User equipment assistance on extended reality awareness support information for uplink traffic

Abstract

This disclosure describes systems, methods, and devices related to extended reality (XR) awareness assistance. A device may initiate transmission of a UE Assistance Information message to provide uplink traffic information. The device may set a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session. The device may set a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session. The device may determine if XR awareness information is available. The device may set the XR Awareness to a latest known value. The device may a memory to store the QoS notification.

Description

[0001] USER EQUIPMENT ASSISTANCE ON EXTENDED REALITY AWARENESS SUPPORT INFORMATION FOR UPLINK TRAFFIC

[0002] CROSS-REFERENCE TO RELATED PATENT APPLICATION(S)

[0003] This application claims the benefit of U.S. Provisional Application No. 63 / 586,197, filed September 28, 2023, the disclosure of which is incorporated herein by reference as if set forth in full.

[0004] TECHNICAL FIELD

[0005] This disclosure generally relates to systems and methods for wireless communications and, more particularly, to extended reality (XR) awareness assistance.

[0006] BACKGROUND

[0007] Extended reality (XR) is a catch-all term that refers to augmented reality (AR), virtual reality (VR), mixed reality or mediated reality (MR) technologies, where "X" in "XR" is a variable that can interpolate between these various realities or extrapolate or extend beyond them. The XR fields are rapidly growing and being applied in a wide range of areas, such as entertainment, marketing, real estate, training, maintenance, and remote work.

[0008] BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG. 1 depicts an illustrative schematic diagram for XR awareness assistance, in accordance with one or more example embodiments of the present disclosure.

[0010] FIG. 2 illustrates a flow diagram of illustrative process for an illustrative XR awareness assistance system, in accordance with one or more example embodiments of the present disclosure.

[0011] FIG. 3 illustrates an example network architecture, in accordance with one or more example embodiments of the present disclosure.

[0012] FIG. 4 illustrates a wireless network, in accordance with one or more example embodiments of the present disclosure.

[0013] FIG. 5 illustrates components of a computing device, in accordance with one or more example embodiments of the present disclosure.

[0014] FIG. 6 illustrates a network in accordance with various embodiments.

[0015] FIG. 7 shows example network deployments, in accordance with one or more example embodiments of the present disclosure. FIG. 8 depicts an example XR traffic model, in accordance with one or more example embodiments of the present disclosure.

[0016] FIG. 9 depicts an example architecture and system model for XR traffic, in accordance with one or more example embodiments of the present disclosure.

[0017] FIG. 10 depicts an example 5G-XR functions integrated in a 5 GS, in accordance with one or more example embodiments of the present disclosure.

[0018] FIG. 11 depicts an example 5G-XR architecture integrated in 5G and related interfaces, in accordance with one or more example embodiments of the present disclosure.

[0019] FIG. 12 depicts an example of processor (e.g., CPU and GPU) operations for XR applications, in accordance with one or more example embodiments of the present disclosure.

[0020] DETAILED DESCRIPTION

[0021] The following description and the drawings sufficiently illustrate specific embodiments to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, algorithm, and other changes. Portions and features of some embodiments may be included in, or substituted for, those of other embodiments. Embodiments set forth in the claims encompass all available equivalents of those claims.

[0022] The present disclosure is generally related to wireless communication, cellular networks, cloud computing, edge computing, data centers, network topologies, and communication system implementations, and in particular, to user equipment (UE) assistance on XR awareness support information for uplink (UL) traffic.

[0023] The following discussion is described in the context of XR data transmission, however, it should be understood that the embodiments herein are not limited to XR data, and can be straightforwardly applied to other types of critical data, such as cloud gaming (CG) data, ultrareliable low latency communications (URLLC) data, loT data, QoS flows / data, and / or any other type of high-priority data / traffic.

[0024] Extended Reality (XR) Aspects: The RANI release (Rel-)17 Study Item “Study on XR Evaluations for NR” has shown that extended Reality (XR) and Cloud Gaming (CG) are within the use cases and services considered important for NR in Rel- 18 and beyond. In general, XR and CG are wide terms referring to various types of augmented, virtual, and mixed environments, where human-to-machine and human-to-human communications are performed with the assistance of handheld and wearable end user devices (UEs). Cloud gaming (CG) refers to a group of use cases where the overwhelming majority of computations related to gaming (e.g., single-player or multi-player games) is / are offloaded from a UE 1802 to an edge compute node or remote server(s) (e.g., XR server(s) 838 of FIG. 8, server(s) 338 of FIG. 3, and / or the like). XR is a broad-scope umbrella term for multiple heterogeneous use cases and services that were studied and outlined in 3GPP TR 22.842, 3GPP TR 26.928, among others. These XR use cases can be roughly divided into AR, VR, MR. While XR and CG present a set of attractive use cases for future mobile systems, they also impose a set of challenges for NR / 5GS that need to be studied and potentially addressed.

[0025] Many of the XR and CG use cases are characterized by quasi-periodic traffic (with possible jitter) with high data rate in the downlink (DL) (e.g., video streams, and / or the like) combined with the frequent UL (e.g., pose / control update) and / or UL video streams. Both DL and UL traffic are also characterized by relatively strict packet delay budget (PDB).

[0026] Many of the end-user XR and CG devices are expected to be mobile and small-scale (or small form factor) with limited battery power resources. Therefore, additional power enhancements and / or power- saving enhancements may be needed to reduce the overall UE power consumption when running XR / CG services and to extend the effective UE battery lifetime. It is understood that the current discontinuous reception (DRX) configurations do not fit well for non-integer XR traffic periodicity, variable XR data rate, and quasi-periodic XR periodicity.

[0027] The set of anticipated XR / CG services has a certain variety and characteristics of the data streams (e.g., video and the like) may change “on-the-fly”, while the services are running over NR / 5G. Therefore, additional information on the running services from higher layers (e.g., the QoS flow association, frame-level QoS, application data unit (ADU)-based QoS, XR-specific QoS, and / or the like) may be beneficial to facilitate informed choices of radio parameters. It is clear that XR application awareness by the UE 302 and RAN 304 (or RAN node 314) would improve user experience, improve the NR / 5G system capacity in supporting XR services, and reduce UE power consumption.

[0028] For DL traffic, a RAN node 314 gets to know of XR information per PDU or QoS flow level. For UL traffic, current mechanism only targets for the RAN node 314 to know about the XR awareness at per UE level (e.g., whether a UE 302 is able or not to support the ability to be aware of XR information on UL traffic). However, a UE 302 may support different kinds of XR applications (e.g., XR aware application (AA) 1020 and / or the like), and potentially the UE 302 may not be able to differentiate or have visibility of the XR information for all the XR applications, and hence, the UE’s 302 ability to perform XR awareness related functions and capability can change dynamically depending on the application. There is currently no mechanism for UEs 302 to provide this dynamic (or semi-static) capability or support change to the network (e.g., to the RAN 314).

[0029] The present disclosure describes mechanisms for a node (e.g., a UE or RAN node) to inform a peer node (e.g., a UE or RAN node) about support for XR awareness / visibility in a semi-static and / or dynamic way, for example, depending on the kind of traffic, application, conditions, and / or the like.

[0030] This allows the peer node to be aware of which XR related enhancements (e.g., PDU set based discard, PSI based discard, reporting of remaining time, or UE assistance information associated to the UL XR traffic, such as, jitter, periodicity or burst arrival time) that the node is currently capable of supporting / using.

[0031] In some implementations, these mechanisms can be captured / defined as part of 3 GPP RAN2 specifications, such as 3GPP TS 38.300 and / or [TS38331]. [TS38331] captures UE assistance information related to UL traffic, such as jitter associated with a periodicity or burst arrival time or periodicity. This UL traffic information is provided per QoS flow level. Related endorsed text proposal (TP) to [TS38331] is available in 3GPP document R2-2309315.

[0032] XR Awareness Support / Visibility Information: XR traffic comprises bursts of traffic that can carry one or more protocol data unit (PDU) sets (see e.g., FIG. 1), where an individual PDU set includes one or more PDUs carrying the payload of at least one unit of information generated at the application level (e.g., one or more video frames, one or more video slices, one or more audio frames, and / or the like). XR awareness (also referred to as “XR-awareness” or the like) includes various aspects of XR traffic (in both UL and DL) characteristics, QoS metrics, and / or application layer attributes beneficial for a XR node (e.g., RAN node 314 and / or UE 302) to be aware of, which may be used for XR-specific traffic handling. In particular, XR awareness in RAN 304 is intended to make the RAN 304 aware of both the XR traffic characteristics and the requirements of XR applications (e.g., XR aware application (AA) 1020 and / or the like), as well as any changes to either of them in terms of, for example, the number and types of flows, minimum / maximum / average packet size for each of the flows, flow periodicity, jitter, and / or the association between internet protocol (IP) packets and application packets. In both UL and DL, XR awareness contributes to optimizations of radio resource for XR traffic.

[0033] XR awareness information (also referred to as “XR awareness support information”, “XR visibility information”, “XR awareness indicator”, and / or the like”) represents whether a node (e.g., UE 302) has or does not have visibility to XR kind of information in UL and / or DL. In some examples, the XR awareness in UL and / or DL could be defined as a Boolean indicator, such as true / false (e.g., 1 or 0) and / or using enumerated values (e.g., “XR- Awareness” or “Not-XR- Awareness”).

[0034] Additionally, or alternatively, the XR awareness information could include granularity of information as part of the same parameter (in which multiple values could be provided) and / or multiple independent parameters (in which each separate parameter could be conveyed at the same time with different kind of information). For example, the XR awareness information can include PDU set awareness information, PDU set importance (PSI) awareness information, and / or other awareness information / characteristics that may vary the support across different XR traffic.

[0035] The PDU set awareness information can include information about individual PDU sets such as, for example, PDU set QoS parameters, PDU set delay budget (PSDB), PDU set error rate (PS ER), PDU set integrated handling information (PSIHI), PDU set level packet handling / treatment requirements, PDU set jitter information, PDU set information as provided by a UPF 348 (see e.g., [TS23501] § 5.37.5.2), PSI information (e.g., which may or may not include the PSI awareness information), dependency within or among PDU sets (e.g., intra- PDU set dependencies and / or inter-PDU set dependency), size of individual PDU sets, PDU set sequence number(s) carried of constituent PDUs, boundary indicators (e.g., first and last PDUs of a PDU set), and / or the like. The PSI awareness information can include, for example, the importance or criticality of one or more PDUs within a PDU set, if other PDUs / PDU sets are dependent on a given critical PDU and / or PDU set, the number of level visible and relation / importance between them, and / or the like.

[0036] PDU set awareness involves the ability of the UE to identify PDU Sets for a given Quality of Service (QoS) flow. If the UE can identify these sets, it enhances the management of data transmission. PDU Set Importance (PSI) awareness adds another layer of granularity, allowing the UE to recognize the importance levels within the PDU Sets and their relationships. The parameter pduSetldentification indicates whether the UE can identify PDU Sets for the QoS flow. If set to true, the UE can identify these sets; otherwise, it cannot. Initially, the network assumes this value is false until indicated otherwise. Similarly, psildentification shows whether the UE can identify PSI for the QoS flow. This field is only true if pduSetldentification is also true, either currently or previously for the same QoS flow. If true, the UE can identify PSI; otherwise, it cannot. The network also assumes this value is false until it receives an indication to the contrary. The other information / characteristics related to XR awareness can also be considered such as, for example, jitter awareness, burst arrival awareness, periodicity awareness, traffic pattern information, statistics, QoS characteristics, application characteristics, associated PCC rules, burst periodicity, traffic periodicity and periodicity changes, number of temporal and spatial media layers and their (PDU set) periodicities and their (PDU set) dependencies, media detection rules that specify RTP header type (for media where RTP header is used), and / or the like. The XR related information may also be associated with a burst of data which may contain one or more PDUs or PDU sets.

[0037] Additionally or alternatively, the XR awareness support information can be associated with a QoS flow (e.g., using QFI), PDU session (e.g., using PDU session ID), radio bearer (RB), logical channel (LCH), logical channel group (LCG), and / or per UE (e.g., using some ID related to a UE 302).

[0038] Additionally, or alternatively, the XR awareness / visibility information may also be defined as a capability that can change over time in a semi-static or dynamic way. In these examples, the XR awareness / visibility information may be dependent and / or change on the different XR applications and / or the kind of XR stream starting / ongoing / ending.

[0039] In one or more embodiments, a mechanism using RRC signaling to inform when XR awareness support information may be available for UL / DL traffic.

[0040] In some embodiments, RRC signaling is used to convey XR awareness information.

[0041] In some examples, a UL RRC message is used by a UE 302 to provide XR awareness support / visibility information for a given UL and / or DE traffic (e.g., traffic flow, QoS flow, data radio bearer (DRB), and / or the like). In these examples, the UL RRC message could be a new RRC message or an existing RRC message, such as a UE Assistanceinformation message and / or the like. Additionally, or alternatively, the XR awareness information could be provided by the UE 302 as its preference when configured / allowed and / or based on a trigger event / condition (e.g., when an XR awareness information value changes and / or the like). Additionally, or alternatively, the XR awareness support information could be defined as part of the UL traffic assistance information (e.g., the ul-T rajficlnfo lE / parameter and / or the like) or by itself (e.g., independently of other UE assistance information) in a new lE / parameter. Additionally or alternatively, a prohibit timer may be defined to be applied per QoS flow (e.g., if information of different QoS flows is available). This can be sent regardless of the ongoing prohibit timer that may be associated to a different QoS flow. As an example, the TP that captured the XR awareness for a given QoS flow / PDU session, the corresponding UE assistance information procedure could be updated as shown by Table 1.2.1-1. Table 1.2.1-1:

[0042] MAC CE or PDCP control PDUs: In some examples, the information about whether a UE 302 is capable of XR awareness can be conveyed in a MAC control element (CE) and / or using one or more PDCP control PDUs.

[0043] In some examples, finer and / or more dynamic approaches can be used to convey XR awareness information, for example, on per PDU / packet level or per PDU set.

[0044] In some cases, some kinds of XR awareness information for UL / DL traffic is most likely not to change dynamically for a given XR application, and therefore, it may be sufficient to define it using RRC signaling as discussed previously. However, if the XR awareness of DL / UL traffic is not constant (e.g., different kind of packets / data could be sent for a given application at different instance of time), a more dynamic mechanism may be preferable, such as using MAC CEs and / or PDCP control PDUs. Additionally or alternatively, a combination of RRC signaling, MAC CE signaling, and / or PDCP control PDUs can be used based on the frequency of the changes expected.

[0045] FIG. 1 depicts an illustrative schematic diagram for XR awareness assistance, in accordance with one or more example embodiments of the present disclosure.

[0046] Referring to FIG. 1 , there is shown an example of PDU sets and data bursts.

[0047] PDU sets and Data Bursts enable the RAN (e.g., RAN 304 in FIG. 3) to identify the PDUs which carry content that the application processes as a single unit (e.g., portion of an image, one or more video frames, one or more audio frames, and / or the like) and the duration of a data transmission, respectively.

[0048] With PDU set integrated handling indication (PSIHI), the RAN and / or UE (e.g., UE 302 in FIG. 3) knows whether all PDUs of a PDU set are needed for the usage of PDU set by application layer. This allows the RAN and / or UE to stop transmitting a PDU set as soon as one of the PDUs in the set is known to be lost (e.g., as other PDUs in that set may be useless). Additionally, each PDU set can be signaled with an importance value, which is referred to as PDU set importance (PSI). The PSI identifies the relative importance of a corresponding PDU set compared to the importance (PSI) of other PDU sets. The RAN and / or UE may use the PSI in case of congestion and / or other issues to discard PDU sets of lower importance (e.g., PDU sets associated with PSIs that are lower than a subject / ego PSI / PDU set).

[0049] PDU set QoS parameters are used to support PDU set based QoS handling in the NG- RAN 304. At least one PDU Set QoS Parameter is sent to the NG-RAN 304 to enable PDU Set based QoS handling. The following PDU Set QoS Parameters are specified: (1) PDU Set Delay Budget (PSDB); (2) PDU Set Error Rate (PSER); (3) PDU Set Integrated Handling Information (PSIHI).

[0050] The QoS Profile may include the PDU Set QoS Parameters described in this clause (see e.g., [TS23501] § 5.7.1.2). The PCF 356 determines the PDU Set QoS Parameters based on information provided by the AF 360 and / or local configuration. The PDU Set QoS parameters are sent to the SMF 346 as part of PCC rule. The SMF 346 sends them to NG-RAN 304 as part of the QoS Profile. If the NG-RAN 304 receives PDU Set QoS Parameters and supports them, it enables the PDU Set based QoS handling and applies PDU Set QoS Parameters as described herein and / or in [TS23501] § 5.7.7.

[0051] The PDU set delay budget (PSDB)defines an upper bound for the delay that a PDU Set may experience for the transfer between the UE 302 and the N6 termination point at the UPF 348, for example, the duration between the reception time of the first PDU (at the N6 termination point for DL or the UE 302 for UL) and the time when all PDUs of a PDU Set have been successfully received (at the UE 302 for DL or N6 termination point for UL). PSDB applies to the DL PDU Set received by the PDU session anchor (PSA) UPF 348 over the N6 interface, and to the UL PDU Set sent by the UE 302. To enable support for PSDB, a maximum inter arrival time between the first received PDU and the last received PDU of a PDU Set may need to comply with an SLA, and this maximum inter arrival time may not exceed the PSDB.

[0052] In some examples, a QoS flow is associated with only one PSDB, although in other examples, a QoS flow may be associated with more than one PSDB. The value of the PSDB is the same in UL and DL, or may be different for UL and DL. In some examples, the PSDB is an optional parameter that may be provided by the PCF 356. The provided PSDB can be used by the NG-RAN 304 to support the configuration of scheduling and link layer functions. When the PSDB is available, the PSDB supersedes the PDB for the given QoS flow. The AN PSDB is derived at NG-RAN 304 by subtracting CN PDB (as described in clause 5.7.3.4 of [TS23501 ]) from the PSDB.

[0053] The PDU set error rate (PSER) defines an upper bound for the rate of PDU Sets that have been processed by the sender of a link layer protocol (e.g., RLC in RAN of a 3GPP access) but that are not successfully delivered by the corresponding receiver to the upper layer (e.g., PDCP in RAN of a 3GPP access). Thus, the PSER defines an upper bound for a rate of non-congestion related PDU Set losses. The purpose of the PSER is to allow for appropriate link layer protocol configurations (e.g., RLC and HARQ in RAN of a 3GPP access). In some examples, a PDU Set is considered as successfully delivered only when all PDUs of a PDU Set are delivered successfully. The way in which the RAN 304 enforces the PSER is up to RAN implementation.

[0054] In some examples, a QoS flow is associated with only one PSER, although in other examples, a QoS flow may be associated with more than one PSER. In some examples, the PSER is an optional parameter. If the PSER is available, the PSER supersedes the PER. The value of the PDU Set Error Rate is the same in UL and DL.

[0055] The PDU Set Integrated Handling Information (PSIHI) indicates whether all PDUs of the PDU set are needed for the usage of the PDU Set by the application layer in the receiver side. PSIHI is an optional parameter.

[0056] A PDU set comprises one or more PDUs carrying an application layer payload such as, for example, video frame(s), video slice(s), audio frame(s), XR data / traffic, and / or the like. The PDU set based QoS handling by the NG-RAN 304 is determined by PDU Set QoS parameters discussed herein and / or as specified in clause 5.7.7 of ITS23501 ], and PDU set information as provided by the PSA UPF 348 as discussed herein and / or as described in clause 5.37.5.2 of [TS23501].

[0057] In addition to the PDU related service information, the AF 360 may provide PDU Set related assistance information for dynamic PCC control. One or more of the following PDU Set related assistance information may be provided to the NEF 352 and / or PCF 356 using the AF session with required QoS procedures (see e.g., clauses 4.15.6.6 and 4.15.6.6a of [TS23501]): PDU Set QoS parameters as described in clause 5.7.7 of [TS23501] and / or a protocol description. The protocol description indicates protocol and payload type used by a service data flow.

[0058] AF 360 provided PDU Set QoS Parameters and Protocol Description may be used in determining PCC rules by the PCF 356 as defined in clause 6.1.3.27.4 of 3GPP TS 23.503 and the protocol description may be used for identifying the PDU Set information by the PSA UPF 348.

[0059] When the PCF 356 determines that PDU Set based QoS Handling is to be performed for an application service flow, the PCF 356 generates a PCC rule containing the PDU Set QoS parameters (e.g., PSER, PSDB and PSIHI) and the SMF 346 determines a QoS Profile for the QoS flow. Alternatively, the SMF 346 may be configured to support PDU Set QoS without receiving PCC rules from a PCF 356. The PSA UPF 348 identifies PDUs that belong to PDU Sets. If the UPF 348 receives a PDU that does not belong to a PDU Set based on Protocol Description for PDU Set identification, then the UPF 348 still maps it to a PDU Set and determines the PDU Set Information as described in section 1.3.6 and / or in clause 5.37.5.2 of [TS23501]. In some examples, if the PSA UPF 348 receives a PDU that does not belong to a PDU Set, then it is assumed that the UPF 348 determines the PDU Set Importance (PSI) value based on preconfiguration.

[0060] To support PDU Set based QoS handling, the PSA UPF 348 identifies PDUs that belong to PDU Sets and determines the below PDU Set Information which it sends to the NG-RAN 304 in the GTP-U header. The PDU Set information is used by the NG-RAN 304 for PDU Set based QoS handling as described above.

[0061] The PDU Set Information comprises: PDU Set sequence number; indication of End PDU of the PDU Set; PDU sequence number within a PDU Set; PDU Set size (e.g., in bytes); and / or PSI, which identifies the relative importance of a PDU Set compared to other PDU Sets within a QoS flow.

[0062] The NG-RAN 304 may use the Priority Level (see e.g., clause 5.7.3.3 of |TS23501 |) across QoS flows and PSI within a QoS flow for PDU Set level packet discarding in presence of congestion. In addition to considering the PSI within a QoS flow, NG-RAN 304 could also consider the relative PSI across QoS flows of the same Priority Level when determining which PDU Set needs to be discarded, which is up to implementation and configuration of operator. In some examples, the PDU Set information can be different for different PDU Sets within a QoS flow.

[0063] The SMF 346 instructs PSA UPF 348 to perform PDU Set marking and may provide the PSA UPF 348 the Protocol Description indicating the header, extension header (e.g., RTP / SRTP and / or the like) and pay load type (e.g., H.264 and / or the like) used by the service data flow. The Protocol Description may be received in the PCC rule, based on information provided by the AF 360 or by PCF 356 local policies as described in clause 5.37.5.1 of [TS23501],

[0064] The PSA UPF 348 can identify the PDU Set Information using the Protocol Description and the received RTP / SRTP headers or using implementation specific means. The details of the RTP / SRTP headers, header extensions and / or payloads used to identify PDU Set Information are defined in 3GPP TS 26.522. For each DL PDU received on N6 for which PDU Set based QoS handling is indicated from the SMF 346, the PSA UPF 348 applies the rules for PDU Set identification and provides PDU Set Information which is available to the RAN in the GTP-U header.

[0065] Non-homogenous support of PDU set based handling in NG-RAN: by sending at least one PDU Set QoS parameter to the NG-RAN 304, the SMF 346 requests the NG-RAN 304 to activate PDU Set QoS handling for a given QoS flow and the NG-RAN 304 provides the SMF 346 with an indication of whether the PDU Set QoS parameter is accepted or not. At NG-RAN 304 Xn handover and N2 handover, the target NG-RAN 304 provides to the SMF 346 with an indication of whether the target NG-RAN node 314 supports PDU Set based handling, as specified in 3GPP TS 38.413. Based on the NG-RAN 304 indications, the SMF 346 configures the PSA UPF 348 to activate / deactivate the PDU Set identification and marking.

[0066] In the case where the PSA UPF 348 identifies and marks PDUs with PDU Set information in GTP-U header it starts doing so from a complete PDU Set. In the case of handover from a source NG-RAN node 314 not supporting PDU Set handling to a target NG-RAN node 314 supporting PDU Set handling, whether there is a reason for the target NG-RAN node to temporarily handle both unmarked PDUs and marked PDUs within the same QoS flow is FFS.

[0067] In some embodiments, the electronic device(s), network(s), system(s), chip(s) or component(s), or portions or implementations thereof, of FIGs. 3-12, or some other figure herein, may be configured to perform one or more processes, techniques, or methods as described herein, or portions thereof. One such process is depicted in FIG. 2.

[0068] For example, the process may include, at 202, initiate transmission of a UE Assistance Information message to provide uplink traffic information.

[0069] The process further includes, at 204, setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session.

[0070] The process further includes, at 206, setting a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session.

[0071] The process further includes, at 208, determining if XR awareness information is available.

[0072] The process further includes, at 210, setting the XR Awareness to a latest known value.

[0073] For one or more embodiments, at least one of the components set forth in one or more of the preceding figures may be configured to perform one or more operations, techniques, processes, and / or methods as set forth in the example section below. For example, the baseband circuitry as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below. For another example, circuitry associated with a UE, base station, network element, etc. as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below in the example section.

[0074] It is understood that the above descriptions are for purposes of illustration and are not meant to be limiting.

[0075] FIG. 3 depicts an example network architecture 300. The network 300 may operate in a manner consistent with 3 GPP technical specifications for LTE or 5G / NR systems. However, the example embodiments are not limited in this regard and the described examples may apply to other networks that benefit from the principles described herein, such as future 3 GPP systems, or the like.

[0076] The network 300 is a comprehensive communication system that integrates various components for efficient connectivity. At its core, the User Equipment (UE) 302 includes both mobile and non-mobile devices like smartphones, tablets, loT devices, autonomous vehicles, drones, and more. These devices communicate with the Radio Access Network (RAN) 304 through over-the-air connections and may also interact directly using Device-to-Device (D2D), ProSe, PC5, or Sidelink (SL) interfaces, enabling communication without traversing network nodes.

[0077] The RAN 304 comprises Network Access Nodes (NANs) 314 that handle communication with UEs 302 by providing air interfaces through protocols like RRC, PDCP, RLC, MAC, and PHY. NANs 314 may operate as macrocell or smaller cells, including femtocells and picocells, or may be arranged in a “CU / DU split” architecture where a Central Unit (CU) interfaces with Distributed Units (DUs) and Radio Units (RUs). Additional configurations include various network interfaces such as X2 (for LTE) or Xn (for NG-RAN), facilitating communication between nodes.

[0078] UEs 302 also connect to Access Points (APs) 306 for WLAN communication, which offloads traffic from the RAN 304 using protocols like LWA or LWIP. Cellular-WLAN integration allows devices to use both cellular and WLAN resources, optimizing data transmission. The RAN 304 can handle licensed and unlicensed spectrums, supporting advanced features such as multi-radio dual connectivity (MR-DC) for simultaneous connections to multiple nodes with different radio access technologies.

[0079] The system supports extensive data collection and reporting through UEs 302, NANs 314, and edge compute nodes, such as 338 (Application / Content Server). The collected data includes a wide range of radio measurements like RSRP, RSSI, SINR, latency jitter, and more, which are crucial for network optimization and analytics. Edge compute nodes in the network, often located near RAN nodes, provide local processing, reducing latency and enhancing performance.

[0080] Core network elements are hosted in the 5G Core (5GC) 340, which includes functions like the Authentication Server Function (AUSF) 342, Access and Mobility Management Function (AMF) 344, and Session Management Function (SMF) 346, among others. These functions interact through multiple interfaces such as Nl, N2, N3, N4, and others, handling authentication, mobility management, session control, and policy enforcement. The Network Data Analytics Function (NWDAF) 362 plays a critical role by collecting data from other network functions and generating analytics for optimization. NWDAF 362 interacts with other network functions via interfaces like NEF 352, which securely exposes network capabilities to third parties and internal functions. Additionally, the Data Collection Coordination Function (DCCF) 363 and Messaging Framework Adaptor Function (MFAF) 365 coordinate data collection and facilitate analytics.

[0081] To support advanced applications like Vehicle-to-Everything (V2X) communications, UEs 302 or NANs 314 may act as roadside units (RSUs) for direct vehicle communication. These units utilize technologies like DSRC or cellular V2X, providing low-latency communication for traffic management and safety applications.

[0082] The network 300 includes several specific reference points and interfaces. For example, the N14 and N17 interfaces connect different AMFs 344, enabling inter- AMF communication, while the N22 interface links AMF 344 and NSSF 350 for slice selection. Other elements like the Analytics Data Repository Function (ADRF) 363 and Network Slice Admission Control Function (NSACF) provide additional support for data analytics and slice management. For data optimization, the system includes advanced measurement types related to Data Radio Bearer (DRB), Radio Resource Control (RRC), Radio Resource Utilization (RRU), and more. These measurements, including channel interference, power levels, and signal strength, help in the real-time adjustment of network parameters and conditions.

[0083] Finally, elements like the Unified Data Repository (UDR), Unstructured Data Storage Function (UDSF), Network Slice-specific Authentication and Authorization Function (NSSAAF), and the 5G Equipment Identity Register (5G-EIR) provide essential support for data storage, management, and security within the network.

[0084] By including these additional elements, the network 300 presents a comprehensive, multilayered architecture designed for diverse communication scenarios, from everyday mobile use to advanced loT and edge computing applications. FIG. 4 illustrates a wireless network 400. The wireless network 400 includes a UE 402 in wireless communication with an AN 404. The UE 402 and AN 404 may be similar to, and substantially interchangeable with, like-named components described elsewhere herein.

[0085] The UE 402 is communicatively connected to an Access Node (AN 404) through a connection 406, which is represented as an air interface. This connection 406 supports cellular communication protocols like LTE or 5G NR, operating at mmWave or sub-6GHz frequencies.

[0086] The UE 402 comprises a host platform 408 and a modem platform 410. The host platform 408 contains application processing circuitry 412, which is coupled with the protocol processing circuitry 414 on the modem platform 410. The application processing circuitry 412 runs applications for the UE 402 that handle application data, and implements operations for data transmission and reception, including transport (e.g., UDP) and internet operations (e.g., IP).

[0087] The protocol processing circuitry 414 performs various layer operations required for transmitting or receiving data over connection 406, including MAC, RLC, PDCP, RRC, and NAS operations. Additionally, the modem platform 410 includes digital baseband circuitry 416, which performs lower-layer operations in the network protocol stack, such as PHY operations like HARQ-ACK functions, scrambling / descrambling, encoding / decoding, modulation symbol mapping, and multi-antenna port processing.

[0088] The modem platform 410 further integrates transmit circuitry 418, receive circuitry 420, RF circuitry 422, and an RF front end (RFFE) 424. The RFFE 424 is connected to one or more antenna panels 426. The transmit circuitry 418 includes components like digital-to-analog converters, mixers, and IF components, while the receive circuitry 420 includes analog-to- digital converters, mixers, and IF components. The RF circuitry 422 includes components such as low-noise amplifiers, power amplifiers, and power tracking components. The RFFE 424 consists of filters, switches, antenna tuners, and beamforming components, all designed to support specific implementations (e.g., TDM or FDM communication, mmWave, or sub-6GHz frequencies).

[0089] The antenna panels 426 are used to establish reception at the UE 402 by receivebeamforming signals via a set of antennas or antenna elements. Similarly, for transmission, the UE 402 components — including protocol processing circuitry 414, digital baseband circuitry 416, transmit circuitry 418, RF circuitry 422, RFFE 424, and antenna panels 426 — form a transmit beam using spatial filtering techniques.

[0090] Like the UE 402, the AN 404 also includes a host platform 428 and a modem platform 430. The host platform 428 incorporates application processing circuitry 432, which is coupled with protocol processing circuitry 434 on the modem platform 430. The modem platform 430 features digital baseband circuitry 436, transmit circuitry 438, receive circuitry 440, RF circuitry 442, RFFE circuitry 444, and antenna panels 446. These components of AN 404 are similar to and can be interchanged with the like-named components of UE 402.

[0091] The components of AN 404 perform data transmission and reception and execute various logical functions such as Radio Network Controller (RNC) functions, radio bearer management, dynamic radio resource management, and data packet scheduling.

[0092] Antenna elements in the antenna panels 426 (of UE 402) and 446 (of AN 404) can include a variety of types, such as planar inverted-F antennas (PIFAs), monopole antennas, dipole antennas, loop antennas, patch antennas, Yagi antennas, parabolic dish antennas, omnidirectional antennas, and others.

[0093] FIG. 5 illustrates components capable of reading instructions from a machine-readable or computer-readable medium (e.g., a non-transitory machine-readable storage medium) and perform any one or more of the methodologies discussed herein.

[0094] FIG. 5 shows the hardware resources 500, consisting of various components such as processors (or processor cores) 510, memory / storage devices 520, and communication resources 530. These elements are interconnected via a bus 540 or other interface circuitry. In scenarios utilizing node virtualization, a hypervisor 502 may be used to provide an execution environment for network slices / sub-slices, allowing them to effectively utilize the hardware resources 500. The hardware resources 500 can be implemented in a single compute node housed in various enclosures or distributed across multiple compute nodes located in data centers and geographic regions.

[0095] The processors 510, such as processor 512 and processor 514, can include various types of processing units like CPUs, RISC and CISC processors, GPUs, DSPs, ASICs, FPGAs, RFICs, microprocessors, multi-core or multithreaded processors, DPUs, IPUs, and NPUs. These processors can handle different types of computational tasks and are essential for the operation of the hardware resources 500.

[0096] The memory / storage devices 520 may include a wide range of memory types, such as RAM, DRAM, SRAM, NVRAM, flash memory, and various types of solid-state storage. They support both volatile and non-volatile storage needs, facilitating fast access to data and instructions 550 for processing by the hardware resources 500. These devices may include block addressable memory (e.g., NAND or NOR-based devices), magnetic storage, optical storage, resistive memory, and advanced types like MRAM, PCM, FeTRAM, STT-MRAM, and memristor technology, among others. Communication resources 530 are critical for connecting with peripheral devices 504, databases 506, or other network elements via a network 508. These resources may include various wired communication components (e.g., USB, Ethernet), as well as wireless technologies like cellular, NFC, Bluetooth®, and Wi-Fi®, enabling data transfer and network connectivity.

[0097] Instructions 550, including software, firmware, and application code, reside within the processors 510, memory / storage devices 520, or may be transferred from peripheral devices 504 or databases 506. These instructions control the execution of methodologies or techniques by processors 510 and can be dynamically loaded into various memory components, ensuring flexibility and adaptability of the hardware resources 500.

[0098] Peripheral devices 504 can include various sensors, such as accelerometers, gyroscopes, magnetometers, temperature sensors, cameras, LiDAR sensors, depth sensors, and more. These sensors detect environmental or internal changes and send the data to other devices or systems. Actuators, also part of peripheral devices 504, allow for mechanical or electrical actions such as moving parts, controlling mechanisms, or adjusting positions and orientations.

[0099] The compute node or platform can operate actuators based on captured events, instructions, or control signals. These actuators can include devices like motors, servomechanisms, electromechanical switches, thermal biomorphs, shape-memory alloys, and others. They enable physical actions like gripping, propulsion, and auditory or visual warnings. Virtualized actuators can also be implemented to simulate physical actions or manage internal components such as cooling elements and controllers.

[0100] Overall, the hardware resources 500 and their associated components enable flexible, scalable, and efficient operation across various environments, supporting both local and distributed computing needs. They facilitate the seamless execution of complex workloads, ranging from basic computational tasks to advanced, resource-intensive processes in diverse network and data center environments.

[0101] FIG. 6 illustrates an example cellular network 600. The network 600 operates in accordance with 3GPP technical specifications or reports for 6G systems and may operate concurrently with network 300, sharing frequency or bandwidth resources. A User Equipment (UE), such as UE 602, can be configured to operate in both networks by utilizing circuitry designed for communication with both 300 and 600 networks.

[0102] UE 602 may represent various computing devices, such as smartphones, tablets, wearables, desktop and laptop computers, in-vehicle systems, loT devices, and machine-type communication devices, similar to UE 302. These UEs can communicate directly via a sidelink interface using physical sidelink channels, including PSBCH, PSDCH, PSSCH, PSCCH, and PSFCH. The RAN 608 enables over-the-air communication with UE 602 and may include one or more access nodes similar to those in RAN 304.

[0103] RAN 608 also supports communication with a 6G Core Network (CN 610). The 6G air interface may include features like terahertz (THz) or sub-THz bandwidth communication and joint communication and sensing, operating in the 80 GHz and above frequency ranges, also referred to as “mmWave” frequencies.

[0104] CN 610 includes several network functions, such as NSSF 350, NEF 352, NRF 354, PCF 356, UDM 358, AF 360, SMF 346, and AUSF 342, along with additional functions like UPF 348 and DN 336.

[0105] The RAN 608 also incorporates new functions beyond those found in 4G or 5 G networks. This includes the Compute Control Function (Comp CF 624) and Compute Service Function (Comp SF 636), which are parts of the Computing Service Plane. Comp CF 624 manages Comp SF 636 instances, oversees computing resource management, and provides functionalities such as task management. Comp SF 636 serves as a gateway between computing service users and nodes, handling tasks like parsing service data, enforcing policies, and monitoring performance.

[0106] The Communication Control Function (Comm CF 628) and Communication Service Function (Comm SF 638) are components of the Communication Service Plane. Comm CF 628 manages Comm SF 638 instances and communication session contexts, while Comm SF 638 serves as a user plane function for data transport. These functions provide service-aware transport, improving upon the 5G SMF (346) and UPF (348).

[0107] The Data Control Function (Data CF 622) and Data Service Function (Data SF 632) are part of the Data Service Plane. Data CF 622 manages Data SF 632 instances and data service contexts, while Data SF 632 functions as a gateway for data service users, handling tasks like data forwarding, generating charging data, and reporting service status.

[0108] The Service Orchestration and Chaining Function (SOCF 620) orchestrates and chains communication, computing, and data services. It interacts with Comp CF 624, Comm CF 628, and Data CF 622 to create and maintain service chains.

[0109] The Service Registration Function (SRF 612) acts as a registry for system services, registering user plane services and managing endpoints similar to NRF 354.

[0110] The network also includes the Evolved Service Communication Proxy (eSCP) and Service Infrastructure Control Function (SICF 626). eSCP includes a control plane (eSCP-C 614) and user plane (eSCP-U 634) service communication proxy, while SICF 626 manages configurations like traffic routing, access rules, and load balancing.

[0111] AMF 644 functions similarly to AMF 344 but with additional roles such as potentially moving message forwarding functionality to RAN 608. The Service Orchestration Exposure Function (SOEF 618) exposes service orchestration and chaining services to external users.

[0112] UE 602 includes a Computing Client Service Function (Comp CSF 604) that handles control and user plane functionalities, interacting with various network functions for service discovery, task management, and workload exchange. The Comp CSF 604 may determine whether tasks should be executed on UE 602, RAN 608, or an element of CN 610.

[0113] Additionally, UE 602 or Comp CSF 604 may include a Service Mesh Proxy (606) to facilitate secure, balanced, and efficient service-to-service communication in the user plane.

[0114] FIG. 7 shows example network deployments including an example next generation fronthaul (NGF) deployment 700a where a user equipment (UE) 702 is connected to an RU 730 (also referred to as a “remote radio unit 730”, “a remote radio head 730”, or “ RRH 730”) via an air interface, the RU 730 is connected to a Digital Unit (DU) 731 via a NGF interface (NGFl)-l, the DU 731 is connected to a Central Unit (CU) 732 via an NGF1-11, and the CU 732 is connected to a core network (CN) 742 via a backhaul interface. In 3 GPP NG-RAN implementations (see e.g., [TS38401]), the DU 731 may be a distributed unit (for purposes of the present disclosure, the term “DU” may refer to a digital unit and / or a distributed unit unless the context dictates otherwise). The UEs 702 may be the same or similar to, and / or share one or more features with UE 302, UE 402, hardware resources yzOO, UE zx02, and / or any other UE described herein.

[0115] In some implementations, the NGF deployment 700a may be arranged in a distributed RAN (D-RAN) architecture where the CU 732, DU 731, and RU 730 reside at a cell site and the CN 742 is located at a centralized site. Alternatively, the NGF deployment 700a may be arranged in a centralized RAN (C-RAN) architecture with centralized processing of one or more baseband units (BBUs) at the centralized site. In C-RAN architectures, the radio components are split into discrete components, which can be located in different locations. In one example C-RAN implementation, only the RU 730 is disposed at the cell site, and the DU 731, the CU 732, and the CN 742 are centralized or disposed at a central location. In another example C-RAN implementation, the RU 730 and the DU 731 are located at the cell site ,and the CU 732 and the CN 742 are at the centralized site. In another example C-RAN implementation, only the RU 730 is disposed at the cell site, the DU 731 and the CU 732 are located a RAN hub site, and the CN 742 is at the centralized site. The CU 732 is a central controller that can serve or otherwise connect to one or multiple DUs 731 and / or multiple RUs 730. The CU 732 is network (logical) nodes hosting higher / upper layers of a network protocol functional split. For example, in the 3GPP NG-RAN and / or O- RAN architectures, a CU 732 hosts the radio resource control (RRC), Service Data Adaptation Protocol (SDAP), and / or Packet Data Convergence Protocol (PDCP) layers of a next generation NodeB (gNB), or hosts the RRC and PDCP protocol layers when included in or operating as an E-UTRA-NR gNB (en-gNB). The SDAP sublayer performs mapping between QoS flows and a data radio bearers (DRBs) and marking QoS flow TDs (QFT) in both DL and UL packets. The PDCP sublayer performs transfers user plane or control plane data; maintains PDCP sequence numbers (SNs); header compression and decompression using the Robust Header Compression (ROHC) and / or Ethernet Header Compression (EHC) protocols; ciphering and deciphering; integrity protection and integrity verification; provides timer based SDU discard; routing for split bearers; duplication and duplicate discarding; reordering and inorder delivery; and / or out-of-order delivery. In various implementations, a CU 732 terminates respective Fl interfaces connected with corresponding DUs 731 (see e.g., [TS38401]).

[0116] A CU 732 may include a CU-control plane (CP) entity (referred to herein as “CU-CP 732”) and a CU-user plane (UP) entity (referred to herein as “CU-UP 732”). The CU-CP 732 is a logical node hosting the RRC layer and the control plane part of the PDCP protocol layer of the CU 732 (e.g., a gNB-CU for an en-gNB or a gNB). The CU-CP terminates an El interface connected with the CU-UP and the Fl-C interface connected with a DU 731. The CU- UP 732 is a logical node hosting the user plane part of the PDCP protocol layer (e.g., for a gNB-CU 732 of an en-gNB), and the user plane part of the PDCP protocol layer and the SDAP protocol layer (e.g., for the gNB-CU 732 of a gNB). The CU-UP 732 terminates the El interface connected with the CU-CP 732 and the Fl-U interface connected with a DU 731.

[0117] The DU 731 controls radio resources, such as time and frequency bands, locally in real time, and allocates resources to one or more UEs. The DUs 731 are network (logical) nodes hosting middle and / or lower layers of the network protocol functional split. For example, in the 3GPP NG-RAN and / or O-RAN architectures, a DU 731 hosts the radio link control (RLC), medium access control (MAC), and high-physical (PHY) layers of the gNB or en-gNB, and its operation is at least partly controlled by the CU 732. The RLC sublayer operates in one or more of a Transparent Mode (TM), Unacknowledged Mode (UM), and Acknowledged Mode (AM). The RLC sublayer performs transfer of upper layer PDUs; sequence numbering independent of the one in PDCP (UM and AM); error Correction through ARQ (AM only); segmentation (AM and UM) and re-segmentation (AM only) of RLC SDUs; reassembly of SDU (AM and UM); duplicate detection (AM only); RLC SDU discard (AM and UM); RLC re-establishment; and / or protocol error detection (AM only). The MAC sublayer performs mapping between logical channels and transport channels; multiplexing / demultiplexing of MAC SDUs belonging to one or different logical channels into / from transport blocks (TB) delivered to / from the physical layer on transport channels; scheduling information reporting; error correction through HARQ (one HARQ entity per cell in case of CA); priority handling between UEs by means of dynamic scheduling; priority handling between logical channels of one UE by means of logical channel prioritization; priority handling between overlapping resources of one UE; and / or padding. In some implementations, a DU 731 can host a Backhaul Adaptation Protocol (BAP) layer (see e.g., 3GPP TS 38.340 vl7.5.0 (2023-06-30)) and / or a Fl application protocol (F1AP) (see e.g., 3GPP TS 38.470 V17.5.0 (2023-06-29)), such as when the DU 731 is operating as an Integrated Access and Backhaul (IAB) node. One DU 731 supports one or multiple cells, and one cell is supported by only one DU 731. A DU 731 terminates the Fl interface connected with a CU 732. Additionally or alternatively, the DU 731 may be connected to one or more RRHs / RUs 730.

[0118] The RU 730 is a transmission / reception point (TRP) or other physical node that handles radiofrequency (RF) processing functions. The RU 730 is a network (logical) node hosting lower layers based on a lower layer functional split. For example, in 3GPP NG-RAN and / or O-RAN architectures, the RU 730 hosts low-PHY layer functions and RF processing of the radio interface based on a lower layer functional split. The RU 730 may be similar to 3GPP’s transmission / reception point (TRP) or RRH, but specifically includes the Low-PHY layer. Examples of the low-PHY functions include fast Fourier transform (FFT), inverse FFT (iFFT), physical random access channel (PRACH) extraction, and the like.

[0119] Each of the CUs 732, DUs 731, and RUs 730 are connected through respective links, which may be any suitable wireless and / or wired (e.g., fiber, copper, and the like) links. In some implementations, various combinations of the CU 732, DU 731, and RU 730 may correspond to one or more of the RAN 304, NAN 314, AP 306, and / or any other NAN, such as any of those discussed herein. Additional aspects of CUs 732, DUs 731, and RUs 730 are discussed in [O-RAN], [TS38401], [TS38410], and [TS38300].

[0120] In some implementations, a fronthaul gateway function (FHGW) may be disposed between the DU 731 and the RU / RRU 730 (not shown by FIG. 7), where the interface between the DU 731 and the FHGW is an Open Fronthaul (e.g., Option 7-2x) interface, the interface between FHGW function and the RU / RRU 730 is an Open Fronthaul (e.g., Option 7-2x) interface or any other suitable interface (e.g., option 7, option 8, or the like) including those that do not support Open Fronthaul (e.g., Option 7-2x). The FHGW may be packaged with one or more other functions (e.g., Ethernet switching and / or the like) in a physical device or appliance. In some implementations, a RAN controller may be communicatively coupled with the CU 732 and / or the DU 731.

[0121] The NGFI (also referred to as “xHaul” or the like) is a two-level fronthaul architecture that separates the traditional RRU 730 to BBU connectivity in the C-RAN architecture into two levels, namely levels I and II. Level I connects the RU 730 via the NGFLI to the DU 731, and level II connects the DU 731 via the NGFI-II to the CU 732 as shown by deployment 700a in FIG. 7. The NGFI-I and NGFLII connections may be wired connections or wireless connections, which may utilize any suitable RAT such as any of those discussed herein. The purpose of the two-level architecture is to distribute (split) the RAN node protocol functions between CU 732 and DU 731 such that latencies are relaxed, giving more deployment flexibilities. In general, the NGFI-I interfaces with the lower layers of the function split which have stringent delay and data rate requirements, whereas NGFI-II interfaces with higher layers of the function split relative to the layers of the NGFI-I, relaxing the requirements for the fronthaul link. Examples of the NGFI fronthaul interfaces and functional split architectures include O-RAN 7.2x fronthaul (see e.g., [ORAN.XPSAAS] and [ORAN.CUS]), Enhanced Common Radio Interface (CPRI) based C-RAN fronthaul (see e.g., Common Public Radio Interface: eCPRI Interface Specification, eCPRI Specification v2.0 (2019-05-10), Common Public Radio Interface: Requirements for the eCPRI Transport Network, eCPRI Transport Network vl.2 (2018-06-25), and [ORAN.CUS]), Radio over Ethernet (RoE) based C-RAN fronthaul (see e.g., IEEE Standard for Radio over Ethernet Encapsulations and Mappings, IEEE Standards Association, IEEE 1914.3-2018 (05 Oct. 2018) (“[IEEE1914.3]”)), and / or the like. Additional aspects of NGFI are also discussed in [ORAN.XPSAAS], [ORAN.CUS], IEEE Standard for Packet-based Fronthaul Transport Networks, IEEE Standards Association, IEEE 1914.1-2019 (21 Apr. 2020) (“[IEEE1914.1]”), [IEEE1914.3], and Nasrallah et al., Ultra-Low Latency (ULL) Networks: A Comprehensive Survey Covering the IEEE TSN Standard and Related ULL Research, arXiv:1803.07673vl [cs.NI] (20 Mar. 2018) (“[Nasrallah]”).

[0122] In one example, the deployment 700a may implement a low level split (LLS) (also referred to as a “Lower Layer Functional Split 7-2x” or “Split Option 7-2x”) that runs between the RU 730 (e.g., an O-RU in O-RAN architectures) and the DU 731 (e.g., an O-DU in O-RAN architectures) (see e.g., [ORAN.IPC-HRD-Opt7-2], [ORAN.OMAC-HRD], [ORAN.OMC- HRD-Opt7-2], [ORAN.OMC-HRD-Opt7-2]). In this example implementation, the NGFI-I is the Open Fronthaul interface described in the O-RAN Open Fronthaul Specification (see e.g., [ORAN.CUS]). Other LLS options may be used such as the relevant interfaces described in other standards or specifications such as, for example, the 3GPP NG-RAN functional split (see e.g., [TS38401] and 3GPP TR 38.801 V14.0.0 (2017-04-03)), the Small Cell Forum for Split Option 6 (see e.g., 5G small cell architecture and product definitions: Configurations and Specifications for companies deploying small cells 2020-2025, Small Cell Forum, document 238.10.01 (05 Jul. 2020) (“[SCF238]”), 5G NR FR1 Reference Design: The case for a common, modular architecture for 5G NR FR1 small cell distributed radio units, Small Cell Forum, document 251.10.01 (15 Dec. 2021) (“[SCF251 ]”), and [ORAN.TPC-HRD-Opt6], and / or in O- RAN white-box hardware Split Option 8 (e.g., [ORAN.IPC-HRD-Opt8]).

[0123] Additionally or alternatively, the CUs 732, DUs 731 , and / or RUs 730 may be IAB nodes. IAB enables wireless relaying in an NG-RAN where a relaying node (referred to as an “IAB- node”) supports access and backhauling via 3GPP 5G / new radio (NR) links / interfaces. The terminating node of NR backhauling on the network side is referred to as an “IAB-donor”, which represents a RAN node (e.g., a gNB) with additional functionality to support IAB. Backhauling can occur via a single or via multiple hops. All lAB-nodes that are connected to an IAB-donor via one or multiple hops form a directed acyclic graph (DAG) topology with the IAB-donor as its root. The IAB-donor performs centralized resource, topology and route management for the IAB topology. The IAB architecture is shown and described in [TS38300].

[0124] Although the NGF deployment 700a shows the CU 732, DU 731, RRH 730, and CN 742 as separate entities, in other implementations some or all of these network nodes can be bundled, combined, or otherwise integrated with one another into a single device or element, including collapsing some internal interfaces (e.g., Fl-C, Fl-U, El, E2, and the like). At least the following implementations are possible: (i) integrating the CU 732 and the DU 731 (e.g., a CU- DU), which is connected to the RRH 730 via the NGFI-I; (ii) integrating the DU 731 and the RRH 730 integrated (e.g., CU-DU), which is connected to the CU 732 via NGFI-II; (iii) integrating a RAN controller and the CU 732, which is connected to the DU 731 via NGFI-II; (iv) integrating the CU 732, the DU 731, and the RU 730, which is connected to the CN 742 via backhaul interface; and (v) integrating the network controller (or intelligent controller), the CU 732, the DU 731, and the RU 730. Any of the aforementioned example implementations involving the CU 732 may also include integrating the CU-CP 732 and CP-UP 732.

[0125] FIG. 7 also shows an example RAN disaggregation deployment 700b (also referred to as “disaggregated RAN 700b”) where the UE 702 is connected to the RRH 730, and the RRH 730 is communicatively coupled with one or more of the RAN functions (RANFs) 1-77 (where N is a number). The RANFs l -N are disaggregated and distributed geographically across several component segments and network nodes. In some implementations, each RANF 1-7V is a software (SW) element operated by a physical compute node and the RRH 730 includes radiofrequency (RF) circuitry (e.g., an RF propagation module for a particular RAT and / or the like). In this example, the RANF 1 is operated on a physical compute node that is co-located with the RRH 730 and the other RANFs are disposed at locations further away from the RRH 730. Additionally in this example, the CN 742 is also disaggregated into CN NFs 1 -x (where x is a number) in a same or similar manner as the RANFs I - / V, although in other implementations the CN 742 is not disaggregated.

[0126] Network disaggregation (or disaggregated networking) involves the separation of networking equipment into functional components and allowing each component to be individually deployed. This may encompass separation of SW elements (e.g., NFs) from specific HW elements and / or using APIs to enable software defined network (SDN) and / or and NF virtualization (NFV). RAN disaggregation involves network disaggregation and virtualization of various RANFs (e.g., RANFs 1-N in FIG. 7). The RANFs 1-N can be placed in different physical sites in various topologies in a RAN deployment based on the use case. This enables RANF distribution and deployment over different geographic areas and allows a breakout of RANFs to support various use cases (e.g., low latency use cases and the like) as well as flexible RAN implementations. Disaggregation offers a common or uniform RAN platform capable of assuming a distinct profile depending on where it is deployed. This allows fewer fixed-function devices, and a lower total cost of ownership, in comparison with existing RAN architectures. Example RAN disaggregation frameworks are provided by Telecom Infra Project (TIP) OpenRAN™, Cisco® Open vRAN™, [O-RAN], Open Optical & Packet Transport (OOPT), Reconfigurable Optical Add Drop Multiplexer (RO ADM), and / or the like.

[0127] In a first example implementation, the RANFs 1-N disaggregate RAN HW and SW with commercial off-the-shelf (COTS) HW and open interfaces (e.g., NGFI-I and NGFI-II, and the like). In this example implementation, each RANF 1-N may be a virtual BBU or vRAN controller operating on COTS compute infrastructure with HW acceleration for BBU / vRANFs.

[0128] In a second example implementation, the RANFs 1-N disaggregate layers of one or more RAT protocol stacks. As an example of this implementation, RANF 1 is a DU 731 operating on first COTS compute infrastructure with HW acceleration for BBU / vRANFs, and RANF 2 is a virtual CU 732 operating on second COTS compute infrastructure.

[0129] In a third example implementation, the RANFs 1 -N disaggregate control plane and user plane functions. As an example of this implementation, the RANF 1 is a DU 731 operating on COTS compute infrastructure with HW acceleration for BBU / vRANFs, RANF 2 is a virtual CU-CP 732 operating on COTS compute infrastructure, and a third RANF (e.g., RANF 3 (not shown by FIG. 7)) is a virtual CU-UP 732 operating on the same or different COTS compute infrastructure as the virtual CU-CP 732. Additionally or alternatively, in this implementation, one or more CN NFs 1-x may be CN-UP functions and one or more other CN NFs 1-x may be CN-CP functions.

[0130] In a fourth example implementation, the RANFs 1-N disaggregate layers of an [IEEE802] RAT. As an example of this implementation, the RRH 730 implements a WiFi PHY layer, RANF 1 implements a WiFi MAC sublayer, RANF 1 implements a WiFi logical link control (LLC) sublayer, RANF 2 implements one or more WiFi upper layer protocols (e.g., network layer, transport layer, session layer, presentation layer, and / or application layer), and so forth.

[0131] In a fifth example implementation, the RANFs 1-N disaggregate different O-RAN RANFs including E2SMs. As an example of this implementation, RANF 1 implements the near-RT RIC, RANF 2 implements the E2SM-KPM, RANF 3 implements the E2SM-CCC, RANF 4 implements the E2SM RAN control, RANF 5 implements the E2SM-NI, RANF 6 implements functions for providing Al services, and so forth.

[0132] In any of the implementations discussed herein, the lower layers of the RAN protocol stack can be characterized by real-time (RT) functions and relatively complex signal processing algorithms, and the higher layers of the RAN protocol stack can be characterized by non-RT functions. In these implementations, the RT functions and signal processing algorithms can be implemented in DUs 731 and / or RRHs 730 either using purpose-built network elements or in COTS hardware augmented with purpose-built HW accelerators.

[0133] FIG. 7 also shows various functional split options 700c, for both DL and UL directions. The traditional RAN is an integrated network architecture based on a distributed RAN (D- RAN) model, where D-RAN integrates all RANFs into a few network elements. As alluded to previously, the disaggregated RAN architecture provides flexible function split options to overcome various drawbacks of the D-RAN model. The disaggregated RAN breaks up the integrated network system into several function components that can then be individually relocated as needed without hindering their ability to work together to provide a holistic network services. The split options 700c are mostly split between the CU 732 and the DU 731, but can include a split between the CU 732, DU 731, and RU 730. For each option 700c, protocol entities on the left side of the figure are included in the RANF implementing the CU 732 and the protocol entities on the right side of the figure are included in the RANF implementing the DU 731. For example, the Option 2 function split includes splitting non-RT processing (e.g., RRC and PDCP layers) from RT processing (e.g., RLC, MAC, and PHY layers), where the RANF implementing the CU 732 performs network functions of the RRC and PDCP layers, and the RANF implementing the DU 731 performs the baseband processing functions of the RLC (including high-RLC and low-RLC), MAC (including high-MAC and low MAC), and PHY layers. In some implementations, the PHY layer is further split between the DU 731 and the RU 730, where the RANF implementing the DU 731 performs the high-PHY layer functions and the RU 730 handles the low-PHY layer functions. In some implementations, the Low-PHY entity may be operated by the RU 730 regardless of the selected functional split option. Under the Option 2 split, the RANF implementing the CU 732 can connect to multiple DU 731 (e.g., the CU 732 is centralized), which allows RRC and PDCP anchor change to be eliminated during a handover across DUs 731 and allows the centralized CU 732 to pool resources across several DUs 731. In these ways, the option 2 function split can improve resource efficiencies. The particular function split option used may vary depending on the service requirements and network deployment scenarios, and may be implementation specific. It should also be noted that in some implementations, all of the function split options can be selected where each protocol stack entity is operated by a respective RANF (e.g., a first RANF operates the RRC layer, a second RANF operates the PDCP layer, a third RANF operates the high-RLC layer, and so forth until an eighth RANF operates the low-PHY layer). Other split options are possiple such as those discussed in [ORAN.IPC-HRD-Opt6], [ORAN.IPC-HRD- Opt7-2], [ORAN.IPC-HRD-Opt8], [ORAN.OMAC-HRD], and [ORAN.OMC-HRD-Opt7-2],

[0134] Extended reality (XR) is a catch-all term (or umbrella term) for different types of realities and refers to all real-and-virtual combined environments and human-machine interactions generated by computer technology and wearables. In particular, the term “XR” includes and / or refers to augmented reality (AR), virtual reality (VR), mixed reality or mediated reality (MR) technologies, where “X” in “XR” is a variable that can interpolate between these various realities or extrapolate or extend beyond them. The XR fields are rapidly growing and being applied in a wide range of areas, such as entertainment, marketing, real estate, training, maintenance, and remote work.

[0135] FIG. 8 depicts an example XR traffic model 800. The XR traffic model 800 follows the 5GS architecture discussed w.r.t FIG. 3 and / or as defined in [TS23501]. In particular, the user plane aspects are considered as shown by FIG. 8 for which an XR server 838 is in the external DN 338 or in a trusted DN 338, and the XR device 802 is a 5G-capable UE, which may be the same or similar as UE 302 of FIG. 3.

[0136] As examples, the XR server 838 may be hosted in the cloud (e.g., by one or more cloud compute nodes of a cloud computing service) or may be hosted at the edge (e.g., by one or more edge compute nodes of an edge computing system / network). The XR device 802 can include suitable XR hardware components for communicating and rendering / displaying XR content. Examples of such XR hardware components include processor circuitry, output circuitry (e.g., actuators, display(s), and / or the like), optical elements (e.g., waveguides (e.g., diffractive, reflective, holographic, polarized, and / or the like), diffusers, lenses, mirrors, projectors, picture generation units, holographic optical elements (HOEs), and / or the like), one or more sensors, and input circuitry. The input circuitry and / or sensor(s) may include, for example, image capture devices (e.g., visible-light cameras, infrared cameras, ultraviolet-light cameras, and / or the like), proximity sensors, GPS circuitry, and / or microelectromechanical systems (MEMS) sensors, such as accelerometers, gyroscopes, solid state compasses, and / or the like. Additionally or alternatively, the sensor(s), input circuitry, and / or output circuitry, may include any of the devices / components as the peripheral devices yz04 discussed w.r.t FIG. yz. As examples, the XR device 802 may be a head-up display (HUD), head-mounted display (HMD) and / or optical HMD, AR / VR headset, smart glasses, EyeTap device, XR contact lenses and / or bionic contact lenses, smart watch, handheld XR device, projector / projection mapper, and / or any other suitable devices, such as any of those discussed herein.

[0137] In this example, the exchange of data is carried out using the 5GS 300. Interfaces to the 5GC functions for charging, QoS control, and / or the like are not shown by FIG. 8, but may include any of those discussed infra w.r.t FIG. 3 and / or as discussed in [TS23501]. Additionally, aspects of the XR traffic model 800 are discussed in 3GPP TR 26.926 v2.0.0 (2023-09-05) (“[TR26926]”), 3GPP TR 26.928 vl 8.0.0 (2023-03-30) (“[TR26298]”), 3GPP TR 26.925 vl7.1.0 (2022-03-31), 3GPP TR 38.838 vl7.0.0 (2022-01-04), and 3GPP TS 26.501 vl 8.2.0 (2023-06-29).

[0138] FIG. 9 depicts an example architecture and system model for XR traffic, which supports modelling of end-to-end XR Traffic. This system is used as a baseline and may be refined for specific traffic classes. The system follows the basic building blocks from FIG. 8, but provides details for each of those aspects. In order to support simpler system modelling and simulation, the interfaces are supported by traces. Traces define a well-defined format to describe a sequence of timed data units together with relevant metadata for system simulation. Aspects of the traces in FIG. 9 are discussed infra.

[0139] The system model of FIG. 9 includes a content model based on traces, which may be provided based on stakeholder input providing sufficient information on a rendered application (e.g., a game or a scene). Based on these content model traces, codec centric experts defines a content encoding and delivery model taking into account a system design, for example based on [TR26298]. The system model includes encoding, delivery, decoding, and also a quality definition, providing packet traces. 5GS and RAN simulations may be carried out by the 3GPP radio experts using the packet traces to simulate different traffic characteristics and evaluate different performance options.

[0140] The system model of FIG. 9 includes various functions, which are described infra. Se veral of these functions are initialized by appropriate configuration(s). An overview of configurations is introduced in each of the functions, if needed. Additional aspects of the various functions and / or configurations are discussed in [TR26926].

[0141] The content model provides typical characteristics for the XR content model for video, audio, and potentially other data. This content is rendered for XR / CG consumption. The content encoding model provides the details for the content encoding in order to meet certain objectives. This includes the generation of sequences of application data units (e.g., slices, video frames, audio frames, and / or the like) and the incurred timestamp of each of the units is available.

[0142] The content delivery model provides details on content delivery, for example, packetization, delay jitter, but possibly also more sophisticated models such as retransmission, TCP operations, and so forth. This also includes emulation of the 5GC 340. It produces packet traces (e.g., timestamp and size of each packet) based on traces of application data units.

[0143] The core network model emulates the core network behavior in terms of delay, latency, and packet losses in the core network 340 (e.g., the interface between the UPF 348 and gNB 314). The packet radio model receives sequences / traces of packets at a given time and of a specified size. The packets may have additional metadata assigned that can potentially be used by the radio simulator. The packet traces are provided for multiple users and reflect typical traffic characteristics. The RAN simulator provides packet traces after delivery that reflect the occurred delays and losses for each user. The content receiver model converts the packet traces into application units taking into account delays and losses occurred. It may also model additional functions, such as retransmissions or FEC, if applicable. The content decoding model uses the received application units to model the reconstruction of timed data (e.g., video frames, audio, and the like) considering delays, losses and also content model properties (e.g., error propagation, refresh data, and the like). A quality evaluation tool is provided that takes into account traces to compute different quality metrics based on packet, application unit and media quality. The uplink model is a model for uplink traffic in a similar fashion also providing packet traces. Generally, traces include the following information: time series of data units; size of each data units; association to the application; and / or additional “metadata”. Traces can also directly be fed to a quality evaluation tool obtain the application quality based on the simulation as shown in clause 5.8 of [TR26926]. The benefit of traces compared to first order statistical model are as follows: traces to represent time correlations; traces can be used to assign additional metadata in the time series; statistical models can be developed based on time series; traces can be directly fed to quality evaluation tool. The trace formats are defined as CSV files and follow the recommendation in Y. Shafranovich, Common Format and MIME Type for CSV Files, IETF RFC 4180 (Oct. 2005). For CSV files, headers are added to identify the data types. From existing CSV types, the online tool https: / / csv.openbridge.dev / has been used to validate the csv file, and create a schema for the files.

[0144] FIG. 9 shows different traces, associated to different interfaces, including video traces (V-Traces), video receive traces (V’-Traces), slice traces (S-Traces), S’-Traces, packet / PDU traces (P-Traces), and P’-Traces. V-Traces provide a time series of the statistics / complexity of a video frame (see e.g., [TR26926] § 5.5). Such a V-Trace is expected to provide sufficient information such that a coding model can create suitable statistics statics for encoded video streams at the output. V’-Traces provide a time series of received video frames together with an associated encoding and delivery quality (see e.g., [TR26926] § 5.8). S-Traces provide a time series of encoded video application data units, referred to as slices as known from H.264 / AVC and H.265 / HEVC suitable application data units as outputs from a video codecs (see e.g., [TR26926] § 5.6). S-Traces are expected to provide sufficient information to the content delivery module to create IP packets. S’-Traces are have the same format as S-Traces, but in addition may include information on losses and distortions due to the delivery over a network (see e.g., [TR26926] § 5.7). P Traces provide a time series of IP packets, possibly associated with different application flows and / or QoS Flows (see e.g., [TR26926] § 5.3). In addition, they provide metadata information that may be beneficial for advanced delivery. P’- Traces have the same format as P-Traces, but in addition may include losses and delays observed due to the delivery over a network. Additional aspects of the various traces are discussed in [TR26926].

[0145] FIG. 10 depicts an example 5G-XR functions integrated in a 5GS (e.g., 5GS 300). The integration of XR applications (e.g., 5G-XR aware application 1020) within the 5GS is approached following the model of 5G media streaming as defined in 3GPP TS 26.501 (“[TS26501 ]”). Assume a 5G-XR application provider (AP) 1040 being an XR AP 1040 that makes use of 5GS functionalities for its services. For this purpose, it provides a 5G-XR aware application (AA) 1020 on the UE 302 to make use of a 5G-XR client 1002 and NFs using network interfaces and APIs, potentially defined in 5G-XR related specifications.

[0146] The architecture in FIG. 10 represents potential 5G-XR functions within the 5GS as defined in [TS23501], and includes a 5G-XR AF 1060, 5G-XR application server (AS) 1062, and a 5G-XR client 1002. The 5G-XR AF 1060 is an AF similar to AF 360 and / or the AF as defined in [TS23501] § 6.2.10, dedicated to 5G-XR Services. The 5G-XR AS 1062 is an AS dedicated to 5G-XR services, and the 5G-XR client 1002 is a UE internal function dedicated to 5G-XR services.

[0147] The 5G-XR AF 1060 and 5G-XR AS 1062 are initially considered Data Network (DN) functions and communicate with the UE 302 via the N6, N3, and Uu interfaces as discussed herein and / or as defined in [TS23501J. Communication through sidelink PC5 may be an alternative to Uu based communication. Additionally or alternatively, 5G radio may also be differentiated between 5G Uu and 5G Sidelink / PC5. Uu is the interface between the UE 302 and the RAN 304 as defined in 3GPP TS 38.300, and sidelink is a mode of communication whereby UEs 302 can communicate with each other directly as defined in 3GPP TS 38.300.

[0148] Functions in trusted DNs 336 are trusted by the operator’s network as illustrated. Therefore, AFs in trusted DNs 336 may directly communicate with all 5GC functions. Functions in external DNs 336 may only communicate with 5GC functions via the NEF 352 using the N33 interface.

[0149] The architecture of FIG. 10 is used as a starting point. With XR related functions exclusively assigned to either DN 336 or UE 302. However, architectural extensions may be identified for the 3GPP system that may benefit from XR applications. Examples include the use of network slicing, edge computing, and / or usage of 5G QoS models.

[0150] FIG. 11 depicts an example 5G-XR architecture integrated in 5G and related interfaces. The XR architecture of FIG. 11 includes an 5G-XR client 1002 on UE 302. The 5G-XR client 1002 is a trasnmitter / receiver of 5G-XR session data that may be accessed through well-defined interfaces / APIs by the 5G-XR A A 1020.

[0151] In this example, the 5G-XR client 1002 contains two sub-functions: an XR engine 1110 and an XR session handler 1115. The XR session handler 1115 is a function of the UE 302 that communicates with the 5G-XR AF in order to establish, control and support the delivery of an XR session. The XR session handler 1115 exposes APIs that can be used by the 5G-XR AA 1020.

[0152] The XR engine 1110 is a function of the UE 302 that communicates with the 5G-XR AS 1062 in order to get access to XR related data, includes XR relevant functionalities (e.g., sensors, actuators, tracking, and / or the like), processes the XR data and communicates with the XR session handler 1115 for XR session control.

[0153] XR engines 11 10 provide a middleware that abstracts hardware and software functionalities for developers of XR applications. In the market as understood when initially writing this report, such engines are predominantly based on proprietary and commercial solutions, but with a trend towards providing standardized abstraction layers and APIs, notably provided by The OpenXR™ Specification, THE KHRONOS® OPENXR WORKING GROUP, version 1 .0.30 (25 Jan. 2020), https: / / registry.khronos.org / OpenXR / specs / ! .O / html / xrspec.html, as well as WebXR Device API, W3C CANDIDATE RECOMMENDATION DRAFT (01 Sep. 2023), https : / / www.w3.org / TR / webxr / .

[0154] The 5G-XR client 1002 may be controlled by an internal and / or external XR AA 1020. In some examples, the XR AA 1020 is an app, which implements the external application service provider specific logic and enables establishment of an XR session. The 5G-XR A A 1020 makes use of 5G-XR client 1002 and NFs using interfaces and APIs.

[0155] The 5G-XR AS 1062 is an AS that hosts 5G-XR media and media functions. The 5G-XR AP 1040 is an external XR AP that makes use of 5G-XR client 1002 and network functionalities to provide an XR experience to 5G-XR AAs 1020. The 5G-XR AF 1060 provides various control functions to the XR session handler 1115 on / in the UE 302 and / or to the 5G-XR AP 1040. The 5G-XR AF 1060 may relay or initiate a request for different policy or charging function (PCF) 356 treatment or interact with other network functions.

[0156] FIG. 12 depicts an example of processor (e.g., CPU and GPU) operations for XR applications. The XR engine 1110 is operated on or by one or more processors 1210, which interacts with one or more processors 1220. As examples, the processor(s) 1210, 1220 may include one or more CPUs, hardware accelerators, GPUs, FPGAs, ASICs, SoCs, MCPs, DSPs, and / or other like hardware elements. In some examples, one or more of the processor(s) 1210, 1220 correspond to processor(s) yzlO of FIG. yz. In the example of FIG. 11 , the processor(s) 1210 include one or more CPUs and the processor / s) 1220 include one or more GPUs.

[0157] The XR engine 1110 is a software-development environment designed for people to build XR experiences, such as games, virtual worlds, and / or other XR applications. Examples of the core functionality provided by XR engines 1110 include a rendering engine ("renderer") for 2D or 3D graphics (e.g., provided by a main control loop / engine 1201 and / or provided by processors, such as GPU(s), accelerator(s), and / or the like), a physics engine or collision detection (and collision response) (e.g., provided by physics engine 1203), sound (e.g., provided by audio engine 1202), scripting, animation, artificial intelligence (e.g., provided by Al engine 1204), networking, streaming (e.g., provided by streaming engine 1206), memory management, threading, localization support (e.g., provided by localization engine 1207), scene graph (e.g., provided by scene graph engine 1205), and may include video support.

[0158] The rendering engine provides the functionalities as documented in [TR26298] § 4.2.2 with a set of well defined APIs. The rendering engine generates animated 3D graphics by any of a number of methods (e.g., rasterization, ray-tracing, and / or the like). Instead of being programmed and compiled to be executed on the CPU or GPU directly, most often rendering engines are built upon one or multiple rendering (abstraction) APIs 121 1 , such as Direct3D, OpenGL, Vulkan, and / or the like, which provide a software abstraction of the GPU(s).

[0159] The audio engine 1202 is a component that includes algorithms related to the loading, modifying, and output of sound through the client's speaker system. At a minimum it is able to load, decompress, and play sound files. More advanced audio engines 1202 can calculate and produce such configurations as Doppler effects, echoes, pitch / amplitude adjustments, oscillation, and / or the like. The audio engine 1202 can perform calculations on the CPU, a dedicated ASIC, FPGA, and / or some other hardware device, component, or element, such as any of those discussed herein. Abstraction APIs 1211 (e.g., OpenAL, SDL audio, XAudio 2, Web Audio, and / or the like) are also available.

[0160] The physics engine 1203 is responsible for emulating the laws of physics realistically within the XR application. Specifically, the physics engine 1203 provides a set of functions for simulating physical forces and collisions, acting on the various objects within the scene at run time.

[0161] The Al engine 1204 is usually outsourced from the main XR engine 1110 into a special module, device, component, or other entity / element. XR applications may implement very different Al systems, and thus, Al is considered to be specific to the particular XR application for which it is created.

[0162] One of the major game engines used to create several notable games such as Fortnite ™, PlayerUnknown’s Battlegrounds ™, and Life is Strange 2 ™, is the Unreal Engine 4 ™. Another game engine with significant share is the Unity ™ engine. This engine is the one behind games such as Rust ™, Subnautica ™, and Life is Strange Before the Storm ™. Unity™ is a cross-platform XR engine 1110 developed by Unity Technologies, first announced and released in June 2005. A component of Unity are scriptable rendering pipelines for developers to create high-end graphics including high-end ones for consoles and PC experiences, as well as the lightweight ones for mobile, virtual reality, augmented reality, and mixed reality. The Unreal Engine was first showcased in the 1998 first-person shooter game Unreal. Although initially developed for first-person shooters, it is used in a variety of other genres, including platformers, fighting games, MMORPGs, and other RPGs.

[0163] As mentioned previously, key aspects of such XR engines 1110 and abstraction layers is the integration of advanced functionalities for new XR experiences including video, sound, scripting, networking, streaming, localization support, and scene graphs. By well-defined APIs (e.g., APIs 121 1), XR engines 1110 may also be distributed, where part of the functionality is hosted in the network on an XR server and other parts of the functionality are carried out in the XR device.

[0164] GPU / accelerator operations and rendering can include rendering or graphics pipelines, which are built by a sequence of shaders that operate on different buffers in order to create a desired output. Shaders are a type of computer programs that were originally used for shading (e.g., the production of appropriate levels of light, darkness, and color within an image), but can also perform a variety of programmable functions in various fields of computer graphics as well as image and video processing.

[0165] The input to the shaders is handled by the application, which decides what kind of data each stage of the rendering pipeline should operate on. Typically, this data is 3D assets including geometric primitives and material components. The application controls the rendering by providing the shaders with instructions describing how models should be transformed and projected on a 2D surface.

[0166] Generally, there are two types of rendering pipelines (i) rasterization rendering and (ii) ray-traced rendering (also referred to as ray-tracing). Rasterization is the task of taking an image described in a vector graphics format (shapes) and converting it into a raster image (a series of pixels, which, when displayed together, create the image which was represented via shapes). The rasterized image may then be displayed on a computer display, video display or printer, stored in a bitmap file format, or processed and encoded by regular 2D image and video codecs. Ray tracing heavy pipelines are typically considered as more computationally expensive thus less suitable for real-time rendering. However, in recent years real-time ray tracing has leaped forward due to improved hardware support and advances in ray tracing algorithms and post-processing.

[0167] However, there are several flavors to each type of rendering, and they may in some cases be combined to generate hybrid pipelines. Generally, both pipelines process similar data; the input consists of geometric primitives such as triangles and their material components. The main difference is that rasterization focuses to enable real-time rendering at a desired level of quality, whereas ray tracing is likely to be used to mimic light transmission to produce more realistic images. Additional aspects of rendering and / or other operations are discussed in [TR26298],

[0168] Additional examples of the presently described methods, devices, systems, and networks discussed herein include the following, non- limiting implementations. Each of the following non-limiting examples may stand on its own or may be combined in any permutation or combination with any one or more of the other examples provided below or throughout the present disclosure.

[0169] Example 1 may include an apparatus for a user equipment (UE) in a wireless communication network, configured to manage extended reality (XR) awareness comprising a processor configured to: initiate transmission of a UE Assistance Information message to provide uplink traffic information; set a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; set a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determine if XR awareness information may be available; and set the XR Awareness to a latest known value; and a memory to store the QoS notification.

[0170] Example 2 may include the apparatus of example 1 and / or some other example herein, wherein the UE Assistance Information message may be initiated based on configuration or change in uplink traffic information.

[0171] Example 3 may include the apparatus of example 1 and / or some other example herein, wherein the PDU Session ID may be dynamically updated based on active PDU sessions.

[0172] Example 4 may include the apparatus of example 1 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify one or more PDU sets.

[0173] Example 5 may include the apparatus of example 1 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify a PDU Set Importance (PSI).

[0174] Example 6 may include the apparatus of example 1 and / or some other example herein, wherein the QFI may be updated for each QoS flow to reflect current traffic conditions.

[0175] Example 7 may include the apparatus of example 1 and / or some other example herein, wherein the XR awareness information may be set if it has not been provided since configuration or if it has changed since the last transmission. Example 8 may include the apparatus of example 1 and / or some other example herein, wherein the transmission of the UE Assistance Information message may be triggered by a change in XR awareness status.

[0176] Example 9 may include the apparatus of example 1 and / or some other example herein, wherein the UE Assistance Information message may include jitter range or burst arrival time.

[0177] Example 10 may include a computer-readable medium storing computer-executable instructions which when executed by one or more processors result in performing operations comprising: initiating transmission of a UE Assistance Information message to provide uplink traffic information; setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; setting a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determining if XR awareness information may be available; and setting the XR Awareness to a latest known value.

[0178] Example 11 may include the computer-readable medium of example 10 and / or some other example herein, wherein the UE Assistance Information message may be initiated based on configuration or change in uplink traffic information.

[0179] Example 12 may include the computer-readable medium of example 10 and / or some other example herein, wherein the PDU Session ID may be dynamically updated based on active PDU sessions.

[0180] Example 13 may include the computer-readable medium of example 10 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify one or more PDU sets.

[0181] Example 14 may include the computer-readable medium of example 10 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify a PDU Set Importance (PSI).

[0182] Example 15 may include the computer-readable medium of example 10 and / or some other example herein, wherein the QFI may be updated for each QoS flow to reflect current traffic conditions.

[0183] Example 16 may include the computer-readable medium of example 10 and / or some other example herein, wherein the XR awareness information may be set if it has not been provided since configuration or if it has changed since the last transmission.

[0184] Example 17 may include the computer-readable medium of example 10 and / or some other example herein, wherein the transmission of the UE Assistance Information message may be triggered by a change in XR awareness status. Example 18 may include the computer-readable medium of example 10 and / or some other example herein, wherein the UE Assistance Information message may include jitter range or burst arrival time.

[0185] Example 19 may include a method comprising: initiating transmission of a UE Assistance Information message to provide uplink traffic information; setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; setting a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determining if XR awareness information may be available; and setting the XR Awareness to a latest known value.

[0186] Example 20 may include the method of example 19 and / or some other example herein, wherein the UE Assistance Information message may be initiated based on configuration or change in uplink traffic information.

[0187] Example 21 may include the method of example 19 and / or some other example herein, wherein the PDU Session ID may be dynamically updated based on active PDU sessions.

[0188] Example 22 may include the method of example 19 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify one or more PDU sets.

[0189] Example 23 may include the method of example 19 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify a PDU Set Importance (PSI).

[0190] Example 24 may include the method of example 19 and / or some other example herein, wherein the QFI may be updated for each QoS flow to reflect current traffic conditions.

[0191] Example 25 may include the method of example 19 and / or some other example herein, wherein the XR awareness information may be set if it has not been provided since configuration or if it has changed since the last transmission.

[0192] Example 26 may include the method of example 19 and / or some other example herein, wherein the transmission of the UE Assistance Information message may be triggered by a change in XR awareness status.

[0193] Example 27 may include the method of example 19 and / or some other example herein, wherein the UE Assistance Information message may include jitter range or burst arrival time.

[0194] Example 28 may include an apparatus comprising means for: initiating transmission of a UE Assistance Information message to provide uplink traffic information; setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; setting a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determining if XR awareness information may be available; and setting the XR Awareness to a latest known value.

[0195] Example 29 may include the apparatus of example 28 and / or some other example herein, wherein the UE Assistance Information message may be initiated based on configuration or change in uplink traffic information.

[0196] Example 30 may include the apparatus of example 28 and / or some other example herein, wherein the PDU Session ID may be dynamically updated based on active PDU sessions.

[0197] Example 31 may include the apparatus of example 28 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify one or more PDU sets.

[0198] Example 32 may include the apparatus of example 28 and / or some other example herein, wherein the XR awareness information may be defined to indicate an awareness based on whether the UE may be able to identify a PDU Set Importance (PSI).

[0199] Example 33 may include the apparatus of example 28 and / or some other example herein, wherein the QFI may be updated for each QoS flow to reflect current traffic conditions.

[0200] Example 34 may include the apparatus of example 28 and / or some other example herein, wherein the XR awareness information may be set if it has not been provided since configuration or if it has changed since the last transmission.

[0201] Example 35 may include the apparatus of example 28 and / or some other example herein, wherein the transmission of the UE Assistance Information message may be triggered by a change in XR awareness status.

[0202] Example 36 may include the apparatus of example 28 and / or some other example herein, wherein the UE Assistance Information message may include jitter range or burst arrival time.

[0203] Example 37 may include an apparatus comprising means for performing any of the methods of examples 1-36.

[0204] Example 38 may include a network node comprising a communication interface and processing circuitry connected thereto and configured to perform the methods of examples 1- 36.

[0205] Example 39 may include an apparatus comprising means to perform one or more elements of a method described in or related to any of examples 1-36, or any other method or process described herein.

[0206] Example 40 may include one or more non- transitory computer-readable media comprising instructions to cause an electronic device, upon execution of the instructions by one or more processors of the electronic device, to perform one or more elements of a method described in or related to any of examples 1-36, or any other method or process described herein.

[0207] Example 41 may include an apparatus comprising logic, modules, or circuitry to perform one or more elements of a method described in or related to any of examples 1-36, or any other method or process described herein.

[0208] Example 42 may include a method, technique, or process as described in or related to any of examples 1-36, or portions or parts thereof.

[0209] Example 43 may include an apparatus comprising: one or more processors and one or more computer-readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the method, techniques, or process as described in or related to any of examples 1-36, or portions thereof.

[0210] Example 44 may include a signal as described in or related to any of examples 1-36, or portions or parts thereof.

[0211] Example 45 may include a datagram, packet, frame, segment, protocol data unit (PDU), or message as described in or related to any of examples 1-36, or portions or parts thereof, or otherwise described in the present disclosure.

[0212] Example 46 may include a signal encoded with data as described in or related to any of examples 1-36, or portions or parts thereof, or otherwise described in the present disclosure.

[0213] Example 47 may include a signal encoded with a datagram, packet, frame, segment, protocol data unit (PDU), or message as described in or related to any of examples 1-36, or portions or parts thereof, or otherwise described in the present disclosure.

[0214] Example 48 may include an electromagnetic signal carrying computer-readable instructions, wherein execution of the computer-readable instructions by one or more processors is to cause the one or more processors to perform the method, techniques, or process as described in or related to any of examples 1-36, or portions thereof.

[0215] Example 49 may include a computer program comprising instructions, wherein execution of the program by a processing element is to cause the processing element to carry out the method, techniques, or process as described in or related to any of examples 1-36, or portions thereof.

[0216] Example 50 may include a signal in a wireless network as shown and described herein.

[0217] Example 51 may include a method of communicating in a wireless network as shown and described herein.

[0218] Example 52 may include a system for providing wireless communication as shown and described herein. Example 53 may include a device for providing wireless communication as shown and described herein.

[0219] TERMINOLOGY

[0220] For the purposes of the present document, the following terms and definitions are applicable to the examples and embodiments discussed herein. As used herein, the singular forms “a,” “an” and “the” are intended to include plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specific the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operation, elements, components, and / or groups thereof. The phrase “A and / or B” means (A), (B), or (A and B). For the purposes of the present disclosure, the phrase “A, B, and / or C” means (A), (B), (C), (A and B), (A and C), (B and C), or (A, B and C). The phrase “X(s)” means one or more X or a set of X. The description may use the phrases “in an embodiment,” “In some embodiments,” “in one implementation,” “In some implementations,” “in some examples”, and the like, each of which may refer to one or more of the same or different embodiments, implementations, and / or examples. Furthermore, the terms “comprising,” “including,” “having,” and the like, as used with respect to the present disclosure, are synonymous.

[0221] The terms “master” and “slave” at least in some examples refers to a model of asymmetric communication or control where one device, process, element, or entity (the “master”) controls one or more other device, process, element, or entity (the “slaves”). The terms “master” and “slave” are used in this disclosure only for their technical meaning. The term “master” or “grandmaster” may be substituted with any of the following terms “main”, “source”, “primary”, “initiator”, “requestor”, “transmitter”, “host”, “maestro”, “controller”, “provider”, “producer”, “client”, "source", "mix", "parent", “chief’, “manager”, “reference” (e.g., as in “reference clock” or the like), and / or the like. Additionally, the term “slave” may be substituted with any of the following terms “receiver”, “secondary”, “subordinate”, “replica”, target”, “responder”, “device”, “performer”, “agent”, “standby”, “consumer”, “peripheral”, “follower”, “server”, “child”, “helper”, “worker”, “node”, and / or the like.

[0222] The terms “coupled,” “communicatively coupled,” along with derivatives thereof are used herein. The term “coupled” may mean two or more elements are in direct physical or electrical contact with one another, may mean that two or more elements indirectly contact each other but still cooperate or interact with each other, and / or may mean that one or more other elements are coupled or connected between the elements that are said to be coupled with each other. The term “directly coupled’- may mean that two or more elements are in direct contact with one another. The term “communicatively coupled” may mean that two or more elements may be in contact with one another by a means of communication including through a wire or other interconnect connection, through a wireless communication channel or ink, and / or the like.

[0223] The term “establish” or “establishment” at least in some examples refers to (partial or in full) acts, tasks, operations, and the like, related to bringing or the readying the bringing of something into existence either actively or passively (e.g., exposing a device identity or entity identity). Additionally or alternatively, the term “establish” or “establishment” at least in some examples refers to (partial or in full) acts, tasks, operations, and the like, related to initiating, starting, or warming communication or initiating, starting, or warming a relationship between two entities or elements (e.g., establish a session, establish a session, and the like). Additionally or alternatively, the term “establish” or “establishment” at least in some examples refers to initiating something to a state of working readiness. The term “established” at least in some examples refers to a state of being operational or ready for use (e.g., full establishment). Furthermore, any definition for the term “establish” or “establishment” defined in any specification or standard can be used for purposes of the present disclosure and such definitions are not disavowed by any of the aforementioned definitions.

[0224] The term “obtain” at least in some examples refers to (partial or in full) acts, tasks, operations, and the like, of intercepting, movement, copying, retrieval, or acquisition (e.g., from a memory, an interface, or a buffer), on the original packet stream or on a copy (e.g., a new instance) of the packet stream. Other aspects of obtaining or receiving may involving instantiating, enabling, or controlling the ability to obtain or receive a stream of packets (or the following parameters and templates or template values).

[0225] The term “receipt” at least in some examples refers to any action (or set of actions) involved with receiving or obtaining an object, data, data unit, and the like, and / or the fact of the object, data, data unit, and the like being received. The term “receipt” at least in some examples refers to an object, data, data unit, and the like, being pushed to a device, system, element, and the like (e.g., often referred to as a push model), pulled by a device, system, element, and the like (e.g., often referred to as a pull model), and / or the like.

[0226] The term “element” at least in some examples refers to a unit that is indivisible at a given level of abstraction and has a clearly defined boundary, wherein an element may be any type of entity including, for example, one or more devices, systems, controllers, network elements, modules, engines, components, and so forth, or combinations thereof. The term “entity” at least in some examples refers to a distinct element of a component, architecture, platform, device, and / or system. Additionally or alternatively, the term “entity” at least in some examples refers to information transferred as a payload.

[0227] The term “measurement” at least in some examples refers to the observation and / or quantification of attributes of an object, event, or phenomenon. Additionally or alternatively, the term “measurement” at least in some examples refers to a set of operations having the object of determining a measured value or measurement result, and / or the actual instance or execution of operations leading to a measured value. Additionally or alternatively, the term “measurement” at least in some examples refers to data recorded during testing.

[0228] The term “metric” at least in some examples refers to a quantity produced in an assessment of a measured value. Additionally or alternatively, the term “metric” at least in some examples refers to data derived from a set of measurements. Additionally or alternatively, the term “metric” at least in some examples refers to set of events combined or otherwise grouped into one or more values. Additionally or alternatively, the term “metric” at least in some examples refers to a combination of measures or set of collected data points. Additionally or alternatively, the term “metric” at least in some examples refers to a standard definition of a quantity, produced in an assessment of performance and / or reliability of the network, which has an intended utility and is carefully specified to convey the exact meaning of a measured value.

[0229] The term “signal” at least in some examples refers to an observable change in a quality and / or quantity. Additionally or alternatively, the term “signal” at least in some examples refers to a function that conveys information about of an object, event, or phenomenon. Additionally or alternatively, the term “signal” at least in some examples refers to any time varying voltage, current, or electromagnetic wave that may or may not carry information. The term “digital signal” at least in some examples refers to a signal that is constructed from a discrete set of waveforms of a physical quantity so as to represent a sequence of discrete values.

[0230] The terms “ego” (as in, e.g., “ego device”) and “subject” (as in, e.g., “data subject”) at least in some examples refers to an entity, element, device, system, and the like, that is under consideration or being considered. The terms “neighbor” and “proximate” (as in, e.g., “proximate device”) at least in some examples refers to an entity, element, device, system, and the like, other than an ego device or subject device.

[0231] The term “identifier” at least in some examples refers to a value, or a set of values, that uniquely identify an identity in a certain scope. Additionally or alternatively, the term “identifier” at least in some examples refers to a sequence of characters that identifies or otherwise indicates the identity of a unique object, element, or entity, or a unique class of objects, elements, or entities. Additionally or alternatively, the term “identifier” at least in some examples refers to a sequence of characters used to identify or refer to an application, program, session, object, element, entity, variable, set of data, and / or the like. The “sequence of characters” mentioned previously at least in some examples refers to one or more names, labels, words, numbers, letters, symbols, and / or any combination thereof. Additionally or alternatively, the term “identifier” at least in some examples refers to a name, address, label, distinguishing index, and / or attribute. Additionally or alternatively, the term “identifier” at least in some examples refers to an instance of identification. The term “persistent identifier” at least in some examples refers to an identifier that is reused by a device or by another device associated with the same person or group of persons for an indefinite period. The term “identification” at least in some examples refers to a process of recognizing an identity as distinct from other identities in a particular scope or context, which may involve processing identifiers to reference an identity in an identity database. The term “application identifier”, “application ID”, or “app ID” at least in some examples refers to an identifier that can be mapped to a specific application, application instance, or application instance. In the context of 3GPP 5G / NR, an “application identifier” at least in some examples refers to an identifier that can be mapped to a specific application traffic detection rule.

[0232] The term “circuitry” at least in some examples refers to a circuit or system of multiple circuits configured to perform a particular function in an electronic device. The circuit or system of circuits may be part of, or include one or more hardware components, such as a logic circuit, a processor (shared, dedicated, or group) and / or memory (shared, dedicated, or group), an application- specific integrated circuit (ASIC), field-programmable gate array (FPGA), programmable logic controller (PLC), single-board computer (SBC), system on chip (SoC), system in package (SiP), multi-chip package (MCP), digital signal processor (DSP), and the like, that are configured to provide the described functionality. In addition, the term “circuitry” may also refer to a combination of one or more hardware elements with the program code used to carry out the functionality of that program code. Some types of circuitry may execute one or more software or firmware programs to provide at least some of the described functionality. Such a combination of hardware elements and program code may be referred to as a particular type of circuitry.

[0233] The term “processor circuitry” at least in some examples refers to, is part of, or includes circuitry capable of sequentially and automatically carrying out a sequence of arithmetic or logical operations, or recording, storing, and / or transferring digital data. The term “processor circuitry” at least in some examples refers to one or more application processors, one or more baseband processors, a physical CPU, a single-core processor, a dual-core processor, a triplecore processor, a quad-core processor, and / or any other device capable of executing or otherwise operating computer-executable instructions, such as program code, software modules, and / or functional processes. The terms “application circuitry” and / or “baseband circuitry” may be considered synonymous to, and may be referred to as, “processor circuitry.”

[0234] The term “memory” and / or “memory circuitry” at least in some examples refers to one or more hardware devices for storing data, including random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), conductive bridge Random Access Memory (CB-RAM), spin transfer torque (STT)-MRAM, phase change RAM (PRAM), core memory, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), flash memory, non-volatile RAM (NVRAM), magnetic disk storage mediums, optical storage mediums, flash memory devices or other machine readable mediums for storing data. The term “computer-readable medium” includes, but is not limited to, memory, portable or fixed storage devices, optical storage devices, and various other mediums capable of storing, containing or carrying instructions or data.

[0235] The term “interface circuitry” at least in some examples refers to, is part of, or includes circuitry that enables the exchange of information between two or more components or devices. The term “interface circuitry” at least in some examples refers to one or more hardware interfaces, for example, buses, I / O interfaces, peripheral component interfaces, network interface cards, and / or the like.

[0236] The term “SmartNIC” at least in some examples refers to a network interface controller (NIC), network adapter, or a programmable network adapter card with programmable hardware accelerators and network connectivity (e.g., Ethernet or the like) that can offload various tasks or workloads from other compute nodes or compute platforms such as servers, application processors, and / or the like and accelerate those tasks or workloads. A SmartNIC has similar networking and offload capabilities as an IPU, but remains under the control of the host as a peripheral device.

[0237] The term “infrastructure processing unit” or “IPU” at least in some examples refers to an advanced networking device with hardened accelerators and network connectivity (e.g., Ethernet or the like) that accelerates and manages infrastructure functions using tightly coupled, dedicated, programmable cores. In some implementations, an IPU offers full infrastructure offload and provides an extra layer of security by serving as a control point of a host for running infrastructure applications. An IPU is capable of offloading the entire infrastructure stack from the host and can control how the host attaches to this infrastructure. This gives service providers an extra layer of security and control, enforced in hardware by the IPU.

[0238] The term “device” at least in some examples refers to a physical entity embedded inside, or attached to, another physical entity in its vicinity, with capabilities to convey digital information from or to that physical entity.

[0239] The term “controller” at least in some examples refers to an element or entity that has the capability to affect a physical entity, such as by changing its state or causing the physical entity to move.

[0240] The term “scheduler” at least in some examples refers to an entity or element that assigns resources (e.g., processor time, network links, memory space, and / or the like) to perform tasks. The term “network scheduler” at least in some examples refers to a node, element, or entity that manages network packets in transmit and / or receive queues of one or more protocol stacks of network access circuitry (e.g., a network interface controller (NIC), baseband processor, and the like). The term “network scheduler” at least in some examples can be used interchangeably with the terms “packet scheduler”, “queueing discipline” or “qdisc”, and / or “queueing algorithm”.

[0241] The term “terminal” at least in some examples refers to point at which a conductor from a component, device, or network comes to an end. Additionally or alternatively, the term “terminal” at least in some examples refers to an electrical connector acting as an interface to a conductor and creating a point where external circuits can be connected. In some examples, terminals may include electrical leads, electrical connectors, electrical connectors, solder cups or buckets, and / or the like.

[0242] The term “compute node” or “compute device” at least in some examples refers to an identifiable entity implementing an aspect of computing operations, whether part of a larger system, distributed collection of systems, or a standalone apparatus. In some examples, a compute node may be referred to as a “computing device”, “computing system”, or the like, whether in operation as a client, server, or intermediate entity. Specific implementations of a compute node may be incorporated into a server, base station, gateway, road side unit, onpremise unit, user equipment, end consuming device, appliance, or the like. For purposes of the present disclosure, the term “node” at least in some examples refers to and / or is interchangeable with the terms “device”, “component”, “sub-system”, and / or the like. The term “computer system” at least in some examples refers to any type interconnected electronic devices, computer devices, or components thereof. Additionally, the terms “computer system” and / or “system” at least in some examples refer to various components of a computer that are communicatively coupled with one another. Furthermore, the term “computer system” and / or “system” at least in some examples refer to multiple computer devices and / or multiple computing systems that are communicatively coupled with one another and configured to share computing and / or networking resources.

[0243] The term “server” at least in some examples refers to a computing device or system, including processing hardware and / or process space(s), an associated storage medium such as a memory device or database, and, in some instances, suitable application(s) as is known in the art. The terms “server system” and “server” may be used interchangeably herein, and these terms at least in some examples refers to one or more computing system(s) that provide access to a pool of physical and / or virtual resources. The various servers discussed herein include computer devices with rack computing architecture component(s), tower computing architecture component(s), blade computing architecture component(s), and / or the like. The servers may represent a cluster of servers, a server farm, a cloud computing service, or other grouping or pool of servers, which may be located in one or more datacenters. The servers may also be connected to, or otherwise associated with, one or more data storage devices (not shown). Moreover, the servers includes an operating system (OS) that provides executable program instructions for the general administration and operation of the individual server computer devices, and includes a computer-readable medium storing instructions that, when executed by a processor of the servers, may allow the servers to perform their intended functions. Suitable implementations for the OS and general functionality of servers are known or commercially available, and are readily implemented by persons having ordinary skill in the art.

[0244] The term “platform” at least in some examples refers to an environment in which instructions, program code, software elements, and the like can be executed or otherwise operate, and examples of such an environment include an architecture (e.g., a motherboard, a computing system, and / or the like), one or more hardware elements (e.g., embedded systems, and the like), a cluster of compute nodes, a set of distributed compute nodes or network, an operating system, a virtual machine (VM), a virtualization container, a software framework, a client application (e.g., web browser or the like) and associated application programming interfaces, a cloud computing service (e.g., platform as a service (PaaS)), or other underlying software executed with instructions, program code, software elements, and the like. The term “architecture” at least in some examples refers to a computer architecture or a network architecture. The term “computer architecture” at least in some examples refers to a physical and logical design or arrangement of software and / or hardware elements in a computing system or platform including technology standards for interacts therebetween. The term “network architecture” at least in some examples refers to a physical and logical design or arrangement of software and / or hardware elements in a network including communication protocols, interfaces, and media transmission.

[0245] The term “appliance,” “computer appliance,” and the like, at least in some examples refers to a computer device or computer system with program code (e.g., software or firmware) that is specifically designed to provide a specific computing resource. The term “virtual appliance” at least in some examples refers to a virtual machine image to be implemented by a hypervisor-equipped device that virtualizes or emulates a computer appliance or otherwise is dedicated to provide a specific computing resource. The term “security appliance”, “firewall”, and the like at least in some examples refers to a computer appliance designed to protect computer networks from unwanted traffic and / or malicious attacks. The term “policy appliance” at least in some examples refers to technical control and logging mechanisms to enforce or reconcile policy rules (information use rules) and to ensure accountability in information systems.

[0246] The term “gateway” at least in some examples refers to a network appliance that allows data to flow from one network to another network, or a computing system or application configured to perform such tasks. Examples of gateways include IP gateways, Intemet-to-Orbit (120) gateways, loT gateways, cloud storage gateways, and / or the like.

[0247] The term “user equipment” or “UE” at least in some examples refers to a device with radio communication capabilities and may describe a remote user of network resources in a communications network. The term “user equipment” or “UE” may be considered synonymous to, and may be referred to as, client, mobile, mobile device, mobile terminal, user terminal, mobile unit, station, mobile station, mobile user, subscriber, user, remote station, access agent, user agent, receiver, radio equipment, reconfigurable radio equipment, reconfigurable mobile device, and the like. Furthermore, the term “user equipment” or “UE” includes any type of wireless / wired device or any computing device including a wireless communications interface. Examples of UEs, client devices, and the like, include desktop computers, workstations, laptop computers, mobile data terminals, smartphones, tablet computers, wearable devices, machine-to-machine (M2M) devices, machine-type communication (MTC) devices, Internet of Things (loT) devices, embedded systems, sensors, autonomous vehicles, drones, robots, in-vehicle infotainment systems, instrument clusters, onboard diagnostic devices, dashtop mobile equipment, electronic engine management systems, electronic / engine control units / modules, microcontrollers, control module, server devices, network appliances, head-up display (HUD) devices, helmut-mounted display devices, augmented reality (AR) devices, virtual reality (VR) devices, mixed reality (MR) devices, and / or other like systems or devices.

[0248] The term “station” or “STA” at least in some examples refers to a logical entity that is a singly addressable instance of a medium access control (MAC) and physical layer (PHY) interface to the wireless medium (WM). The term “wireless medium” or WM” at least in some examples refers to the medium used to implement the transfer of protocol data units (PDUs) between peer physical layer (PHY) entities of a wireless local area network (LAN).

[0249] The term “network element” at least in some examples refers to physical or virtualized equipment and / or infrastructure used to provide wired or wireless communication network services. The term “network element” may be considered synonymous to and / or referred to as a networked computer, networking hardware, network equipment, network node, router, switch, hub, bridge, radio network controller, network access node ( AN), base station, access point (AP), RAN device, RAN node, gateway, server, network applicance, network function (NF), virtualized NF (VNF), and / or the like.

[0250] The term “network controller” at least in some examples refers to a functional block that centralizes some or all of the control and management functionality of a network domain and may provide an abstract view of the network domain to other functional blocks via an interface.

[0251] The term “network access node” or “NAN” at least in some examples refers to a network element in a radio access network (RAN) responsible for the transmission and reception of radio signals in one or more cells or coverage areas to or from a UE or station. A “network access node” or “NAN” can have an integrated antenna or may be connected to an antenna array by feeder cables. Additionally or alternatively, a “network access node” or “NAN” includes specialized digital signal processing, network function hardware, and / or compute hardware to operate as a compute node. In some examples, a “network access node” or “NAN” may be split into multiple functional blocks operating in software for flexibility, cost, and performance. In some examples, a “network access node” or “NAN” may be a base station (e.g., an evolved Node B (eNB) or a next generation Node B (gNB)), an access point and / or wireless network access point, router, switch, hub, radio unit or remote radio head, Transmission Reception Point (TRxP), a gateway device (e.g., Residential Gateway, Wireline 5G Access Network, Wireline 5G Cable Access Network, Wireline BBF Access Network, and the like), network appliance, and / or some other network access hardware.

[0252] The term “access point” or “AP” at least in some examples refers to an entity that contains one station (STA) and provides access to the distribution services, via the wireless medium (WM) for associated STAs. An AP comprises a STA and a distribution system access function (DSAF).

[0253] The term “cell” at least in some examples refers to a radio network object that can be uniquely identified by a UE from an identifier (e.g., cell ID) that is broadcasted over a geographical area from a network access node (NAN). Additionally or alternatively, the term “cell” at least in some examples refers to a geographic area covered by a NAN. The term “handover” at least in some examples refers to the transfer of a user’s connection from one radio channel to another (can be the same or different cell). Additionally or alternatively, the term “handover” at least in some examples refers to the process in which a radio access network changes the radio transmitters, radio access mode, and / or radio system used to provide the bearer services, while maintaining a defined bearer service QoS.

[0254] The term “serving cell” at least in some examples refers to a primary cell (PCell) for a UE in a connected mode or state (e.g., RRC_CONNECTED) and not configured with carrier aggregation (CA) and / or dual connectivity (DC). Additionally or alternatively, the term “serving cell” at least in some examples refers to a set of cells comprising zero or more special cells and one or more secondary cells for a UE in a connected mode or state (e.g., RRC_CONNECTED) and configured with CA.

[0255] The term “primary cell” or “PCell” at least in some examples refers to a Master Cell Group (MCG) cell, operating on a primary frequency, in which a UE either performs an initial connection establishment procedure or initiates a connection re-establishment procedure. The term “Secondary Cell” or “SCell” at least in some examples refers to a cell providing additional radio resources on top of a special cell (SpCell) for a UE configured with CA. The term “special cell” or “SpCell” at least in some examples refers to a PCell for non-DC operation or refers to a PCell of an MCG or a PSCell of an SCG for DC operation.

[0256] The term “Master Cell Group” or “MCG” at least in some examples refers to a group of serving cells associated with a “Master Node” comprising a SpCell (PCell) and optionally one or more SCells. The term “Secondary Cell Group” or “SCG” at least in some examples refers to a subset of serving cells comprising a Primary SCell (PSCell) and zero or more SCells for a UE configured with DC. The term “Primary SCG Cell” refers to the SCG cell in which a UE performs random access when performing a reconfiguration with sync procedure for DC operation.

[0257] The term “Master Node” or “MN” at least in some examples refers to a NAN that provides control plane connection to a core network. The term “Secondary Node” or “SN” at least in some examples refers to a NAN providing resources to the UE in addition to the resources provided by an MN and / or a NAN with no control plane connection to a core network

[0258] The term “E-UTEAN NodeB”, “eNodeB”, or “eNB” at least in some examples refers to a RAN node providing E-UTRA user plane (PDCP / RLC / MAC / PHY) and control plane (RRC) protocol terminations towards a UE, and connected via an S 1 interface to the Evolved Packet Core (EPC). Two or more eNBs are interconnected with each other (and / or with one or more en-gNBs) by means of an X2 interface.

[0259] The term “next generation eNB” or “ng-eNB” at least in some examples refers to a RAN node providing E-UTRA user plane and control plane protocol terminations towards a UE, and connected via the NG interface to the 5GC. Two or more ng-eNBs are interconnected with each other (and / or with one or more gNBs) by means of an Xn interface.

[0260] The term “Next Generation NodeB”, “gNodeB”, or “gNB” at least in some examples refers to a RAN node providing NR user plane and control plane protocol terminations towards a UE, and connected via the NG interface to the 5GC. Two or more gNBs are interconnected with each other (and / or with one or more ng-eNBs) by means of an Xn interface.

[0261] The term “E-UTRA-NR gNB” or “en-gNB” at least in some examples refers to a RAN node providing NR user plane and control plane protocol terminations towards a UE, and acting as a Secondary Node in E-UTRA-NR Dual Connectivity (EN-DC) scenarios (see e.g., 3GPP TS 37.340 vl7.0.0 (2022-04-15) (“[TS37340]”)). Two or more en-gNBs are interconnected with each other (and / or with one or more eNBs) by means of an X2 interface.

[0262] The term “Next Generation RAN node” or “NG-RAN node” at least in some examples refers to either a gNB or an ng-eNB.

[0263] The term “lAB-node” at least in some examples refers to a RAN node that supports new radio (NR) access links to user equipment (UEs) and NR backhaul links to parent nodes and child nodes. The term “lAB-donor” at least in some examples refers to a RAN node (e.g., a gNB) that provides network access to UEs via a network of backhaul and access links.

[0264] The term “Transmission Reception Point” or “TRxP” at least in some examples refers to an antenna array with one or more antenna elements available to a network located at a specific geographical location for a specific area. The term “Central Unit” or “CU” at least in some examples refers to a logical node hosting radio resource control (RRC), Service Data Adaptation Protocol (SDAP), and / or Packet Data Convergence Protocol (PDCP) protocols / layers of an NG-RAN node, or RRC and PDCP protocols of the en-gNB that controls the operation of one or more DUs; a CU terminates an Fl interface connected with a DU and may be connected with multiple DUs. The term “Distributed Unit” or “DU” at least in some examples refers to a logical node hosting Backhaul Adaptation Protocol (BAP), Fl application protocol (Fl AP), radio link control (RLC), medium access control (MAC), and physical (PHY) layers of the NG-RAN node or en-gNB, and its operation is partly controlled by a CU; one DU supports one or multiple cells, and one cell is supported by only one DU; and a DU terminates the Fl interface connected with a CU. The term “Radio Unit” or “RU” at least in some examples refers to a logical node hosting PHY layer or Low- PHY layer and radiofrequency (RF) processing based on a lower layer functional split. The term “split architecture” at least in some examples refers to an architecture in which an CU, DU, and / or RU are physically separated from one another. Additionally or alternatively, the term “split architecture” at least in some examples refers to a RAN architecture such as those discussed in 3GPP TS 38.401 V17.5.0 (2023-06-29) (“ITS38401 ]”), 3GPP TS 38.410 v 17.1.0 (2022-06-23) (“[TS38410]”), and / or 3GPP TS 38.473 V17.5.0 (2023-06-29) (“[TS38473]”).The term “integrated architecture at least in some examples refers to an architecture in which an RU and DU are implemented on one platform, and / or an architecture in which a DU and a CU are implemented on one platform.

[0265] The term “Residential Gateway” or “RG” at least in some examples refers to a device providing, for example, voice, data, broadcast video, video on demand, to other devices in customer premises. The term “Wireline 5G Access Network” or “W-5GAN” at least in some examples refers to a wireline AN that connects to a 5GC via N2 and N3 reference points. The W-5GAN can be either a W-5GBAN or W-5GCAN. The term “Wireline 5G Cable Access Network” or “W-5GCAN” at least in some examples refers to an Access Network defined in / by CableLabs. The term “Wireline BBF Access Network” or “W-5GBAN” at least in some examples refers to an Access Network defined in / by the Broadband Forum (BBF). The term “Wireline Access Gateway Function” or “W-AGF” at least in some examples refers to a Network function in W-5GAN that provides connectivity to a 3GPP 5G Core network (5GC) to 5G-RG and / or FN-RG. The term “5G-RG” at least in some examples refers to an RG capable of connecting to a 5GC playing the role of a user equipment with regard to the 5GC; it supports secure element and exchanges N1 signaling with 5GC. The 5G-RG can be either a 5G-BRG or 5G-CRG. The term “SMTC” refers to an SSB-based measurement timing configuration configured by SSB-MeasurementTimingConfiguration. The term “SSB” refers to an SS / PBCH block.

[0266] The term “edge computing” at least in some examples refers to an implementation or arrangement of distributed computing elements that move processing activities and resources (e.g., compute, storage, acceleration, and / or network resources) towards the “edge” of the network in an effort to reduce latency and increase throughput for endpoint users (client devices, user equipment, and the like). Additionally or alternatively, term “edge computing” at least in some examples refers to a set of services hosted relatively close to a client / UE’s access point of attachment to a network to achieve relatively efficient service delivery through reduced end-to-end latency and / or load on the transport network. In some examples, edge computing implementations involve the offering of services and / or resources in a cloud-like systems, functions, applications, and subsystems, from one or multiple locations accessible via wireless networks. Additionally or alternatively, term “edge computing” at least in some examples refers to the concept, as described in Error! Reference source not found., that enables operator and 3rd party services to be hosted close to a UE’s access point of attachment, to achieve an efficient service delivery through the reduced end-to-end latency and load on the transport network.

[0267] The term “edge compute node” or “edge compute device” at least in some examples refers to an identifiable entity implementing an aspect of edge computing operations, whether part of a larger system, distributed collection of systems, or a standalone apparatus. In some examples, a compute node may be referred to as a “edge node”, “edge device”, “edge system”, whether in operation as a client, server, or intermediate entity. Additionally or alternatively, the term “edge compute node” at least in some examples refers to a real-world, logical, or virtualized implementation of a compute-capable element in the form of a device, gateway, bridge, system or subsystem, component, whether operating in a server, client, endpoint, or peer mode, and whether located at an “edge” of an network or at a connected location further within the network, however, references to an “edge computing system” generally refer to a distributed architecture, organization, or collection of multiple nodes and devices, and which is organized to accomplish or offer some aspect of services or resources in an edge computing setting.

[0268] The term “edge computing platform” or “edge platform” at least in some examples refers to a collection of functionality that is used to instantiate, execute, or run edge applications on a specific edge compute node (e.g., virtualisation infrastructure and / or the like), enable such edge applications to provide and / or consume edge services, and / or otherwise provide one or more edge services. The term “edge application” or “edge app” at least in some examples refers to an application that can be instantiated on, or executed by, an edge compute node within an edge computing network, system, or framework, and can potentially provide and / or consume edge computing services.

[0269] The term “edge service” at least in some examples refers to a service provided via an edge compute node and / or edge platform, either by the edge platform itself and / or by an edge application.

[0270] The term “colocated” or “co-located” at least in some examples refers to two or more elements being in the same place or location, or relatively close to one another (e.g., within some predetermined distance from one another). Additionally or alternatively, the term “colocated” or “co-located” at least in some examples refers to the placement or deployment of two or more compute elements or compute nodes together in a secure dedicated storage facility, or within a same enclosure or housing.

[0271] The term “central office” or “CO” at least in some examples refers to an aggregation point for telecommunications infrastructure within an accessible or defined geographical area, often where telecommunication service providers have traditionally located switching equipment for one or multiple types of access networks. In some examples, a CO can be physically designed to house telecommunications infrastructure equipment or compute, data storage, and network resources. The CO need not, however, be a designated location by a telecommunications service provider. The CO may host any number of compute devices for edge applications and services, or even local implementations of cloud-like services.

[0272] The term “cloud computing” or “cloud” at least in some examples refers to a paradigm for enabling network access to a scalable and elastic pool of shareable computing resources with self-service provisioning and administration on-demand and without active management by users. Cloud computing provides cloud computing services (or cloud services), which are one or more capabilities offered via cloud computing that are invoked using a defined interface (e.g., an API or the like).

[0273] The term “cloud gaming” or “CG” at least in some examples refers to a group of use cases where the at least some computations related to gaming (e.g., single-player or multiplayer) is offloaded from a UE to edge compute node(s), a cloud computing service, and / or remote server(s).

[0274] The term “data center” at least in some examples refers to a purpose-designed structure that is intended to house multiple high-performance compute and data storage nodes such that a large amount of compute, data storage and network resources are present at a single location. This often entails specialized rack and enclosure systems, suitable heating, cooling, ventilation, security, fire suppression, and power delivery systems. The term may also refer to a compute and data storage node in some contexts. A data center may vary in scale between a centralized or cloud data center (e.g., largest), regional data center, and edge data center (e.g., smallest).

[0275] The term “cluster” at least in some examples refers to a set or grouping of entities as part of a cloud computing service and / or an edge computing system (or systems), in the form of physical entities (e.g., different computing systems, network elements, networks and / or network groups), logical entities (e.g., applications, functions, security constructs, virtual machines, virtualization containers, and the like), and the like. In some examples, a “cluster” is also referred to as a “group” or a “domain”. The membership of cluster may be modified or affected based on conditions, parameters, criteria, configurations, functions, and / or other aspects including from dynamic or property-based membership, from network or system management scenarios, and / or the like.

[0276] The term “compute resource” or simply “resource” at least in some examples refers to an object with a type, associated data, a set of methods that operate on it, and, if applicable, relationships to other resources. Additionally or alternatively, the term “compute resource” or “resource” at least in some examples refers to any physical or virtual component, or usage of such components, of limited availability within a computer system or network. Examples of computing resources include usage / access to, for a period of time, servers, processor(s), storage equipment, memory devices, memory areas, networks, electrical power, input / output (peripheral) devices, mechanical devices, network connections (e.g., channels / links, ports, network sockets, and the like), operating systems, virtual machines (VMs), software / applications, computer files, and / or the like. A “hardware resource” at least in some examples refers to compute, storage, and / or network resources provided by physical hardware element(s). A “virtualized resource” at least in some examples refers to compute, storage, and / or network resources provided by virtualization infrastructure to an application, device, system, and the like. The term “network resource” or “communication resource” at least in some examples refers to resources that are accessible by computer devices / systems via a communications network. The term “system resources” at least in some examples refers to any kind of shared entities to provide services, and includes computing and / or network resources. System resources may be considered as a set of coherent functions, network data objects or services, accessible through a server where such system resources reside on a single host or multiple hosts and are clearly identifiable. The term “workload” at least in some examples refers to an amount of work performed by a computing system, device, entity, and the like, during a period of time or at a particular instant of time. A workload may be represented as a benchmark, such as a response time, throughput (e.g., how much work is accomplished over a period of time), and / or the like. Additionally or alternatively, the workload may be represented as a memory workload (e.g., an amount of memory space needed for program execution to store temporary or permanent data and to perform intermediate computations), processor workload (e.g., a number of instructions being executed by a processor during a given period of time or at a particular time instant), an I / O workload (e.g., a number of inputs and outputs or system accesses during a given period of time or at a particular time instant), database workloads (e.g., a number of database queries during a period of time), a network-related workload (e.g., a number of network attachments, a number of mobility updates, a number of radio link failures, a number of handovers, an amount of data to be transferred over an air interface, and the like), and / or the like. Various algorithms may be used to determine a workload and / or workload characteristics, which may be based on any of the aforementioned workload types.

[0277] The term “network function” or “NF” at least in some examples refers to a functional block within a network infrastructure that has one or more external interfaces and a defined functional behavior.

[0278] The term “network service” or “NS” at least in some examples refers to a composition or collection of NF(s) and / or network service(s), defined by its functional and behavioral specification(s).

[0279] The term “RAN function” or “RANF” at least in some examples refers to a functional block within a RAN architecture that has one or more external interfaces and a defined behavior related to the operation of a RAN or RAN node. Additionally or alternatively, the term “RAN function” or “RANF” at least in some examples refers to a set of functions and / or NFs that are part of a RAN.

[0280] The term “Application Function” or “AF” at least in some examples refers to an element or entity that interacts with a 3GPP core network in order to provide services. Additionally or alternatively, the term “Application Function” or “AF” at least in some examples refers to an edge compute node or ECT framework from the perspective of a 5G core network. The term “edge compute function” or “ECF” at least in some examples refers to an element or entity that performs an aspect of an edge computing technology (ECT), an aspect of edge networking technology (ENT), or performs an aspect of one or more edge computing services running over the ECT or ENT. The term “management function” at least in some examples refers to a logical entity playing the roles of a service consumer and / or a service producer. The term “management service’- at least in some examples refers to a set of offered management capabilities. The term “network function virtualization” or “NFV” at least in some examples refers to the principle of separating network functions from the hardware they run on by using virtualisation techniques and / or virtualization technologies.

[0281] The term “virtualized network function” or “VNF” at least in some examples refers to an implementation of an NF that can be deployed on a Network Function Virtualisation Infrastructure (NFVI). The term “Network Functions Virtualisation Infrastructure Manager” or “NFVI” at least in some examples refers to a totality of all hardware and software components that build up the environment in which VNFs are deployed.

[0282] The term “slice” at least in some examples refers to a set of characteristics and behaviors that separate one instance, traffic, data flow, application, application instance, link or connection, RAT, device, system, entity, element, and the like from another instance, traffic, data flow, application, application instance, link or connection, RAT, device, system, entity, element, and the like, or separate one type of instance, and the like, from another instance, and the like.

[0283] The term “network slice” at least in some examples refers to a logical network that provides specific network capabilities and network characteristics and / or supports various service properties for network slice service consumers. Additionally or alternatively, the term “network slice” at least in some examples refers to a logical network topology connecting a number of endpoints using a set of shared or dedicated network resources that are used to satisfy specific service level objectives(SLOs) and / or service level agreements (SLAs).

[0284] The term “network slicing” at least in some examples refers to methods, processes, techniques, and technologies used to create one or multiple unique logical and virtualized networks over a common multi-domain infrastructure. The term “access network slice”, “radio access network slice”, or “RAN slice” at least in some examples refers to a part of a network slice that provides resources in a RAN to fulfill one or more application and / or service requirements (e.g., SLAs, and the like). The term “network slice instance” at least in some examples refers to a set of Network Function instances and the required resources (e.g., compute, storage and networking resources) which form a deployed network slice. Additionally or alternatively, the term “network slice instance” at least in some examples refers to a representation of a service view of a network slice. The term “network instance” at least in some examples refers to information identifying a domain. The term “service consumer” at least in some examples refers to an entity that consumes one or more services. The term “service producer” at least in some examples refers to an entity that offers, serves, or otherwise provides one or more services. The term “service provider” at least in some examples refers to an organization or entity that provides one or more services to at least one service consumer. For purposes of the present disclosure, the terms “service provider” and “service producer” may be used interchangeably even though these terms may refer to difference concepts. Examples of service providers include cloud service provider (CSP), network service provider (NSP), application service provider (ASP) (e.g., Application software service provider in a service-oriented architecture (ASSP)), internet service provider (ISP), telecommunications service provider (TSP), online service provider (OSP), payment service provider (PSP), managed service provider (MSP), storage service providers (SSPs), SAML service provider, and / or the like. At least in some examples, SLAs may specify, for example, particular aspects of the service to be provided including quality, availability, responsibilities, metrics by which service is measured, as well as remedies or penalties should agreed-on service levels not be achieved. The term “SAML service provider” at least in some examples refers to a system and / or entity that receives and accepts authentication assertions in conjunction with a single sign-on (SSO) profile of the Security Assertion Markup Language (SAML) and / or some other security mechanism(s).

[0285] The term “Virtualized Infrastructure Manager” or “VIM” at least in some examples refers to a functional block that is responsible for controlling and managing the NFVI compute, storage and network resources, usually within one operator's infrastructure domain.

[0286] The term “virtualization container”, “execution container”, or “container” at least in some examples refers to a partition of a compute node that provides an isolated virtualized computation environment. The term “OS container” at least in some examples refers to a virtualization container utilizing a shared Operating System (OS) kernel of its host, where the host providing the shared OS kernel can be a physical compute node or another virtualization container. Additionally or alternatively, the term “container” at least in some examples refers to a standard unit of software (or a package) including code and its relevant dependencies, and / or an abstraction at the application layer that packages code and dependencies together. Additionally or alternatively, the term “container” or “container image” at least in some examples refers to a lightweight, standalone, executable software package that includes everything needed to run an application such as, for example, code, runtime environment, system tools, system libraries, and settings. The term “virtual machine” or “VM” at least in some examples refers to a virtualized computation environment that behaves in a same or similar manner as a physical computer and / or a server. The term “hypervisor” at least in some examples refers to a software element that partitions the underlying physical resources of a compute node, creates VMs, manages resources for VMs, and isolates individual VMs from each other.

[0287] The term “Data Network” or “DN” at least in some examples refers to a network hosting data-centric services such as, for example, operator services, the internet, third-party services, or enterprise networks. Additionally or alternatively, a DN at least in some examples refers to service networks that belong to an operator or third party, which are offered as a service to a client or user equipment (UE). DNs are sometimes referred to as “Packet Data Networks” or “PDNs”. The term “Local Area Data Network” or “LADN” at least in some examples refers to a DN that is accessible by the UE only in specific locations, that provides connectivity to a specific DNN, and whose availability is provided to the UE.

[0288] The term “Internet of Things” or “loT” at least in some examples refers to a system of interrelated computing devices, mechanical and digital machines capable of transferring data with little or no human interaction, and may involve technologies such as real-time analytics, machine learning and / or Al, embedded systems, wireless sensor networks, control systems, automation (e.g., smarthome, smart building and / or smart city technologies), and the like. loT devices are usually low-power devices without heavy compute or storage capabilities. The term “edge loT devices” at least in some examples refers to any kind of loT devices deployed at a network’s edge.

[0289] The term “application context” at at least in some examples refers to a set of data about an application client that resides in an edge application server (EAS). The term “application context relocation” or “ACR” at least in some examples refers to an end-to-end service continuity procedure described in [TS23558] § 8.8. The term “application context transfer” or “ACT” at least in some examples refers to the transfer of an application context between a source edge application server (EAS) and a target EAS, which is a part of the service continuity procedure described in [TS23558] § 8.8. The term “application server” at least in some examples refers to an application or other software element resident in the cloud and / or edge compute network / system / server performing one or more server functions. The term “edge application server” or “EAS” at least in some examples refers to an application server resident in an edge hosting environment. The term “edge computing service provider” or “ECSP” at least in some examples refers to a mobile network operator or a 3rd party service provider offering edge computing services. The term “ECSP management system” at least in some examples refers to a part of 3GPP management system that utilizes 3GPP defined management services to enable consumers (e.g., ASP. ECSP) to orchestrate and manage the EDN. The term “PLMN Management System” at least in some examples refers to a part of 3GPP Management System that utilizes 3GPP defined management services to enable consumers (e.g., PLMN operator) to orchestrate and manage the mobile networks. The term “Availability Zone” at least in some examples refers to GSMA Operator Platform Telco Edge Requirements (see e.g., Operator Platform Telco Edge Requirements, version 2.0, GSM Association (GSMA), Official Document OPG.02 (14 Apr. 2022)). The term “edge data network” or “EDN” at least in some examples refers to a local data network that supports the architecture for enabling edge applications. The term “edge enabler client context” or “EEC context” at least in some examples refers to a set of data about the Edge Enabler Client that resides in the edge enabler server (EES). The term “edge enabler layer” at least in some examples refers to the overall functionality provided by the entities, such as edge enabler client (EEC), edge enabler server (EES), and / or edge configuration server (ECS), in support of applications as per the architecture (see e.g., [TS23558] § 6). The term “edge hosting environment” at least in some examples refers to an environment providing support required for an edge application server's execution. The term “cloud data network” at least in some examples refers to a data network having a set of servers deployed in a central place and capable of serving UEs from wider coverage area, as opposed to the edge data network (EDN). The term “primary ECS” at least in some examples refers to an ECS whose address information is configured with the EEC. EEC is authorized to communicate with the Primary ECS directly. Additionally or alternatively, the term “primary ECS” can also be referred to as a “configured ECS” during the normative phase. The term “primary ECSP” at least in some examples refers to an ECSP for which a UE has authorization to obtain service. The term “partner ECS” at least in some examples refers to a federation partner of a primary ECS; in some examples, an EEC is not configured with the address information of partner ECSs. The term “partner ECSP” at least in some examples refers to an ECSP with whom a primary ECSP has a service level agreement (SLA) for resource sharing, for example, a federation partner of the primary ECSP.

[0290] The term “protocol” at least in some examples refers to a predefined procedure or method of performing one or more operations. Additionally or alternatively, the term “protocol” at least in some examples refers to a common means for unrelated objects to communicate with each other (sometimes also called interfaces). The term “communication protocol” at least in some examples refers to a set of standardized rules or instructions implemented by a communication device and / or system to communicate with other devices and / or systems, including instructions for packetizing / depacketizing data, modulating / demodulating signals, implementation of protocols stacks, and / or the like. In various implementations, a “protocol” and / or a “communication protocol” may be represented using a protocol stack, a finite state machine (FSM), and / or any other suitable data structure. The term “standard protocol” at least in some examples refers to a protocol whose specification is published and known to the public and is controlled by a standards body. The term “protocol stack” or “network stack” at least in some examples refers to an implementation of a protocol suite or protocol family. In various implementations, a protocol stack includes a set of protocol layers, where the lowest protocol deals with low-level interaction with hardware and / or communications interfaces and each higher layer adds additional capabilities. Additionally or alternatively, the term “protocol” at least in some examples refers to a formal set of procedures that are adopted to ensure communication between two or more functions within the within the same layer of a hierarchy of functions.

[0291] The term “application layer” at least in some examples refers to an abstraction layer that specifies shared communications protocols and interfaces used by hosts in a communications network. Additionally or alternatively, the term “application layer” at least in some examples refers to an abstraction layer that interacts with software applications that implement a communicating component, and includes identifying communication partners, determining resource availability, and synchronizing communication. Examples of application layer protocols include HTTP, HTTPs, File Transfer Protocol (FTP), Dynamic Host Configuration Protocol (DHCP), Internet Message Access Protocol (IMAP), Lightweight Directory Access Protocol (LDAP), MQTT (MQ Telemetry Transport), Remote Authentication Dial-In User Service (RADIUS), Diameter protocol, Extensible Authentication Protocol (EAP), RDMA over Converged Ethernet version 2 (RoCEv2), Real-time Transport Protocol (RTP), RTP Control Protocol (RTCP), Real Time Streaming Protocol (RTSP), SBMV Protocol, Skinny Client Control Protocol (SCCP), Session Initiation Protocol (SIP), Session Description Protocol (SDP), Simple Mail Transfer Protocol (SMTP), Simple Network Management Protocol (SNMP), Simple Service Discovery Protocol (SSDP), Small Computer System Interface (SCSI), Internet SCSI (iSCSI), iSCSI Extensions for RDMA (iSER), Transport Layer Security (TLS), voice over IP (VoIP), Virtual Private Network (VPN), Extensible Messaging and Presence Protocol (XMPP), and / or the like.

[0292] The term “session layer” at least in some examples refers to an abstraction layer that controls dialogues and / or connections between entities or elements, and may include establishing, managing and terminating the connections between the entities or elements. The term “transport layer” at least in some examples refers to a protocol layer that provides end-to-end (e2e) communication services such as, for example, connection-oriented communication, reliability, flow control, and multiplexing. Examples of transport layer protocols include datagram congestion control protocol (DCCP), fibre channel protocol (FBC), Generic Routing Encapsulation (GRE), GPRS Tunneling (GTP), Micro Transport Protocol (|1TP), Multipath TCP (MPTCP), MultiPath QUIC (MPQUIC), Multipath UDP (MPUDP), Quick UDP Internet Connections (QUIC), Remote Direct Memory Access (RDMA), Resource Reservation Protocol (RSVP), Stream Control Transmission Protocol (SCTP), transmission control protocol (TCP), user datagram protocol (UDP), and / or the like.

[0293] The term “network layer” at least in some examples refers to a protocol layer that includes means for transferring network packets from a source to a destination via one or more networks. Additionally or alternatively, the term “network layer” at least in some examples refers to a protocol layer that is responsible for packet forwarding and / or routing through intermediary nodes. Additionally or alternatively, theterm “network layer” or “internet layer” at least in some examples refers to a protocol layer that includes interworking methods, protocols, and specifications that are used to transport network packets across a network. As examples, the network layer protocols include internet protocol (IP), IP security (IPsec), Internet Control Message Protocol (ICMP), Internet Group Management Protocol (IGMP), Open Shortest Path First protocol (OSPF), Routing Information Protocol (RIP), RDMA over Converged Ethernet version 2 (RoCEv2), Subnetwork Access Protocol (SNAP), and / or some other internet or network protocol layer.

[0294] The term “link layer” or “data link layer” at least in some examples refers to a protocol layer that transfers data between nodes on a network segment across a physical layer. Examples of link layer protocols include logical link control (LLC), medium access control (MAC), Ethernet, RDMA over Converged Ethernet version 1 (RoCEvl), and / or the like.

[0295] The term “radio resource control”, “RRC layer”, or “RRC” at least in some examples refers to a protocol layer or sublayer that performs system information handling; paging; establishment, maintenance, and release of RRC connections; security functions; establishment, configuration, maintenance and release of Signaling Radio Bearers (SRBs) and Data Radio Bearers (DRBs); mobility functions / services; QoS management; and some sidelink specific services and functions over the Uu interface (see e.g., 3GPP TS 36.331 vl7.5.0 (2023- 07-04) (“[TS36331]”) and / or 3GPP TS 38.331 vl7.5.0 (2023-07-01) (“[TS38331]”)).

[0296] The term “Service Data Adaptation Protocol”, “SDAP layer”, or “SDAP” at least in some examples refers to a protocol layer or sublayer that performs mapping between QoS flows and a data radio bearers (DRBs) and marking QoS flow IDs (QFI) in both DL and UL packets (see e.g., 3GPP TS 37.324 V17.0.0 (2022-04-13) (“[TS37324]”).

[0297] The term “Packet Data Convergence Protocol”, “PDCP layer”, or “PDCP” at least in some examples refers to a protocol layer or sublayer that performs transfer user plane or control plane data; maintains PDCP sequence numbers (SNs); header compression and decompression using the Robust Header Compression (ROHC) and / or Ethernet Header Compression (EHC) protocols; ciphering and deciphering; integrity protection and integrity verification; provides timer based SDU discard; routing for split bearers; duplication and duplicate discarding; reordering and in-order delivery; and / or out-of-order delivery (see e.g., 3GPP TS 36.323 V17.2.0 (2023-01-13) and / or 3GPP TS 38.323 vl7.5.0 (2023-06-30) (“[TS38323]”)).

[0298] The term “radio link control layer”, “RLC layer”, or “RLC” at least in some examples refers to a protocol layer or sublayer that performs transfer of upper layer PDUs; sequence numbering independent of the one in PDCP; error Correction through ARQ; segmentation and / or re-segmentation of RLC SDUs; reassembly of SDUs; duplicate detection; RLC SDU discarding; RLC re-establishment; and / or protocol error detection (see e.g., 3GPP TS 36.322 V17.0.0 (2022-04-15) and 3GPP TS 38.322 V17.3.0 (2023-06-30) (“ITS38322]”)).

[0299] The term “medium access control protocol”, “MAC protocol”, or “MAC” at least in some examples refers to a protocol that governs access to the transmission medium in a network, to enable the exchange of data between stations in a network. Additionally or alternatively, the term “medium access control layer”, “MAC layer”, or “MAC” at least in some examples refers to a protocol layer or sublayer that performs functions to provide frame-based, connectionlessmode (e.g., datagram style) data transfer between stations or devices. Additionally or alternatively, the term “medium access control layer”, “MAC layer”, or “MAC” at least in some examples refers to a protocol layer or sublayer that performs mapping between logical channels and transport channels; multiplexing / demultiplexing of MAC SDUs belonging to one or different logical channels into / from transport blocks (TB) delivered to / from the physical layer on transport channels; scheduling information reporting; error correction through HARQ (one HARQ entity per cell in case of CA); priority handling between UEs by means of dynamic scheduling; priority handling between logical channels of one UE by means of logical channel prioritization; priority handling between overlapping resources of one UE; and / or padding (see e.g., [IEEE802], 3GPP TS 36.321 vl7.5.0 (2023-06-30), and 3GPP TS 38.321 vl7.5.0 (2023- 06-30) (“[TS38321]”).

[0300] The term “physical layer”, “PHY layer”, or “PHY” at least in some examples refers to a protocol layer or sublayer that includes capabilities to transmit and receive modulated signals for communicating in a communications network (see e.g., [IEEE802], 3GPP TS 36.201 V17.0.0 (2022-03-31), and 3GPP TS 38.201 V17.0.0 (2022-01-05) (“[TS38201]”).

[0301] The term “access technology” at least in some examples refers to the technology used for the underlying physical connection to a communication network. The term “radio access technology” or “RAT” at least in some examples refers to the technology used for the underlying physical connection to a radio based communication network. The term “radio technology” at least in some examples refers to technology for wireless transmission and / or reception of electromagnetic radiation for information transfer. The term “RAT type” at least in some examples may identify a transmission technology and / or communication protocol used in an access network. Examples of access technologies include wireless access technologies / RATs, wireline, wireline-cable, wireline broadband forum (wireline-BBF), Ethernet (see e.g., IEEE Standard for Ethernet, IEEE Std 802.3-2018 (31 Aug. 2018) (“[IEEE8023]”)) and variants thereof, fiber optics networks (e.g., ITU-T G.651, ITU-T G.652, Optical Transport Network (OTN), Synchronous optical networking (SONET) and synchronous digital hierarchy (SDH), and the like), digital subscriber line (DSL) and variants thereof, Data Over Cable Service Interface Specification (DOCSIS) technologies, hybrid fiber-coaxial (HFC) technologies, and / or the like. Examples of RATs (or RAT types) and / or communications protocols include Advanced Mobile Phone System (AMPS) technologies (e.g., Digital AMPS (D-AMPS), Total Access Communication System (TACS) and variants thereof, such as Extended TACS (ETACS), and the like); Global System for Mobile Communications (GSM) technologies (e.g., Circuit Switched Data (CSD), High-Speed CSD (HSCSD), General Packet Radio Service (GPRS), and Enhanced Data Rates for GSM Evolution (EDGE)); Third Generation Partnership Project (3GPP) technologies (e.g., Universal Mobile Telecommunications System (UMTS) and variants thereof (e.g., UMTS Terrestrial Radio Access (UTRA), Wideband Code Division Multiple Access (W-CDMA), Freedom of Multimedia Access (FOMA), Time Division-Code Division Multiple Access (TD-CDMA), Time Division-Synchronous Code Division Multiple Access (TD-SCDMA), and the like), Generic Access Network (GAN) / Unlicensed Mobile Access (UMA), High Speed Packet Access (HSPA) and variants thereof (e.g., HSPA Plus (HSPA+)), Long Term Evolution (LTE) and variants thereof (e.g., LTE- Advanced (LTE- A), Evolved UTRA (E-UTRA), LTE Extra, LTE-A Pro, LTE LAA, MuLTEfire, and the like), Fifth Generation (5G) or New Radio (NR), narrowband loT (NB-IOT), 3GPP Proximity Services (ProSe), and / or the like); ETSI RATs (e.g., High Performance Radio Metropolitan Area Network (HiperMAN), Intelligent Transport Systems (ITS) (e.g., ITS-G5, ITS-G5B, ITS-G5C, and the like), and the like); Institute of Electrical and Electronics Engineers (IEEE) technologies and / or WiFi (e.g., IEEE Standard for Local and Metropolitan Area Networks: Overview and Architecture, IEEE Std 802-2014, pp. 1- 74 (30 Jun. 2014) (“[IEEE802]”), IEEE Standard for Information Technology- Telecommunications and Information Exchange between Systems - Local and Metropolitan Area Networks-Specific Requirements - Part 11 : Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE Std 802.11-2020, pp.1-4379 (26 Feb. 2021) (“[IEEE80211]”), IEEE 802.15 technologies (e.g., IEEE Standard for Low-Rate Wireless Networks, IEEE Std 802.15.4-2020, pp.1-800 (23 July 2020) (“[IEEE802154]”) and variants thereof (e.g., ZigBee, WirelessHART, MiWi, ISAlOO.l la, Thread, IPv6 over Low power WPAN (6L0WPAN), and the like), IEEE Standard for Local and metropolitan area networks - Part 15.6: Wireless Body Area Networks, IEEE Std 802.15.6-2012, pp. 1-271 (29 Feb. 2012), and the like), WLAN V2X RATs (e.g., IEEE Standard for Information technology- - Local and metropolitan area networks— Specific requirements— Part 11 : Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments, IEEE Std 802.11p-2010, pp.1-51 (15 July 2010) (“I1EEE8021 lp|”) (which is now part of (1EEE80211 ]), IEEE Guide for Wireless Access in Vehicular Environments (WAVE) Architecture, IEEE Standards Association, IEEE 1609.0- 2019 (10 Apr. 2019) (“[IEEE16090]”), IEEE 802.1 Ibd, Dedicated Short Range Communications (DSRC), and / or the like), Worldwide Interoperability for Microwave Access (WiMAX) (e.g., IEEE Standard for Air Interface for Broadband Wireless Access Systems, IEEE Std 802.16-2017, pp. 1-2726 (02 Mar. 2018) (“[WiMAX]”)), Mobile Broadband Wireless Access (MBWA) / iBurst (e.g., IEEE 802.20 and variants thereof), Wireless Gigabit Alliance (WiGig) standards (e.g., IEEE 802.1 lad, IEEE 802.1 lay, and the like), and so forth); Integrated Digital Enhanced Network (iDEN) and variants thereof (e.g., Wideband Integrated Digital Enhanced Network (WiDEN)); millimeter wave (mmWave) technologies / standards (e.g., wireless systems operating at 10-300 GHz and above 3GPP 5G); short-range and / or wireless personal area network (WPAN) technologies / standards (e.g., IEEE 802.15 technologies (e.g., as mentioned previously); Bluetooth and variants thereof (e.g., Bluetooth 5.3, Bluetooth Low Energy (BLE), and the like), WiFi-direct, Miracast, ANT / ANT+, Z-Wave, Universal Plug and Play (UPnP), low power Wide Area Networks (LPWANs), Long Range Wide Area Network (LoRA or LoRaWAN™), and the like); optical and / or visible light communication (VLC) technologies / standards (e.g., IEEE Standard for Local and metropolitan area networks— Part 15.7: Short-Range Optical Wireless Communications, IEEE Std 802.15.7-2018, pp.1-407 (23 Apr. 2019), and the like); Sigfox; Mobitex; 3GPP2 technologies (e.g., cdmaOne (2G), Code Division Multiple Access 2000 (CDMA 2000), and Evolution-Data Optimized or Evolution- Data Only (EV-DO); Push-to-talk (PTT), Mobile Telephone System (MTS) and variants thereof (e.g., Improved MTS (IMTS), Advanced MTS (AMTS), and the like); Personal Digital Cellular (PDC); Personal Handy-phone System (PHS), Cellular Digital Packet Data (CDPD); Cellular Digital Packet Data (CDPD); DataTAC; Digital Enhanced Cordless Telecommunications (DECT) and variants thereof (e.g., DECT Ultra Low Energy (DECT ULE), DECT-2020, DECT-5G, and the like); Ultra High Frequency (UHF) communication; Very High Frequency (VHF) communication; and / or any other suitable RAT or protocol. In addition to the aforementioned RATs / standards, any number of satellite uplink technologies may be used for purposes of the present disclosure including, for example, radios compliant with standards issued by the International Telecommunication Union (ITU), or the ETSI, among others. The examples provided herein are thus understood as being applicable to various other communication technologies, both existing and not yet formulated.

[0302] The term “Ethernet” at least in some examples refers to a term that is used to refer either to the IEEE 802.3 media access method or to the frame format discussed in [IEEE8023].

[0303] The term “V2X” at least in some examples refers to vehicle to vehicle (V2V), vehicle to infrastructure (V2I), infrastructure to vehicle (12 V), vehicle to network (V2N), and / or network to vehicle (N2V) communications and associated radio access technologies.

[0304] The term “channel” at least in some examples refers to any transmission medium, either tangible or intangible, which is used to communicate data or a data stream. The term “channel” may be synonymous with and / or equivalent to “communications channel,” “data communications channel,” “transmission channel,” “data transmission channel,” “access channel,” “data access channel,” “link,” “data link,” “carrier,” “radiofrequency carrier,” and / or any other like term denoting a pathway or medium through which data is communicated. Additionally, the term “link” at least in some examples refers to a connection between two devices through a RAT for the purpose of transmitting and receiving information.

[0305] The term “carrier” at least in some examples refers to a modulated waveform conveying one or more physical channels (e.g., 5G / NR, E-UTRA, UTRA, and / or GSM / EDGE physical channels). The term “carrier frequency” at least in some examples refers to the center frequency of a cell.

[0306] The term “bearer” at least in some examples refers to an information transmission path of defined capacity, delay, bit error rate, and / or the like. The term “radio bearer” at least in some examples refers to the service provided by Layer 2 (L2) for transfer of user data between user equipment (UE) and a radio access network (RAN). The term “radio access bearer” at least in some examples refers to the service that the access stratum provides to the non-access stratum for transfer of user data between a UE and a CN.

[0307] The terms “beamforming” and “beam steering” at least in some examples refer to a spatial filtering mechanism used at a transmitter (Tx) to improve the received signal power, signal-to- noise ratio (SNR), or some other signaling metric at an intended receiver (Rx). The term “beamformer” at least in some examples refers to a STA that transmits a physical layer PDU (PPDU) using a beamforming steering matrix. The term “beamforming steering matrix” at least in some examples refers to a matrix determined using knowledge of the channel between a Tx and an intended Rx that maps from space-time streams to transmit antennas with the goal of improving the signal power, SNR, and / or some other signaling metric at the intended Rx.

[0308] The term “subframe” at least in some examples at least in some examples refers to a time interval during which a signal is signaled. In some implementations, a subframe is equal to 1 millisecond (ms). The term “time slot” at least in some examples at least in some examples refers to an integer multiple of consecutive subframes. The term “superframe” at least in some examples at least in some examples refers to a time interval comprising two time slots.

[0309] The term “interoperability” at least in some examples refers to the ability of STAs utilizing one communication system or RAT to communicate with other STAs utilizing another communication system or RAT. The term “Coexistence” at least in some examples refers to sharing or allocating radiofrequency resources among STAs using either communication system or RAT.

[0310] The term “reliability” at least in some examples refers to the ability of a computer-related component (e.g., software, hardware, or network element / entity) to consistently perform a desired function and / or operate according to a specification. Reliability in the context of network communications (e.g., “network reliability”) at least in some examples refers to the ability of a network to carry out communication. The term “network reliability” at least in some examples refers to a probability or measure of delivering a specified amount of data from a source to a destination (or sink).

[0311] The term “local area network” or “LAN” at least in some examples refers to a network of devices, whether indoors or outdoors, covering a limited area or a relatively small geographic area (e.g., within a building or a campus). The term “wireless local area network”, “wireless LAN”, or “WLAN” at least in some examples refers to a LAN that involves wireless communications.

[0312] The term “wide area network” or “WAN” at least in some examples refers to a network of devices that extends over a relatively large geographic area (e.g., a telecommunications network). Additionally or alternatively, the term “wide area network” or “WAN” at least in some examples refers to a computer network spanning regions, countries, or even an entire planet.

[0313] The term “backbone network”, “backbone”, or “core network” at least in some examples refers to a computer network which interconnects networks, providing a path for the exchange of information between different subnetworks such as LANs or WANs.

[0314] The term “interworking” at least in some examples refers to the use of interconnected stations in a network for the exchange of data, by means of protocols operating over one or more underlying data transmission paths.

[0315] The term “flow” at least in some examples refers to a sequence of data and / or data units (e.g., datagrams, packets, or the like) from a source entity / element to a destination entity / element. Additionally or alternatively, the terms “flow” or “traffic flow” at least in some examples refer to an artificial and / or logical equivalent to a call, connection, or link. Additionally or alternatively, the terms “flow” or “traffic flow” at least in some examples refer to a sequence of packets sent from a particular source to a particular unicast, anycast, or multicast destination that the source desires to label as a flow; from an upper-layer viewpoint, a flow may include of all packets in a specific transport connection or a media stream, however, a flow is not necessarily 1:1 mapped to a transport connection. Additionally or alternatively, the terms “flow” or “traffic flow” at least in some examples refer to a set of data and / or data units (e.g., datagrams, packets, or the like) passing an observation point in a network during a certain time interval. Additionally or alternatively, the term “flow” at least in some examples refers to a user plane data link that is attached to an association. Examples are circuit switched phone call, voice over IP call, reception of an SMS, sending of a contact card, PDP context for internet access, demultiplexing a TV channel from a channel multiplex, calculation of position coordinates from geopositioning satellite signals, and the like. For purposes of the present disclosure, the terms “traffic flow”, “data flow”, “dataflow”, “packet flow”, “network flow”, and / or “flow” may be used interchangeably even though these terms at least in some examples refers to different concepts.

[0316] The term “dataflow” or “data flow” at least in some examples refers to the movement of data through a system including software elements, hardware elements, or a combination of both software and hardware elements. Additionally or alternatively, the term “dataflow” or “data flow” at least in some examples refers to a path taken by a set of data from an origination or source to destination that includes all nodes through which the set of data travels. The term “stream” or “data stream” at least in some examples refers to a sequence of data elements made available over time. Additionally or alternatively, the term “stream”, “data stream”, or “streaming” refers to a unidirectional flow of data. Additionally or alternatively, the term “stream”, “data stream”, or “streaming” refers to a manner of processing in which an object is not represented by a complete data structure of nodes occupying memory proportional to a size of that object, but are processed “on the fly” as a sequence of events. At least in some examples, functions that operate on a stream, which may produce another stream, are referred to as “filters,” and can be connected in pipelines, analogously to function composition; filters may operate on one item of a stream at a time, or may base an item of output on multiple input items, such as a moving average or the like.

[0317] The term “distributed computing” at least in some examples refers to computation resources that are geographically distributed within the vicinity of one or more localized networks’ terminations. The term “distributed computations” at least in some examples refers to a model in which components located on networked computers communicate and coordinate their actions by passing messages interacting with each other in order to achieve a common goal.

[0318] The term “service” at least in some examples refers to the provision of a discrete function within a system and / or environment. Additionally or alternatively, the term “service” at least in some examples refers to a functionality or a set of functionalities that can be reused. The term “microservice” at least in some examples refers to one or more processes that communicate over a network to fulfil a goal using technology-agnostic protocols (e.g., HTTP or the like). Additionally or alternatively, the term “microservice” at least in some examples refers to services that are relatively small in size, messaging-enabled, bounded by contexts, autonomously developed, independently deployable, decentralized, and / or built and released with automated processes. Additionally or alternatively, the term “microservice” at least in some examples refers to a self-contained piece of functionality with clear interfaces, and may implement a layered architecture through its own internal components. Additionally or alternatively, the term “microservice architecture” at least in some examples refers to a variant of the service-oriented architecture (SOA) structural style wherein applications are arranged as a collection of loosely-coupled services (e.g., fine-grained services) and may use lightweight protocols. The term “network service” at least in some examples refers to a composition of Network Function(s) and / or Network Service(s), defined by its functional and behavioural specification. The term “session” at least in some examples refers to a temporary and interactive information interchange between two or more communicating devices, two or more application instances, between a computer and user, and / or between any two or more entities or elements. Additionally or alternatively, the term “session” at least in some examples refers to a connectivity service or other service that provides or enables the exchange of data between two entities or elements. The term “network session” at least in some examples refers to a session between two or more communicating devices over a network. The term “web session” at least in some examples refers to session between two or more communicating devices over the Internet or some other network. The term “session identifier,” “session ID,” or “session token” at least in some examples refers to a piece of data that is used in network communications to identify a session and / or a series of message exchanges.

[0319] The term “quality” at least in some examples refers to a property, character, attribute, or feature of something as being affirmative or negative, and / or a degree of excellence of something. Additionally or alternatively, the term “quality” at least in some examples, in the context of data processing, refers to a state of qualitative and / or quantitative aspects of data, processes, and / or some other aspects of data processing systems.

[0320] The term “Quality of Service” or “QoS’ at least in some examples refers to a description or measurement of the overall performance of a service (e.g., telephony and / or cellular service, network service, wireless communication / connectivity service, cloud computing service, and the like). In some cases, the QoS may be described or measured from the perspective of the users of that service, and as such, QoS may be the collective effect of service performance that determine the degree of satisfaction of a user of that service. In other cases, QoS at least in some examples refers to traffic prioritization and resource reservation control mechanisms rather than the achieved perception of service quality. In these cases, QoS is the ability to provide different priorities to different applications, users, or flows, or to guarantee a certain level of performance to a flow. In either case, QoS is characterized by the combined aspects of performance factors applicable to one or more services such as, for example, service operability performance, service accessibility performance; service retain ability performance; service reliability performance, service integrity performance, and other factors specific to each service. Several related aspects of the service may be considered when quantifying the QoS, including packet loss rates, bit rates, throughput, transmission delay, availability, reliability, jitter, signal strength and / or quality measurements, and / or other measurements such as those discussed herein. Additionally or alternatively, the term “Quality of Service” or “QoS’ at least in some examples refers to mechanisms that provide traffic-forwarding treatment based on flow-specific traffic classification. In some examples, Additionally or alternatively, the term “Quality of Service” or “QoS’ at least in some examples is based on the definitions provided by SERIES E: OVERALL NETWORK OPERATION, TELEPHONE SERVICE, SERVICE OPERATION AND HUMAN FACTORS Quality of telecommunication services: concepts, models, objectives and dependability planning - Terms and definitions related to the quality of telecommunication services, Definitions of terms related to quality of service, ITU-T Recommendation E.800 (09 / 2008) (“[ITUE800]”). Additionally or alternatively, the term “Quality of Service” or “QoS ’ at least in some examples refers to the collective effect of service performances which determine the degree of satisfaction of a user of a service. In some examples, QoS is characterised by the combined aspects of performance factors applicable to all services, such as service operability performance; service accessibility performance; service retainability performance; service integrity performance; and / or other factors specific to each service. In some implementations, the term “Quality of Service” or “QoS” can be used interchangeably with the term “Class of Service” or “CoS”. The term “Class of Service” or “CoS’ at least in some examples refers to mechanisms that provide traffic-forwarding treatment based on non-flow- specific traffic classification. In some implementations, the term “Class of Service” or “CoS” can be used interchangeably with the term “Quality of Service” or “QoS”.

[0321] The term “QoS flow” at least in some examples refers to the finest granularity for QoS forwarding treatment in a network. The term “5G QoS flow’ at least in some examples refers to the finest granularity for QoS forwarding treatment in a 5G System (5GS). Traffic mapped to the same QoS flow (or 5G QoS flow) receive the same forwarding treatment. The term “QoS Identifier” at least in some examples refers to a scalar that is used as a reference to a specific QoS forwarding behavior (e.g., packet loss rate, packet delay budget, and the like) to be provided to a QoS flow. This may be implemented in an access network by referencing node specific parameters that control the QoS forwarding treatment (e.g., scheduling weights, admission thresholds, queue management thresholds, link layer protocol configuration, and the like). The term “QoS profile” at least in some examples refers to a QoS profile comprises a number of QoS parameters. A QoS profile is associated with each QoS session. The QoS profile defines the performance expectations placed on the bearer network. The term “QoS session” at least in some examples refers to a lifetime of PDP context. Additionally or alternatively, the term “QoS session” at least in some examples refers to a period between the opening and closing of a network connection whose characteristics are defined by a QoS profile. In some examples, multiple QoS sessions may exist, each with a different QoS profile. The term “data buffer” or “buffer” at least in some examples refers to a region of a physical or virtual memory used to temporarily store data, for example, when data is being moved from one storage location or memory space to another storage location or memory space, data being moved between processes within a computer, allowing for timing corrections made to a data stream, reordering received data packets, delaying the transmission of data packets, and the like. At least in some examples, a “data buffer” or “buffer” may implement a queue. The term “circular buffer”, “circular queue”, “cyclic buffer”, or “ring buffer” at least in some examples refers to a data structure that uses a single fixed-size buffer or other area of memory as if it were connected end-to-end or as if it has a circular or elliptical shape.

[0322] The term “piggyback” or “piggybacking”, in the context of computer communications and / or networking, refers to attaching, appending, or hooking a first data unit to a second data unit that is to be transmitted next or sometime before the first data unit; in this way, the first data unit gets a “free ride” in the data packet or frame carrying the second data unit.

[0323] The term “channel coding” at least in some examples refers to processes and / or techniques to add redundancy to messages or packets in order to make those messages or packets more robust against noise, channel interference, limited channel bandwidth, and / or other errors. For purposes of the present disclosure, the term “channel coding” can be used interchangeably with the terms “forward error correction” or “FEC”; “error correction coding”, “error correction code”, or “ECC”; and / or “network coding” or “NC”. The term “network coding” at least in some examples refers to processes and / or techniques in which transmitted data is encoded and decoded to improve network performance. The term “code rate” at least in some examples refers to the proportion of a data stream or flow that is useful or non-redundant (e.g., for a code rate of k / n, for every k bits of useful information, the (en)coder generates a total of n bits of data, of which n - k are redundant). The term “systematic code” at least in some examples refers to any error correction code in which the input data is embedded in the encoded output. The term “non-systematic code” at least in some examples refers to any error correction code in which the input data is not embedded in the encoded output. The term “interleaving” at least in some examples refers to a process to rearrange code symbols so as to spread bursts of errors over multiple codewords that can be corrected by ECCs. The term “code word” or “codeword” at least in some examples refers to an element of a code or protocol, which is assembled in accordance with specific rules of the code or protocol.

[0324] The term “network path” or “path” at least in some examples refers to a data communications feature of a communication system describing the sequence and identity of system components visited by one or more packets, where the components of the path may be either logical or physical. The term “network forwarding path” at least in some examples refers to an ordered list of connection points forming a chain of NFs and / or nodes, along with policies associated to the list.

[0325] The term “PDU Connectivity Service” at least in some examples refers to a service that provides exchange of protocol data units (PDUs) between a UE and a data network (DN). The term “PDU Session” at least in some examples refers to an association between a UE and a DN that provides a PDU connectivity service (see e.g., 3GPP TS 38.415 V17.0.0 (2022-04-06) (“[TS38415]”) and 3GPP TS 38.413 V17.3.0 (2023-01 -06) (“[TS38413]”)); a PDU Session type can be IPv4, IPv6, IPv4v6, Ethernet), Unstructured, or any other network / connection type, such as those discussed herein. The term “PDU Session Resource” at least in some examples refers to an NG-RAN interface (e.g., NG, Xn, and / or El interfaces) and radio resources provided to support a PDU Session. The term “multi-access PDU session” or “MA PDU Session” at least in some examples refers to a PDU Session that provides a PDU connectivity service, which can use one access network at a time or multiple access networks simultaneously.

[0326] The term “traffic shaping” at least in some examples refers to a bandwidth management technique that manages data transmission to comply with a desired traffic profile or class of service. Traffic shaping ensures sufficient network bandwidth for time- sensitive, critical applications using policy rules, data classification, queuing, QoS, and other techniques. The term “throttling” at least in some examples refers to the regulation of flows into or out of a network, or into or out of a specific device or element. The term “access traffic steering” or “traffic steering” at least in some examples refers to a procedure that selects an access network for a new data flow and transfers the traffic of one or more data flows over the selected access network. Access traffic steering is applicable between one 3GPP access and one non-3GPP access. The term “access traffic switching” or “traffic switching” at least in some examples refers to a procedure that moves some or all traffic of an ongoing data flow from at least one access network to at least one other access network in a way that maintains the continuity of the data flow. The term “access traffic splitting” or “traffic splitting” at least in some examples refers to a procedure that splits the traffic of at least one data flow across multiple access networks. When traffic splitting is applied to a data flow, some traffic of the data flow is transferred via at least one access channel, link, or path, and some other traffic of the same data flow is transferred via another access channel, link, or path.

[0327] The term “network address” at least in some examples refers to an identifier for a node or host in a computer network, and may be a unique identifier across a network and / or may be unique to a locally administered portion of the network. Examples of identifiers and / or network addresses can include am application identifier, Bluetooth hardware device address (BD_ADDR), a cellular network address (e.g., Absolute Radio-Frequency Channel Number (ARFCN), Access Point Name (APN), AMF name and / or AMF identifier (ID), AF- Service-Identifier, Cell Global Identifier (CGI) (e.g., NR CGI (NCGI), CGI NG-RAN, CGI EUTRA, and / or the like), Closed Access Group Identifier (CAG-ID), Edge Application Server (EAS) ID, Data Network Access Identifier (DNAI), Data Network Name (DNN), Evolved Cell Global Identifier (ECGI), EPS Bearer Identity (EBI), Equipment Identity Register (EIR) and / or 5G-EIR, Extended Unique Identifier (EUI), Group ID for Network Selection (GIN), Generic Public Subscription Identifier (GPSI), Globally Unique AMF Identifier (GUAMI), Globally Unique Temporary Identifier (GUTI) and / or 5G-GUTI, gNB Identifier (gNB ID), Global gNB ID, International Mobile Equipment Identity (IMEI), IMEI Type Allocation Code (IMEA / TAC), International Mobile Subscriber Identity (IMSI), IMSI software version (IMSISV), permanent equipment identifier (PEI), Local Area Data Network (LADN) DNN, Local NG-RAN Node Identifier, Mobile Subscriber Identification Number (MSIN), Mobile Subscriber / Station ISDN Number (MS1SDN), Network identifier (NID), Network Slice Instance (NSI) ID, Network Slice AS Group (NSAG), Permanent Equipment Identifier (PEI), Public Land Mobile Network (PLMN) identity (ID), Physical Cell Identifier (PCI), QoS Flow ID (QFI) and / or 5G QoS Identifier (5QI), RAN ID, Routing Indicator, Radio Network Temporary Identifier (RNTI) and variants thereof (e.g., any of those discussed in clause 8 of 3GPP TS 38.300 V17.5.0 (2023-06-30) (“[TS38300]”)), SMS Function (SMSF) ID, Standalone Non-Public Network (SNPN) ID, Single Network Slice Selection Assistance information (S-NSSAI), sidelink identities (e.g., Source Layer-2 ID, Destination Layer-2 ID, PC5 Link Identifier, and the like), Subscription Concealed Identifier (SUCI), Subscription Permanent Identifier (SUPI), Temporary Mobile Subscriber Identity (TMSI) and variants thereof, Tracking Area identity (TAI), UE Access Category and Identity, and / or other cellular network related identifiers), CAG-ID, drivers license number, Global Trade Item Number (GTIN) (e.g., Australian Product Number (APN), EPC, European Article Number (EAN), Universal Product Code (UPC), and the like), email address, Enterprise Application Server (EAS) ID, an endpoint address, an Electronic Product Code (EPC) as defined by the EPCglobal Tag Data Standard, Fully Qualified Domain Name (FQDN), flow ID and / or flow hash, hash value, index, internet protocol (IP) address in an IP network (e.g., IP version 4 (IPv4), IP version 6 (IPv6), and the like), an internet packet exchange (IPX) address, LAN ID, a MAC address, personal area network (PAN) ID, port number (e.g., TCP port number, UDP port number, and the like), price lookup code (PLC), product key, QUIC connection ID, RFID tag, sequence number, service set identifier (SSID) and variants thereof, screen name, serial number, stock keeping unit (SKU), socket address, social security number (SSN), telephone number (e.g., in a public switched telephone network (PTSN)), unique identifier (UID) (e.g., including globally UID, universally unique identifier (UUID) (e.g., as specified in ISO / IEC 11578:1996), and the like), a Universal Resource Locator (URL) and / or Universal Resource Identifier (URI), user name (e.g., ID for logging into a service provider platform, such as a social network and / or some other service), vehicle identification number (VIN), Virtual LAN (VLAN) ID, X.21 address, an X.25 address, Zigbee® ID, Zigbee® Device Network ID, and / or any other suitable network address and components thereof.

[0328] The term “universally unique identifier” or “UUID” at least in some examples refers to a number used to identify information in computer systems. In some examples, a UUID includes 128-bit numbers and / or are represented as 32 hexadecimal digits displayed in five groups separated by hyphens in the following format: “xxxxxxxx-xxxx-Mxxx-Nxxx-xxxxxxxxxxxx” where the four-bit M and the 1 to 3 bit N fields code the format of the UUID itself. Additionally or alternatively, the term “universally unique identifier” or “UUID” at least in some examples refers to a “globally unique identifier” and / or a “GUID”. The term “endpoint address” at least in some examples refers to an address used to determine the host / authority part of a target URI, where the target URI is used to access an NF service (e.g., to invoke service operations) of an NF service producer or for notifications to an NF service consumer.

[0329] The term “port” in the context of computer networks, at least in some examples refers to a communication endpoint, a virtual data connection between two or more entities, and / or a virtual point where network connections start and end. Additionally or alternatively, a “port” at least in some examples is associated with a specific process or service. Additionally or alternatively, the term “port” at least in some examples refers to a particular interface of the specified equipment (apparatus) with an electromagnetic environment (e.g., any connection point on an equipment intended for connection of cables to or from that equipment is considered as a port).

[0330] The term “subnetwork” or “subnet” at least in some examples refers to a logical subdivision of a network, such as an IP network. The practice of dividing a network into two or more networks is called “subnetting.”

[0331] The term “delay” at least in some examples refers to a time interval between two events. Additionally or alternatively, the term “delay” at least in some examples refers to a time interval between the propagation of a signal and its reception. The term “delay bound” at least in some examples refers to a predetermined or configured amount of acceptable delay. The term “per- packet delay bound” at least in some examples refers to a predetermined or configured amount of acceptable packet delay where packets that are not processed and / or transmitted within the delay bound are considered to be delivery failures and are discarded or dropped. The term “goodput” at least in some examples refers to a number of useful information bits delivered by the network to a certain destination per unit of time. The term “jitter” at least in some examples refers to a deviation from a predefined (“true”) periodicity of a presumably periodic signal in relation to a reference clock signal. The term “latency” at least in some examples refers to the amount of time it takes to transfer a first / initial data unit in a data burst from one point to another. Additionally or alternatively, the term “latency” at least in some examples refers to the delay experienced by a data unit (e.g., frame) in the course of its propagation between two points in a network, measured from the time that a known reference point in the frame passes the first point to the time that the reference point in the data unit passes the second point. The term “network delay” at least in some examples refers to the delay of an a data unit within a network (e.g., an IP packet within an IP network). The term “packet delay” at least in some examples refers to the time it takes to transfer any packet from one point to another. Additionally or alternatively, the term “packet delay” or “per packet delay” at least in some examples refers to the difference between a packet reception time and packet transmission time. Additionally or alternatively, the “packet delay” or “per packet delay” can be measured by subtracting the packet sending time from the packet receiving time where the transmitter and receiver are at least somewhat synchronized. The term “packet drop rate” at least in some examples refers to a share of packets that were not sent to the target due to high traffic load or traffic management and should be seen as a part of the packet loss rate. The term “packet loss rate” at least in some examples refers to a share of packets that could not be received by the target, including packets droped, packets lost in transmission and packets received in wrong format. The term “performance indicator” at least in some examples refers to performance data aggregated over a group of network functions (NFs), which is derived from performance measurements collected at the NFs that belong to the group, according to the aggregation method identified in a Performance Indicator definition. The term “physical rate” or “PHY rate” at least in some examples refers to a speed at which one or more bits are actually sent over a transmission medium. Additionally or alternatively, the term “physical rate” or “PHY rate” at least in some examples refers to a speed at which data can move across a wireless link between a transmitter and a receiver. The term “processing delay” at least in some examples refers to an amount of time taken to process a packet in a network node. The term “propagation delay” at least in some examples refers to amount of time it takes a signal’s header to travel from a sender to a receiver. The term “queuing delay” at least in some examples refers to an amount of time a job waits in a queue until that job can be executed. Additionally or alternatively, the term “queuing delay” at least in some examples refers to an amount of time a packet waits in a queue until it can be processed and / or transmitted. The term “throughput” or “network throughput” at least in some examples refers to a rate of production or the rate at which something is processed. Additionally or alternatively, the term “throughput” or “network throughput” at least in some examples refers to a rate of successful message (date) delivery over a communication channel. The term “transmission delay” at least in some examples refers to an amount of time needed (or necessary) to push a packet (or all bits of a packet) into a transmission medium.

[0332] The term “application” or “app” at least in some examples refers to a computer program designed to carry out a specific task other than one relating to the operation of the computer itself. Additionally or alternatively, term “application” or “app” at least in some examples refers to a complete and deployable package, environment to achieve a certain function in an operational environment.

[0333] The term “process” at least in some examples refers to an instance of a computer program that is being executed by one or more threads. In some implementations, a process may be made up of multiple threads of execution that execute instructions concurrently.

[0334] The term “algorithm” at least in some examples refers to an unambiguous specification of how to solve a problem or a class of problems by performing calculations, input / output operations, data processing, automated reasoning tasks, and / or the like.

[0335] The term “analytics” at least in some examples refers to the discovery, interpretation, and communication of meaningful patterns in data.

[0336] The term “application programming interface” or “API” at least in some examples refers to a set of subroutine definitions, communication protocols, and tools for building software. Additionally or alternatively, the term “application programming interface” or “API” at least in some examples refers to a set of clearly defined methods of communication among various components. In some examples, an API may be defined or otherwise used for a web-based system, operating system, database system, computer hardware, software library, and / or the like.

[0337] The terms “instantiate,” “instantiation,” and the like at least in some examples refers to the creation of an instance. In some examples, an “instance” also at least in some examples refers to a concrete occurrence of an object, which may occur, for example, during execution of program code.

[0338] The term “reference point” at least in some examples refers to a conceptual point at the conjunction of two non-overlapping functional groups, elements, or entities.

[0339] The term “reference” at least in some examples refers to data useable to locate other data and may be implemented a variety of ways (e.g., a pointer, an index, a handle, a key, an identifier, a hyperlink, and / or the like).

[0340] The term “use case” at least in some examples refers to a description of a system from a user's perspective. Use cases sometimes treat a system as a black box, and the interactions with the system, including system responses, are perceived as from outside the system. In some examples, use cases avoid technical jargon, preferring instead the language of the end user or domain expert. The term “user” at least in some examples refers to an abstract representation of any entity issuing commands, requests, and / or data to a compute node or system, and / or otherwise consumes or uses services. Additionally or alternative, the term “user” at least in some examples refers to an entity, not part of a 3GPP system, which uses 3GPP system services (e.g., a person using a 3GPP system mobile station as a portable telephone). The term “user profile” at least in some examples refers to a set of information used to provide a user with a consistent, personalised service environment, irrespective of the user's location or the terminal used (within the limitations of the terminal and the serving network).

[0341] The terms “configuration”, “policy”, “ruleset”, and / or “operational parameters”, at least in some examples refer to a machine-readable information object that contains instructions, conditions, parameters, and / or criteria that are relevant to a device, system, or other element / entity.

[0342] The term “data set” or “dataset” at least in some examples refers to a collection of data; a “data set” or “dataset” may be formed or arranged in any type of data structure. In some examples, one or more characteristics can define or influence the structure and / or properties of a dataset such as the number and types of attributes and / or variables, and various statistical measures (e.g., standard deviation, kurtosis, and / or the like). The term “data structure” at least in some examples refers to a data organization, management, and / or storage format. Additionally or alternatively, the term “data structure” at least in some examples refers to a collection of data values, the relationships among those data values, and / or the functions, operations, tasks, and the like, that can be applied to the data. Examples of data structures include primitives (e.g., Boolean, character, floating-point numbers, fixed-point numbers, integers, reference or pointers, enumerated type, and / or the like), composites (e.g., arrays, records, strings, union, tagged union, and / or the like), abstract data types (e.g., data container, list, tuple, associative array, map, dictionary, set (or dataset), multiset or bag, stack, queue, graph (e.g., tree, heap, and the like), and / or the like), routing table, symbol table, quad-edge, blockchain, purely-functional data structures (e.g., stack, queue, (multi)set, random access list, hash consing, zipper data structure, and / or the like).

[0343] The term “association” at least in some examples refers to a model of relationships between Managed Objects. Associations can be implemented in several ways, such as: (1) name bindings, (2) reference attributes, and (3) association objects.

[0344] The term “information element” or “IE” at least in some examples refers to a structural element containing one or more fields. Additionally or alternatively, the term “information element” or “IE” at least in some examples refers to a field or set of fields defined in a standard or specification that is used to convey data and / or protocol information.

[0345] The term “field” at least in some examples refers to individual contents of an information element, or a data element that contains content. The term “data frame”, “data field”, or “DF” at least in some examples refers to a data type that contains more than one data element in a predefined order.

[0346] The term “data element” or “DE” at least in some examples refers to a data type that contains one single data. Additionally or alternatively, the term “data element” at least in some examples refers to an atomic state of a particular object with at least one specific property at a certain point in time, and may include one or more of a data element name or identifier, a data element definition, one or more representation terms, enumerated values or codes (e.g., metadata), and / or a list of synonyms to data elements in other metadata registries. Additionally or alternatively, a “data element” at least in some examples refers to a data type that contains one single data. Data elements may store data, which may be referred to as the data element’s content (or “content items”). In some examples, content items may include text content, attributes, properties, and / or other elements referred to as “child elements.” Additionally or alternatively, data elements may include zero or more properties and / or zero or more attributes, each of which may be defined as database objects (e.g., fields, records, and the like), object instances, and / or other data elements.

[0347] The term “attribute” at least in some examples refers to a markup construct including a name-value pair that exists within a start tag or empty element tag. Attributes contain data related to its element and / or control the element’ s behavior.

[0348] The term “Information Object Class” or “IOC” at least in some examples refers to a representation of the management aspect of a network resource. Additionally or alternatively, the term “Information Object Class” or “IOC” at least in some examples refers to a description of the information that can be passed / used in management interfaces. Their representations are technology agnostic software objects. IOC has attributes that represents the various properties of the class of objects. Furthermore, IOC can support operations providing network management services invocable on demand for that class of objects. An IOC may support notifications that report event occurrences relevant for that class of objects. It is modelled using the stereotype "Class" in the UML meta-model.

[0349] The term “Managed Object” or “MO” at least in some examples refers to an instance of a Managed Object Class (MOC) representing the management aspects of a network resource. Its representation is a technology specific software object. In some examples, an MO is called an “MO instance” or “MOI”. Additionally or alternatively, the term “Managed Object” or “MO” at least in some examples refers to a class of technology specific software objects. In some examples, an MOC is the same as an IOC except that the former is defined in technology specific terms and the latter is defined in technology agnostic terms. MOCs are used / defined in SS level specifications. In some examples, IOCS are used / defined in IS level specifications.

[0350] The term “Management Information Base” or “M1B” at least in some examples refers to an instance of an NRM and has some values on the defined attributes and associations specific for that instance. In some examples, an MIB includes a name space (describing the MO containment hierarchy in the MIB through Distinguished Names), a number of MOs with their attributes, and a number of associations between the MOs.

[0351] The term “name space” at least in some examples refers to a collection of names. In some examples, a name space is restricted to a hierarchical containment structure, including its simplest form - the one-level, flat name space. In some examples, all MOs in an MIB are included in the corresponding name space and the MIB / name space shall only support a strict hierarchical containment structure (with one root object). An MO that contains another is said to be the superior (parent); the contained MO is referred to as the subordinate (child). The parent of all MOs in a single name space is called a Local Root. The ultimate parent of all MOs of all managed systems is called the Global Root.

[0352] The term “network resource” at least in some examples refers to a discrete entity represented by an IOC for the purpose of network and service management. In some examples, a network resource may represent intelligence, information, hardware and / or software of a telecommunication network. The term “Network Resource Model” or “NRM” at least in some examples refers to a collection of IOCS, inclusive of their associations, attributes and operations, representing a set of network resources under management.

[0353] The term “self-organizing network” or “SON” at least in some examples refers to a type of network architecture or system that is designed to automate the planning, configuration, optimization, and / or healing processes of a wireless network with little or no direct human intervention (see e.g., 3GPP TS 28.313 V18.2.0 (2023-06-22), 3GPP TS 28.627 vl7.0.0 (2022- 03-31), 3GPP TS 28.628 v 17.0.0 (2022-03-31 ), 3GPP TS 32.500 vl 7.0.0 (2022-04-04), 3GPP TS 32.522 vl 1.7.0 (2013-09-20), 3GPP TS 32.541 vl7.0.0 (2022-04-05), and 3GPP TS 32.551 v 17.0.0 (2022-04-05)).

[0354] The term “performance indicator” at least in some examples refers to performance data aggregated over a group of NFs that is derived from performance measurements collected at the NFs that belong to the group. In some examples, performance indicators are derived, collected or aggregated according to an aggregation method identified in a performance indicator definition.

[0355] The term “datagram” at least in some examples at least in some examples refers to a basic transfer unit associated with a packet-switched network; a datagram may be structured to have header and payload sections. The term “datagram” at least in some examples may be synonymous with any of the following terms, even though they may refer to different aspects: “data unit”, a “protocol data unit” or “PDU”, a “service data unit” or “SDU”, “frame”, “packet”, a “network packet”, “segment”, “block”, “cell”, “chunk”, “Type Length Value” or “TLV”, and / or the like. Examples of datagrams, network packets, and the like, include internet protocol (IP) packet, Internet Control Message Protocol (ICMP) packet, UDP packet, TCP packet, SCTP packet, ICMP packet, Ethernet frame, RRC messages / packets, SDAP PDU, SDAP SDU, PDCP PDU, PDCP SDU, MAC PDU, MAC SDU, BAP PDU. BAP SDU, RLC PDU, REC SDU, WiFi frames as discussed in a [IEEE802] protocol / standard (e.g., [IEEE80211] or the like), Type Length Value (TLV), and / or other like data structures. The term “packet” at least in some examples refers to an information unit identified by a label at layer 3 of the OSI reference model. In some examples, a “packet” may also be referred to as a “network protocol data unit” or “NPDU”. The term “protocol data unit” at least in some examples refers to a unit of data specified in an (N)-protocol layer and consisting of (N)-protocol control information and possibly (N)-user data.

[0356] The term “type length value”, “tag length value”, or “TLV” at least in some examples refers to an encoding scheme used for informational elements in a protocol; TLVs are sometimes used to encode additional or optional information elements in a protocol. In some examples, a TLV-encoded data stream contains code related to the type of value, the length of the value, and the value itself. In some examples, the type in a TLV includes a binary and / or alphanumeric code, which indicates the kind of field that this part of the message represents; the length in a TLV includes a size of the value field (e.g., in bytes); and the value in a TLV includes a variable-sized series of bytes which contains data for this part of the message.

[0357] The term “authorization” at least in some examples refers to a prescription that a particular behavior shall not be prevented.

[0358] The term “authentication” at least in some embodiments refers to a process of proving or verifying an identity. Additionally or alternatively, the term “authentication” at least in some embodiments refers to a mechanism by which a computer system checks or verifies that a user or entity is really the user or entity being claimed. Examples of the authentication and / or authorization techniques include using API keys, basic access authentication (“Basic Auth”), Open Authorization (OAuth), hash-based message authentication codes (HMAC), Kerberos protocol, OpenlD, WeblD, and / or other authentication and / or authorization techniques.

[0359] The term “cryptographic mechanism” at least in some examples refers to any cryptographic protocol and / or cryptographic algorithm. Examples of cryptographic mechanisms include a cryptographic hash algorithm, such as a function in the Secure Hash Algorithm (SHA) 2 set of cryptographic hash algorithms (e.g., SHA-226, SHA-256, SHA-512, and the like), SHA 3, and so forth, or any type of keyed or unkeyed cryptographic hash function and / or any other function discussed herein; an elliptic curve cryptographic (ECC) algorithm (e.g., Elliptic Curve cryptography Key Agreement algorithm (ECKA) algorithm, Elliptic Curve cryptography Digital Signature Algorithm (ECDSA), Lenstra elliptic-curve factorization or elliptic-curve factorization method (ECM), Menezes-Qu- Vans tone (MQV) or elliptic curve MQV (ECMQV), Elliptic Curve Diffie-Hellman (ECDH) key agreement, Elliptic Curve Integrated Encryption Scheme (ECIES) or Elliptic Curve Augmented Encryption Scheme, Edwards-curve Digital Signature Algorithm (EdDSA), and / or the like); Rivest-Shamir- Adleman (RSA) cryptography; Merkle signature scheme, advanced encryption system (AES) algorithm; a triple data encryption algorithm (3DES); Quantum cryptography algorithms; and / or the like. Additionally or alternatively, the term “cryptographic protocol” at least in some examples refers to a sequence of steps precisely specifying the actions required of two or more entities to achieve specific security objectives (e.g., cryptographic protocol for key agreement). Additionally or alternatively, the term “cryptographic algorithm” at least in some examples refers to an algorithm specifying the steps followed by a single entity to achieve specific security objectives (e.g., cryptographic algorithm for symmetric key encryption).

[0360] The term “cryptographic hash function”, “hash function”, or “hash”) at least in some examples refers to a mathematical algorithm that maps data of arbitrary size (sometimes referred to as a “message”) to a bit array of a fixed size (sometimes referred to as a "hash value", “hash”, or “message digest”). A cryptographic hash function is usually a one-way function, which is a function that is practically infeasible to invert.

[0361] The term “cryptographic key” or “key”in cryptography at least in some examples refers to a piece of information, usually a string of numbers or letters that are stored in a file, which, when processed through a cryptographic algorithm can encode or decode cryptographic data. The term “symmetric-key algorithm” at least in some examples refers to a cryptographic algorithm that uses the same cryptographic key for both the encryption of plaintext and the decryption of ciphertext; the keys may be identical, or there may be a simple transformation to go between the two keys.

[0362] The term “encryption” at least in some examples refers to a process of encoding information wherein the original representation of information (referred to as “plaintext”) into an alternative form (referred to as “ciphertext”). In some examples, an encryption scheme includes use of a pseudo-random encryption key generated by a cryptographic mechanism or some other algorithm to generate an encryption key, which can be used to encrypt and / or decrypt the plaintext.

[0363] The term “artificial intelligence” or “Al” at least in some examples refers to any intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Additionally or alternatively, the term “artificial intelligence” or “Al” at least in some examples refers to the study of “intelligent agents” and / or any device that perceives its environment and takes actions that maximize its chance of successfully achieving a goal.

[0364] The terms “artificial neural network”, “neural network”, or “NN” refer to an ML technique comprising a collection of connected artificial neurons or nodes that (loosely) model neurons in a biological brain that can transmit signals to other arterial neurons or nodes, where connections (or edges) between the artificial neurons or nodes are (loosely) modeled on synapses of a biological brain. The artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. The artificial neurons can be aggregated or grouped into one or more layers where different layers may perform different transformations on their inputs. Signals travel from the first layer (the input layer), to the last layer (the output layer), possibly after traversing the layers multiple times. Examples of NNs include deep NN, feed forward NN (FFN), deep FNN (DFF), convolutional NN (CNN), deep CNN (DCN), deconvolutional NN (DNN), a deep belief NN, a perception NN, recurrent NN (RNN) (e.g., including Long Short Term Memory (LSTM) algorithm, gated recurrent unit (GRU), echo state network (ESN), and the like), spiking NN (SNN), deep stacking network (DSN), Markov chain, perception NN, generative adversarial network (GAN), transformers, stochastic NNs (e.g., Bayesian Network (BN), Bayesian belief network (BBN), a Bayesian NN (BNN), Deep BNN (DBNN), Dynamic BN (DBN), probabilistic graphical model (PGM), Boltzmann machine, restricted Boltzmann machine (RBM), Hopfield network or Hopfield NN, convolutional deep belief network (CDBN), and the like), Linear Dynamical System (LDS), Switching LDS (SLDS), Optical NNs (ONNs), an NN for reinforcement learning (RL) and / or deep RL (DRL), attention and / or self-attention mechanisms, and / or the like. NNs are usually used for supervised learning, but can be used for unsupervised learning and / or RL.

[0365] The term “mathematical model” at least in some examples refer to a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs including governing equations, assumptions, and constraints. The term “statistical model” at least in some examples refers to a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data and / or similar data from a population; in some examples, a “statistical model” represents a data-generating process.

[0366] The term “machine learning” or “ML” at least in some examples refers to the use of computer systems to optimize a performance criterion using example (training) data and / or past experience. ML involves using algorithms to perform specific task(s) without using explicit instructions to perform the specific task(s), and / or relying on patterns, predictions, and / or inferences. ML uses statistics to build ML model(s) (also referred to as “models”) in order to make predictions or decisions based on sample data (e.g., training data).

[0367] The term “machine learning model” or “ML model” at least in some examples refers to an application, program, process, algorithm, and / or function that is capable of making predictions, inferences, or decisions based on an input data set and / or is capable of detecting patterns based on an input data set. In some examples, a “machine learning model” or “ML model” is trained on a training data to detect patterns and / or make predictions, inferences, and / or decisions. In some examples, a “machine learning model” or “ML model” is based on a mathematical and / or statistical model. For purposes of the present disclosure, the terms “ML model”, “Al model”, “AI / ML model”, and the like may be used interchangeably.

[0368] The term “machine learning algorithm” or “ML algorithm” at least in some examples refers to an application, program, process, algorithm, and / or function that builds or estimates an ML model based on sample data or training data. Additionally or alternatively, the term “machine learning algorithm” or “ML algorithm” at least in some examples refers to a program, process, algorithm, and / or function that learns from experience w.r.t some task(s) and some performance measure(s) / metric(s), and an ML model is an object or data structure created after an ML algorithm is trained with training data. For purposes of the present disclosure, the terms “ML algorithm”, “Al algorithm”, “AI / ML algorithm”, and the like may be used interchangeably. Additionally, although the term “ML algorithm” may refer to different concepts than the term “ML model,” these terms may be used interchangeably for the purposes of the present disclosure.

[0369] The term “machine learning application” or “ML application” at least in some examples refers to an application, program, process, algorithm, and / or function that contains some AI / ML model(s) and application-level descriptions. Additionally or alternatively, the term “machine learning application” or “ML application” at least in some examples refers to a complete and deployable application and / or package that includes at least one ML model and / or other data capable of achieving a certain function and / or performing a set of actions or tasks in an operational environment. For purposes of the present disclosure, the terms “ML application”, “Al application”, “AI / ML application”, and the like may be used interchangeably.

[0370] The term “machine learning training”, “ML training”, or “MLT” at least in some examples refers to capabilities and associated end-to-end (e2e) processes to enable an ML training function to perform ML model training (e.g., as defined herein). In some examples, ML training capabilities include interaction with other parties / entities to collect and / or format the data required for ML model training.

[0371] The term “machine learning entity” or “ML entity” at least in some examples refers to an entity that is either an ML model or contains an ML model and ML model-related metadata that can be managed as a single composite entity. In some examples, metadata may include, for example, the applicable runtime context for the ML model. The term “Al decision entity”, “machine learning decision entity”, or “ML decision entity” at least in some examples refers to an entity that applies a non- Al and / or non- ML based logic for making decisions that can be managed as a single composite entity. The term “machine learning model training” or “ML model training” at least in some examples refers to capabilities of an ML training function to take data, run the data through an ML model, derive associated loss, optimization, and / or objective / goal, and adjust the parameterization of the ML model based on the computed loss, optimization, and / or objective / goal.

[0372] The term “machine learning training function”, “ML training function”, or “MLT function” at least in some examples refers to a function with MLT capabilities.

[0373] The term “AI / ML inference function” or “ML inference function” at least in some examples refers to a function (or set of functions) that employs an ML model and / or Al decision entity to conduct inference. Additionally or alternatively, the term “AI / ML inference function” or “ML inference function” at least in some examples refers to an inference framework used to run a compiled model in the inference host. In some examples, an “AI / ML inference function” or “ML inference function” may also be referred to an “model inference engine”, “ML inference engine”, or “inference engine”.

[0374] The term “machine learning workflow” or “ML workflow” at least in some examples refers to a process including data collection and preparation, AI / ML model building / generation; ML model training and testing; ML model deployment, ML model execution, ML model validation and / or verification; continuous, periodic and / or asynchronous ML model monitoring; ML model tuning, learning, and / or retraining. In some examples, the ML model monitoring includes self- monitoring or autonomous monitoring). In some examples, the ML model tuning, learning, and / or retraining includes self-tuning (or autonomous tuning), self-learning (or autonomous learning), and / or self-retraining (or autonomous retraining). The term “machine learning lifecycle” or “ML lifecycle” at least in some examples refers to process(es) of planning and / or managing the development, deployment, instantiation, and / or termination of an ML model and / or individual ML model components.

[0375] The term “instrumentation” at least in some examples refers to measuring instruments used for indicating, measuring, and / or recording physical quantities and / or physical events. Additionally or alternatively, the term “instrumentation” at least in some examples refers to the measure of performance (e.g., of SW and / or HW (sub)systems) in order to diagnose errors and / or to write trace information. The term “trace” or “tracing” at least in some examples refers to logging or otherwise recording information about a program's execution and / or information about the operation of a component, subsystem, device, system, and / or other entity; in some examples, “tracing” is used for debugging and / or analysis purposes. The term “telemetry” at least in some examples refers to the in situ collection of measurements, metrics, or other data (often referred to as “telemetry data” or the like) and their conveyance to another device or equipment. Additionally or alternatively, the term “telemetry” at least in some examples refers to the automatic recording and transmission of data from a remote or inaccessible source to a system for monitoring and / or analysis. The term “telemeter” at least in some examples refers to a device used in telemetry, and at least in some examples, includes sensor(s), a communication path, and a control device.

[0376] The term “telemetry data” at least in some examples refers to the measurements, metrics, or other data collected via instrumentation and / or collected by a telemeter, a telemetry system, and / or telemetry pipeline. Examples of telemetry data can include system-based metrics such as for example, assists (e.g., floating point (FP) assists, MS assists, and the like), available core time, average bandwidth (BW), core frequency, core usage, frame time, latency, logical core utilization, physical core utilization, effective CPU utilization, effective physical core utilization, effective time, elapsed time, execution stalls, task time, back-end bound, memory BW, contested accesses (e.g., intra-compute tile, intra-core, and / or the like), cache metrics / measurements for individual cache devices / elements (e.g., cache hits, cache misses, cache hit rate, cache bound, stall cycles, cache pressure, and the like), pressure metrics (e.g., memory pressure, cache pressure, register pressure, and the like), translation lookaside buffer (TLB) overhead (e.g., average miss penalty, memory accesses per miss, and so forth), input / output TLB (IOTLB) overhead, first-level TLB (UTLB) overhead, port utilization for individual ports, BACLEARS (e.g., fraction of cycles lost due to the Branch Target Buffer (BTB) prediction corrected by a later branch predictor), bad speculation (e.g., cancelled pipeline slots, back-end bound pipeline slots), FP metrics (e.g., FP arithmetic, FP assists, FP scalars, FP vector, FP x87, and the like), microarchitecture usage, microcode sequencer (MS) metrics, GPU metrics, OpenCL™ kernel analysis metrics, energy analysis metrics, user interface metrics, and / or any other metrics such as those discussed herein and / or those discussed in Intel® VTune™ Profiler User Guide, Intel Corp., version 2023.1 (31 Mar. 2023) (“[VTune]”). Additionally or alternatively, “telemetry data” can include performance measurements (see e.g., [TS28552]), key performance indicators (KPIs) (see e.g., [TS28554]), performance threshold monitoring events (see e.g., [TS28532]), and / or fault supervision events (see e.g., [TS28532]). Additionally or alternatively, “telemetry data” can include any of the measurements / metrics discussed herein; network identifiers (IDs), session IDs, application instance IDs, and / or the like (including any of those discussed herein); and / or any other type of data such as any of those discussed herein. The term “telemetry pipeline” at least in some examples refers to a set of elements / entities / components in a telemetry system through which telemetry data flows, is routed, or otherwise passes through the telemetry system. Additionally or alternatively, the term “telemetry pipeline” at least in some examples refers to a system, mechanism, and / or set of elements / entities / components that takes collected data from an agent and leads to the generation of insights via analytics. Examples of entities / elements / components of a telemetry pipeline include a collector or collection agent, analytics function, data upload and transport (e.g., to the cloud or the like), data ingestion (e.g., Extract Transform and Load (ETL)), storage, and analysis functions.

[0377] The term “telemetry system” at least in some examples refers to a set of physical and / or virtual components that interconnect to provide telemetry services and / or to provide for the collection, communication, and analysis of data

[0378] Although many of the previous examples are provided with use of specific cellular / mobile network terminology, including with the use of 4G / 5G 3GPP network components (or expected terahertz-based 6G / 6G+ technologies), it will be understood these examples may be applied to many other deployments of wide area and local wireless networks, as well as the integration of wired networks (including optical networks and associated fibers, transceivers, and / or the like). Furthermore, various standards (e.g, 3GPP, ETSI, and / or the like) may define various message formats, PDUs, containers, frames, and / or the like, as comprising a sequence of optional or mandatory data elements (DEs), data frames (DFs), information elements (IES), and / or the like. However, it should be understood that the requirements of any particular standard should not limit the examples discussed herein, and as such, any combination of containers, frames, DFs, DEs, IEs, values, actions, and / or features are possible in various examples, including any combination of containers, DFs, DEs, values, actions, and / or features that are strictly required to be followed in order to conform to such standards or any combination of containers, frames, DFs, DEs, IEs, values, actions, and / or features strongly recommended and / or used with or in the presence / absence of optional elements.

[0379] Aspects of the inventive subject matter may be referred to herein, individually and / or collectively, merely for convenience and without intending to voluntarily limit the scope of this application to any single aspect or inventive concept if more than one is in fact disclosed. Thus, although specific aspects have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific aspects shown. This disclosure is intended to cover any and all adaptations or variations of various aspects. Combinations of the above aspects and other aspects not specifically described herein will be apparent to those of skill in the art upon reviewing the above description.

Claims

CLAIMSWhat is claimed is:

1. An apparatus for a user equipment (UE) in a wireless communication network, configured to manage extended reality (XR) awareness comprising: a processor configured to: initiate transmission of a UE Assistance Information message to provide uplink traffic information; set a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; set a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determine if XR awareness information is available; and set the XR Awareness to a latest known value; and a memory to store the PDU session ID.

2. The apparatus of claim 1 , wherein the UE Assistance Information message is initiated based on configuration or change in uplink traffic information.

3. The apparatus of claim 1, wherein the PDU Session ID is dynamically updated based on active PDU sessions.

4. The apparatus of claim 1, wherein the XR awareness information is defined to indicate an awareness based on whether the UE is able to identify one or more PDU sets.

5. The apparatus of claim 1 , wherein the XR awareness information is defined to indicate an awareness based on whether the UE is able to identify a PDU Set Importance (PSI).

6. The apparatus of claim 1 , wherein the QFI is updated for each QoS flow to reflect current traffic conditions.

7. The apparatus of claim 1 , wherein the XR awareness information is set if it has not been provided since configuration or if it has changed since the last transmission.

8. The apparatus of claim 1 , wherein the transmission of the UE Assistance Information message is triggered by a change in XR awareness status.

9. The apparatus of any one of claims 1-8, wherein the UE Assistance Information message includes jitter range or burst arrival time.

10. A computer-readable medium storing computer-executable instructions which when executed by one or more processors result in performing operations comprising: initiating transmission of a UE Assistance Information message to provide uplink traffic information; setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; setting a quality of service (QoS) Flow Identifier (QF1) to the value of the QFI for each QoS flow within the PDU session; determining if XR awareness information is available; and setting the XR Awareness to a latest known value.1 1. The computer-readable medium of claim 10, wherein the UE Assistance Information message is initiated based on configuration or change in uplink traffic information.

12. The computer-readable medium of claim 10, wherein the PDU Session ID is dynamically updated based on active PDU sessions.

13. The computer-readable medium of claim 10, wherein the XR awareness information is defined to indicate an awareness based on whether the UE is able to identify one or more PDU sets.

14. The computer-readable medium of claim 10, wherein the XR awareness information is defined to indicate an awareness based on whether the UE is able to identify a PDU Set Importance (PSI).

15. The computer-readable medium of claim 10, wherein the QFI is updated for each QoS flow to reflect current traffic conditions.

16. The computer-readable medium of claim 10, wherein the XR awareness information is set if it has not been provided since configuration or if it has changed since the last transmission.

17. The computer-readable medium of claim 10, wherein the transmission of the UE Assistance Information message is triggered by a change in XR awareness status.

18. The computer-readable medium of any one of claims 10-17, wherein the UE Assistance Information message includes jitter range or burst arrival time.

19. A method comprising: initiating transmission of a UE Assistance Information message to provide uplink traffic information; setting a protocol data unit (PDU) Session identification (ID) to a value of the PDU session ID for each PDU session; setting a quality of service (QoS) Flow Identifier (QFI) to the value of the QFI for each QoS flow within the PDU session; determining if XR awareness information is available; and setting the XR Awareness to a latest known value.

20. The method of claim 19, wherein the UE Assistance Information message is initiated based on configuration or change in uplink traffic information.

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