Network analytics for navigation routes sustaining a quality of service in a wireless communication system

Abstract

Various aspects of the present disclosure relate to a consumer entity for wireless communication. The consumer entity may be configured to, capable of, or operable to transmit, to a first network entity, a first request for predictive analytics for maximizing sustainability of a Quality of Service (QoS) flow associated with one or more QoS parameters in an area of interest; and receive, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing sustainability of the QoS flow in the area of interest. The present disclosure also relates to a first network entity and a UE.

Description

NETWORK ANALYTICS FOR NAVIGATION ROUTES SUSTAINING A QUALITY OF SERVICE IN A WIRELESS COMMUNICATION SYSTEMTECHNICAL FIELD

[0001] The present disclosure relates generally to wireless communication, including the implementation of network analytics for navigation routes sustaining a Quality of Service (QoS) in a wireless communication system.BACKGROUND

[0002] A wireless communications system may include one or multiple network communication devices, which may be otherwise known as network equipment (NE), supporting wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE), or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers, or the like). Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G)).SUMMARY

[0003] An article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a,” “at least one,” “one or more,” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of’ or “one or more of’ or “one or both of’) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an examplestep that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on. Further, as used herein, including in the claims, a “set” may include one or more elements.

[0004] In wireless communication systems, for instance a 5G network, a certain QoS may be required for an application. The QoS may be associated with a QoS flow having one or more QoS parameters. By way of example, a UE may be required to transmit realtime video or telemetry. This may be because the UE (e.g., an emergency vehicle) is associated with emergency services transmitting real-time video or telemetry to a control centre. A guaranteed bit rate (GBR), as an example of a QoS parameter, may be required for the QoS flow, with, for instance, a low-latency, to enable and sustain (e.g., maintain) reliable communications. The QoS may be required to be sustained (e.g., maintained) whether the UE is stationary (e.g., static, fixed) or is mobile (i.e., dynamic, traveling along a navigation route between a first location and a second location).

[0005] A consumer entity for wireless communication is described. The consumer entity may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the consumer entity may include at least one memory, and at least one processor coupled with the at least one memory and configured to cause the consumer entity to: transmit, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and receive, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0006] A method performed or performable by the consumer entity is described herein. The method may comprise: transmitting, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and receiving, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics compriseat least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0007] A first network entity for wireless communication is described. The first network entity may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the first network entity may comprise at least one memory; and at least one processor coupled with the at least one memory and configured to cause the first network entity to: receive, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generate at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmit, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0008] A method performed or performable by the first network entity is described. The method may comprise: receiving, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generating at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmitting, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0009] A UE for wireless communication is described. The UE may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the UE may comprise at least one memory and at least one processor coupled with the at least one memory and configured to cause the UE to: transmit, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and receive, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0010] A method performed or performable by the UE is described. The method may comprise: transmitting, to a consumer entity, a second request for a navigation route formaximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and receiving, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0011] A processor for wireless communication is described. The processor may be configured to, capable of, or operable to perform one or more operations as described herein. For example, the processor may comprise at least one controller coupled with at least one memory and configured to cause the processor to: output a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and input a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0012] A method performed or performable by the processor is described. The method may comprise: outputting a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and inputting a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 illustrates an example of a wireless communications system in accordance with aspects of the present disclosure.

[0014] Figure 2A illustrates an example of a navigation route in accordance with aspects of the present disclosure.

[0015] Figure 2B illustrates an example of a process flow that supports determining a navigation route in accordance with aspects of the present disclosure.

[0016] Figure 3A illustrates an example of a navigation route in accordance with aspects of the present disclosure.

[0017] Figure 3B illustrates an example of a process flow that supports determining a navigation route in accordance with aspects of the present disclosure.

[0018] Figure 3C illustrates an example diagram of waypoints in accordance with aspects of the present disclosure.

[0019] Figure 4A illustrates an example of a navigation route in accordance with aspects of the present disclosure.

[0020] Figure 4B illustrates an example of a process flow that supports determining a navigation route in accordance with aspects of the present disclosure.

[0021] Figure 5 illustrates an example of a UE in accordance with aspects of the present disclosure.

[0022] Figure 6 illustrates an example of a processor in accordance with aspects of the present disclosure.

[0023] Figure 7 illustrates an example of a NE in accordance with aspects of the present disclosure.

[0024] Figure 8 illustrates a flowchart of a method performed by a NE in accordance with aspects of the present disclosure.

[0025] Figure 9 illustrates a flowchart of a method performed by a NE in accordance with aspects of the present disclosure.

[0026] Figure 10 illustrates a flowchart of a method performed by a UE in accordance with aspects of the present disclosure.

[0027] Figure 11 illustrates a flowchart of a method performed by a processor in accordance with aspects of the present disclosure.DETAILED DESCRIPTION

[0028] In a wireless communication system, a UE may be stationary (e.g., static) or non-stationary (i.e., dynamic, mobile). A stationary UE may refer to a UE that remains in a fixed location. A non-stationary (i.e., dynamic) UE may refer to a UE that may be mobile (e.g., moving) and traversing different network areas (e.g., coverage areas), for example, along a route (also referred to herein as a navigation route or navigation path) between a first location and a second location. By way of example, a UE may be a vehicle (such as, a car, motorcycle, truck, bicycle, helicopter, drone, plane, etc.). The UE may be navigating (e.g., traveling, traversing) from the first location to the second location, wherein the second location is geographically remote to (e.g., distant from) the first location. Some navigation systems (such as navigation or mapping applications, software or servers) determine routes (e.g., paths) between locations based on parameters, such as travel time and traffic (i.e., road traffic and conditions). These navigation systems, however, do not consider any sort of sustainability of a QoS along the determined route.

[0029] As a UE navigates along a route, the UE may, in some cases, traverse one or more network areas of the wireless communication system, for which network congestion may be high (e.g., greater than or equal to a threshold). This congestion may result in abnormal release of QoS flows. This tends to impact one or more QoS parameters associated with the QoS flow, such as a bit rate and / or latency. This can be particularly problematic where the QoS parameters are associated with real-time data communications (e.g., transmission and / or receipt). For example, real-time video, audio, or telemetry data may be required to be communicated with the one or more QoS parameters sustained along the navigation route. This may be particularly applicable for emergency vehicles.

[0030] Some wireless communication systems, such as 5G networks can support a network data analytics function (NWDAF) that can provide network analytics. The network analytics may be predictive analytics derived using one or more models such as artificial intelligence (Al) or machine learning (ML) models. However, the analytics that can be provided by the NWDAF might not be currently used for the purpose of deriving navigation routes for satisfying (e.g., optimising) QoS sustainability along a navigation route. Improving (e.g., maximising) the probability of maintaining a certain QoS along anavigation path is desirable, such that a UE can travel along the navigation route and through network areas where the QoS flow will not be abnormally released. Therefore, there is a need for a solution that allows for network analytics to be requested, generated, and applied to sustain a specific QoS for a UE (e.g., a vehicle, drone, plane) as the UE moves along a navigation route.

[0031] A consumer entity is described in the present disclosure. The consumer entity may be an application function (AF) such as a navigation or mapping application. The consumer entity is enabled to request and receive network analytics. The network analytics may comprise a list or set of waypoints for maximising the sustainability of a QoS flow in an area of interest. The list or set of waypoints may be used to generate a navigation route for a UE.

[0032] A network entity is described in the present disclosure. The network entity receives the request for analytics from the consumer entity. The network entity may predict a list of waypoints in the area of interest. The waypoints may be selected to maximise the sustainability of the QoS flow. This may take into account real-time network data, congestion and other relevant metrics. The waypoints may then be provided as a set or list of waypoints to the consumer entity for generating an optimal navigation route.

[0033] In the present disclosure, a UE is enabled to transmit a request to the consumer entity for a navigation route for maximising the sustainability of a QoS flow. The UE may then receive the navigation route based on waypoints that maximise the sustainability of the QoS flow.

[0034] Accordingly, a UE tends to be provided with a navigation route, along which it can travel between first and second locations, whilst also sustaining (i.e., maintaining one or more QoS parameters of) the QoS flow. The UE may accordingly travel along a navigation route that mitigates congested network areas. This tends to mitigate the abnormal release of QoS flows, enabling a required QoS level to be maintained for the realtime transmission of audio, video, or telemetry data.

[0035] Aspects of the present disclosure are described in the context of a wireless communications system.

[0036] Figure 1 illustrates an example of a wireless communications system 100 in accordance with aspects of the present disclosure. The wireless communications system 100 may include one or more NE 102, one or more UE 104, and a core network (CN) 106. The wireless communications system 100 may support various radio access technologies. In some implementations, the wireless communications system 100 may be a 4G network, such as an LTE network or an LTE- Advanced (LTE-A) network. In some other implementations, the wireless communications system 100 may be a NR network, such as a 5G network, a 5G- Advanced (5G-A) network, or a 5G ultrawideband (5G-UWB) network. In other implementations, the wireless communications system 100 may be a combination of a 4G network and a 5G network, or other suitable radio access technology including Institute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20. The wireless communications system 100 may support radio access technologies beyond 5G, for example, 6G. Additionally, the wireless communications system 100 may support technologies, such as time division multiple access (TDMA), frequency division multiple access (FDMA), or code division multiple access (CDMA), etc.

[0037] The one or more NE 102 may be dispersed throughout a geographic region to form the wireless communications system 100. One or more of the NE 102 described herein may be or include or may be referred to as a network node, a base station, a network element, a network function, a network entity, a radio access network (RAN), a NodeB, an eNodeB (eNB), a next-generation NodeB (gNB), or other suitable terminology. An NE 102 and a UE 104 may communicate via a communication link, which may be a wireless or wired connection. For example, an NE 102 and a UE 104 may perform wireless communication (e.g., receive signalling, transmit signalling) over a Uu interface.

[0038] An NE 102 may provide a geographic coverage area for which the NE 102 may support services for one or more UEs 104 within the geographic coverage area. For example, an NE 102 and a UE 104 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc.) according to one or multiple radio access technologies. In some implementations, an NE 102 may be moveable, for example, a satellite associated with a non-terrestrial network (NTN). In someimplementations, different geographic coverage areas associated with the same or different radio access technologies may overlap, but the different geographic coverage areas may be associated with different NE 102.

[0039] The one or more UE 104 may be dispersed throughout a geographic region of the wireless communications system 100. A UE 104 may include or may be referred to as a remote unit, a mobile device, a wireless device, a remote device, a subscriber device, a transmitter device, a receiver device, or some other suitable terminology. In some implementations, the UE 104 may be referred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 104 may be referred to as an Internet-of-Things (loT) device, an Internet-of-Everything (loE) device, or machine-type communication (MTC) device, among other examples.

[0040] A UE 104 may be able to support wireless communication directly with otherUEs 104 over a communication link. For example, a UE 104 may support wireless communication directly with another UE 104 over a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular-V2X deployments, the communication link may be referred to as a sidelink. For example, a UE 104 may support wireless communication directly with another UE 104 over a PC5 interface.

[0041] An NE 102 may support communications with the CN 106, or with another NE 102, or both. For example, an NE 102 may interface with other NE 102 or the CN 106 through one or more backhaul links (e.g., SI, N2, N2, or network interface). In some implementations, the NE 102 may communicate with each other directly. In some other implementations, the NE 102 may communicate with each other or indirectly (e.g., via the CN 106. In some implementations, one or more NE 102 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC). An ANC may communicate with the one or more UEs 104 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs).

[0042] The CN 106 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The CN 106 may be anevolved packet core (EPC), or a 5G core (5GC), which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME), an access and mobility management functions (AMF)) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW), a Packet Data Network (PDN) gateway (P-GW), or a user plane function (UPF)). In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc.) for the one or more UEs 104 served by the one or more NE 102 associated with the CN 106.

[0043] The CN 106 may communicate with a packet data network over one or more backhaul links (e.g., via an SI, N2, N2, or another network interface). The packet data network may include an application server. In some implementations, one or more UEs 104 may communicate with the application server. A UE 104 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the CN 106 via an NE 102. The CN 106 may route traffic (e.g., control information, data, and the like) between the UE 104 and the application server using the established session (e.g., the established PDU session). The PDU session may be an example of a logical connection between the UE 104 and the CN 106 (e.g., one or more network functions of the CN 106).

[0044] In the wireless communications system 100, the NEs 102 and the UEs 104 may use resources of the wireless communications system 100 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers)) to perform various operations (e.g., wireless communications). In some implementations, the NEs 102 and the UEs 104 may support different resource structures. For example, the NEs 102 and the UEs 104 may support different frame structures. In some implementations, such as in 4G, the NEs 102 and the UEs 104 may support a single frame structure. In some other implementations, such as in 5 G and among other suitable radio access technologies, the NEs 102 and the UEs 104 may support various frame structures (i.e., multiple frame structures). The NEs 102 and the UEs 104 may support various frame structures based on one or more numerologies.

[0045] One or more numerologies may be supported in the wireless communications system 100, and a numerology may include a subcarrier spacing and a cyclic prefix. A firstnumerology (e.g., / r=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., / r=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., / r=l) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., / r=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., / r=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., / r=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.

[0046] A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames). Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.

[0047] Additionally or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 100. For instance, the first, second, third, fourth, and fifth numerologies (i.e., / r=0, jU=l , / r=2, jU=3, / r=4) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols). In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing), a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extendedcyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., 1=0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots.

[0048] In the wireless communications system 100, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 100 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz - 7.125 GHz), FR2 (24.25 GHz - 52.6 GHz), FR3 (7.125 GHz - 24.25 GHz), FR4 (52.6 GHz - 114.25 GHz), FR4a or FR4-1 (52.6 GHz - 71 GHz), and FR5 (114.25 GHz - 300 GHz). In some implementations, the NEs 102 and the UEs 104 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the NEs 102 and the UEs 104, among other equipment or devices for cellular communications traffic (e.g., control information, data). In some implementations, FR2 may be used by the NEs 102 and the UEs 104, among other equipment or devices for short-range, high data rate capabilities.

[0049] FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies). For example, FR1 may be associated with a first numerology (e.g., / r=0), which includes 15 kHz subcarrier spacing; a second numerology (e.g., / z=l), which includes 30 kHz subcarrier spacing; and a third numerology (e.g., / r=2), which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies). For example, FR2 may be associated with a third numerology (e.g., / r=2), which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., / z=3), which includes 120 kHz subcarrier spacing.

[0050] The present disclosure describes methods and systems for managing (i.e., requesting, generating, providing and using) network analytics, referred to herein as "Path for Maximum QoS Sustainability," that predict a path / navigation route (i.e., a list of waypoints) which, if followed by a UE (i.e., a vehicle) traveling from a first location (i.e., a point A) to a second location (i.e., a point B), tends to maximize the probability of sustaining a communication service with a specific QoS level. These analytics tend to be applicable in scenarios where communication services with strict QoS requirements(referred to herein as QoS parameters), such as GBR and low latency, need to be maintained as the UE (e.g., the vehicle) travels through network areas that may experience congestion. Such congestion may otherwise cause these communication services to be abnormally released.

[0051] In wireless communication systems, including 5G networks, the QoS of a communication flow (also referred to as a 'QoS flow') tends to be required to be maintained to ensure proper functioning of certain applications. For example, an emergency vehicle transmitting real-time video or telemetry to a control centre may require a GBR and low latency to ensure reliable communications. It tends to be important that the QoS flows established by the vehicle are maintained as the vehicle traverses different areas of the network, which may experience congestion and may abnormally release QoS flows as a result of the congestion. In order to achieve this, it would be useful to guide the vehicle to follow a certain path that avoids congested network areas and, thus, maximizes the probability to maintain the established QoS. Such guidance is not supported by the current navigation systems and 5G networks.

[0052] In addition, navigation systems optimize routes based on parameters such as travel time and road traffic, without considering the sustainability of network QoS along the route. Therefore, there is a need for a solution that provides network analytics to maximize the likelihood of maintaining a specific QoS level as a vehicle moves across a certain geographic area.

[0053] 5G networks support a NWDAF, which can provide “QoS Sustainability” analytics. A consumer of these analytics, e.g., the Network Exposure Function (NEF) or a V2X Application Server, can subscribe to “QoS Sustainability” events and receive notifications from the NWDAF when the rate of abnormally released QoS flows in a network area exceeds a certain threshold. This feature, sometimes referred to as “Predictive QoS,” provides notifications that help applications predict whether the network may or may not sustain a certain QoS flow for much longer. These notifications can be used proactively by applications to take preventive actions in order to maintain established QoS flows.

[0054] However, the “QoS Sustainability” analytics cannot be used to derive a navigation route that maximizes the QoS sustainability along the route. For example, if anemergency vehicle travels from a first location (i.e., a point A) to a second location (i.e., a point B), a question arises as to which route should the vehicle follow to avoid congested network areas. A related question is which route should the vehicle follow to maximize the probability to maintain a QoS flow until it reaches the second location? These questions cannot yet be answered by using the legacy “QoS Sustainability” analytics and predictions supported by the 5G networks. This disclosure aims to fill this gap by enabling the requesting, generating, providing and using of network analytics to derive navigation routes (paths) that maximize the QoS sustainability.

[0055] Figure 2 A and 2B illustrate an example case in which a UE, such as a vehicle, requests a navigation route from a navigation application server. The request relates to a navigation route that satisfies (e.g., maximizes) a likelihood of sustaining (e.g., maintaining) an established QoS flow for the UE as the UE travels from a first location to a second location.

[0056] Figure 2 A illustrates an example of a navigation route 210 in accordance with aspects of the present disclosure. The navigation route 210 may implement or be implemented by aspects of the wireless communication system 100. The navigation route 210 may be multi-dimensional (e.g., two-dimensional, three-dimensional) navigation route (traversing latitude and longitude). In the example of Figure 2A, the navigation route 210 (e.g., path, route) may include a starting location, such as a first location 212 (Point ‘A’ in Figure 2A) and an ending location (e.g., destination), such as a second location 214 (Point ‘B’ in Figure 2A). The first location 212 and the second location 214 may be geographically remote (e.g., distance) from each other.

[0057] The navigation route 210 may include one or more waypoints 216 (e.g., checkpoints, markers, navigation points), such as waypoint 216a, waypoint 216b, waypoint 216c, waypoint 216d, and / or waypoint 216e. Each of the one or more waypoints 216 may be located between the first location 212 and the second location 214 and along the navigation route 210. As described here, the navigation route 210 may be determined and / or generated based at least in part on (i.e., to be spatially close to / follow closely) one or more of the waypoints 216 in addition to the first location 212 and second location 214.

[0058] Figure 2B illustrates an example of a process flow 220 that supports determining a navigation route in accordance with aspects of the present disclosure. The process flow 220 may implement or be implemented by aspects for determining the navigation route 210 of Figure 2A. Additionally, the process flow 220 may implement or be implemented by aspects of the wireless communication system 100. For example, the process flow 220 may include one or more of a UE 222, a navigation application server 224, and a network 226 (e.g., a 5G network), which may be examples of UE and NE described with reference to Figure 1.

[0059] The process flow 220 may be referred to as a procedure, including one or more operations performed by one or more of the UE 222, the navigation application server 224, and the network 226. In the following description of the process flow 220, the operations or signaling performed between one or more of the UE 222, the navigation application server 224, and the network 226 may be performed or signalled (e.g., transmitted, received) in a different order than the example order shown, or the operations or signaling performed by one or more of the UE 222, the navigation application server 224, and the network 226 may be performed or signalled (e.g., transmitted, received) in different orders or at different times. Some operations or signaling may also be omitted from the process flow 220. Additionally, although some operations or signaling may be shown to occur at different times, these operations or signaling may occur at the same time or in overlapping time periods.

[0060] At step 201, the UE 222 may transmit a first request message for a route (e.g., path) from a first location (e.g., a starting location) to a second location (e.g., an ending location). For example, the UE 222 may transmit to, and the navigation application server 224 may receive, the first request message for a route from the first location 412 to the second location 414 as described with reference to Figure 4A. The first request message may include a request for the route from the first location 412 to the second location 414 satisfies (e.g., maximizes) a probability to maintain a QoS flow with one or more QoS parameters (e.g., GBR for uplink and downlink, latency). The one or more QoS parameters may be provided (e.g., in the first request message) to the navigation application server 224.

[0061] At step 202, the navigation application server 224 may transmit, and the network 226 may receive, a second request message for network analytics (e.g., “Path for Maximum QoS Sustainability”). In the example of Figure 2B, the navigation application server 224 may be configured to or operable to function as an AF.

[0062] At step 203, the network 226 may predict a set of waypoints, such as waypoints 216 as described herein with reference to Figure 2A, that the UE 222 should follow for satisfying (e.g., maximizing) the probability of sustaining the QoS flow. The prediction performed by the network 226 may be based at least in part on real-time network data, congestion, and other relevant metrics.

[0063] At step 204, the network 226 may transmit, and the navigation application server 224 may receive, a response message that includes an indication of the waypoints 216.

[0064] At step 205, the navigation application server 224 may determine and generate the route (e.g., the navigation route 210) based at least in part on the indicated waypoints 216 (e.g., waypoint 216a, waypoint 216b, waypoint 216c, waypoint 216d, and / or waypoint 216e). The route (e.g., the navigation route 210) can be used by the UE 222 (e.g., a vehicle) to navigate effectively and maintain a QoS flow associated with the UE 222 as it travels from the first location 212 to the second location 214.

[0065] Accordingly, one or more aspects of the present disclosure support satisfying (e.g., maximizing) a probability of maintaining a QoS level for a QoS flow.

[0066] By way of example and with reference to Figures 2A and 2B, the UE 222 may be an emergency vehicle. The emergency vehicle may have an onboard system capable of establishing a QoS flow with one or more QoS parameters, such as a GBR flow for realtime video transmission. The onboard system may communicate (e.g., transmit, receive) with the navigation application server 224 (e.g., which may function as an AF) to request a route that satisfies (e.g., maximizes, optimizes) a probability of maintaining a QoS level for a QoS flow.

[0067] The navigation application server 224 functioning as an AF may be referred to herein as a consumer or consumer entity. For instance, the AF may function as a consumerof network analytics within a network architecture (e.g., a 5G network or network beyond 5G). In response to (or based at least in part on) receiving a request from the emergency vehicle for network analytics, the AF may communicate (e.g., exchange one or more messages) with a NWDAF via a NEF in the network 226 to obtain predictions that can be used to determine (e.g., calculate) a navigation route to satisfy (e.g., maximize) the probability of sustaining the QoS level.

[0068] The NEF, including one or more operations and signaling performed with or by the NEF, may be optional. The NEF may function as an intermediary network node between the AF (e.g., the navigation application server 224) and the NWDAF, enabling secure and controlled access to network analytics. For example, the NEF may receive the request from the AF and forwards it to the NWDAF. The NWDAF may be part of the network 226 and may be configured or operable to provide network analytics and predictions based on real-time and historical network data. As described herein, the NWDAF may use information such as cell load, mobility patterns, interference levels, and other metrics to determine a set of one or more waypoints 216, which define a path for the navigation route 210 that satisfies (e.g., maximizes) the probability to sustain the QoS level.

[0069] Figure 3 A illustrates an example of a navigation route 310 in accordance with aspects of the present disclosure. The navigation route 310 may implement or be implemented by aspects of the wireless communication system 100. The navigation route 310 (e.g., path) may include a starting location, such as a first location 312 (Point A) and an ending location, such as a second location 314 (Point B). The navigation route 310 may also include one or more waypoints 316 (e.g., checkpoints, markers, navigation points), such as waypoint 316a, waypoint 316b, waypoint 316c, waypoint 316d, and / or waypoint 316e. Each of the one or more waypoints 316 may be located (e.g., along a path) between the first location 312 and the second location 314.

[0070] Figure 3B illustrates an example of a process flow 320 that supports determining a navigation route in accordance with aspects of the present disclosure. The process flow 320 may implement or be implemented by aspects for determining the navigation route 310 of Figure 3 A. Additionally, the process flow 320 may implement or be implemented by aspects of the wireless communication system 100. For example, the process flow 320 mayinclude one or more of a UE 322, a navigation applicator server 324 (e.g., functioning as an AF), and a network 326. The network 326 may comprise a NEG 326a and a NWDAF 326b.

[0071] The process flow 320 may be referred to as a procedure, including one or more operations performed by one or more of the UE 322, the navigation applicator server 324 (e.g., functioning as an AF), the network 326 (e.g., including one or more of the NEG 326a or the NWDAF 326b). In the following description of the process flow 320, the operations or signaling performed between one or more of the UE 322, the navigation applicator server 324 (e.g., functioning as an AF), the network 326 (e.g., including one or more of the NEG 326a or the NWDAF 326b) may be performed or signalled (e.g., transmitted, received) in a different order than the example order shown, or the operations or signaling performed by one or more of the UE 322, the navigation applicator server 324 (e.g., functioning as an AF), the network 326 (e.g., including one or more of the NEF 326a or the NWDAF 326b) may be performed or signalled (e.g., transmitted, received) in different orders or at different times. Some operations or signaling may also be omitted from the process flow 320. Additionally, although some operations or signaling may be shown to occur at different times, these operations or signaling may occur at the same time or in overlapping time periods.

[0072] At step 301, the UE 322 may transmit to, and the navigation application server 324 may receive, a request message that request for a navigation route. For example, the UE 322 may be an emergency vehicle that transmits (e.g., sends) a request to the navigation application server 324 (e.g., Google Maps™ or a similar application) for a navigation route that satisfies (e.g., maximizes) a probability of sustaining a QoS flow with one or more QoS parameters (e.g., 5QI=4, GBFR-UL=lMbps, GBFR-DL=5Mbps). With reference to Figure 3 A, the navigation route may be from the first location 312 to the second location 314. In some examples, the request may include (e.g., indicate) the first location 312 (Point A) and the second location 314 (Point B), and the one or more QoS parameters of the QoS flow (5QI, GBFR-UL, GBFR-DL).

[0073] At step 302, there is communication with NWDAF 326b. The navigation application server 324 may communicate directly with NWDAF 326b or the communication may be via the NEF 326a. By way of example, upon receiving the requestfrom the UE 322, the navigation application server 324 sends a further request to the NEF 326a of 5G network 326 for network analytics, specifically for predicting a "Path for Maximum QoS Sustainability." The NEF 326a then forwards this request to the NWDAF 326b of the 5G network 326. The request may contain the QoS parameters of the QoS flow received from the UE 322, such as 5QI, GBR for uplink / downlink, and an identifier for the target UE 322 or indicating any UE, and the area of interest (for instance the first location 312 (point A), and the second location 314 (point B)). The analytics ID in the request may be “path for maximum QoS sustainability”.

[0074] The request from the navigation application server 324 to the NEF 326a and the request from the navigation application server 324 to the NWDAF 326b may be hypertext transfer protocol (HTTP) request messages (such as HTTP POST messages) including several [key, value] pairs in their payloads.

[0075] The pay loads may include an Analytics ID: “PATH FOR MAX QOS SUSTAINABILITY”. The Analytics ID key (aka Event ID) indicates what type of analytics or predictions are requested from the NWDAF. Several values for this key are already defined in the 3GPP specification TS 23.288 titled, “Architecture enhancements for 5G System (5GS) to support network data analytics services”. In this disclosure, a new value is defined in this respect that is expressed as “PATH FOR MAX QOS SUSTAINABILITY”, which indicates that the NWDAF 326b is requested to predict a path (list of waypoints) that maximizes the probability for the UE 322 to sustain a given QoS flow.

[0076] The payloads may include location information, for instance the path the UE is moving on; also known as a "Path of Interest" as per the 3GPP Specification TS 23.288. This key indicates the path which the UE 322 is moving on. It could be the first location 312 and the second location 314 (Point A, Point B) or it could be a list of cells (Origin cell, Destination cell). For example the NEF 326a may receive the first location 312 and the second location 314 from the navigation application server 324 and may translate them into an Origin cell and a Destination cell.

[0077] The payloads may include a QoS requirement. The QoS requirement may comprise one or more QoS parameters, such as the 5QI, GFBR-UL, GFBR-DL. This keydefines the QoS parameters of the associated QoS flow. For instance the QoS parameters may comprise 5QI = 4, GFBR-UL = 1Mbps, GFBR-DL = 5Mbps.

[0078] The payloads may include the target, i.e., an identifier of the UE 322 or other UE identity. This key contains the identity of the associated UE which may be “any UE”.

[0079] At step 303, there is the generation of waypoints. The NWDAF 326b processes the request from the navigation application server 324 by analyzing real-time network data, historical performance metrics, predicted conditions, and other data to provide an optimal path, i.e., a list of waypoints (waypoints 316a, 316b, 316c, 316d, 316e) . If the UE 322 follows these waypoints as it moves from the first location 312 (point A) to the second location 314 (point B), it is expected that the probability to sustain its QoS flow will be maximized. In essence, these waypoints 316a, 316b, 316c, 316d, 316e indicate which base stations should preferably serve the UE 322 as it travels from the first location 312 to the second location 314, and how close the UE 322 should remain to each one of these base stations. The NWDAF 326b predicts these waypoints 316a, 316b, 316c, 316d, 316e by considering factors such as cell load, congestion levels, interference, and mobility patterns of UEs.

[0080] At step 304, a response is provided to the navigation application server 324. The NWDAF 326b sends the predicted waypoints 316a, 316b, 316c, 316d, 316e to the NEF 326a, which then relays this information back to the navigation application server 324.

[0081] The response from NWDAF 326b to the NEF 326a and the response from NEF 326a to the navigation application server 324 are typically HTTP response messages (such as HTTP 200 messages), or HTTP notification messages including several [key, value] pairs in their payloads.

[0082] Included in the pay load may be the Analytics ID: PATH FOR MAX QOS SUSTAINABILITY. This indicates that the response provides information associated with a request for PATH FOR MAX QOS SUSTAINABILITY predictions or analytics.

[0083] Also included in the payload may be PathForMaxQosSustainabilitylnfo. This relates to information about the derived predictions / analytics. ThePathForMaxQosSustainabilitylnfo is a new information element defined in this disclosure, which contains information about the derived predictions / analytics, including the list of waypoints 316a, 316b, 316c, 316d, 316e. It may also contain a confidence level which measures how certain the prediction model used by the NWDAF 326b is that the provided waypoints 316a, 316b, 316c, 316d, 316e really maximize the probability to sustain the QoS flow. It may be expressed as a probability or percentage (e.g., 92%). In some scenarios, the NWDAF 326b may create multiple lists of waypoints, e.g., when it predicts that different waypoint lists have similar or identical probabilities to sustain the QoS flow. In such scenarios, the response from the NWDAF 326b to the NEF 326a and the response from the NEF 326a to the navigation application server 324 will contain multiple PathForMaxQosSustainabilitylnfo elements.

[0084] The payload may also contain the QoS requirement such as the one or more QoS parameters such as 5QI=4, GFBR-UL=lMbps, GFBR-DL=5Mbps.

[0085] At step 305 there is the utilization of the waypoint information. The navigation application server 324 utilizes the list of waypoints 316a, 316b, 316c, 316d, 316e as guidance for creating the requested navigation route 310 from the first location 312 (point A) to the second location 314 (point B). The navigation application server 324 uses this list of waypoints 316a, 316b, 316c, 316d, 316e, and possibly additional information (e.g., road traffic conditions, expected fuel consumptions, etc.), to generate the navigation route 310.

[0086] In scenarios where the navigation application server 324 receives multiple lists of waypoints, it may use them to provide multiple alternative navigation routes from the first location 312 to the second location 314.

[0087] At step 306, the navigation route 310 is provided to the UE 322. The UE 322 (e.g., vehicle) receives the route(s) generated by the navigation application server 324 as a response to its request in step 301. The UE 322 follows this route 310 to reach its destination at the second location 314 (point B) in a way that maximizes the probability to sustain its QoS flow.

[0088] Figure 3C illustrates an example of waypoints in accordance with aspects of the present disclosure. In Figure 3C, the first location 312 and second location 314 of Figure3 A are shown. Between the first location 312 and second location 314 are a plurality of waypoints 316.

[0089] Each waypoint of the plurality of waypoints 316 is shown as a circle defined by a centre and a radius. In Figure 3 A, each waypoint 316a, 316b, 316c, 316d, 316e is shown as a small circle. However, in more practical scenarios, each waypoint would be a larger circle, as shown in Figure 3C. In a typical scenario, the centre of a waypoint would be the location of a base station and the radius of a waypoint would indicate how close the UE 322 should remain to the base station in order to have sufficiently good signal quality and minimize the probability for the base station to abnormally release its QoS flow.

[0090] The definition of a waypoint as a circle is aligned with the waypoint definition in the 3GPP Technical Specification TS 23.288. Essentially a list of waypoints may be expressed as longitude and latitude in geographical coordinates and combined with a radius value.

[0091] An alternative system and method of determining a navigation route is shown in Figures 4A-4B. This alternative system and method comprises a modification to the system and method shown in Figures 3A-3B.

[0092] Figure 4 A illustrates an example of a navigation route 410 in accordance with aspects of the present disclosure. The navigation route 410 may implement or be implemented by aspects of the wireless communication system 100. The navigation route 410 (e.g., path, route) may include a starting location, such as a first location 412 (Point A) and an ending (e.g., destination) location, such as a second location 414 (Point B). The navigation route 410 may also include one or more waypoints 416 (e.g., checkpoints, markers, navigation points), such as waypoint 416a, waypoint 416b, waypoint 416c, waypoint 416d, and / or waypoint 416e. Each of the one or more waypoints 416 may be located between the first location 412 and the second location 414 and along the navigation route 410.

[0093] Figure 4B illustrates an example of a process flow 420 that supports determining a navigation route in accordance with aspects of the present disclosure. The process flow 420 may implement or be implemented by aspects for determining the navigation route 410of Figure 4 A. Additionally, the process flow 420 may implement or be implemented by aspects of the wireless communication system 100. For example, the process flow 420 may include one or more of UE 422, a navigation application server 424 (e.g., an AF), a network 426 comprising a NEF 426a and a NWDAF 426b, and an operator platform 428, which may be examples of UE and NE described with reference to Figure 1. The operator platform 428 may include a component 428a operating as an AF.

[0094] The process flow 420 may be referred to as a procedure, including one or more operations performed by one or more of the UE 422, the navigation application server 424, the NEF 426a, the NWDAF 426b, and / or the operator platform 428. In the following description of the process flow 420, the operations or signaling performed between one or more of the UE 422, the navigation application server 424, the NEF 426a, the NWDAF 426b, and / or the operator platform 428 may be performed or signalled (e.g., transmitted, received) in a different order than the example order shown, or the operations or signaling performed by one or more of the UE 422, the navigation application server 424, the NEF 426a, the NWDAF 426b, and / or the operator platform 428 may be performed or signalled (e.g., transmitted, received) in different orders or at different times. Some operations or signaling may also be omitted from the process flow 420. Additionally, although some operations or signaling may be shown to occur at different times, these operations or signaling may occur at the same time or in overlapping time periods.

[0095] In the example of Figure 4B, a new application programming interface (API) is defined, called CAMARA “Path for Maximum QoS Sustainability” API. The CAMARA Alliance (see https: / / camaraproject.org / ) is an open, collaborative initiative that focuses on defining and developing standardized APIs for telecommunication networks. These APIs make the telecommunication networks programmable and enable external applications to access network capabilities and indicate their requirements for communication. CAMARA has defined several APIs covering a wide range of use cases, such as: Edge Cloud APIs; Device Location APIs; Device Status APIs; Quality on Demand APIs; Number Verification APIs; Network Slice Booking APIs.

[0096] The process flow 420 shown in Figure 4B differs from the process flow 320 shown in Figure 3B because the navigation application server 424 operates as a CAMARAclient application and communicates with the network 426 via one or more CAMARA APIs. These APIs are supported and delivered by (e.g., through, via) the operator platform 428 within the network 426. The operator platform 428 may serve (e.g., function) as an interface between one or more network (e.g., telco) operators and external applications, allowing them to access and leverage network capabilities in a standardized, programmable way.

[0097] At step 401, the UE 422 may transmit a first request message for a route (e.g., navigation route) from a first location (e.g., a starting location) to a second location (e.g., an ending location). For example, the UE 422 may transmit to, and the navigation application server 424 may receive, the first request message for a route from the first location 412 to the second location 414 as described with reference to Figure 4A. The navigation application server 424 may determine a route from the first location to the second location for which a probability (e.g., likelihood) of sustaining a QoS flow with one or more QoS parameters (e.g., 5QI=4, GBFR-UL=lMbps, GBFR-DL=5Mbps) is satisfied (e.g., maximized). As such, the first request message may include (e.g., indicate) one or more of the first location (e.g., the first location 412 (Point A)), the second location (e.g., the second location 414 (Point B)), and one or more QoS parameters of the QoS flow. In some examples, the navigation application server 424 may be a Google Maps™ or a similar application.

[0098] In the example of Figure 4B, at step 401 A, in response to (or based at least in part on) the received first request message from the UE 422, the navigation application server 424 may generate and transmit a second request message to the operator platform 428 using the CAMARA API 424a. The operator platform 428 (or the component 428a of the operator platform 428 functioning as AF) may transform the received second request message into a third request message, which the operator platform 428 (or the component 428a of the operator platform 428 functioning as AF) may transmit to, and the NWDAF 426b may receive, directly. In some other examples, the operator platform 428 (or the component 428a of the operator platform 428 functioning as AF) may transform the received second request message into a third request message, which the operator platform428 (or the component 428a of the operator platform 428 functioning as AF) may transmit to, and the NWDAF 426b may receive, via the NEF 426a.

[0099] At step 402, the NWDAF 426b may output (e.g., forward, transmit), and the NEF 426a may obtain (e.g., receive), a request message for network analytics. In some examples, the request message may include (e.g., indicate) one or more QoS parameters of the QoS flow associated with the UE 422, including 5QI, GBR, an identifier of the UE 422, an area of interest (e.g., the first location 412 (Point A), the second location 414 (Point B)), etc. An analytics identifier included in the request message may be “Path for Maximum QoS Sustainability.” In response to (or based at least in part on) the received request message, the NEF 426a may perform the network analytics for predicting (e.g., forecasting, estimating) a “Path for Maximum QoS Sustainability,” and output (e.g., forward, transmit) to the NWDAF 426b a response message that includes the network analytics.

[0100] One or more of the request messages or the response messages exchanged between one or more of the UE 422, the navigation application server 424, the NEF 426a, the NWDAF 426b, and / or the operator platform 428 may be HTTP request messages (e.g., HTTP POST messages), including one or more [key, value] pairs in a corresponding payload of a corresponding message.

[0101] A payload of one or more of the above example messages may include anAnalytics ID: “PATH FOR MAX QOS SUSTAINABILITY”. An analytics ID key (e.g., Event ID) that indicates a type of analytics or prediction requested by the NWDAF 426b. A set of one or more values for the key may be defined in 3 GPP TS 23.288, “Architecture Enhancements For 5G System (5GS) To Support Network Data Analytics Services”. In the present disclosure, a new value is defined that is expressed as“PATH FOR MAX QOS SUSTAINABILITY”, which indicates that the NWDAF 426b is requested to predict a route (e.g., path, including a set (list) of waypoints) that maximizes a probability for the UE 422 to sustain (e.g., maintain) a QoS flow.

[0102] Additionally, or alternatively, a payload of one or more of the above example messages may include location information, for example a path the UE 422 is traveling (e.g., moving, traversing) on, which may also be known as a path of interest as per the 3GPP TS 23.288. The location information may include the first location 412, the secondlocation 414 (Point A, Point B) and / or a set (list) of cells (e.g., an origin (e.g., source, reference) cell, a destination cell). For example, the NEF 426a may receive an indication of the first location 412 and the second location 414, from the navigation application server 324, and may translate the locations into an origin cell and a destination cell.

[0103] Additionally, or alternatively, a payload of one or more of the above example messages may include (e.g. indicate) a QoS requirement. The QoS requirement may include one or more QoS parameters, such as 5QI, GFBR-UL, GFBR-DL. This defines the QoS parameters of a QoS flow. For example, one or more of the QoS parameters may include 5QI = 4, GFBR-UL = 1Mbps, GFBR-DL = 5Mbps.

[0104] The payloads may include a target UE (e.g., an identifier of the UE 422 or other UE (not shown). This identifies a corresponding UE which may be any UE.

[0105] At step 403, the NWDAF 426b may generate a set of waypoints (e.g., checkpoints, markers, navigation points). In some examples, the NWDAF 426b may analyze network data (e.g., real-time, or historic), including one or more performance metrics, predicted conditions, and other data to provide an optimal route (e.g., path), i.e., a set of waypoints (e.g., waypoints 416 as described in Figure 4A).

[0106] If the UE 422 follows (e.g., navigates, tacks, moves along) these waypoints as it travels from the first location 412 (Point A) to the second location 414 (Point B), the UE 422 may maintain a quality of a QoS flow (i.e., maximized). As such, these waypoints 416 indicate navigation points that are associated with (e.g., correspond to) base stations that may optimally (e.g., preferably, ideally) serve the UE 422 as it travels from the first location 412 to the second location 414, and indicate a distance (i.e., how close) for the UE 422 to maintain to each one of these base stations. The NWDAF 426b may determine or predict these waypoints 416 based at least in part on factors such as a cell load (e.g., a throughput of a base station), a congestion level (e.g., network traffic load of a base station), an interference (e.g., object that may cause a blockage or other device that may cause interference for the UE 422 and / or the base station), and mobility patterns of the UE 422 and / or other UEs (not shown).

[0107] At step 404, the NWDAF 426b may output (e.g., transmit) to, and the NEF 426a may receive, a response message, which may include an indication of the waypoints 416 as described in Figure 4A. Additionally, the NEF 426 may output (e.g., transmit, forward) to, and the operator platform 428 may receive, the response message, which may include the indication of the waypoints 416 as described in Figure 4A.

[0108] One or more of the response messages may be an HTTP response messages (such as HTTP 200 messages), or an HTTP notification messages including one or more [key, value] pairs in a corresponding payload of a corresponding message.The corresponding pay load may include an Analytics ID:PATH FOR MAX QOS SUSTAINABILITY, which may indicate that the response message provides information associated with a request for PATH FOR MAX QOS SUSTAINABILITY predictions or analytics.

[0109] Additionally, or alternatively, a payload may include a new information element PathForMaxQosSustainabilitylnfo, which may include information associated with the predictions and / or analytics. This information element may also contain information about the predictions and / or analytics, including the set (e.g., list) of waypoints 416.

[0110] Additionally, or alternatively, this information element may include (e.g., indicate) a confidence level (e.g., confidence score) that represents the accuracy or certainty of a prediction performed (e.g., a prediction model used) by the NWDAF 426b for the waypoints 416, including optimized probability to sustain a QoS flow. In some examples, the confidence level may be expressed as a probability or percentage (e.g., 92%). The NWDAF 426b may generate (e.g., construct, create, form) multiple sets (e.g., lists) of waypoints, for example, when the NWDAF 426b predicts that different waypoint sets (e.g., lists) have similar or equivalent probabilities to sustain the QoS flow. In these examples, the response message from the NWDAF 426b to the NEF 426a, including the response message from the NEF 426a to the operator platform 428 may include (e.g., contain) multiple information elements (i.e., PathForMaxQosSustainabilitylnfo elements).

[0111] Additionally, or alternatively, a payload may include (e.g., indicate) one or more QoS requirement such as the one or more QoS parameters such as 5QI=4, GFBR- UL=lMbps, GFBR-DL=5Mbps.

[0112] At step 404A, in response to (e.g., after or based at least in part on) the received response message from the NWDAF 426b, the operator platform 428 may transform the received response message into a CAMARA response. The operator platform 428 may transmit, and the navigation application server 424 may receive, the CAMARA response.

[0113] At step 405, the navigation application server 424 may generate a route (requested at step 401) based at least in part on the set of waypoints 416 provided (e.g., included, indicated) in the CAMARA response. Additionally, the navigation application server 424 may generate the requested route (from step 401) based at least in part on assistance information (e.g., road traffic conditions, expected fuel consumptions, etc.), to determine and generate the route (e.g., the navigation route 410 of Figure 4A). In some examples, the navigation application server 424 may generate multiple routes, based at least in part on multiple sets of waypoints, and select at least one generated route based at least in part on the route having a highest probability among the routes to sustain a QoS flow for the UE 422.

[0114] At step 406, the navigation application server 424 may transmit, and the UE 422 may receive, a response message that includes (e.g., indicates) the route (e.g., the navigation route 410 of Figure 4A). Accordingly, the UE 422 may travel according to the route 410 in a way that maximizes the probability to sustain a QoS flow for the UE 422.

[0115] Figure 5 illustrates an example of a UE 500 in accordance with aspects of the present disclosure. The UE 500 may include a processor 502, a memory 504, a controller 506, and a transceiver 508. The processor 502, the memory 504, the controller 506, or the transceiver 508, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. These components may be coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces.

[0116] The processor 502, the memory 504, the controller 506, or the transceiver 508, or various combinations or components thereof may be implemented in hardware (e.g., circuitry). The hardware may include a processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other programmable logic device, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure.

[0117] The processor 502 may include an intelligent hardware device (e.g., a general- purpose processor, a DSP, a CPU, an ASIC, an FPGA, or any combination thereof). In some implementations, the processor 502 may be configured to operate the memory 504. In some other implementations, the memory 504 may be integrated into the processor 502. The processor 502 may be configured to execute computer-readable instructions stored in the memory 504 to cause the UE 500 to perform various functions of the present disclosure.

[0118] The memory 504 may include volatile or non-volatile memory. The memory 504 may store computer-readable, computer-executable code including instructions when executed by the processor 502 cause the UE 500 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such the memory 504 or another type of memory. Computer-readable media includes both non- transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer.

[0119] In some implementations, the processor 502 and the memory 504 coupled with the processor 502 may be configured to cause the UE 500 to perform one or more of the functions described herein (e.g., executing, by the processor 502, instructions stored in the memory 504). For example, the processor 502 may support wireless communication at the UE 500 in accordance with examples as disclosed herein. The UE 500 may be the UE 104, the UE 222, the UE 322, the UE 422. The UE 500 may be configured or operable to support a means for transmitting, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; andreceiving, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0120] The controller 506 may manage input and output signals for the UE 500. The controller 506 may also manage peripherals not integrated into the UE 500. In some implementations, the controller 506 may utilize an operating system such as iOS®, ANDROID®, WINDOWS®, or other operating systems. In some implementations, the controller 506 may be implemented as part of the processor 502.

[0121] In some implementations, the UE 500 may include at least one transceiver 508. In some other implementations, the UE 500 may have more than one transceiver 508. The transceiver 508 may represent a wireless transceiver. The transceiver 508 may include one or more receiver chains 510, one or more transmitter chains 512, or a combination thereof.

[0122] A receiver chain 510 may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receiver chain 510 may include one or more antennas for receive the signal over the air or wireless medium. The receiver chain 510 may include at least one amplifier (e.g., a low-noise amplifier (LNA)) configured to amplify the received signal. The receiver chain 510 may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receiver chain 510 may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

[0123] A transmitter chain 512 may be configured to generate and transmit signals (e.g., control information, data, packets). The transmitter chain 512 may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The transmitter chain 512 may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitablefor transmission over the wireless medium. The transmitter chain 512 may also include one or more antennas for transmitting the amplified signal into the air or wireless medium.

[0124] Figure 6 illustrates an example of a processor 600 in accordance with aspects of the present disclosure. The processor 600 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 600 may include a controller 602 configured to perform various operations in accordance with examples as described herein. The processor 600 may optionally include at least one memory 604, which may be, for example, an L1 / L2 / L3 cache. Additionally, or alternatively, the processor 600 may optionally include one or more arithmetic-logic units (ALUs) 606. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses).

[0125] The processor 600 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 600) or other memory (e.g., random access memory (RAM), read-only memory (ROM), dynamic RAM (DRAM), synchronous dynamic RAM (SDRAM), static RAM (SRAM), ferroelectric RAM (FeRAM), magnetic RAM (MRAM), resistive RAM (RRAM), flash memory, phase change memory (PCM), and others).

[0126] The controller 602 may be configured to manage and coordinate various operations (e.g., signalling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 600 to cause the processor 600 to support various operations in accordance with examples as described herein. For example, the controller 602 may operate as a control unit of the processor 600, generating control signals that manage the operation of various components of the processor 600. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

[0127] The controller 602 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 604 and determine subsequent instruction(s) to be executed to cause the processor 600 to support various operations in accordance with examples as described herein. The controller 602 may be configured to track memory address of instructions associated with the memory 604. The controller 602 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 602 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 600 to cause the processor 600 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 602 may be configured to manage flow of data within the processor 600. The controller 602 may be configured to control transfer of data between registers, arithmetic logic units (ALUs), and other functional units of the processor 600.

[0128] The memory 604 may include one or more caches (e.g., memory local to or included in the processor 600 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementations, the memory 604 may reside within or on a processor chipset (e.g., local to the processor 600). In some other implementations, the memory 604 may reside external to the processor chipset (e.g., remote to the processor 600).

[0129] The memory 604 may store computer-readable, computer-executable code including instructions that, when executed by the processor 600, cause the processor 600 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 602 and / or the processor 600 may be configured to execute computer-readable instructions stored in the memory 604 to cause the processor 600 to perform various functions. For example, the processor 600 and / or the controller 602 may be coupled with or to the memory 604, the processor 600, the controller 602, and the memory 604 may be configured to perform various functions described herein. In some examples, the processor 600 may include multiple processors and the memory 604 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiplememories, which may, individually or collectively, be configured to perform various functions herein.

[0130] The one or more ALUs 606 may be configured to support various operations in accordance with examples as described herein. In some implementations, the one or more ALUs 606 may reside within or on a processor chipset (e.g., the processor 600). In some other implementations, the one or more ALUs 606 may reside external to the processor chipset (e.g., the processor 600). One or more ALUs 606 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 606 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 606 be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 606 may support logical operations such as AND, OR, exclusive-OR (XOR), not-OR (NOR), and not- AND (NAND), enabling the one or more ALUs 606 to handle conditional operations, comparisons, and bitwise operations.

[0131] The processor 600 may support wireless communication in accordance with examples as disclosed herein. The processor 600 may be configured to support a means for outputting a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and inputting a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0132] The processor 600 may alternatively be configured to or operable to support a means for inputting a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generating at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and outputting a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0133] Alternatively, the processor 600 may be configured to or operable to support a means for outputting a second request for a navigation route for maximizing sustainabilityof a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and inputting a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0134] Figure 7 illustrates an example of a NE 700 in accordance with aspects of the present disclosure. The NE 700 may include a processor 702, a memory 704, a controller 706, and a transceiver 708. The processor 702, the memory 704, the controller 706, or the transceiver 708, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. These components may be coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces.

[0135] The processor 702, the memory 704, the controller 706, or the transceiver 708, or various combinations or components thereof may be implemented in hardware (e.g., circuitry). The hardware may include a processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other programmable logic device, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure.

[0136] The processor 702 may include an intelligent hardware device (e.g., a general- purpose processor, a DSP, a CPU, an ASIC, an FPGA, or any combination thereof). In some implementations, the processor 702 may be configured to operate the memory 704. In some other implementations, the memory 704 may be integrated into the processor 702.The processor 702 may be configured to execute computer-readable instructions stored in the memory 704 to cause the NE 700 to perform various functions of the present disclosure.

[0137] The memory 704 may include volatile or non-volatile memory. The memory 704 may store computer-readable, computer-executable code including instructions when executed by the processor 702 cause the NE 700 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such the memory 704 or another type of memory. Computer-readable media includes both non- transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitorystorage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer.

[0138] In some implementations, the processor 702 and the memory 704 coupled with the processor 702 may be configured to cause the NE 700 to perform one or more of the functions described herein (e.g., executing, by the processor 702, instructions stored in the memory 704). For example, the processor 702 may support wireless communication at the NE 700 (e.g., an AF, an AF server, an NWDAF) in accordance with examples as disclosed herein. The NE 700 may be the NE 224, the NE 324, the NE 326a, the NE 326b, the NE 424, the NE 428, the NE 426a, and / or the NE 426b.

[0139] The NE 700 (e.g., an AF, an AF server) may be configured to support a means for transmitting, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and receiving, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0140] Alternatively, the NE 700 (e.g., an NWDAF) may be configured to or operable to support a means for receiving, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generating at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmitting, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0141] The controller 706 may manage input and output signals for the NE 700. The controller 706 may also manage peripherals not integrated into the NE 700. In some implementations, the controller 706 may utilize an operating system such as iOS®, ANDROID®, WINDOWS®, or other operating systems. In some implementations, the controller 706 may be implemented as part of the processor 702.

[0142] In some implementations, the NE 700 may include at least one transceiver 708. In some other implementations, the NE 700 may have more than one transceiver 708. The transceiver 708 may represent a wireless transceiver. The transceiver 708 may include one or more receiver chains 710, one or more transmitter chains 712, or a combination thereof.

[0143] A receiver chain 710 may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receiver chain 710 may include one or more antennas for receive the signal over the air or wireless medium. The receiver chain 710 may include at least one amplifier (e.g., a low-noise amplifier (LN A)) configured to amplify the received signal. The receiver chain 710 may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receiver chain 710 may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

[0144] A transmitter chain 712 may be configured to generate and transmit signals (e.g., control information, data, packets). The transmitter chain 712 may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM), frequency modulation (FM), or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The transmitter chain 712 may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmitter chain 712 may also include one or more antennas for transmitting the amplified signal into the air or wireless medium.

[0145] Figure 8 illustrates a flowchart of a method 800 in accordance with aspects of the present disclosure. The operations of the method may be implemented by a NE (e.g., a consumer entity, such as an AF or an AF server) as described herein. In some implementations, the NE may execute a set of instructions to control the function elements of the NE to perform the described functions.

[0146] At 802, the method 800 may include transmitting, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associatedwith one or more QoS parameters in an area of interest. The operations of 802 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 802 may be performed by a NE as described with reference to Figure 7.

[0147] At 804, the method 800 may include receiving, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest. The operations of 804 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 804 may be performed by a NE as described with reference to Figure 7.

[0148] It should be noted that the method 800 described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0149] Figure 9 illustrates a flowchart of a method 900 in accordance with aspects of the present disclosure. The operations of the method 900 may be implemented by a NE (e.g., a NWDAF) as described herein. In some implementations, the NE may execute a set of instructions to control the function elements of the NE to perform the described functions.

[0150] At 902, the method 900 may include receiving, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest. The operations of 902 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 902 may be performed by a NE as described with reference to Figure 7.

[0151] At 904, the method 900 may include generating at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest. The operations of 904 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 904 may be performed by a NE as described with reference to Figure 7.

[0152] At 906, the method 900 may include transmitting, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints. The operations of 906 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 906 may be performed a NE as described with reference to Figure 7.

[0153] It should be noted that the method 900 described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0154] Figure 10 illustrates a flowchart of a method 1000 in accordance with aspects of the present disclosure. The operations of the method 1000 may be implemented by a UE as described herein. In some implementations, the UE may execute a set of instructions to control the function elements of the UE to perform the described functions.

[0155] At 1002, the method 1000 may include transmitting, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest. The operations of 1002 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1002 may be performed by a UE as described with reference to Figure 5.

[0156] At 1004, the method 1000 may include receiving, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest. The operations of 1004 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1004 may be performed by a UE as described with reference to Figure 5.

[0157] It should be noted that the method 1000 described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0158] Figure 11 illustrates a flowchart of a method 1100 in accordance with aspects of the present disclosure. The operations of the method 1100 may be implemented by aprocessor as described herein. In some implementations, the UE may execute a set of instructions to control the function elements of the UE to perform the described functions.

[0159] At 1102, the method 1100 may include outputting a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest. The operations of 1102 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1102 may be performed by a processor as described with reference to Figure 6.

[0160] At 1104, the method 1100 may include inputting a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest. The operations of 1104 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1104 may be performed by a processor as described with reference to Figure 6.

[0161] It should be noted that the method 1100 described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0162] The disclosure herein provides, a consumer entity for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the consumer entity to: transmit, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and receive, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0163] The at least one processor may be further configured to: receive, from a user equipment, UE, a second request for a navigation route for maximizing the sustainability of the QoS flow, wherein the navigation route is associated with the area of interest; generate,based on the at least one set of waypoints, the navigation route; and transmit, to the UE, a second response comprising the navigation route.

[0164] In the present disclosure, a consumer entity requests a network function of a wireless communication network to provide predictive analytics (i.e., waypoints) for a UE travelling between first and second locations. The waypoints are selected to maximise the probability of sustaining a QoS flow. This may take into account real-time network data, congestion and other relevant metrics. The waypoints can then be provided to and used by the consumer entity, such as a navigation application server, to generate an optimal navigation route for the UE for travelling between the first and second locations.Accordingly, the UE can travel between the first and second locations whilst maintaining its QoS flow. Accordingly, the present disclosure provides the ability for a UE to request a navigation route that sustains a certain QoS level for a QoS flow, with the mobile network able to obtain analytics and respond with an optimised set of waypoints for generating a navigation route in response to the request.

[0165] A first location as referred to herein may also be referred to herein as an origin point. A second location as referred to herein may be referred to herein as a destination point.

[0166] A UE as referred to herein may comprise a vehicle.

[0167] Each set of waypoints referred to herein may correspond to waypoints that should be followed by the UE to sustain the QoS flow. Expressed differently, each set of waypoints if followed by the UE tends to maximize the probability of sustaining the QoS flow.

[0168] The generation of the navigation route may also be based on road traffic conditions and / or fuel consumption.

[0169] The area of interest may comprise the first location and second location.

[0170] The first request for analytics may be provided as a HTTP request message, such as an HTTP post message. Said message may include several key-value pairs in their respective payloads.

[0171] The first response may be an HTTP response message or notification message including several key-value pairs. This may include an identifier for the analytics (the path_for_max_QoS_sustainability). This may include a PathForMaxSustainbilitylnfo element for each set of waypoints.

[0172] The first request for predictive analytics is for maximizing the sustainability of a QoS flow associated with one or more QoS parameters in an area of interest. Expressed differently, the first request for predictive analytics is for maximizing the sustainability of a QoS flow having one or more QoS parameters in an area of interest. The first request may also be referred to herein as being for maximizing the sustainability of one or more QoS parameters of a QoS flow in an area of interest.

[0173] The second request may comprise at least one of: an identifier of the QoS flow; the one or more QoS parameters; the area of interest; or an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0174] The one or more QoS parameters may comprise at least one of: a GBR for uplink; a GBR for downlink; or a latency requirement.

[0175] The first request for predictive analytics may comprise at least one of: the one or more QoS parameters; the area of interest; a first cell associated with a first location in the area of interest; a second cell associated with a second location in the area of interest; an identifier of the UE; or an identifier for the predictive analytics. The area of interest may comprise the first location and the second location, for instance.

[0176] The identifier for the predictive analytics may indicate the type of analytics being requested. The identifier for the predictive analytics (also referred to as an analytics ID) may be a new value referred to as “Path_For_Max_QoS_Sustainability” that indicates the first network entity is to predict a path (a set of list of waypoints) that maximises a probability of the UE to sustain the QoS flow.

[0177] The at least one processor may be further configured to cause the consumer entity to: transmit the first request to the first network entity NEF and receive the first response from the first network entity via the NEF; and / or transmit the first request to thefirst network entity via a CAMARA API and receive the first response from the first network entity via the CAMARA API.

[0178] The CAMARA Alliance is an open, collaborative initiative that focuses on defining and developing standardized APIs for telecommunication networks. These APIs tend to make telecommunication networks programmable and enable external applications to access network capabilities and indicate their communication requirements. The CAMARA API may be supported and delivered through an operator platform (for instance in the telecommunication network). The consumer entity may generate and send the first request to the operator platform via the CAMARA API. The operator platform may then transform the first request into another request that is transmitted to the first network entity (directly or via the NEF).The first response may be a response received by the CAMARA API and transformed into a CAMARA response received by the consumer entity.

[0179] The consumer entity may comprise at least one of an AF or an AF server; and / or the first network entity comprises a NWDAF.

[0180] The first response may further comprise a confidence level for each respective set of waypoints.

[0181] The confidence level may relate to how certain the prediction model used by the first network entity is that the set of waypoints maximises the probability to sustain the QoS flow.

[0182] A way point may be associated with a base station, for instance that serves a UE. The waypoint may have a circular area in latitude and longitude that is centred on the base station. The radius of the circular area may indicate how close a UE should remain to the base station to have sufficiently good signal quality and minimize probability for the base station to abnormally release the QoS flow. The waypoints may be defined in accordance with the 3GPP specification TS 23.288, titled “Architecture enhancements for 5G System (5GS) to support network data analytics services”.

[0183] There is further provided a first network entity for wireless communication comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the first network entity to: receive, from a consumerentity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generate at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmit, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0184] The one or more QoS parameters may comprise at least one of: a GBR for uplink; a GBR for downlink; or a latency requirement.

[0185] The first request may be associated with a navigation route for a UE. The navigation route may be associated with the area of interest.

[0186] The UE may comprise a vehicle.

[0187] The first request for predictive analytics may comprise at least one of: the one or more QoS parameters; the area of interest a first cell associated with a first location in the area of interest; a second cell associated with a second location in the area of interest; an identifier of the UE; or an identifier for the predictive analytics. The area of interest may comprise the first location and the second location, for instance.

[0188] The at least one processor may be further configured to cause the first network entity to generate the at least one set of waypoints based on at least one of: the first request or a part thereof; a real time data of conditions of a wireless communication network; a predicted data of conditions of the wireless communication network; or a historical data of conditions of the wireless communication network.

[0189] The real-time, predicted and / or historical data may comprise cell load, interference levels, handover success rates, predicted mobility patterns, QoS sustainability thresholds.

[0190] The at least one processor may be further configured to cause the first network entity to: receive the first request from the consumer entity via a NEF, and transmit the first response to the consumer entity via the NEF; and / or receive the first request from theconsumer entity via a CAMARA. API and transmit the first response to the consumer entity via the CAMARA API.

[0191] The first response may further comprise a confidence level for each respective set of waypoints.

[0192] Each waypoint may be associated with the location of a base station.

[0193] The consumer entity may comprise at least one of an AF or an AF server; and / or the first network entity may comprise a NWDAF.

[0194] There is further provided a UE for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the UE to: transmit, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and receive, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0195] The one or more QoS parameters may comprise at least one of: a QoS identifier, a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5G QoS identifier (5QI).

[0196] The second request may comprise at least one of: an identifier of the QoS flow; the one or more QoS parameters; the area of interest; or an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0197] The consumer entity may comprise at least one of: an AF; or an AF server. The AF may be a navigation application. The AF server may be a navigation AF server.

[0198] The UE may comprise a vehicle such as an emergency vehicle.

[0199] There is further provided a processor for wireless communication, comprising: at least one controller coupled with at least one memory and configured to cause the processor to: output a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route isassociated with an area of interest; and input a second response comprising the navigation route, the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0200] The one or more QoS parameters may comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5 QI.

[0201] The second request may comprise an identifier of the QoS flow; the one or more QoS parameters; the area of interest; and an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0202] There is further provided a method performed by a consumer entity for wireless communication, comprising: transmitting, to a first network entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; and receiving, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

[0203] The method may comprise receiving, from a UE, a second request for a navigation route for maximizing the sustainability of the QoS flow, wherein the navigation route is associated with the area of interest; generating, based on the at least one set of waypoints, the navigation route; and transmitting, to the UE, a second response comprising the navigation route.

[0204] The second request may comprise at least one of: an identifier of the QoS flow; the one or more QoS parameters; the area of interest; or an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0205] The one or more QoS parameters may comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5 QI.

[0206] The first request for predictive analytics may comprise at least one of: the one or more QoS parameters; the area of interest; a first cell associated with a first location in the area of interest; a second cell associated with a second location in the area of interest; an identifier of the UE; or an identifier for the predictive analytics. The area of interest may comprise the first location and the second location, for instance.

[0207] The method may comprise transmitting the first request to the first network entity via a NEF and receiving the first response from the first network entity via the NEF; and / or transmitting the first request to the first network entity via a CAMARA API and receiving the first response from the first network entity via the CAMARA API.

[0208] The consumer entity may comprise at least one of an AF or an AF server. The first network entity may comprise a NWDAF.

[0209] The first response may further comprise a confidence level for each respective set of waypoints.

[0210] There is further provided a method performed by a first network entity for wireless communication, comprising: receiving, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generating at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmitting, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

[0211] The one or more QoS parameters may comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5 QI.

[0212] The first request may be associated with a navigation route for a UE. The navigation route may be associated with the area of interest.

[0213] The first request for predictive analytics may comprise at least one of: the one or more QoS parameters; the area of interest; a first cell associated with a first location in the area of interest; a second cell associated with a second location in the area of interest; anidentifier of the UE; or an identifier for the predictive analytics. The area of interest may comprise the first location and the second location, for instance.

[0214] The at least one set of waypoints may be based on at least one of: the first request or a part thereof; a real time data of conditions of a wireless communication network; a predicted data of conditions of the wireless communication network; or a historical data of conditions of the wireless communication network.

[0215] The first response may further comprise a confidence level for each respective set of waypoints.

[0216] Each waypoint may be associated with the location of a base station.

[0217] The consumer entity may comprise at least one of an AF or an AF server. The first network entity may comprise a NWDAF.

[0218] There is further provided a method performed by a UE for wireless communication, comprising: transmitting, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and receiving, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

[0219] The one or more QoS parameters may comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5 QI.

[0220] The second request may comprise at least one of: an identifier of the QoS flow; the one or more QoS parameters; the area of interest; or an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0221] The consumer entity may comprise at least one of: an AF; or an AF server. The AF may be a navigation application. The AF server may be a navigation AF server.

[0222] There is further provided a method performed by a processor for wireless communication, comprising: outputting a second request for a navigation route formaximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and inputting a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow.

[0223] The one or more QoS parameters may comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement. The QoS identifier may be a 5 QI.

[0224] The second request may comprise an identifier of the QoS flow; the one or more QoS parameters; the area of interest; and an identifier of the UE. The area of interest may comprise the first location and the second location, for instance.

[0225] The disclosure herein tends to solve the problem of ensuring the sustainability of a specific QoS level for vehicles traveling between two points in a 5G network, especially in scenarios where strict QoS requirements, such as GBR or low latency, are necessary. Current navigation systems do not account for network congestion that may impact QoS flows. By providing real-time network analytics that predict an optimal route avoiding congested areas, this system tends to assist a UE (such as a vehicle) maintain the required QoS for their communications, such as emergency vehicle telemetry or video feeds, as they travel through various network zones.

[0226] In 5G networks, the NWDAF may offer "QoS Sustainability" analytics that provide notifications when the probability of maintaining a specific QoS flow decreases due to network congestion. While these notifications help applications take preventive actions, they do not offer guidance on determining optimal navigation routes to sustain QoS levels. Current navigation systems, such as local or online mapping systems (i.e., Google Maps™), may optimize routes based on road traffic and travel time but may not consider network conditions that impact communication services. This limitation leaves a gap in ensuring the continuity of QoS for critical applications during travel.

[0227] The disclosure herein provides a method and system for optimizing vehicle navigation routes by predicting the path that maximizes the probability of sustaining a specific QoS level in wireless communication systems (such as 5G / 6G networks). Itleverages real-time and historical network analytics to identify waypoints that avoid congested areas, ensuring critical communication flows, such as GBR or low latency services, are maintained. By integrating these network insights into navigation systems, the disclosure herein allows for the guiding of vehicles along routes that prioritize stable network performance, addressing gaps in current navigation systems that do not account for network QoS sustainability.

[0228] There is provided a method for providing network analytics to maximize the probability of sustaining a certain QoS level, the method comprising: receiving, at an AF, a request from a vehicle or user for network analytics that predict a path to meet specified QoS parameters; communicating the request from the AF to a NWDAF via a NEF; determining, at the NWDAF, network analytics that predict a path maximizing the probability of sustaining the QoS level based on real-time and predictive network data; and providing the path analytics to the AF.

[0229] The QoS parameters may include a GBR for uplink and / or downlink, and a 5QI.

[0230] The NWDAF may determine the path analytics based on network conditions including cell load, interference levels, handover success rates, predicted mobility patterns, and QoS Sustainability thresholds.

[0231] There is further provides a system for providing network analytics to maximize the probability of sustaining a specified QoS level, comprising: an AF configured to receive a request from a vehicle or user for network analytics and communicate with a NWDAF via a NEF; a NWDAF configured to provide network analytics that predict a path maximizing the probability of sustaining a specified QoS level.

[0232] It should be noted that the method described herein describes a possible implementation, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible.

[0233] The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, thedisclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

[0234] The following abbreviations are relevant in the field addressed by this document: 5GC, 5G Core; 5QI, 5G QoS Identifier; AMF, Access and Mobility Management Function; ANC, Access Node Controller; AF, Application Function; API, Application Programming Interface; CDMA, Code Division Multiple Access; CN, Core Network; D2D, Device to Device; EM, Electromagnetic; EPC, Evolved packet core; 5G, Fifth Generation; 4G, Fourth Generation; FDMA, Frequency Division Multiple Access; GBR, Guaranteed Bit Rate; loE, Internet of Everything; loT, Internet of Things; MTC, Machine Type Communication; MME, Mobility Management Entity; NWDAF, Network Data Analytics Function; NE, Network Equipment; NEF, Network Exposure Function; NAS, Non Access Stratum; NTN, Non Terrestrial Network; PDN, Packet Data Network; PDU, Protocol Data Unit; QoS, Quality of Service; RAN, Radio Access Network; S-GW, Serving Gateway; 6G, Sixth Generation; 3G, Third Generation; TDMA, Time Division Multiple Access; TRP, Transmit Receive Point; UWB, Ultrawideband; UE, User Equipment; UPF, User Plane Function; V2X, Vehicle to Everything; and V2V, Vehicle to Vehicle.

Claims

CLAIMSWhat is claimed is:

1. A consumer entity for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the consumer entity to: transmit, to a first network entity, a first request for predictive analytics for maximizing sustainability of a Quality of Service, QoS, flow associated with one or more QoS parameters in an area of interest; and receive, from the first network entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest.

2. The consumer entity of claim 1 , wherein the at least one processor is further configured to: receive, from a user equipment, UE, a second request for a navigation route for maximizing sustainability of the QoS flow, wherein the navigation route is associated with the area of interest; generate, based on the at least one set of waypoints, the navigation route; and transmit, to the UE, a second response comprising the navigation route.

3. The consumer entity of claim 2, wherein the second request comprises at least one of: an identifier of the QoS flow; the one or more QoS parameters; the area of interest; or an identifier of the UE.

4. The consumer entity of any one of claims 1-3, wherein the one or more QoS parameters comprise at least one of:a QoS identifier; a guaranteed bit rate, GBR, for uplink; a GBR for downlink; or a latency requirement.

5. The consumer entity of any one of claims 2-4, wherein the first request for predictive analytics comprises at least one of: the one or more QoS parameters; the area of interest; a first cell associated with a first location in the area of interest; a second cell associated with a second location in the area of interest; an identifier of the UE; or an identifier for the predictive analytics.

6. The consumer entity of any one of claims 1-5, where the at least one processor is further configured to cause the consumer entity to: transmit the first request to the first network entity via a network exposure function, NEF, and receive the first response from the first network entity via the NEF; and / or transmit the first request to the first network entity via a CAMARA application programming interface, API, and receive the first response from the first network entity via the CAMARA API.

7. The consumer entity of any one of claims 1-6, wherein: the consumer entity comprises at least one of an application function or an application function server; and / or the first network entity comprises a network data analytics function, NWDAF.

8. The consumer entity of any one of claims 1-7, wherein the first response further comprises a confidence level for each respective set of waypoints.

9. The consumer entity of any one of the preceding claims, wherein each waypoint is associated with a location of a base station.

10. A first network entity for wireless communication comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the first network entity to: receive, from a consumer entity, a first request for predictive analytics for maximizing sustainability of a QoS flow associated with one or more QoS parameters in an area of interest; generate at least one set of waypoints, each set of waypoints for maximizing the sustainability of the QoS flow in the area of interest; and transmit, to the consumer entity, a first response comprising the predictive analytics, wherein the predictive analytics comprise the at least one set of waypoints.

11. The first network entity of claim 10, wherein the one or more QoS parameters comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement.

12. The first network entity of any one of claims 10-11, wherein the first request is associated with a navigation route for a UE, the navigation route being associated with the area of interest.

13. The first network entity of claim 12, wherein the first request for predictive analytics comprises at least one of: the one or more QoS parameters; the area of interest; a first cell associated with a first location in the area of interest;a second cell associated with a second location in the area of interest; an identifier of the UE; or an identifier for the predictive analytics.

14. The first network entity of any one of claims 10-13, wherein the at least one processor is further configured to cause the first network entity to generate the at least one set of waypoints based on at least one of: the first request or a part thereof; a real time data of conditions of a wireless communication network; a predicted data of conditions of the wireless communication network; or a historical data of conditions of the wireless communication network.

15. The first network entity of any one of claims 10-14, wherein the first response further comprises a confidence level for each respective set of waypoints.

16. The first network entity of any one of claims 10-15, wherein each waypoint is associated with a location of a base station.

17. The first network entity of any one of claims 10-16, wherein: the consumer entity comprises at least one of an application function or an application function server; and / or the first network entity comprises a NWDAF.

18. A UE for wireless communication, comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the UE to: transmit, to a consumer entity, a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; andreceive, from the consumer entity, a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

19. The UE of claim 18, wherein the one or more QoS parameters comprise at least one of: a QoS identifier; a GBR for uplink; a GBR for downlink; or a latency requirement.

20. A processor for wireless communication, comprising: at least one controller coupled with at least one memory and configured to cause the processor to: output a second request for a navigation route for maximizing sustainability of a QoS flow associated with one or more QoS parameters, wherein the navigation route is associated with an area of interest; and input a second response comprising the navigation route, wherein the navigation route is based on a respective set of waypoints that maximize the sustainability of the QoS flow in the area of interest.

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