for control channel candidates can refer to the number of control channel resources (e.g., control channel elements (CCEs)) associated with coded information for a control information format having a given payload size. The search space set may include a common search space set configured to send control information to multiple UEs 115, and a UE-specific search space set used to send control information to a specific UE 115. Novel, rather than conventional, additional search spaces and configurations for monitoring and decoding them are disclosed herein.

[0065] Base station 105 may provide communication coverage via one or more cells (e.g., macro cells, small cells, hotspots, or other types of cells, or any combination thereof). The term "cell" may refer to a logical communication entity used for communication with base station 105 (e.g., via a carrier) and may be associated with an identifier used to distinguish neighboring cells (e.g., Physical Cell Identifier (PCID), Virtual Cell Identifier (VCID), or other identifier). In some examples, a cell may also refer to a geographic coverage area 110 or a portion (e.g., a sector) of geographic coverage area 110 on which the logical communication entity operates. Depending on various factors such as the capabilities of base station 105, the extent of such a cell can range from a smaller area (e.g., a structure, a subset of structures) to a larger area. For example, a cell may be or include a building, a subset of buildings, or external space between or overlapping with geographic coverage area 110.

[0066] Macro cells typically cover a relatively large geographic area (e.g., a radius of several kilometers) and can allow unrestricted access by UE 115 with a service subscription to a network provider supporting the macro cell. In contrast, small cells can be associated with a lower-power base station 105 and can operate on the same or different (e.g., licensed, unlicensed) frequency bands as macro cells. Small cells can provide unrestricted access to UE 115 with a service subscription to a network provider, or restricted access to UE 115 associated with a small cell (e.g., UE 115 in a Closed Subscriber Group (CSG), or UE 115 associated with a user in a home or office). Base station 105 can support one or more cells and can also use one or more component carriers to support communication on one or more cells.

[0067] In some examples, a carrier can support multiple cells, and different cells can be configured according to different protocol types (e.g., MTC, Narrowband Internet of Things (NB-IoT), Enhanced Mobile Broadband (eMBB)), which can provide access for different types of devices.

[0068] In some examples, base station 105 may be mobile and thus provide communication coverage for mobile geographic coverage areas 110. In some examples, different geographic coverage areas 110 associated with different technologies may overlap, but the different geographic coverage areas 110 may be supported by the same base station 105. In other examples, overlapping geographic coverage areas 110 associated with different technologies may be supported by different base stations 105. Wireless communication system 100 may include, for example, a heterogeneous network, in which different types of base stations 105 use the same or different wireless access technologies to provide coverage for various geographic coverage areas 110.

[0069] The wireless communication system 100 can support synchronous or asynchronous operation. For synchronous operation, base stations 105 can have similar frame timing, and transmissions from different base stations 105 can be approximately aligned in time. For asynchronous operation, base stations 105 can have different frame timing, and in some examples, transmissions from different base stations 105 may not be aligned in time. The techniques described herein can be used for both synchronous and asynchronous operation.

[0070] Some UE 115 devices (such as MTC or IoT devices) can be low-cost or low-complexity devices that can provide automated communication between machines (e.g., via machine-to-machine (M2M) communication). M2M communication or MTC can refer to data communication technologies that allow devices to communicate with each other or with base station 105 without human intervention. In some examples, M2M communication or MTC can include communication from devices that integrate sensors or meters to measure or capture information and relay such information to a central server or application that utilizes or presents the information to people interacting with the application. Some UE 115 devices can be designed to collect information or automate the behavior of machines or other devices. Examples of applications for MTC devices include smart metering, inventory monitoring, water level monitoring, equipment monitoring, healthcare monitoring, wildlife monitoring, weather and geological event monitoring, fleet management and tracking, remote security sensing, physical access control, and transaction-based business billing.

[0071] Some UE 115s can be configured to operate in a power-saving mode, such as half-duplex communication (e.g., a mode that supports unidirectional communication via transmission or reception but not both transmission and reception simultaneously). In some examples, half-duplex communication can be performed at a reduced peak rate. Other power-saving techniques for UE 115 include entering a power-saving deep sleep mode when not engaged in active communication, operating on limited bandwidth (e.g., according to narrowband communication), or a combination of these techniques. For example, some UE 115s can be configured to operate using a narrowband protocol type associated with a defined portion or range (e.g., a set of subcarriers or resource blocks (RBs)) within a carrier, within a carrier's guard band, or outside a carrier.

[0072] Wireless communication system 100 can be configured to support ultra-reliable communication or low-latency communication, or various combinations thereof. For example, wireless communication system 100 can be configured to support ultra-reliable low-latency communication (URLLC) or mission-critical communication. UE 115 can be designed to support ultra-reliable, low-latency, or mission-critical functions (e.g., mission-critical functions). Ultra-reliable communication may include dedicated communication or group communication and may be supported by one or more mission-critical services, such as mission-critical push-to-talk (MCPTT), mission-critical video (MCVideo), or mission-critical data (MCData). Support for mission-critical functions may include service prioritization, and mission-critical services may be used for public safety or general commercial applications. The terms ultra-reliable, low-latency, mission-critical, and ultra-reliable low-latency are used interchangeably herein.

[0073] In some examples, UE 115 may also be able to communicate directly with other UE 115 via device-to-device (D2D) communication link 135 (e.g., using peer-to-peer (P2P) or D2D protocols). Communication link 135 may include a sidelink communication link. One or more UE 115s utilizing D2D communication (such as sidelink communication) may be within the geographic coverage area 110 of base station 105. Other UE 115s in such a group may be outside the geographic coverage area 110 of base station 105 or otherwise unable to receive transmissions from base station 105. In some examples, the group of UE 115s communicating via D2D communication may utilize a one-to-many (1:M) system, where a UE transmits to each other UE in the group. In some examples, base station 105 facilitates resource scheduling for D2D communication. In other cases, D2D communication is performed between UE 115s without involving base station 105.

[0074] In some systems, the D2D communication link 135 can be an example of a communication channel between vehicles (e.g., UE 115), such as a side-link communication channel. In some examples, vehicles can communicate using vehicle-to-everything (V2X) communication, vehicle-to-vehicle (V2V) communication, or some combination thereof. Vehicles can signal information related to traffic conditions, signal control, weather, safety, emergencies, or any other information related to the V2X system. In some examples, vehicles in a V2X system can use vehicle-to-network (V2N) communication to communicate with roadside infrastructure (such as roadside units), or via one or more RAN network nodes (e.g., base station 105) to communicate with the network, or both. Figure 1In this configuration, vehicle UE 116 is displayed within the RAN coverage area, while vehicle UE 118 is displayed outside the coverage area of ​​the same RAN. Vehicle UE 115, which is wirelessly connected to the RAN, can be a sidelink relay to vehicle UE 116 within the RAN coverage area or to vehicle UE 118 outside the RAN coverage area.

[0075] Core network 130 can provide user authentication, access authorization, tracking, Internet Protocol (IP) connectivity, and other access, routing, or mobility functions. Core network 130 can be an evolved packet core (EPC) or a 5G core (5GC), which may include at least one control plane entity (e.g., a mobility management entity (MME), access and mobility management function (AMF)) managing access and mobility, and at least one user plane entity (e.g., a serving gateway (S-GW), packet data network (PDN) gateway (P-GW), or user plane function (UPF)) routing packets or interconnects to external networks. The control plane entity can manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management for UE 115 served by base station 105 associated with core network 130. User IP packets can be transmitted through the user plane entity, which can provide IP address allocation and other functions. The user plane entity can connect to IP service 150 for one or more network operators. IP service 150 may include access to the Internet, intranet(s), IP Multimedia Subsystem (IMS), or packet-switched streaming services.

[0076] Some network devices (such as base station 105) may include sub-components, such as access network entity 140, which may be an example of an access node controller (ANC). Each access network entity 140 may communicate with UE 115 through one or more other access network transport entities 145, which may be referred to as a radio headend, smart radio headend, or transmit / receive point (TRP). Each access network transport entity 145 may include one or more antenna panels. In some configurations, the various functions of each access network entity 140 or base station 105 may be distributed across various network devices (e.g., radio headends and ANCs) or combined into a single network device (e.g., base station 105).

[0077] Wireless communication system 100 can operate using one or more frequency bands, typically in the range of 300 MHz to 300 GHz. The region from 300 MHz to 3 GHz is generally referred to as the Ultra High Frequency (UHF) region or decimeter band because the wavelength range is from approximately one decimeter to one meter. UHF waves can be blocked or reoriented by buildings and environmental features, but these waves can penetrate structures sufficiently for macrocells to provide service to UE 115 located indoors. Compared to transmissions using smaller frequencies and longer waves in the High Frequency (HF) or Very High Frequency (VHF) portions of the spectrum below 300 MHz, UHF wave transmission can be associated with smaller antennas and shorter ranges (e.g., less than 100 km).

[0078] The wireless communication system 100 can also operate in the ultra-high frequency (SHF) region using a frequency band from 3 GHz to 30 GHz (also known as the centimeter band), or in the extremely high frequency (EHF) region of the spectrum (e.g., from 30 GHz to 300 GHz) (also known as the millimeter band). In some examples, the wireless communication system 100 can support millimeter-wave (mmW) communication between the UE 115 and the base station 105, and the EHF antennas of the corresponding devices can be smaller and more closely spaced than UHF antennas. In some examples, this can facilitate the use of antenna arrays within the device. However, the propagation of EHF transmissions can be subject to even greater atmospheric attenuation and a shorter range than SHF or UHF transmissions. The techniques disclosed herein can be employed across transmissions using one or more different frequency regions, and the designated use of frequency bands across these frequency regions can vary by country or regulatory body.

[0079] Wireless communication system 100 can utilize both licensed and unlicensed radio frequency spectrum bands. For example, wireless communication system 100 can employ Licensed Assisted Access (LAA), LTE-Unlicensed (LTE-U) radio access technology, or NR technology in unlicensed frequency bands, such as the 5 GHz Industrial, Scientific, and Medical (ISM) band. When operating in unlicensed radio frequency spectrum bands, devices such as base station 105 and UE 115 can employ carrier sensing for collision detection and avoidance. In some examples, operation in unlicensed frequency bands can be based on carrier aggregation configurations that combine component carriers operating in licensed frequency bands (e.g., LAA). Operation in unlicensed spectrum can include downlink transmissions, uplink transmissions, P2P transmissions, or D2D transmissions, etc.

[0080] Base station 105 or UE 115 may be equipped with multiple antennas that can be used to employ techniques such as transmit diversity, receive diversity, multiple-input multiple-output (MIMO) communication, or beamforming. The antennas of base station 105 or UE 115 may be located within one or more antenna arrays or antenna panels that can support MIMO operation or transmit or receive beamforming. For example, one or more base station antennas or antenna arrays may be juxtaposed at an antenna assembly, such as an antenna tower. In some examples, the antennas or antenna arrays associated with base station 105 may be located in different geographical locations. Base station 105 may have an antenna array with multiple row and column line ports that base station 105 can use to support beamforming for communication with UE 115. Similarly, UE 115 may have one or more antenna arrays that can support various MIMO or beamforming operations. Additionally or alternatively, antenna panels may support radio frequency beamforming for signals transmitted via antenna ports.

[0081] Base station 105 or UE 115 can use MIMO communication to utilize multipath signal propagation and improve spectral efficiency by transmitting or receiving multiple signals via different spatial layers. This technique can be referred to as spatial multiplexing. For example, multiple signals can be transmitted by a transmitting device via different antennas or different combinations of antennas. Similarly, multiple signals can be received by a receiving device via different antennas or different combinations of antennas. Each of the multiple signals can be referred to as a separate spatial stream and can carry bits associated with the same data stream (e.g., the same codeword) or different data streams (e.g., different codewords). Different spatial layers can be associated with different antenna ports used for channel measurement and reporting. MIMO techniques include single-user MIMO (SU-MIMO) (where multiple spatial layers are transmitted to the same receiving device) and multi-user MIMO (MU-MIMO) (where multiple spatial layers are transmitted to multiple devices).

[0082] Beamforming (also known as spatial filtering, directional transmission, or directional reception) is a signal processing technique that can be used at a transmitting or receiving device (e.g., base station 105, UE 115) to shape or manipulate an antenna beam (e.g., a transmit beam, a receive beam) along a spatial path between the transmitting and receiving devices. Beamforming can be achieved by combining signals transmitted via antenna elements of an antenna array, such that some signals propagating with respect to a particular orientation of the antenna array experience constructive interference, while other signals experience destructive interference. The conditioning of signals transmitted via antenna elements can include the transmitting or receiving device applying amplitude offset, phase offset, or both to the signals carried via the antenna elements associated with that device. The conditioning associated with each antenna element can be defined by a beamforming weight set associated with a particular orientation (e.g., the antenna array of the transmitting or receiving device, or with respect to some other orientation).

[0083] Base station 105 or UE 115 may use beam scanning technology as part of beamforming operations. For example, base station 105 may use multiple antennas or antenna arrays (e.g., antenna panels) for beamforming operations to enable directional communication with UE 115. Some signals (e.g., synchronization signals, reference signals, beam selection signals, or other control signals) may be transmitted multiple times by base station 105 in different directions. For example, base station 105 may transmit signals based on different beamforming weight sets associated with different transmission directions. Transmissions in different beam directions may be used to identify (e.g., by a transmitting device such as base station 105, or by a receiving device such as UE 115) the beam direction for later transmission or reception by base station 105.

[0084] Some signals (such as data signals associated with a specific receiving device) may be transmitted by base station 105 in a single beam direction (e.g., the direction associated with a receiving device such as UE 115). In some examples, the beam direction associated with transmission along a single beam direction may be determined based on the signals transmitted in one or more beam directions. For example, UE 115 may receive one or more signals transmitted by base station 105 in different directions and may report to the base station an indication of the signal received by UE 115 with the highest signal quality or other acceptable signal quality.

[0085] In some examples, transmissions performed by a device (e.g., base station 105 or UE 115) may be executed using multiple beam directions, and the device may use a combination of digital precoding or radio frequency beamforming to generate a combined beam for transmission (e.g., from base station 105 to UE 115). UE 115 may report feedback indicating precoding weights for one or more beam directions, and this feedback may correspond to the number of beam configurations across the system bandwidth or one or more subbands. Base station 105 may transmit reference signals (e.g., cell-specific reference signals (CRS), channel state information reference signals (CSI-RS)), which may or may not be precoded. UE 115 may provide feedback for beam selection, which may be a precoding matrix indicator (PMI) or codebook-based feedback (e.g., a multi-panel type codebook, a linear combination type codebook, or a port selection type codebook). While these techniques are described with reference to signals transmitted by base station 105 in one or more directions, UE 115 may employ similar techniques for transmitting signals multiple times in different directions (e.g., for identifying beam directions for subsequent transmissions or receptions made by UE 115) or for transmitting signals in a single direction (e.g., for transmitting data to a receiving device).

[0086] When receiving various signals (such as synchronization signals, reference signals, beam selection signals, or other control signals) from base station 105, the receiving device (e.g., UE 115) can attempt multiple receiving configurations (e.g., directional listening). For example, the receiving device can attempt multiple receiving directions by: receiving via different antenna subarrays; processing signals received according to different antenna subarrays; receiving according to different sets of receiving beamforming weights applied to signals received at multiple antenna elements of the antenna array (e.g., different directional listening weight sets); or processing received signals according to different sets of receiving beamforming weights applied to signals received at multiple antenna elements of the antenna array. Any of these methods can be referred to as "listening" according to different receiving configurations or receiving directions. In some examples, the receiving device can use a single receiving configuration to receive along a single beam direction (e.g., when receiving data signals). The single receiving configuration can be aligned on a beam direction determined based on listening according to different receiving configuration directions (e.g., a beam direction determined to have the highest signal strength, highest signal-to-noise ratio (SNR), or other acceptable signal quality based on listening according to multiple beam directions).

[0087] The wireless communication system 100 can be a packet-based network operating according to a layered protocol stack. In the user plane, communication at the bearer or packet data convergence protocol (PDCP) layer can be IP-based. The radio link control (RLC) layer can perform packet segmentation and reassembly for communication over logical channels. The media access control (MAC) layer can perform priority processing and multiplexing logical channels into transport channels. The MAC layer can also use error detection techniques, error correction techniques, or both to support MAC layer retransmissions to improve link efficiency. In the control plane, the radio resource control (RRC) protocol layer can provide the establishment, configuration, and maintenance of RRC connections between the UE 115 and the base station 105 or core network 130 that supports radio bearers for user plane data. At the physical layer, transport channels can be mapped to physical channels.

[0088] UE 115 and base station 105 can support data retransmission to increase the likelihood of successful data reception. Hybrid Automatic Repeat Request (HARQ) feedback is a technique used to increase the likelihood of data being correctly received over communication link 125. HARQ can include a combination of error detection (e.g., using Cyclic Redundancy Check (CRC)), forward error correction (FEC), and retransmission (e.g., Automatic Repeat Request (ARQ)). HARQ can improve MAC layer throughput under poor radio conditions (e.g., low signal-to-noise ratio conditions). In some examples, the device can support same-slot HARQ feedback, where the device can provide HARQ feedback in a specific time slot for data received in a previous symbol within that time slot. In other cases, the device can provide HARQ feedback in subsequent time slots or according to some other time interval.

[0089] Configured grant scheduling is a type of uplink resource scheduling that facilitates minimizing scheduling latency, which is beneficial for the delivery of latency-critical services (e.g., service packets corresponding to low latency requirements / standards). Radio network nodes can semi-statically configure one or more periodic resource sets or resource timings for devices to handle latency-critical uplink service arrivals. Configured periodic resource timings can be referred to as configured grant (“CG”) timings. CG resource timings can correspond to the allocation or grant of specific frequency resources within a periodically repeating amount of time available for uplink service transmission. Therefore, when a device facilitating latency-critical services has latency-critical uplink packets arriving (e.g., from an application or from another device), the device can immediately transmit the latency-critical packets during one or more of the next available CG timings. Using CG resource timings can facilitate avoiding service buffering delays caused by the device first requesting a scheduling grant with an indication of how much uplink service to transmit, receiving resource grants, and finally transmitting the uplink service (e.g., CG scheduling can facilitate avoiding dynamic scheduling).

[0090] CG scheduling clearly provides fast uplink packet transmission with less control overhead. However, since CG scheduling typically involves scheduling resources at periodic times, it is more efficient and beneficial when packet arrival rates at a device are nearly periodic. For example, to achieve high network spectral efficiency, radio network nodes can adjust the periodicity of CG resource timings configured for a given device to align with the desired packet arrival rate at the device, thus maximizing the likelihood of efficient utilization of CG resource sets or timings. Furthermore, CG resource sets or timings can be dedicated to a single device or shared among multiple active devices, where each device can be assigned orthogonal scrambling codes or preambles to modulate traffic with respect to the serving network node. This orthogonal modulation facilitates multiple devices simultaneously transmitting their respective uplink traffic loads via the same CG resource timings and enables network nodes to distinguish and individually decode individual traffic flows corresponding to different transmission devices.

[0091] Turn now Figure 2 The accompanying figure illustrates a virtual reality (“VR”) application system 200. In system 200, a wearable VR device 117 is shown from the perspective of a wearer or viewer. The VR device 117 may include a central or gestural visual display portion 202, a left visual display portion 204, and a right visual display portion 206, which can be used to display primary visual information, left peripheral visual information, and right peripheral visual information, respectively. As shown in the figure, portions 202, 204, and 206 are depicted by different lines; however, it should be understood that hardware or software can facilitate a gradual transition from primary information display to peripheral information display.

[0092] As discussed above, different XR use cases may require different corresponding radio performance. Typically, for XR use cases, but unlike for URLLC or eMBB use cases, a reasonable end-user experience requires a high-capacity radio link carrying XR data services (e.g., data streams including visual information) with stringent radio performance requirements (e.g., latency) and reliability. For example, some XR applications require a 100 Mbps link with an allowable radio latency of approximately 2 ms, compared to a 5 Mbps URLLC link with a 1 ms radio latency budget.

[0093] Through research, several characteristics of XR data services have been identified: (1) XR service characteristics are usually periodic, with time-varying packet size and packet arrival rate; (2) Due to the limited form factor of the device, XR-enabled devices can be more power-limited than conventional mobile handheld devices (e.g., smart glasses, projection wearables, etc.); (3) Multiple data packet streams corresponding to different visual information of a given XR session are not perceived by the user as having the same impact on the end-user experience.

[0094] Therefore, in addition to requiring XR-specific power efficiency, smart glasses (such as wearable device 117) streaming 180-degree high-resolution frames also require bandwidth capacity to provide an optimal user experience. However, it has been determined that data corresponding to frames carrying primary or central visual information (i.e., posture or forward orientation) is most important to end-user satisfaction, while frames corresponding to peripheral visual information have a smaller impact on user experience. Therefore, accepting higher latency for less important traffic flows allows resources that would otherwise be allocated to less important traffic flows to be used for traffic flows corresponding to more important services or devices carrying more important services. This can be used to optimize the overall capacity and performance of wireless communication systems, such as 5G communication systems using NR technologies, methods, systems, or devices. For example, a wireless data traffic flow carrying visual information for display on the central or posture visual display section 202 can be prioritized over a wireless data traffic flow carrying visual information for the left visual display section 204 or the right visual display section 206.

[0095] The performance of a communication network in providing XR services can be determined, at least in part, based on user satisfaction with the XR services. Each user equipment device using an XR service can be associated with one or more specific QoS parameter standards, with which measurements or metrics corresponding to the traffic flows that facilitate the XR service can be analyzed. Adjusting traffic scheduling so that measured traffic flow metrics meet QoS parameters (such as, for example, data rate, end-to-end latency, or reliability) can improve the user's XR experience.

[0096] 5G NR radio systems typically include a Physical Downlink Control Channel (“PDCCH”), which can be used to deliver downlink and uplink control information to cellular devices. The 5G control channel can facilitate operation according to the requirements of URLLC and eMBB use cases and can promote efficient coexistence between these different QoS categories.

[0097] Multimodal XR can be used in the implementation of XR services. Beyond XR games and entertainment services, multimodal XR services can facilitate diverse use cases. For example, multimodal XR services can facilitate application categories where multiple downlink-downlink or downlink-uplink traffic flows are correlated or interdependent. However, traditional techniques do not facilitate relative QoS enforcement between correlated traffic flows. Instead, correlated traffic flows are processed independently so that independent QoS standards corresponding only to a given flow can be enforced. This independent processing of correlated traffic flows can lead to performance slowdowns and degradation in multimodal XR applications.

[0098] Multimodal XR application categories can include applications where multiple downlink and / or uplink traffic flows, although serving different XR viewing, control, or gesture purposes, can be highly correlated or related to each other. Each traffic flow / flow can be associated with one or more independent QoS parameter standards to be satisfied. However, each flow can have a practically relative or related QoS with reference to another related downlink or uplink traffic flow. For example, from the time the RAN node receives a packet corresponding to a packet of the related traffic flow (uplink or downlink), the RAN node should schedule packets for transmitting the downlink traffic flow within a maximum delay standard to provide an improved user experience. Satisfactory delivery of packets of a traffic flow (e.g., the target traffic flow for the purposes of discussion) can depend on the satisfaction of relative QoS standards (e.g., relative delay, relative reliability, or relative data rate) with respect to the reception or transmission of packets of the relative traffic flow, and not just on the satisfaction of independent standards corresponding to the target flow itself.

[0099] For example, in educational XR applications, where a virtual object pops up in the user's XR device's field of view when a user views or clicks on an associated real / virtual object, the relative Quality of Service ("rQoS") (e.g., relative tolerable latency budget) should be satisfied between the uplink traffic flow carrying the indication that the user has viewed or clicked the real / virtual object and the corresponding downlink traffic flow carrying the corresponding virtual object that will pop up. In another example, the uplink traffic transmitted by the XR device can be correlated with the downlink traffic. In either case, if the latency between the uplink and downlink flows is large (or vice versa), the user experience may be severely impacted.

[0100] Multimodal services can include multiple unidirectional and / or cross-directional service flows (e.g., downlink and uplink service flows) that are related to each other. This requires that one or more relative Quality of Service (QoS) performance targets / requirements corresponding to one of these flows must be met to ensure that the criteria corresponding to another flow are met and to deliver a smooth user experience. For example, based on the reception of packets corresponding to an associated multimodal downlink service at a device, uplink service packets triggered or generated at the device must typically be delivered to the serving RAN node within a strict delay budget regarding the time when the downlink service is received by the device, and therefore must typically be scheduled for transmission.

[0101] The benefits of traditional uplink scheduling schemes, such as configuration-authorized (“CG”) scheduling, which are adapted to maximum latency, typically depend on pre-allocating uplink resources to match the anticipated generation or availability of corresponding uplink services associated with downlink services. However, uplink multimodal services often correspond to associated downlink services that may not be periodic or based on independently, predictably, and periodically generated uplink transmissions or available for uplink transmission. Accordingly, the embodiments disclosed herein may include uplink CG scheduling for multimodal uplink services that facilitates the satisfaction of multiple relative QoS objectives between (multiple) service flows in a spectrum-efficient manner.

[0102] In embodiments, user equipment can be deployed as an extended reality processing unit and can facilitate communication with RAN nodes representing less capable terminal XR devices (e.g., less capable in terms of processing power, battery capacity, transmitter power, etc.). The extended reality processing unit can include "in-box" processing units / devices that facilitate signaling, traffic processing, and overall radio assistance for terminal XR devices (e.g., helmets or glasses), which may be able to communicate directly with RAN nodes, but with reduced capabilities. Therefore, intermediate XR processing units (e.g., laptops or smartphones positioned in between regarding the communication link between RAN nodes and terminal XR devices) can facilitate a reduction in the large subset of radio operations, traffic processing, and battery-consuming loads associated with terminal XR devices, thus leading to more efficient terminal XR device designs (e.g., requiring smaller battery sizes, less heat dissipation, etc.).

[0103] It is expected that RAN nodes can identify XR services corresponding to a given XR application to facilitate optimized scheduling strategies based on XR services, thereby improving the efficiency of network resource capacity utilization and network energy efficiency. This can be achieved by RAN nodes hibernating or shutting down transceivers without negatively impacting XR performance. For many interactive XR applications, human user behaviors corresponding to different users (e.g., user XR device posture orientation patterns, user mobility, user hand orientation, or (multiple) user eye rolls) can significantly influence different service and network behaviors from one user to another. For example, a young, energetic XR user can quickly change the posture orientation of the XR glass / device, which can cause the XR device being used by the young user to trigger frequent uplink control signaling transmissions carrying posture position updates and request faster downlink service scheduling compared to another user (e.g., the young user can correspond to an increase in the average of requested downlink services). The actions of human users using XR devices can deviate from predetermined service characteristics and can be "unknown" to RAN nodes (e.g., RAN nodes neither know nor have any predictive intelligence about short-term XR user behavior corresponding to user behavior). Therefore, using conventional technologies, RAN nodes cannot optimize scheduling strategies and energy-saving measures based on terminal XR user actions.

[0104] Digital Twin (“DT”)

[0105] Digital twins (which can be conceptualized as virtual copies of physical systems) have the potential to provide transformative insights into system and user behavior, diagnostics, and predictive analytics across many technology sectors. Regarding extended reality, DT can facilitate understanding user behavior to optimize resource utilization and energy efficiency measures. The immersive nature of XR, characterized by real-time interaction and rich visual experiences, suggests that DT could be a suitable platform for monitoring user interactions. Beyond its promise of enhanced user experience, it also has the potential to extend battery life corresponding to XR devices and improve their energy efficiency.

[0106] DT (Digital Transmission) can capture a range of user behavior metrics in an XR context, from gestures and orientations to eye rolls and clicks. Given the benefits of 5G and future generations of wireless communication, such as Ultra-Reliable Low-Latency Communication (URLLC) and Enhanced Mobile Broadband (eMBB), the role of DT may be even more crucial. DT can facilitate the identification of correlations between user behavior, network requirements, and energy consumption patterns by simulating user behavior in different scenarios. Predictive analytics embedded within these DT models can predict how changes in the radio network can impact XR user behavior and energy footprint. Modeling XR user metrics by DT can facilitate (multiple) dynamic adjustments to system parameters (e.g., parameters corresponding to RAN nodes or XR devices / headsets) to improve the user experience and energy consumption corresponding to the use of XR devices / headsets. Minimizing image rendering or re-rendering, adjusting display brightness based on needs, or optimizing data transmission corresponding to XR sessions via long-range wireless radio networks can all contribute to reduced energy consumption. Therefore, using DT can not only enhance the user experience but also improve the overall energy consumption of components within the XR ecosystem.

[0107] DT can be beneficial in at least three ways: modeling and predicting user behavior; correlation with RAN resources; or optimizing resource utilization.

[0108] Modeling and predicting user behavior.

[0109] Data analytics (DT) can be trained to understand patterns in user behavior metrics. By analyzing historical data and identifying patterns or trends in how users interact within an XR environment, DT can predict or forecast future user behavior. For example, if users tend to increase their interaction with a particular XR module or application during a specific time of day or under specific conditions, DT can predict this upward trend and update the XR system (including serving RAN nodes) accordingly.

[0110] Correlation with RAN resources.

[0111] Beyond predicting user behavior characteristics, DT can also generate information that can be used to facilitate RAN node resource scheduling to accommodate anticipated / predicted user behavior or actions. As XR experiences become increasingly data-intensive, the balance between latency (e.g., delay) and rate (e.g., data throughput) becomes increasingly important. For example, DT predictions can foresee that a surge in user activity may require higher data rates, or that specific user interactions may demand ultra-low latency to maintain immersion. By associating predicted user behavior with RAN resource utilization, DT can facilitate proactive signaling requests to RAN nodes for resource allocation or reallocation based on predicted user behavior. Thus, for example, network resources can be provisioned based on predicted user activity to facilitate a seamless and immersive XR experience for users.

[0112] Optimizing resource utilization.

[0113] DT (Data Transmission) not only enhances the user experience but also helps optimize network resource scheduling. By predicting user behavior and corresponding RAN resource requirements, it can minimize wasteful over-provisioning and undesirable under-provisioning of RAN nodes. Therefore, it not only saves valuable network resources but also allows the XR (Extremely Responsive Network) environment to respond to and adapt to user needs and expectations.

[0114] According to the embodiments disclosed herein, adaptive predictive signaling instructing feedback on short-term XR user / human behavior or actions can facilitate RAN nodes' awareness of predicted user actions and behaviors, and accordingly optimize radio operations regarding the predicted XR user behavior. Artificial intelligence / machine learning (“AI / ML”) predictive capabilities regarding XR user behavior can be configured or programmed into the XR device or XR processing unit, which can support communication between the XR device and the serving RAN node. In embodiments, the AI ​​learning model that can facilitate the prediction of XR user behavior can be facilitated by DT, which can simulate and effectively predict short-term XR human user actions.

[0115] According to the embodiments disclosed herein, the RAN node can determine possible XR device user behavior / action characteristics (e.g., pose, orientation, mobility, eye roll rate, or various viewing areas), which can be fed back from a third-party XR platform / server, which may be part of or communicatively coupled to the core network equipment. The RAN node can compile or receive from the core network equipment a list of standard or common actions and a list of value ranges corresponding to actions to be predicted by the predictive capabilities at the XR device. During the establishment of an XR session, the RAN node can configure the XR device using the list of user behavior characteristics and the associated value ranges, enabling it to predict one or more supported user behavior metrics. The XR device can also be configured with a minimum confidence level or criterion corresponding to the action to be predicted, which, if met, can trigger a report to the RAN node of future / predicted user behavior metrics corresponding to the user characteristics that the XR device can determine and report. If a determined user characteristic value cannot be determined using a confidence level at least as stringent as the confidence level criterion, the confidence level criterion can facilitate avoiding reporting the determined user characteristic value. Accordingly, when a user characteristic value is determined at a confidence level that meets the confidence level criterion, the XR device can report the corresponding user action user characteristic value as a predicted or forecasted value, along with a corresponding valid period indication during which the predicted user behavior metric can be valid (e.g., a confidence level that meets the confidence level criterion can only be valid for the corresponding user characteristic prediction during the valid period). Therefore, the RAN node can be aware of potential future short- to medium-term XR user behaviors / actions and can accordingly fine-tune resource scheduling and energy consumption strategies to accommodate services that can correspond to the predicted potential user behavior. As an example, when it is realized that the pose orientation corresponding to the XR device (based on the confidence level) will not change during the next determined phase (e.g., a valid period during which the confidence level applies to the corresponding reported user characteristic value), the RAN node can temporarily shut down the uplink control resources, which could otherwise be used to carry potential pose information updates from the XR device, thus increasing the network energy savings due to the temporary receiver shutdown.

[0116] Current technologies facilitate rigorous XR services that focus on information, knowledge, or perception acquired by RAN nodes regarding XR service or application behavior. For example, conventional technologies support signaling procedures that enable XR devices to provide RAN nodes with expected service profiles, expected service arrival rates(s), expected packet sizes(s), and other application-dependent performance indicators. However, conventional technologies do not consider XR user / human actions or behaviors. Therefore, the embodiments disclosed herein facilitate the tracking and prediction of XR user / human behavior, featuring dynamic XR user action characteristic reports adapted to a given XR application.

[0117] Furthermore, conventional technologies focus on reporting radio function / performance metrics for application functions / performance metrics. However, according to the embodiments disclosed herein, reports from XR devices or XR processing units can carry XR user / human behavior characteristics, such as human eye roll rate, which are different in nature from conventional radio performance indicators.

[0118] Proactive signals of XR user behavior.

[0119] Turn now Figure 3 The illustration depicts an example environment 300 with an Extended Reality device 117 attached to a User Equipment 115. Regarding the RAN node 105, the device 117 may be referred to as a terminal XR device, which relates to a relationship at the end of a communication session, where the Extended Reality device 115 is located between the RAN node and the device. The XR processing unit 115 may be more powerful than the XR device 117 in terms of battery capacity (or can be powered via a wired power source receiving power from a wall socket) or processing capability. The terminal XR device 117 may transmit XR user behavior characteristic metric updates (e.g., user action information corresponding to one or more behavioral characteristics) to the intermediate processing unit 115, which can track characteristic update information, and based on the user characteristic update information, it can predict (multiple) future user behavior actions corresponding to the use of the XR device. Therefore, when the minimum prediction confidence level corresponding to one or more user behavior characteristics is met, the XR processing unit can use DT and associated AI capabilities to generate a user characteristic report indicating the predicted user behavior, and transmit this report as part of an uplink control information (“UCI”) signaling message to the serving RAN node. XR user characteristic behavior reports may include one or more indexes or indications corresponding to each of one or more XR behavior actions, one or more corresponding predicted action values, levels, or values, and one or more corresponding expected effective time periods applicable to the corresponding prediction. Upon receiving a user characteristic report, the serving RAN node may optimize energy-saving and scheduling measures based on the information indicated in the report corresponding to the expected XR user behavior or action.

[0120] exist Figure 3 In the example embodiment shown, RAN node 105 may receive a list of possible XR user actions or behavioral metrics or characteristics, which can be used by an XR terminal platform or server 150 (most likely located at the network edge) communicatively coupled to core network equipment, which may be part of core network 130, to facilitate XR sessions with device 117. Examples of XR user behaviors that may be supported by XR server 150 may include XR device pose position in degrees, device orientation in degrees, user mobility, user hand orientation information, XR user eye roll rate, or XR device orientation in space. RAN node 105 may transmit the list of possible XR user actions to XR processing unit 115 via user characteristic reporting configuration 305. During connection establishment with RAN node 105, XR processing unit 115 may announce or provide capabilities related to processing capabilities for predicting XR user behavior via user characteristic capability message 320. RAN node 105 can configure XR processing unit 115 with a list of XR user behavior characteristics to be predicted via user characteristic report request message 310. User characteristic report request message 310 may include one or more user characteristic indications corresponding to user characteristics, as indicated in capability message 320. The XR processing unit is capable of predicting these user characteristics, which may be a subset of the user characteristics listed in configuration 305. Configuration 305 may include quantized indications, which may be referred to as user characteristic indications, corresponding to the user characteristics. Therefore, user characteristic indications may include one, two, or several bits to indicate the user characteristics in messages 310 or 320. User characteristic report request message 310 may be referred to as a request because message 310 indicates to XR processing unit 115 the user characteristics to be predicted and reported to RAN node 105, and message 310 indicates the time relative to when the indicated user characteristics should be reported.

[0121] RAN node 105 can configure, indicate, or request XR processing unit 115 to predict and report at least one of the user characteristics indicated in configuration 305 via user characteristic report request message 310. Characteristic report request 310 may include a minimum prediction confidence level or value associated with the indicated user characteristic. Characteristic report request 310 may include a prediction validity period during which the confidence level is relevant to the validity of the user characteristic prediction made by XR processing unit 115. The minimum prediction confidence level can be used by XR processing unit 115 to trigger the transmission of a predicted XR user behavior characteristic value corresponding to the confidence level to RAN node 105 via user characteristic report 325. For example, if XR processing unit 115 determines that it cannot make a prediction of the user characteristic with a confidence level that satisfies the minimum confidence level configured via request 310 within the validity period specified in the configuration in request 310, the XR processing unit may avoid reporting a user action indication in report 325, which indicates a user action corresponding to the user characteristic indicated by user characteristic report request 310. A confidence level threshold can be specified to enable all XR devices to calculate XR predictions in a consistent and predetermined manner, or a confidence level can be specified to enable RAN node 105 to specify a minimum confidence level applied to determine or report XR user behavior metrics. XR processing unit 115, using AI / ML or DT prediction capabilities, can track XR user behavior actions 315 received from XR user device 117, and therefore can predict all or part of the XR user behavior characteristic metrics configured or requested via request 310, corresponding to the user characteristics(s) configured by request 310. When the minimum configured prediction confidence level corresponding to the prediction of the XR user actions configured or requested via request 310 is satisfied, XR processing unit 115 can compile an XR user behavior report 325, which may include predicted values ​​or information corresponding to the XR user behavior actions valid during the corresponding prediction validity period(s) indicated in request 310. In an embodiment, the XR user behavior report 325 may include one or more prediction validity periods associated with one or more predicted values ​​or information corresponding to the XR user behavior characteristics indicated in request 310, the validity periods of which are shorter or longer than the corresponding prediction validity periods indicated in request 310.

[0122] Turn now Figure 4 The illustration shows an example user feature report configuration 305. The extended reality processing unit can receive configuration 305, which includes features to be processed by the XR processing unit (such as a reference). Figure 3 The XR processing unit 115 describes a list of potential XR user behavior characteristics predicted by the XR processing unit. Serving RAN nodes (such as reference...)Figure 3 The described node 105 can receive from core network equipment (including edge XR servers) a list of all XR user characteristics supported or available by the XR server for potential tracking and prediction purposes, wherein each XR user characteristic or behavior 410 is associated with a user characteristic indication 405 in configuration 305, which is transmitted from the serving RAN node to the XR processing unit. Actions or behaviors 410 may be referred to as user characteristics, and indications 405 may be referred to as user characteristic indications. Examples of user characteristics 410 may include: tracking of the posture and position of an XR device being used by a user; XR device orientation tracking; multiple movements of the user's hands(s); or user eye roll.

[0123] Therefore, during the establishment of an XR session connection, the serving RAN node can utilize the information in configuration 305, which is part of the downlink control information (“DCI”) signaling message, to configure the XR processing unit. (See reference...) Figure 3 As described, configuration information 305 can be processed or interpreted as a request by XR processing unit 115 to provide predictive capabilities regarding the ability to predict user actions corresponding to feature 410, which can be performed by the user of the XR device during an XR session between the XR device and the serving RAN facilitated by the XR processing unit.

[0124] Turn now Figure 5 The illustration shows an example user characteristic report request 310 transmitted in DCI message 500. The user characteristic report request information 310 may include a user characteristic confidence level criterion in field 505, which may be a minimum threshold. This user characteristic confidence level criterion can be used by the XR processing unit to trigger compilation and transmission of the predicted XR user characteristics in user characteristic report 325 to the serving RAN node (see [link to documentation]). Figure 3 (As described). The confidence level standard for user characteristics indicated in field 505 of request information 310 can be included in information 310 along with user characteristic indications (e.g., contained in...). Figure 4 This is related to the indication in field 405 shown in the document. The User Characteristics Report Request Information 310 may include in field 410 an indication of the maximum allowable time length / valid time period during which the XR processing unit should be able to confidently predict predicted XR user behavior characteristic values ​​(e.g., the prediction of future user characteristic behavior meets the user characteristic confidence level standard indicated in field 505 corresponding to the valid time period).

[0125] The user characteristic confidence level criterion indicated in field 505 can facilitate the minimum prediction accuracy corresponding to a given user behavior characteristic before reporting the predicted values(s) corresponding to the user characteristic to the serving RAN node, thus minimizing "misleading" RAN nodes with poorly predicted XR user behavior characteristic values. Therefore, the XR processing unit can avoid transmitting user characteristic reports containing predicted user characteristics until the user characteristic to be reported via the user characteristic report can be predicted using the confidence level that meets the criterion specified in field 505. The effective period indicated in field 510 can be the time period during which the XR processing unit determines the confidence level associated with the predicted user characteristic value can continue or may be applicable.

[0126] Turn now Figure 6 The illustration shows an example user characteristic report 325. Report 325 may include information corresponding to one or more terminal XRs (e.g., Figure 3The terminal XR device 117 shown herein has one or more XR device identifiers 605A to 605n. For a given XR device identifier 605A, 605B, ..., or 605n, one or more user characteristic indications may be indicated in fields 610A, 610B, ..., or 610n. It will be understood that the user characteristic indications indicated in one or more fields 610 may be user character indications(s) indicated in configuration 305 or requested in request message information 310. One or more user characteristic indications may be indicated in a single field 610. For example, for XR device y2 indicated in field 605B, one or more user characteristic indications may be indicated in the corresponding field 610B. For each or more user characteristic indications indicated in field 610, one or more corresponding predicted user characteristic values ​​may be indicated in the corresponding field 615. For each or more predicted user characteristic values ​​indicated in field 615, one or more corresponding valid time periods may be indicated in the corresponding field 620. For example, for the terminal XR device y2 indicated in field 605A, field 610A may include a user characteristic indication (0) and a device orientation indication (1), whereby the user characteristic indication (0) corresponds to the position of the pose portion of the terminal XR device, and the device orientation indication (1) corresponds to the orientation of the terminal XR device y2. In the example, field 615A may include a value in degree indicating the position of the pose portion of the XR device indicated in field 605A, and field 615A may also include a value in degree indicating the orientation of the XR device indicated in field 605A. Field 620A may include a first valid time period corresponding to the pose position value indicated in field 615A and a second valid time period corresponding to the device orientation value indicated in field 615A. The valid time periods indicated in one or more fields 620 may be the same as or different from the valid time periods indicated in request message 310, corresponding to one or more user characteristic indications indicated in field 610A. Therefore, configuration 310 may include a valid time period during which the XR processing unit should have at least the same confidence level as indicated in configuration information 310, i.e., the predicted values ​​corresponding to the user characteristics indicated in configuration 310 are valid. However, the XR processing unit reporting the predicted user characteristic values ​​in field 615 of report 325 may determine a different valid time period than the valid time period indicated in request 310, for example, a shorter valid time period, based on the processing capacity of the processing unit.In an embodiment, the effective period indicated in report 325 may be based on the quality of service corresponding to resources configured by the serving RAN to facilitate the delivery of services corresponding to user actions associated with a given user characteristic indicated in report 325, which are performed by the user after the predicted value indicated in field 615 of report 325 is generated. For example, if the XR processing unit does not need to guarantee that the prediction of the user characteristic value in report 325 with a given confidence level will be valid if the effective period is longer, the effective period may correspond to a reduction, relaxation, or easier processing by the XR processing unit. Therefore, the DT or machine learning model corresponding to the XR processing unit may require less processing to make a prediction that meets the confidence level in a short period compared to if the DT or machine learning model makes a prediction that must meet the confidence level in a long period.

[0127] Turn now Figure 7 The illustration shows an example embodiment of directing user characteristic capability indicators to an extended reality processing unit. Figure 7 The diagram illustrates the communication flow between three entities: XR device 117, the DT (Digital Technology Provider) executing at XR processing unit 115, and serving RAN node 105. Initially, RAN node 105 requests DT prediction capability information from XR device 117, which can forward the request to the DT. The DT responds to XR device 117 using the capability information, and the device relays a list of supported XR user behavior characteristics (e.g., gestures, orientations, eye rolls, clicks, etc.) to RAN 105. In response, RAN node 105 can provide XR processing unit 115 with DT performance provisioning configuration information, including confidence level and effective time period information, such as information that can be included in the reference... Figure 3 The request 310 is described. In an alternative streaming embodiment, XR processing unit 115 can check the prediction confidence and effective period of the DT by requesting the DT user behavior report. Upon confirming the compliance of the report from the DT, XR processing unit 115 can transmit the user behavior characteristic report, such as reference, to RAN node 105. Figure 3 The report described is 325.

[0128] Turn now Figure 8 The illustration shows an example embodiment in which a user characteristic capability indicator is directed to a wireless access network node 105. Figure 8The illustrated embodiment can be useful when the XR processing unit is facilitated by a DT or other learning model to predict user characteristics, but is not equipped with long-range radio functionality to facilitate communication with the serving RAN node. The XR processing unit 115 can continuously relay real-time user behavior characteristic metrics received from the XR device 117 to the DT. The DT can process the metrics to fine-tune the corresponding learning model. The serving RAN node 105 can request information corresponding to the DT's ability to predict user behavior characteristics. The DT can provide user behavior characteristic metrics corresponding to characteristics such as gesture alignment, device orientation, eye roll, or click. Subsequently, the RAN node 105 can determine and facilitate the transmission of a request information message 310 to the DT, which includes indications of the prediction confidence level or the effective time period corresponding to one or more indicated user characteristics.

[0129] Turn now Figure 9The diagram illustrates a timing diagram of an example embodiment method 900 for providing a user characteristic report to RAN node 105. At action 905, XR processing unit 115 may receive an XR digital twin capability information request from serving RAN node 105. This capability request may be referred to as a user characteristic report configuration and may include a list of user behavior characteristics corresponding to the use of terminal XR device 117 (e.g., characteristics may be one or more of the following: device posture orientation, device orientation, eye roll, click, etc.). At action 910, XR processing unit may transmit device capability information to RAN node 105, indicating the ability to predict user actions of device 117. This device capability information may include an indication of the ability of the digital twin to predict (multiple) user actions when using XR device 117. This capability information may include a list of XR user behavior characteristics, about which processing unit 115 or the DT executed thereby can predict (multiple) future user actions. At action 915, XR processing unit 115 may receive a performance provisioning configuration from serving RAN node 105, which may be referred to as a user characteristic report request. The user characteristic report request may include a minimum threshold indication indicating a prediction confidence level for one or more user behavior characteristics indicated in the capability information transmitted at action 910. This confidence level can be used as a criterion or trigger to determine or transmit expected, predicted user characteristic values ​​to the serving RAN node 105. The user characteristic report request may include an indication of the effective DT prediction phase / duration corresponding to the predicted user characteristic values ​​transmitted to the RAN node in terms of OFDM symbols, microslots, or slots. At action 920, provided that the minimum confidence threshold for one or more user characteristic values ​​predicted by the DT / learning model, as configured in the request received in action 915, is met, the XR processing unit 115 may compile and transmit an XR user behavior report, which may be referred to as a user characteristic report, to the serving RAN node 105. The user characteristic report may include one or more information objects containing or indicating one or more user characteristic values ​​predicted by the DT or other learning model type that meet one or more minimum confidence levels included in the request received at action 915. The user characteristic report may include one or more valid time periods that correspond to user behavior characteristic values ​​or metrics predicted by DT or other learning models performed by XR processing unit 115. RAN node 105 may use the information contained in the user characteristic report to allocate, schedule, reschedule, suspend, adjust, modify, or otherwise change the resources configured for delivering XR services between the RAN node and XR processing unit 115 (or XR device 117).

[0130] Turn now Figure 10The diagram illustrates a flowchart of an example embodiment 1000. Method 1000 begins at action 1005. At action 1010, the XR device can establish an XR session with an XR server via a radio access network node. An XR processing unit, located close to the XR device and communicatively coupled to it via a short-range wireless link (such as a Wi-Fi link or a sidelink), can facilitate service delivery between the radio access network node and the XR device. At action 1015, the radio access network node can request a user characteristic prediction capability regarding the ability to predict user action behavior characteristics corresponding to the use of the XR device. In one embodiment, the prediction capability may correspond to a direct twin or other machine learning model executed by the XR processing unit. In another embodiment, the prediction capability may correspond to a direct twin or other machine learning model executed by the XR device; however, the XR processing unit will typically have superior processing capabilities compared to the XR device. The request for the user characteristic prediction capability can be made via a user characteristic reporting configuration, such as referencing... Figure 3 The configuration described is 310.

[0131] At action 1020, the XR processing unit (or XR device) may transmit a capability indication to the radio access network node, indicating the capability to predict user behavioral characteristics. The capability to predict user behavioral characteristics may depend on processing power or battery power. At action 1025, the radio access network node may transmit a user characteristic prediction configuration / request, including information such as reference... Figure 3 and Figure 5 The information described is 310. The request received at action 1025 may include an indication of one or more user characteristics and an indication of one or more confidence level values ​​corresponding to the one or more user characteristics. The request received at 1025 may include a valid period or an indication of a valid period during which one or more confidence levels corresponding to the predictions of one or more user behavior characteristics associated with one or more user characteristics will be valid.

[0132] At action 1030, the XR processing unit (or XR device) can monitor actual user behavior caused by users of the XR device. For example, the XR processing unit can analyze the traffic delivered between the XR device and the radio access network node to determine the actual user behavior. Based on the actual user behavior determined at action 1030, at action 1035, the XR processing unit (or XR device) can predict future user activity corresponding to the characteristics indicated in the request received at action 1025, and can indicate the predicted future user activity using one or more predicted user characteristic values ​​or indications of predicted user characteristic values. At action 1040, the XR processing unit (or XR device) can determine whether the predicted user characteristic value determined at action 1035 meets the criteria indicated in the request received by the XR processing unit (or XR device) at action 1025. If the predicted user characteristic value determined at action 1035 is determined at action 1040 to not meet the corresponding criteria indicated in the request received at action 1025, then method 1000 returns to action 1035. For example, if the predicted user characteristic value determined at action 1035 cannot be predicted by the XR processing unit (or XR device) using a confidence level that meets the confidence level indicated in the request received at action 1025, then the XR processing unit (or XR device) may continue to monitor user behavior at action 1030 and determine the predicted user characteristic value at action 1035.

[0133] If a criterion is determined at action 1040, such as the confidence level corresponding to the predicted user characteristic value, which satisfies the confidence level criterion indicated in the request received at action 1025, method 1000 may proceed to action 1045. At action 1045, the XR processing unit (or XR device) may transmit the predicted user characteristic value corresponding to the user characteristic indicated in the request received at action 1025 as a user characteristic report to the radio access network node. At action 1050, the radio access network node may allocate resources based on the predicted user behavior characteristic value reported at action 1045 and the user characteristic report at action 1045 for use in delivering services corresponding to the XR session established at action 1010. Method 1000 proceeds to action 1055 and ends.

[0134] Turn now Figure 16 The illustration shows an example of information 1600 corresponding to the use of a terminal XR device, which can be used by DT or other learning models to predict user behavior characteristics. These user behavior characteristics can be used by RAN nodes to facilitate the scheduling of resources available for delivering services related to the use of the XR device. Information 1600 may include information that can be used by RAN nodes to facilitate the determination of resources available for delivering services related to the use of the XR device. Figure 4The user behavior characteristics indicated in fields 410A, 410B, ... 410n are shown.

[0135] Turn now Figure 11 The illustration depicts an example embodiment of method 110, which includes: at block 1150, a user equipment including a processor facilitating the reception of a user characteristic report configuration from a radio access network node, including at least one user characteristic indication indicating at least one user characteristic; at block 1110, the user equipment facilitating the reception of a user characteristic report request from the radio access network node, including at least one of the at least one user characteristics indicated by the at least one user characteristic indication; at block 1115, the user equipment determining at least one user action indication indicating at least one user action corresponding to at least one of the at least one user characteristics indicated by the user characteristic report request; and at block 1120, in response to receiving the user characteristic report request, the user equipment facilitating the transmission of a user characteristic report including at least one user action indication to the radio access network node.

[0136] Turn now Figure 12 The illustration depicts an example extended reality processing unit, comprising: at block 1205, a processor configured to process executable instructions that, when executed by the processor, facilitate the execution of operations including: receiving a user characteristic report configuration from a radio access network node, including at least one user characteristic indication indicating at least one user characteristic; at block 1210, receiving a user characteristic report request from a radio access network node, including at least one characteristic of at least one user characteristic indicated by the at least one user characteristic indication and at least one confidence level indication indicating at least one confidence level criterion corresponding to the at least one user characteristic indication; at block 1215, determining at least one user action prediction indication indicating at least one predicted user action corresponding to at least one characteristic of at least one user characteristic indicated by the user characteristic report request; and at block 1220, in response to receiving the user characteristic report request and based on the at least one user action prediction indication satisfying at least one confidence level criterion corresponding to the at least one characteristic, transmitting a user characteristic report including at least one user action indication.

[0137] Turn now Figure 13The illustration depicts a non-transitory machine-readable medium 1300, comprising: at block 1305, executable instructions that, when executed by a processor of an extended reality (XR) processing unit, facilitate the execution of operations including: receiving a user characteristic report configuration from a radio access network node, including at least one user characteristic indication indicating at least one user characteristic; and at block 1310, receiving a user characteristic report request from a radio access network node, including at least one indication of the at least one user characteristic indication, wherein the user characteristic report request includes an indication of at least one confidence level corresponding to the at least one user characteristic indication. At least one confidence level indication of the standard; at block 1315, receiving from the XR device at least one user action indication indicating at least one user action corresponding to at least one of at least one user characteristic indicated by a user characteristic report request; at block 1320, determining at least one user characteristic prediction that satisfies at least one confidence level criterion based on at least one user action indication to obtain a user characteristic prediction satisfaction result; and at block 1325, in response to receiving a user characteristic report request, transmitting a user characteristic report including the user characteristic prediction satisfaction result to the radio access network node.

[0138] To provide additional context for the various embodiments described herein Figure 14 The following discussion is intended to provide a brief overview of a suitable computing environment 1400 in which various embodiments of the examples described herein can be implemented. While the embodiments have been described above in the general context of computer-executable instructions that can run on one or more computers, those skilled in the art will recognize that these embodiments can also be implemented in combination with other program modules and / or as a combination of hardware and software.

[0139] Typically, program modules include routines, programs, components, data structures, etc., that perform specific tasks or implement specific abstract data types. Furthermore, those skilled in the art will appreciate that these methods can be practiced using other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframes, IoT devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, each of which can be operatively coupled to one or more associated devices.

[0140] The embodiments described herein can also be practiced in a distributed computing environment, where certain tasks are performed by remote processing devices linked via a communication network. In a distributed computing environment, program modules can reside on both local and remote memory storage devices.

[0141] Computing devices typically include a variety of media, which may include computer-readable storage media, machine-readable storage media, and / or communication media, these two terms being used herein in ways distinct from each other. A computer-readable storage medium or a machine-readable storage medium can be any available storage medium accessible by a computer, and includes both volatile and non-volatile media, as well as both removable and non-removable media. By way of example, and not limitation, a computer-readable storage medium or a machine-readable storage medium can be implemented in combination with any method or technique for storing information such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0142] Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray disc (BD) or other optical disc storage devices, magnetic cartridges, magnetic tapes, disk storage devices or other magnetic storage devices, solid-state drives or other solid-state storage devices, or other tangible and / or non-transitory media that can be used to store desired information. In this regard, the terms “tangible” or “non-transitory” as used herein for storage devices, memories, or computer-readable media should be understood as modifiers that exclude only the propagation of transient signals themselves, and do not waive the rights to all standard storage devices, memories, or computer-readable media that do not only propagate transient signals themselves.

[0143] Computer-readable storage media can be accessed by one or more local or remote computing devices, for example via access requests, queries or other data retrieval protocols, for various operations concerning the information stored on the media.

[0144] Communication media typically embody computer-readable instructions, data structures, program modules, or other structured or unstructured data in data signals (such as modulated data signals, for example, carrier waves or other transmission mechanisms), and include any information delivery or transmission medium. The term "modulated data signal" or signal refers to a signal having one or more characteristics that are set or altered in such a way as to encode information into one or more signals. By way of example, and not limitation, communication media include wired media (such as wired networks or direct wired connections) and wireless media (such as acoustic, RF, infrared, and other wireless media).

[0145] Refer again Figure 14An example environment 1400 for implementing the various embodiments described herein includes a computer 1402, which includes a processing unit 1404, system memory 1406, and a system bus 1408. The system bus 1408 couples system components, including but not limited to system memory 1406, to the processing unit 1404. The processing unit 1404 can be any processor from a variety of commercially available processors and may include cache memory. Dual-microprocessor and other multiprocessor architectures may also be employed as the processing unit 1404.

[0146] System bus 1408 can be any type of bus architecture among several types of bus architectures, which can also interconnect to memory buses (with or without memory controllers), peripheral buses, and local buses using any of the various commercially available bus architectures. System memory 1406 includes ROM 1410 and RAM 1412. The Basic Input / Output System (BIOS) can be stored in non-volatile memory, such as ROM, erasable programmable read-only memory (EPROM), or EEPROM, and its BIOS contains basic routines that facilitate the transfer of information between components within computer 1402, such as during startup. RAM 1412 may also include high-speed RAM, such as static RAM for caching data.

[0147] Computer 1402 also includes an internal hard disk drive (HDD) 1414 (e.g., EIDE, SATA), one or more external storage devices 1416 (e.g., floppy disk drive (FDD) 1416, memory stick or flash drive reader, memory card reader, etc.), and an optical disc drive 1420 (e.g., capable of reading from or writing to CD-ROMs, DVDs, BDs, etc.). Although the internal HDD 1414 is illustrated as being located within computer 1402, it can also be configured for external use in a suitable chassis (not shown). Additionally, although not shown in environment 1400, a solid-state drive (SSD) can be used in addition to or as an alternative to HDD 1414. HDD 1414, external storage devices 1416, and optical disc drive 1420 can be connected to system bus 1408 via HDD interface 1424, external storage interface 1426, and optical disc drive interface 1428, respectively. The interface 1424 for external driver implementation may include at least one or both of Universal Serial Bus (USB) and Institute of Electrical and Electronics Engineers (IEEE) 1394 interface technologies. Other external driver connectivity technologies are contemplated in the embodiments described herein.

[0148] The drive and its associated computer-readable storage medium provide non-volatile storage of data, data structures, computer-executable instructions, etc. For computer 1402, the drive and storage medium accommodate storage of any data in a suitable digital format. Although the above description of computer-readable storage media refers to a corresponding type of storage device, those skilled in the art will understand that other types of computer-readable storage media (whether currently existing or to be developed in the future) may also be used in the example operating environment, and further, any such storage medium may contain computer-executable instructions for performing the methods described herein.

[0149] Multiple program modules, including an operating system 1430, one or more application programs 1432, other program modules 1434, and program data 1436, can be stored in the drive and RAM 1412. All or part of the operating system, applications, modules, and / or data can also be cached in RAM 1412. The systems and methods described herein can be implemented using various commercially available operating systems or combinations of operating systems.

[0150] Computer 1402 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediate program may emulate a hardware environment for operating system 1430, and the emulated hardware may optionally be compatible with... Figure 14 The hardware shown is different. In this embodiment, the operating system 1430 may include one of a plurality of virtual machines (VMs) hosted on the computer 1402. Furthermore, the operating system 1430 may provide a runtime environment for the application 1432, such as the Java Runtime Environment or the .NET Framework. A runtime environment is a consistent execution environment that allows the application 1432 to run on any operating system that includes that runtime environment. Similarly, the operating system 1430 may support containers, and the application 1432 may be in the form of a container, which is a lightweight, standalone, executable software package that includes, for example, application-specific code, runtime, system tools, system libraries, and settings.

[0151] Furthermore, computer 1402 may include a security module, such as a Trusted Processing Module (TPM). For example, before loading the next startup component, the startup component uses the TPM to hash the next startup component over time and waits for the result to match a security value. This process can occur at any layer of the computer 1402's code execution stack, for example, at the application execution level or at the operating system (OS) kernel level, thereby achieving security at any code execution level.

[0152] Users can input commands and information into computer 1402 through one or more wired / wireless input devices, such as keyboard 1438, touchscreen 1440, and pointing devices such as mouse 1442. Other input devices (not shown) may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls or other remote controls, joysticks, virtual reality controllers and / or virtual reality headsets, gamepads, styluses, image input devices (e.g., cameras), gesture sensor input devices, visual motion sensor input devices, emotion or face detection devices, biometric input devices (e.g., fingerprint or iris scanners), etc. These and other input devices are typically connected to processing unit 1404 via input device interface 1444, which can be coupled to system bus 1408, but may also be connected via other interfaces, such as parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, BLUETOOTH® interfaces, etc.

[0153] Monitor 1446 or other types of display devices can also be connected to system bus 1408 via an interface such as video adapter 1448. In addition to monitor 1446, computers typically include other peripheral output devices (not shown), such as speakers, printers, etc.

[0154] Computer 1402 can operate in a networked environment using logical connections to one or more remote computers (such as (multiple) remote computers 1450) via wired and / or wireless communications. The (multiple) remote computers 1450 can be workstations, server computers, routers, personal computers, laptops, microprocessor-based entertainment devices, peer-to-peer devices, or other public network nodes, and generally include many or all of the elements described relative to computer 1402, although for simplicity, only memory / storage device 1452 is illustrated. The depicted logical connections include wired / wireless connectivity to a local area network (LAN) 1454 and / or a larger network (e.g., a wide area network (WAN) 1456). Such LAN and WAN network environments are common in offices and companies and facilitate enterprise-wide computer networks (such as intranets), all of which can connect to global communication networks (e.g., the Internet).

[0155] When used in a LAN network environment, computer 1402 can connect to local area network 1454 via a wired and / or wireless communication network interface or adapter 1458. Adapter 1458 can facilitate wired or wireless communication to LAN 1454, which may also include a wireless access point (AP) configured thereon for communicating with adapter 1458 in wireless mode.

[0156] When used in a WAN networking environment, computer 1402 may include modem 1460, or may be connected via other means (such as via the Internet) to a communication server on WAN 1456 for establishing communication over WAN 1456. Modem 1460 (which may be internal or external, and wired or wireless) may be connected to system bus 1408 via input device interface 1444. In a networking environment, program modules depicted relative to computer 1402 or portions thereof may be stored in remote memory / storage device 1452. It will be understood that the network connections shown are illustrative, and other means of establishing communication links between computers may be used.

[0157] When used in a LAN or WAN network environment, computer 1402 can access cloud storage systems or other network-based storage systems, in addition to or replacing the external storage device 1416 described above. Typically, the connection between computer 1402 and the cloud storage system can be established via LAN 1454 or WAN 1456, for example, by adapter 1458 or modem 1460. After connecting computer 1402 to the associated cloud storage system, external storage interface 1426 can manage the storage devices provided by the cloud storage system with the aid of adapter 1458 and / or modem 1460, just as it would manage other types of external storage devices. For example, external storage interface 1426 can be configured to provide access to cloud storage sources as if these sources were physically connected to computer 1402.

[0158] Computer 1402 can be operable to communicate with any wireless device or entity operably configured in wireless communication, such as a printer, scanner, desktop and / or laptop computer, portable data assistant, communication satellite, any device or location associated with a wirelessly detectable tag (e.g., newsstand, newsstand, store shelf, etc.), and telephone. This can include Wi-Fi and BLUETOOTH® wireless technologies. Therefore, communication can be a predefined structure like a traditional network, or simply self-organizing communication between at least two devices.

[0159] Turn now Figure 15The accompanying figure shows a block diagram of an example UE 1560. UE 1560 may include a smartphone, a wireless tablet, a laptop computer with wireless capabilities, a wearable device, a machine that can facilitate vehicle telematics, etc. UE 1560 includes a first processor 1530, a second processor 1532, and shared memory 1534. UE 1560 includes a radio front-end circuitry 1562, which may be referred to herein as a transceiver, but is understood to generally include transceiver circuitry, a separate filter, and a separate antenna for facilitating communication over wireless links (such as...). Figure 1 Transceiver 1562 may include multiple sets of circuitry, or may be tunable to accommodate different frequency ranges, different modulation schemes, or different communication protocols to facilitate long-range wireless links (such as link 125, 135, or 137), device-to-device links (such as link 135), and short-range wireless links (such as link 137).

[0160] Continue to Figure 15 As described above, UE 1560 may also include SIM 1564 or SIM profile, which may include information stored in memory (memory 1534 or a separate memory portion) for facilitating communication with... Figure 1 The wireless communication of RAN105 or core network 130 shown in the figure. Figure 15 The SIM 1564 is shown as a single component in the shape of a traditional SIM card, but it will be understood that the SIM 1564 can represent multiple SIM cards, multiple SIM profiles, or multiple eSIMs, some or all of which can be implemented in hardware or software. It will be understood that a SIM profile may include security credentials such as encryption keys, values ​​that can be used to generate encryption keys, or information about the connection between the SIM 1564 and another device (which may be...). Figure 1 Information shared between components of RAN 105 or core network 130 (as shown in the diagram). SIM profile 1564 may also include unique identification information for the SIM or SIM profile, such as, for example, International Mobile Subscriber Identity (“IMSI”) or information that may constitute an IMSI.

[0161] SIM 1564 is shown coupled to both the first processor section 1530 and the second processor section 1532. This implementation offers the advantage that the first processor section 1530 does not need to request or receive information or data from SIM 1564 that could be requested by the second processor section 1532, thus eliminating the use of the first processor as a "middleman" when the second processor uses information from the SIM in performing its functions and executing applications. The first processor 1530 (which may be a modem processor or a baseband processor) is shown smaller than processor 1532 (which may be a more complex application processor) to visually indicate the relative level of complexity (i.e., processing power and performance) and the corresponding level of operational power consumption between the two processor sections. When the UE 1560 does not require the second processor section 1532 to execute applications and process application-related data, keeping the second processor section 1532 in a sleep / inactive / low-power state provides the following advantages: reducing power consumption when only the first processor section 1530 needs to be used, while the UE is in a bearer management and mobility management / maintenance process for monitoring routine configuration, or in a monitoring mode for monitoring the search space where the UE has been configured to remain inactive / sleep in the second processor section.

[0162] UE 1560 may also include sensors 1566 that can provide signals to the first processor 1530 or the second processor 1532, such as temperature sensors, accelerometers, gyroscopes, barometers, humidity sensors, etc. Output devices 1568 may include, for example, one or more visual displays (e.g., computer monitors, VR devices, etc.), acoustic transducers (such as speakers or microphones), vibration components, etc. Output devices 1568 may include software that interfaces with output devices external to UE 1560 (e.g., visual displays, speakers, microphones, tactile devices, olfactory or gustatory devices, etc.).

[0163] The following glossary of terms given in Table 1 may be applied to one or more descriptions of the embodiments disclosed herein. Table 1

[0164] The above description includes non-limiting examples of various embodiments. It is certainly not possible to describe every conceivable combination of components or methods for the purpose of describing the disclosed subject matter, and those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. The disclosed subject matter is intended to cover all such changes, modifications, and variations that fall within the spirit and scope of the appended claims.

[0165] Regarding the various functions performed by the components, devices, circuits, systems, etc., described above, unless otherwise indicated, the terminology used to describe such components (including references to "apparatus") is intended to include any structure(s)(s) performing the specified functions of the described components (e.g., functional equivalents), even if not structurally equivalent to the disclosed structures. Furthermore, while a particular feature of the disclosed subject matter may have been disclosed only with respect to one of several implementations, such feature may be combined with one or more other features of other implementations, as may be desired and advantageous for any given or particular application.

[0166] The terms “exemplary” and / or “illustrative” or variations thereof, as used herein, are intended to refer to examples, instances, or illustrations. For the avoidance of ambiguity, the subject matter disclosed herein is not limited to such examples. Furthermore, any aspect or design described herein as “exemplary” and / or “illustrative” is not necessarily to be construed as superior to or advantageous to other aspects or designs, nor does it exclude equivalent structures and techniques known to those skilled in the art. Additionally, when the terms “include,” “have,” “comprising,” and other similar words are used in the detailed description or claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open-ended transition—without excluding any additional or other elements.

[0167] As used herein, the term “or” is intended to mean inclusive “or” rather than exclusive “or.” For example, the phrase “A or B” is intended to include instances of A, B, and both A and B. Additionally, unless otherwise specified or clearly indicated from the context to be singular, the articles “a” and “an” as used in this application and the appended claims should generally be interpreted as meaning “one or more”.

[0168] As used herein, the term "set" does not include an empty set, i.e., a set containing no elements. Therefore, "set" in this disclosure includes one or more elements or entities. Similarly, as used herein, the term "group" refers to a collection of one or more entities.

[0169] Unless otherwise expressly provided by the context, the terms “first,” “second,” “third,” etc., as used in the claims are for clarity only and do not otherwise indicate or imply any temporal order. For example, “first determination,” “second determination,” and “third determination” do not indicate or imply that the first determination precedes the second determination, or vice versa, etc.

[0170] The description of embodiments of the present disclosure provided herein (including those described in the abstract) is not intended to be exhaustive or to limit the disclosed embodiments to the precise forms disclosed. While specific embodiments and examples have been described herein for illustrative purposes, various modifications are possible within the scope of such embodiments and examples, as will be appreciated by those skilled in the art. In this regard, although the subject matter has been described herein in conjunction with various embodiments and corresponding drawings, it will be understood where applicable that other similar embodiments may be used, or modifications and additions may be made to the described embodiments to perform the same, similar, alternative, or substitute functions as the disclosed subject matter without departing from the content of the disclosed subject matter. Therefore, the disclosed subject matter should not be limited to any single embodiment described herein, but should be interpreted broadly and broadly in accordance with the appended claims.

Claims

1. A method comprising: A user equipment including a processor facilitates the reception of a user characteristic report configuration from a radio access network node, the user characteristic report configuration including at least one user characteristic indication indicating at least one user characteristic; The user equipment facilitates the reception of a user characteristic report request from the radio access network node, the user characteristic report request including at least one of the at least one user characteristic indicated by the at least one user characteristic indicator; The user equipment determines at least one user action indication that indicates at least one user action, the at least one user action corresponding to at least one of the at least one user characteristics indicated by the user characteristic report request; In response to receiving the user characteristic report request, the user equipment facilitates the transmission of a user characteristic report, including the at least one user action indication, to the radio access network node.

2. The method of claim 1, wherein the at least one user action indicates resources that the radio access network node can use to schedule the delivery of services corresponding to the at least one user action.

3. The method of claim 1, wherein the user characteristic report request includes at least one confidence level indication indicating at least one confidence level standard corresponding to the at least one user characteristic indication, the method further comprising: The user equipment determines the at least one user characteristic based on the satisfaction of the at least one confidence level criterion, to obtain at least one determined user characteristic. The transmission of the user characteristic report is based on the at least one determined user characteristic satisfying the at least one confidence level criterion corresponding to the at least one user characteristic.

4. The method of claim 3, wherein the user characteristic report request includes at least one configured user characteristic indication duration indication indicating at least one configured user characteristic indication validity period length, during which the at least one confidence level criterion will be valid with respect to the at least one determined user characteristic.

5. The method of claim 4, wherein the user characteristic report further includes at least one actual user characteristic indication duration indication indicating at least one user characteristic indication validity period indication, the at least one user characteristic indication validity period indication indicating at least one user characteristic indication validity period during which the at least one confidence level criterion is valid with respect to the at least one determined user characteristic.

6. The method of claim 5, wherein the effective period of the at least one user characteristic indication indicated in the user characteristic report is less than the effective period length of the at least one configured user characteristic indication.

7. The method of claim 1, wherein the user characteristic report configuration is generated by an extended reality (XR) server.

8. The method according to claim 1, further comprising: The user equipment facilitates the transmission of at least one user characteristic capability indication to the radio access network node, indicating at least one user characteristic capability, in relation to the user equipment reporting the at least one characteristic of the at least one user characteristic indication requested via the user characteristic reporting request.

9. The method of claim 8, wherein the user equipment includes a digital twin module to facilitate the determination of the at least one user characteristic capability.

10. The method of claim 1, wherein the extended reality (XR) device includes the user equipment.

11. The method of claim 1, wherein the user equipment is a component of an extended reality (XR) processing unit communicatively coupled to an XR device.

12. The method of claim 1, wherein the at least one user characteristic corresponds to at least one action result caused by the execution of at least one action relating to the use of the extended reality (XR) user interface.

13. The method of claim 12, wherein the at least one action result includes at least one of the following: a specified posture orientation, a horizontal orientation, a target acceleration, a target velocity, a specified user hand orientation, a blink, a target blink rate, or a specified orientation in three-dimensional space.

14. The method of claim 1, wherein the determination of the at least one user action indication comprises: Receive the at least one user action instruction from the extended reality (XR) device.

15. An extended reality (XR) processing unit, comprising: A processor configured to process executable instructions, which, when executed by the processor, facilitate the execution of operations, including: Receive user characteristic report configuration from a radio network node, the user characteristic report configuration including at least one user characteristic indication indicating at least one user characteristic; Receive a user characteristic report request from the radio network node, the user characteristic report request including at least one of the at least one user characteristics indicated by the at least one user characteristic indication and at least one confidence level indication indicating at least one confidence level standard corresponding to the at least one user characteristic indication; Determine at least one user action prediction indication that indicates at least one predicted user action, the at least one predicted user action corresponding to at least one of the at least one user characteristics indicated by the user characteristic report request; and In response to receiving the user characteristic report request and based on the at least one user action prediction indication satisfying the at least one confidence level criterion corresponding to the at least one characteristic, a user characteristic report including the at least one user action indication is transmitted.

16. The XR processing unit of claim 15, wherein the operation further comprises: Transmit at least one user characteristic capability indication, indicating at least one user characteristic capability, to the radio network node to determine the at least one user action prediction indication with respect to the user equipment.

17. The XR processing unit of claim 16, wherein the at least one user action prediction indication is determined by a digital twin module.

18. A non-transitory machine-readable medium comprising executable instructions that, when executed by a processor of an extended reality (XR) processing unit, facilitate the execution of operations, said operations including: Receive user characteristic report configuration from a radio network node, the user characteristic report configuration including at least one user characteristic indication indicating at least one user characteristic; Receive a user characteristic report request from the radio network node, the user characteristic report request including at least one of the at least one user characteristic indications, wherein the user characteristic report request includes at least one confidence level indication indicating at least one confidence level standard corresponding to the at least one user characteristic indication; Receive at least one user action indication from the XR device, the at least one user action corresponding to at least one of the at least one user characteristics indicated by the user characteristic report request; Based on the at least one user action indication, determine at least one user characteristic prediction that meets the at least one confidence level standard, so as to obtain the user characteristic prediction satisfaction result; as well as In response to receiving the user characteristic report request, a user characteristic report including the user characteristic prediction satisfaction result is transmitted to the radio network node.

19. The non-transitory machine-readable medium of claim 18, wherein the user characteristic report further comprises: At least one actual user characteristic indication duration indicates at least one period of time during which a user characteristic prediction is valid, and during the at least one period of time during which the at least one confidence level criterion is valid with respect to the user characteristic prediction.

20. The non-transitory machine-readable medium of claim 18, wherein the operation further comprises: The radio network node transmits at least one user characteristic capability indication indicating at least one user characteristic capability, in order to report at least one of the at least one user characteristic indications indicated by the user characteristic report configuration to the XR processing unit regarding the XR device.

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