PATENT DOCUMENT

Publication Number: US-12058543-B2
Application Number: US-202318213072-A
Country: US
Kind Code: B2

Title: RAN condition and cell composite load indicators

Abstract:
An apparatus of a management service equipment includes processing circuitry. To configure the management service equipment for measuring a plurality of key performance indicators (KPIs) in a 5G network with a plurality of network functions (NFs), the processing circuitry is to retrieve using a data analytic function of the management service equipment, a plurality of performance measurements associated with a cell of a radio access network (RAN) within the 5G network. A KPI of the plurality of KPIs associated with the cell is generated using the data analytic function of the management service equipment, based on the plurality of performance measurements. The KPI is encoded for transmission to a service application executing on a user equipment (UE) active within the cell of the RAN or executing within a cloud architecture.

Claims:
What is claimed is: 
     
       1. An apparatus comprising:
 one or more processors for configuring a management service equipment for measuring a plurality of key performance indicators (KPIs) in a cellular network with a plurality of network functions (NFs), the one or more processors are configured to cause the management service equipment to:
 retrieve a plurality of performance measurements associated with a cell of a radio access network (RAN) within the cellular network; 
 generate a KPI of the plurality of KPIs associated with the cell, based on the plurality of performance measurements, wherein the plurality of performance measurements are related to one or more of: a number of handover failures, a number of resource control (RRC) connection setup failures, or a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell; and 
 encode the KPI for transmission. 
 
 
     
     
       2. The apparatus of  claim 1 , wherein the one or more processors are configured to cause the management service equipment to:
 retrieve the plurality of performance measurements from at least one NF of the plurality of NFs. 
 
     
     
       3. The apparatus of  claim 1 , wherein the generated KPI is a RAN condition KPI associated with a condition of RAN latency of the cell. 
     
     
       4. The apparatus of  claim 1 , wherein the plurality of performance measurements comprise a number of radio resource control (RRC) connection setup failures experienced for a predetermined duration interval within the cell. 
     
     
       5. The apparatus of  claim 1 , wherein the plurality of performance measurements comprise a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell. 
     
     
       6. The apparatus of  claim 1 , wherein the one or more processors are configured to cause the management service equipment to:
 retrieve alarm information or configuration information associated with communication conditions for the cell; and 
 generate the KPI of the plurality of KPIs associated with the cell, further based on the alarm information or the configuration information. 
 
     
     
       7. The apparatus of  claim 6 , wherein the alarm information is a cell overload alarm indicating the cell is associated with more than a threshold number of active user equipment (UE) devices. 
     
     
       8. The apparatus of  claim 1 , wherein the KPI is an integer indicating at least one of the following communication conditions of the cell: a normal (healthy) cell, an out-of-service cell, a capacity constraint indicating an overloaded cell, and a capability constraint indicating the cell does not support latency requirements. 
     
     
       9. The apparatus of  claim 1 , further comprising transceiver circuitry coupled to the one or more processors and one or more antennas coupled to the transceiver circuitry, and wherein the one or more processors are configured to cause the management service equipment to:
 decode navigation information received from an autonomous driving-navigation application, the navigation information indicating a planned navigation route through the cell and at least one neighboring cell; 
 determine the KPI in response to the received navigation information; and 
 encode the KPI for transmission to the autonomous driving-navigation application, the autonomous driving-navigation application configured to modify the planned navigation route based on the KPI. 
 
     
     
       10. A non-transitory memory medium for operating a network node configured for generating a plurality of key performance indicators (KPIs) in a cellular network with a plurality of network functions (NFs), wherein the non-transitory memory medium stores program instructions executable by one or more processors of the network node to:
 retrieve a plurality of performance measurements associated with a cell of a radio access network (RAN) within the cellular network; 
 generate a KPI of the plurality of KPIs associated with the cell, based on the plurality of performance measurements, wherein the plurality of performance measurements are related to one or more of: a number of handover failures, a number of resource control (RRC) connection setup failures, or a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell; and 
 encode the KPI for transmission. 
 
     
     
       11. The non-transitory memory medium of  claim 10 , wherein the generated KPI is a RAN condition KPI associated with a condition of RAN latency of the cell. 
     
     
       12. The non-transitory memory medium of  claim 10 , wherein the plurality of performance measurements comprise a number of radio resource control (RRC) connection setup failures experienced for a predetermined duration interval within the cell. 
     
     
       13. The non-transitory memory medium of  claim 10 , wherein the plurality of performance measurements comprise a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell. 
     
     
       14. The non-transitory memory medium of  claim 10 , wherein the KPI is an integer indicating at least one of the following communication conditions of the cell: a normal (healthy) cell, an out-of-service cell, a capacity constraint indicating an overloaded cell, and a capability constraint indicating the cell does not support latency requirements. 
     
     
       15. The non-transitory memory medium of  claim 10 , wherein the program instructions are further executable to:
 decode navigation information received from an autonomous driving-navigation application, the navigation information indicating a planned navigation route through the cell and at least one neighboring cell; 
 determine the KPI in response to the received navigation information; and 
 encode the KPI for transmission to the autonomous driving-navigation application, the autonomous driving-navigation application configured to modify the planned navigation route based on the KPI. 
 
     
     
       16. A method for operating a network node configured for generating a plurality of key performance indicators (KPIs) in a cellular network with a plurality of network functions (NFs), comprising: 
       by the network node:
 retrieving a plurality of performance measurements associated with a cell of a radio access network (RAN) within the cellular network; 
 generating a KPI of the plurality of KPIs associated with the cell, based on the plurality of performance measurements, wherein the plurality of performance measurements are related to one or more of: a number of handover failures, a number of resource control (RRC) connection setup failures, or a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell; and 
 encoding the KPI for transmission. 
 
     
     
       17. The method of  claim 16 , wherein the generated KPI is a RAN condition KPI associated with a condition of RAN latency of the cell. 
     
     
       18. The method of  claim 16 , wherein the plurality of performance measurements comprise a number of radio resource control (RRC) connection setup failures experienced for a predetermined duration interval within the cell. 
     
     
       19. The method of  claim 16 , wherein the plurality of performance measurements comprise a number of random access channel (RACH) procedure failures experienced for a predetermined duration interval within the cell. 
     
     
       20. The method of  claim 16 , further comprising:
 decoding navigation information received from an autonomous driving-navigation application, the navigation information indicating a planned navigation route through the cell and at least one neighboring cell; 
 determining the KPI in response to the received navigation information; and 
 encoding the KPI for transmission to the autonomous driving-navigation application, the autonomous driving-navigation application configured to modify the planned navigation route based on the KPI.

Description:
This application is a continuation of U.S. application Ser. No. 17/257,925, filed Jan. 5, 2021, entitled “RAN Condition and Cell Composite Load Indicators”, which is a U.S. National Stage filing of International Application No. PCT/US2019/045514, filed Aug. 7, 2019, entitled “RAN Condition and Cell Composite Load Indicators”, which claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 62/716,443, filed Aug. 9, 2018, entitled “RAN Condition and Cell Composite Load KPIS, each of which are incorporated herein by reference in their entirety. 
     The claims in the instant application are different than those of the parent application or other related applications. The Applicant therefore rescinds any disclaimer of claim scope made in the parent application or any predecessor application in relation to the instant application. The Examiner is therefore advised that any such previous disclaimer and the cited references that it was made to avoid, may need to be revisited. Further, any disclaimer made in the instant application should not be read into or against the parent application or other related applications. 
     PRIORITY CLAIM 
     This application claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 62/716,443, filed Aug. 9, 2018, and entitled “RAN CONDITION AND CELL COMPOSITE LOAD KPIS,” which provisional patent application is incorporated herein by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     Aspects pertain to wireless communications. Some aspects relate to wireless networks including 3GPP (Third Generation Partnership Project) is networks, 3GPP LTE (Long Term Evolution) networks, 3GPP LTE-A (LTE Advanced) networks, and fifth-generation (5G) networks including 5G new radio (NR) (or 5G-NR) networks and 5G-LTE networks. Other aspects are directed to systems and methods for providing key performance indicators (KPIs), such as radio access network (RAN) condition and cell composite load indicators in 5G networks. 
     BACKGROUND 
     Mobile communications have evolved significantly from early voice systems to today&#39;s highly sophisticated integrated communication platform. With the increase in different types of devices communicating with various network devices, usage of 3GPP LTE systems has increased. The penetration of mobile devices (user equipment or UEs) in modern society has continued to drive demand for a wide variety of networked devices in a number of disparate environments. Fifth generation (5G) wireless systems are forthcoming and are expected to enable even greater speed, connectivity, and usability. Next generation 5G networks (or NR networks) are expected to increase throughput, coverage, and robustness and reduce latency and operational and capital expenditures. 5G-NR networks will continue to evolve based on 3GPP LTE-Advanced with additional potential new radio access technologies (RATs) to enrich people&#39;s lives with seamless wireless connectivity solutions delivering fast, rich content and services. As current cellular network frequency is saturated, higher frequencies, such as millimeter wave (mmWave) frequency, can be beneficial due to their high bandwidth. 
     Potential LTE operation in the unlicensed spectrum includes (and is not limited to) the LTE operation in the unlicensed spectrum via dual connectivity (DC), or DC-based LAA, and the standalone LTE system in the unlicensed spectrum, according to which LTE-based technology solely operates in unlicensed spectrum without requiring an “anchor” in the licensed spectrum, called MulteFire. MulteFire combines the performance benefits of LTE technology with the simplicity of Wi-Fi-like deployments. 
     Further enhanced operation of LTE systems in the licensed as well as unlicensed spectrum is expected in future releases and 5G systems. Such enhanced operations can include techniques for providing KPIs, such as RAN condition and cell composite load indicators in 5G networks. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       In the figures, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The figures illustrate generally, by way of example, but not by way of limitation, various aspects discussed in the present document. 
         FIG.  1 A  illustrates an architecture of a network, in accordance with some aspects. 
         FIG.  1 B  and  FIG.  1 C  illustrate a non-roaming 5G system architecture in accordance with some aspects. 
         FIG.  2    illustrates components of an exemplary 5G-NR architecture with control unit control plane (CU-CP)—control unit user plane (CU-UP) separation, in accordance with some aspects. 
         FIG.  3    illustrates generation of data analytic KPIs by a data analytic function within a management system of a 5G network, in accordance with some aspects. 
         FIG.  4    illustrates a use case for a RAN condition KPI use in connection with outer navigation assistance, in accordance with some aspects. 
         FIG.  5    illustrates a block diagram of a communication device such as an evolved Node-B (eNB), a new generation Node-B (gNB), an access point (AP), a wireless station (STA), a mobile station (MS), or a user equipment (UE), in accordance with some aspects. 
     
    
    
     DETAILED DESCRIPTION 
     The following description and the drawings sufficiently illustrate aspects to enable those skilled in the art to practice them. Other aspects may incorporate structural, logical, electrical, process, and other changes. Portions and features of some aspects may be included in, or substituted for, those of other aspects. Aspects set forth in the claims encompass all available equivalents of those claims. 
       FIG.  1 A  illustrates an architecture of a network in accordance with some aspects. The network  140 A is shown to include user equipment (UE)  101  and UE  102 . The UEs  101  and  102  are illustrated as smartphones (e.g., handheld touchscreen mobile computing devices connectable to one or more cellular networks) but may also include any mobile or non-mobile computing device, such as Personal Data Assistants (PDAs), pagers, laptop computers, desktop computers, wireless handsets, drones, or any other computing device including a wired and/or wireless communications interface. The UEs  101  and  102  can be collectively referred to herein as UE  101 , and UE  101  can be used to perform one or more of the techniques disclosed herein. 
     Any of the radio links described herein (e.g., as used in the network  140 A or any other illustrated network) may operate according to any exemplary radio communication technology and/or standard. 
     LTE and LTE-Advanced are standards for wireless communications of high-speed data for UE such as mobile telephones. In LTE-Advanced and various wireless systems, carrier aggregation is a technology according to which multiple carrier signals operating on different frequencies may be used to carry communications for a single UE, thus increasing the bandwidth available to a single device. In some aspects, carrier aggregation may be used where one or more component carriers operate on unlicensed frequencies. 
     Aspects described herein can be used in the context of any spectrum management scheme including, for example, dedicated licensed spectrum, unlicensed spectrum, (licensed) shared spectrum (such as Licensed Shared Access (LSA) in 2.3-2.4 GHz, 3.4-3.6 GHz, 3.6-3.8 GHz, and further frequencies and Spectrum Access System (SAS) in 3.55-3.7 GHz and further frequencies). 
     Aspects described herein can also be applied to different Single Carrier or OFDM flavors (CP-OFDM, SC-FDMA, SC-OFDM, filter bank-based multicarrier (FBMC), OFDMA, etc.) and in particular 3GPP NR (New Radio) by allocating the OFDM carrier data bit vectors to the corresponding symbol resources. 
     In some aspects, any of the UEs  101  and  102  can comprise an Internet-of-Things (IoT) UE or a Cellular IoT (CIoT) UE, which can comprise a network access layer designed for low-power IoT applications utilizing short-lived UE connections. In some aspects, any of the UEs  101  and  102  can include a narrowband (NB) IoT UE (e.g., such as an enhanced NB-IoT (eNB-IoT) UE and Further Enhanced (FeNB-IoT) UE). An IoT UE can utilize technologies such as machine-to-machine (M2M) or machine-type communications (MTC) for exchanging data with an MTC server or device via a public land mobile network (PLMN), Proximity-Based Service (ProSe) or device-to-device (D2D) communication, sensor networks, or IoT networks. The M2M or MTC exchange of data may be a machine-initiated exchange of data. An IoT network includes interconnecting IoT UEs, which may include uniquely identifiable embedded computing devices (within the Internet infrastructure), with short-lived connections. The IoT UEs may execute background applications (e.g., keep-alive messages, status updates, etc.) to facilitate the connections of the IoT network. 
     In some aspects, any of the UEs  101  and  102  can include enhanced MTC (eMTC) UEs or further enhanced MTC (FeMTC) UEs. 
     The UEs  101  and  102  may be configured to connect, e.g., communicatively couple, with a radio access network (RAN)  110 . The RAN  110  may be, for example, an Evolved Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (E-UTRAN), a NextGen RAN (NG RAN), or some other type of RAN. The UEs  101  and  102  utilize connections  103  and  104 , respectively, each of which comprises a physical communications interface or layer (discussed in further detail below); in this example, the connections  103  and  104  are illustrated as an air interface to enable communicative coupling, and can be consistent with cellular communications protocols, such as a Global System for Mobile Communications (GSM) protocol, a code-division multiple access (CDMA) network protocol, a Push-to-Talk (PTT) protocol, a PTT over Cellular (POC) protocol, a Universal Mobile Telecommunications System (UMTS) protocol, a 3GPP Long Term Evolution (LTE) protocol, a fifth generation (5G) protocol, a New Radio (NR) protocol, and the like. 
     In an aspect, the UEs  101  and  102  may further directly exchange communication data via a ProSe interface  105 . The ProSe interface  105  may alternatively be referred to as a sidelink interface comprising one or more logical channels, including but not limited to a Physical Sidelink Control Channel (PSCCH), a Physical Sidelink Shared Channel (PSSCH), a Physical Sidelink Discovery Channel (PSDCH), and a Physical Sidelink Broadcast Channel (PSBCH). 
     The UE  102  is shown to be configured to access an access point (AP)  106  via connection  107 . The connection  107  can comprise a local wireless connection, such as, for example, a connection consistent with any IEEE 802.11 protocol, according to which the AP  106  can comprise a wireless fidelity (WiFi®) router. In this example, the AP  106  is shown to be connected to the Internet without connecting to the core network of the wireless system (described in further detail below). 
     The RAN  110  can include one or more access nodes that enable the connections  103  and  104 . These access nodes (ANs) can be referred to as base stations (BSs), NodeBs, evolved NodeBs (eNBs), Next Generation NodeBs (gNBs), RAN nodes, and the like, and can comprise ground stations (e.g., terrestrial access points) or satellite stations providing coverage within a geographic area (e.g., a cell). In some aspects, the communication nodes  111  and  12  can be transmission/reception points (TRPs). In instances when the communication nodes  111  and  112  are NodeBs (e.g., eNBs or gNBs), one or more TRPs can function within the communication cell of the NodeBs. The RAN  110  may include one or more RAN nodes for providing macrocells, e.g., macro RAN node  111 , and one or more RAN nodes for providing femtocells or picocells (e.g., cells having smaller coverage areas, smaller user capacity, or higher bandwidth compared to macrocells), e.g., low power (LP) RAN node  112 . 
     Any of the RAN nodes  111  and  112  can terminate the air interface protocol and can be the first point of contact for the UEs  101  and  102 . In some aspects, any of the RAN nodes  111  and  112  can fulfill various logical functions for the RAN  110  including, but not limited to, radio network controller (RNC) functions such as radio bearer management, uplink and downlink dynamic radio resource management and data packet scheduling, and mobility management. In an example, any of the nodes  111  and/or  112  can be a new generation node-B (gNB), an evolved node-B (eNB), or another type of RAN node. 
     The RAN  110  is shown to be communicatively coupled to a core network (CN)  120  via an S1 interface  113 . In aspects, the CN  120  may be an evolved packet core (EPC) network, a NextGen Packet Core (NPC) network, or some other type of CN (e.g., as illustrated in reference to  FIGS.  1 B- 1 I ). In this aspect, the S1 interface  113  is split into two parts: the S1-U interface  114 , which carries traffic data between the RAN nodes  111  and  112  and the serving gateway (S-GW)  122 , and the S1-mobility management entity (MME) interface  115 , which is a signaling interface between the RAN nodes  111  and  112  and MMEs  121 . 
     In this aspect, the CN  120  comprises the MMEs  121 , the S-GW  122 , the Packet Data Network (PDN) Gateway (P-GW)  123 , and a home subscriber server (HSS)  124 . The MMEs  121  may be similar in function to the control plane of legacy Serving General Packet Radio Service (GPRS) Support Nodes (SGSN). The MMEs  121  may manage mobility aspects in access such as gateway selection and tracking area list management. The HSS  124  may comprise a database for network users, including subscription-related information to support the network entities&#39; handling of communication sessions. The CN  120  may comprise one or several HSSs  124 , depending on the number of mobile subscribers, on the capacity of the equipment, on the organization of the network, etc. For example, the HSS  124  can provide support for routing/roaming, authentication, authorization, naming/addressing resolution, location dependencies, etc. 
     The S-GW  122  may terminate the S1 interface  113  towards the RAN  110 , and routes data packets between the RAN  110  and the CN  120 . In addition, the S-GW  122  may be a local mobility anchor point for inter-RAN node handovers and also may provide an anchor for inter-3GPP mobility. Other responsibilities of the S-GW  122  may include a lawful intercept, charging, and some policy enforcement. 
     The P-GW  123  may terminate an SGi interface toward a PDN. The P-GW  123  may route data packets between the EPC network  120  and external networks such as a network including the application server  184  (alternatively referred to as application function (AF)) via an Internet Protocol (IP) interface  125 . The P-GW  123  can also communicate data to other external networks  131 A, which can include the Internet, IP multimedia subsystem (IPS) network, and other networks. Generally, the application server  184  may be an element offering applications that use IP bearer resources with the core network (e.g., UMTS Packet Services (PS) domain, LTE PS data services, etc.). In this aspect, the P-GW  123  is shown to be communicatively coupled to an application server  184  via an IP interface  125 . The application server  184  can also be configured to support one or more communication services (e.g., Voice-over-Internet Protocol (VoIP) sessions, PTT sessions, group communication sessions, social networking services, etc.) for the UEs  101  and  102  via the CN  120 . 
     The P-GW  123  may further be a node for policy enforcement and charging data collection. Policy and Charging Rules Function (PCRF)  126  is the policy and charging control element of the CN  120 . In a non-roaming scenario, in some aspects, there may be a single PCRF in the Home Public Land Mobile Network (HPLMN) associated with a UE&#39;s Internet Protocol Connectivity Access Network (IP-CAN) session. In a roaming scenario with a local breakout of traffic, there may be two PCRFs associated with a UE&#39;s IP-CAN session: a Home PCRF (H-PCRF) within an HPLMN and a Visited PCRF (V-PCRF) within a Visited Public Land Mobile Network (VPLMN). The PCRF  126  may be communicatively coupled to the application server  184  via the P-GW  123 . 
     In some aspects, the communication network  140 A can be an IoT network. One of the current enablers of IoT is the narrowband-IoT (NB-IoT). 
     A NG system architecture can include the RAN  110  and a 5G network core (5GC)  120 . The NG-RAN  110  can include a plurality of nodes, such as gNBs and NG-eNBs. The core network  120  (e.g., a 5G core network or 5GC) can include an access and mobility function (AMF) and/or a user plane function (UPF). The AMF and the UPF can be communicatively coupled to the gNBs and the NG-eNBs via NG interfaces. More specifically, in some aspects, the gNBs and the NG-eNBs can be connected to the AMF by NG-C interfaces, and to the UPF by NG-U interfaces. The gNBs and the NG-eNBs can be coupled to each other via Xn interfaces. 
     In some aspects, the NG system architecture can use reference points between various nodes as provided by 3GPP Technical Specification (TS) 23.501 (e.g., V15.4.0, 2018-12). In some aspects, each of the gNBs and the NG-eNBs can be implemented as a base station, a mobile edge server, a small cell, a home eNB, and so forth. In some aspects, a gNB can be a master node (MN) and NG-eNB can be a secondary node (SN) in a 5G architecture. 
       FIG.  1 B  illustrates a non-roaming 5G system architecture in accordance with some aspects. Referring to  FIG.  1 B , there is illustrated a 5G system architecture  140 B in a reference point representation. More specifically, UE  102  can be in communication with RAN  110  as well as one or more other 5G core (5GC) network entities. The 5G system architecture  140 B includes a plurality of network functions (NFs), such as access and mobility management function (AMF)  132 , session management function (SMF)  136 , policy control function (PCF)  148 , application function (AF)  150 , user plane function (UPF)  134 , network slice selection function (NSSF)  142 , authentication server function (AUSF)  144 , and unified data management (UDM)/home subscriber server (HSS)  146 . The UPF  134  can provide a connection to a data network (DN)  152 , which can include, for example, operator services, Internet access, or third-party services. The AMF  132  can be used to manage access control and mobility and can also include network slice selection functionality. The SMF  136  can be configured to set up and manage various sessions according to a network policy. The UPF  134  can be deployed in one or more configurations according to a desired service type. The PCF  148  can be configured to provide a policy framework using network slicing, mobility management, and roaming (similar to PCRF in a 4G communication system). The UDM can be configured to store subscriber profiles and data (similar to an HSS in a 4G communication system). 
     In some aspects, the 5G system architecture  140 B includes an IP multimedia subsystem (IMS)  168 B as well as a plurality of IP multimedia core network subsystem entities, such as call session control functions (CSCFs). More specifically, the IMS  168 B includes a CSCF, which can act as a proxy CSCF (P-CSCF)  162 BE, a serving CSCF (S-CSCF)  164 B, an emergency CSCF (E-CSCF) (not illustrated in  FIG.  1 B ), or interrogating CSCF (I-CSCF)  166 B. The P-CSCF  162 B can be configured to be the first contact point for the UE  102  within the IM subsystem (IMS)  168 B. The S-CSCF  164 B can be configured to handle the session states in the network, and the E-CSCF can be configured to handle certain aspects of emergency sessions such as routing an emergency request to the correct emergency center or PSAP. The I-CSCF  166 B can be configured to function as the contact point within an operator&#39;s network for all IMS connections destined to a subscriber of that network operator, or a roaming subscriber currently located within that network operator&#39;s service area. In some aspects, the I-CSCF  166 B can be connected to another IP multimedia network  170 E, e.g. an IMS operated by a different network operator. 
     In some aspects, the UDM/HSS  146  can be coupled to an application server  160 E, which can include a telephony application server (TAS) or another application server (AS). The AS  160 B can be coupled to the IMS  168 B via the S-CSCF  164 B or the I-CSCF  166 B. 
     A reference point representation shows that interaction can exist between corresponding NF services. For example,  FIG.  1 B  illustrates the following reference points: N 1  (between the UE  102  and the AMF  132 ), N 2  (between the RAN  110  and the AMF  132 ), N 3  (between the RAN  110  and the UPF  134 ), N 4  (between the SMF  136  and the UPF  134 ), N 5  (between the PCF  148  and the AF  150 , not shown), N 6  (between the UPF  134  and the DN  152 ), N 7  (between the SMF  136  and the PCF  148 , not shown), N 8  (between the UDM  146  and the AMF  132 , not shown), N 9  (between two UPFs  134 , not shown), N 10  (between the UDM  146  and the SMF  136 , not shown), N 11  (between the AMF  132  and the SMF  136 , not shown), N 12  (between the AUSF  144  and the AMF  132 , not shown), N 13  (between the AUSF  144  and the UDM  146 , not shown), N 14  (between two AMFs  132 , not shown), N 15  (between the PCF  148  and the AMF  132  in case of a non-roaming scenario, or between the PCF  148  and a visited network and AMF  132  in case of a roaming scenario, not shown), N 16  (between two SMFs, not shown), and N 22  (between AMF  132  and NSSF  142 , not shown). Other reference point representations not shown in  FIG.  1 E  can also be used. 
       FIG.  1 C  illustrates a 5G system architecture  140 C and a service-based representation. In addition to the network entities illustrated in  FIG.  1 B , system architecture  140 C can also include a network exposure function (NEF)  154  and a network repository function (NRF)  156 . In some aspects, 5G system architectures can be service-based and interaction between network functions can be represented by corresponding point-to-point reference points Ni or as service-based interfaces. 
     In some aspects, as illustrated in  FIG.  1 C , service-based representations can be used to represent network functions within the control plane that enable other authorized network functions to access their services. In this regard, 5G system architecture  140 C can include the following service-based interfaces: Namf  158 H (a service-based interface exhibited by the AMF  132 ), Nsmf  1581  (a service-based interface exhibited by the SMF  136 ), Nnef  158 B (a service-based interface exhibited by the NEF  154 ), Npcf  158 D (a service-based interface exhibited by the PCF  148 ), a Nudm  158 E (a service-based interface exhibited by the UDM  146 ), Naf  158 F (a service-based interface exhibited by the AF  150 ), Nnrf  158 C (a service-based interface exhibited by the NRF  156 ), Nnssf  158 A (a service-based interface exhibited by the NSSF  142 ), Nausf  158 G (a service-based interface exhibited by the AUSF  144 ). Other service-based interfaces (e.g., Nudr, N5g-eir, and Nudsf) not shown in  FIG.  1 C  can also be used. 
       FIG.  2    illustrates components of an exemplary 5G-NR architecture  200  with a control plane (CP)—user plane (UP) separation, in accordance with some aspects. Referring to  FIG.  2   , the 5G-NR architecture  200  can include a 5G core  212  and NG-RAN  214 . The NG-RAN  214  can include one or more gNBs such as gNB  128 A and  128 B (which can be the same as gNB  128 ). The 5GC  212  and the NG-RAN  214 , in some aspects, may be similar or the same as the 5GC  120  and the NG-RAN  110  of  FIG.  1 B , respectively. In some aspects, network elements of the NG-RAN  214  may be split into central and distributed units, and different central and distributed units, or components of the central and distributed units, may be configured for performing different protocol functions. 
     In some aspects, the gNB  128 B can comprise or be split into one or more of a gNB Central Unit (gNB-CU)  202  and a gNB Distributed Unit (gNB-DU)  204 ,  206 . Additionally, the gNB  128 B can comprise or be split into one or more of a gNB-CU-Control Plane (gNB-CU-CP)  208  and a gNB-CU-User Plane (gNB-CU-UP)  210 . The gNB-CU  202  is a logical node configured to host the radio resource control layer (RRC), service data adaptation protocol (SDAP) layer and packet data convergence protocol layer (PDCP) protocols of the gNB or RRC, and PDCP protocols of the E-UTRA-NR gNB (en-gNB) that controls the operation of one or more gNB-DUs. The gNB-DU (e.g.,  204  or  206 ) is a logical node configured to host the radio link control layer (RLC), medium access control layer (MAC) and physical layer (PHY) layers of the gNB  128 A,  128 B or en-gNB, and its operation is at least partly controlled by gNB-CU  202 . In some aspects, one gNB-DU (e.g.,  204 ) can support one or multiple cells. 
     The gNB-CU  202  comprises a gNB-CU-Control Plane (gNB-CU-CP) entity  208  and a gNB-CU-User Plane entity  210 . The gNB-CU-CP  208  is a logical node configured to host the RRC and the control plane part of the PDCP protocol of the gNB-CU  202  for an en-gNB or a gNB. The gNB-CU-UP  210  is a logical (or physical) node configured to host the user plane part of the PDCP protocol of the gNB-CU  202  for an en-gNB, and the user plane part of the PDCP protocol and the SDAP protocol of the gNB-CU  202  for a gNB. 
     The gNB-CU  202  and the gNB-DU  204 ,  206  can communicate via the F1 interface, and the gNB  128 A can communicate with the gNB-CU  202  via the Xn-C interface. The gNB-CU-CP  208  and the gNB-CU-UP  210  can communicate via the E1 interface. Additionally, the gNB-CU-CP  208  and the gNB-DU  204 ,  206  can communicate via the F1-C interface, and the gNB-DU  204 ,  206  and the gNB-CU-UP  210  can communicate via the F1-U interface. 
     In some aspects, the gNB-CU  202  terminates the F1 interface connected with the gNB-DU  204 ,  206 , and in other aspects, the gNB-DU  204 ,  206  terminates the F1 interface connected with the gNB-CU  202 . In some aspects, the gNB-CU-CP  208  terminates the E1 interface connected with the gNB-CU-UP  210  and the F1-C interface connected with the gNB-DU  204 ,  206 . In some aspects, the gNB-CU-UP  210  terminates the E1 interface connected with the gNB-CU-CP  208  and the F1-U interface connected with the gNB-DU  204 ,  206 . 
     In some aspects, the F1 interface is a point-to-point interface between endpoints and supports the exchange of signaling information between endpoints and data transmission to the respective endpoints. The F1 interface can support control plane and user plane separation and separate the Radio Network Layer and the Transport Network Layer. In some aspects, the E1 interface is a point-to-point interface between a gNB-CU-CP and a gNB-CU-UP and supports the exchange of signaling information between endpoints. The E1 interface can separate the Radio Network Layer and the Transport Network Layer, and in some aspects, the E1 interface may be a control interface not used for user data forwarding. 
     In certain aspects, for EN-DC, the S1-U interface and an X2 interface (e.g., X2-C interface) for a gNB, consisting of a gNB-CU and gNB-DUs, can terminate in the gNB-CU. 
     In some aspects, gNB  128 B supporting CP/UP separation, includes a single CU-CP entity  208 , multiple CU-UP entities  210 , and multiple DU entities  204 , . . . ,  206 , with all entities being configured for network slice operation. As illustrated in  FIG.  2   , each DU entity  204 , . . . ,  206  can have a single connection with the CU-CP  208  via a F1-C interface. Each DU entity  204 , . . . ,  206  can be connected to multiple CU-UP entities  210  using F1-U interfaces. The CU-CP entity  208  can be connected to multiple CU-UP entities  210  via E1 interfaces. Each DU entity  204 , . . . ,  206  can be connected to one or more UEs, and the CU-UP entities  210  can be connected to a user plane function (UPF) and the 5G core  212 . 
     In some aspects, applications for 5G networks can be configured to support autonomous driving that may need ultra-low latency and high reliability communications, as issues in the RAN (e.g., such as high latency communications) can have the possibility to cause property damage and body injury. When the auto navigation application (e.g., a navigation service application being executed on a user equipment) first sets up the route for traveling to a desired destination, the auto navigation application may use information (such as KPIs) from the network to assist the vehicle operator in advance in avoiding travel into the areas that may experience (or are experiencing) RAN issues (e.g., as indicated or deduced from the KPIs communicated by the network, such as by a network management service). 
     In some aspects, 5G services (e.g., enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), or massive machine-type communications (mMTC)) may be characterized by high-speed high data volume, low-speed ultra-low latency, and infrequent transmission of low data volume from a large number of emerging smart devices, respectively. To support the wide range of QoS levels, 5G networks may be automatically tuned (e.g., using one or more KPIs as discussed herein) in order to maintain the optimal performance. With the advances of artificial intelligence (AI) and big data, RAN condition and cell composite load KPIs can be collected, as discussed herein, and analyzed to determine the status and traffic patterns of 5G networks (e.g., one or more neighboring cells associated with a navigation route), based on time and locations (when and where) the KPIs were collected to enable analytic applications to predict potential issues, and to plan a solution in advance and resolve the issues (e.g., navigation-related issues) before happening. Techniques disclosed herein discuss the use of the RAN condition KPI and the cell composite load KPI (e.g., by analytic applications) to assist auto navigation (or other applications or services) as well as 5G network optimization. 
     In some aspects, existing 3GPP technical specifications (TSs) (e.g., TS 28.552) may be supplemented to define E2E delay measurements and may also include clarifications on how the measurements are counted and which network functions (NFs) are involved to support the E2E measurements and determination of one or more KPIs based on such measurements. 
     Examples of 5G NFs are illustrated in  FIG.  1 F . Referring again to  FIG.  1 F , in some aspects, the 5G network  140 F may include a management system (or management service)  190 , which is configured to offer management capabilities within the 5G network  140 F. These management capabilities may be accessed by management service consumers via a service interface (e.g.,  196 ), which may be composed of individually specified management service components. In this regard, the management system  190  may be configured to communicate with each of the NFs as well as other network entities within the network  140 F, except the UE  101  (e.g., including the network entities within the dashed area in  FIG.  1 F ), via the service interface  196 . In some aspects, the management system  190  may be configured based on 3GPP TS 28.533 (v16.0.0). 
     In some aspects, the management system  190  may include management functions (MFs)  192 , . . . ,  194 . In some aspects, at least one of the MFs (e.g., MF  192 ) may be configured as a service producer, performing one or to more E2E performance measurement functions. In some aspects, at least another of the MFs (e.g., MF  193 ) can be configured as a data analytic function (DAF)  193 . In some aspects, the service producer (e.g.,  198 ) and the DAF  193  may be implemented within at least one of the NFs within the 5G network  140 F. 
     In some aspects, the DAF  193  can be configured to receive performance measurements, alarm information, and/or configuration information and determine one or more data analytic KPIs associated with the 5G network  140 F. Example KPIs which can be determined by the DAF  193  include a RAN condition KPI and a cell composite load KPI, which can include an uplink cell composite load KPI in a downlink cell composite load KPI. 
     In some aspects, the following measurement definition template (described in greater detail in 3GPP TS 32.404 V15.0.0) may be used in connection with data analytic KPI determination by the DAF  193 : 
     Measurement Name 
     (a) Description. (b) Collection Method—contains the form in which the measurement data is obtained, including: CC (Cumulative Counter); GAUGE (dynamic variable), used when data being measured can vary up or down during the period of measurement; DER (Discrete Event Registration), when data related to a particular event are captured every nth event is registered, where n can be 1 or larger; SI (Status Inspection); TF (Transparent Forwarding); and OM (Object Mapping). 
     (c) Condition—contains the condition which causes the measurement result data to be updated. (d) Measurement Result (measured value(s), Units). This subclause contains a description of expected result value(s) (e.g., a single integer value). If a measurement is related to “external” technologies, this subclause shall also give a brief reference to other standard bodies. (e) Measurement Type. This subclause contains a short form of the measurement name specified in the header, which is used to identify the measurement type in the result files. 
     (f) Measurement Object Class. This subclause describes the measured object class (e.g. UtranCell, RncFunction, SgsnFunction). (g) Switching Technology. This subclause contains the Switching domain(s) this measurement is applicable to i.e. Circuit Switched and/or Packet Switched. (h) Generation. The generation determines if it concerns a GSM, UMTS, EPS, 5GS, combined (GSM+UMTS+EPS+5GS) or IMS measurement. (i) Purpose. This optional clause aims at describing who will be using the measurement. 
       FIG.  3    illustrates generation of data analytic KPIs by a data analytic function within a management system of a 5G network, in accordance with some aspects. Referring to  FIG.  3   , diagram  300  illustrates generation of data analytic KPIs  304 . More specifically, the data analytic function  193  within the management system  190  receives management and data  302 , which can be used to perform KPI calculations  199  in order to generate data analytic KPIs  304 . The data analytic KPIs  304  can include RAN condition KPI and cell composite load KPI, as well as other KPIs indicative of network conditions and status of one or more entities within the 5G network  140 F. In some aspects, the management data  302  can include performance measurements (e.g., a number of handover failures, a number of RRC connection setup failures, a number of RACH failures, packet loss rate, and so forth), alarm information (e.g., an alarm or notification generated in connection with a cell overload, network traffic throughput decrease below threshold, a number of network failures reaching a threshold, or other system or configuration alarms), as well as configuration information related to condition of one or more NR cells within the 5G network. In some aspects, the management data  302  can be generated by one or more of the NFs associated with the 5G network  140 F and communicated to the data analytic function  193  or made available (e.g., stored in network storage) for retrieval by the data analytic function  193 . 
     In some aspects, the data analytic KPIs  304  are communicated to an analytic application  306 , which can be a management function within the management system  190 , a network function within the 5G network  140 F, or a standalone application such as a service application executing on a network device in the edge cloud or a public cloud. In some aspects, the data analytic function  193  can generate a RAN condition KPI, which can be described using the following subsections a)-j) of the above mentioned template: 
     RAN Condition KPI. 
     a) This KPI indicates the condition of an NR cell that can be used to assist the applications, such as auto navigation. b) This KPI describes the condition of an NR cell. c) This KPI is generated from the analysis of performance measurements and alarms related to the condition of an NR cell. In some aspects, the value of the KPI is an integer number to represent the RAN condition of a cell and may include the following values: 0: indicating a healthy/normal functioning cell; 1: out of service cell; 2: capacity constraint (e.g., an overloaded cell); and 3: capability constraint (e.g., the cell does not support latency requirement). In some aspects, the above-listed integer values may be extended to represent additional conditions. d) RanCondition. e) The specific performance measurements used for deriving this KPI are up to implementation. f) 5GS. g) Condition. h) Integer. i) N/A. j) This KPI can be used to assist an application to perform auto navigation in autonomous driving aspects, as discussed in connection with  FIG.  4   . 
       FIG.  4    illustrates a use case  400  for a RAN condition KPI use in connection with outer navigation assistance, in accordance with some aspects. A major application for 5G networks is to support autonomous driving that may use ultra-low latency and high reliability, as issues in the RAN can have the possibility to cause property damage and body injury. When an auto navigation application first sets up a navigation route for a car to reach a destination, it can be configured to avoid directing the car from traveling into the areas that may experience RAN issues in advance. For example, if a cell is overloaded with user traffic, experiencing an outage, or not able to support the latency requirement, then this cell may be removed from the planned navigation route. 
     In some aspects and in connection with autonomous driving, a RAN condition KPI per cell (e.g., for each of the cells  406 - 424 ) may be collected, and made available to assist an autonomous driving vehicle at position  402 A to reach a destination  402 B, and in controlling the auto navigation from position  402 A to position  402 B. Based on a cell identifier received with the RAN condition KPI, the application knows the neighbor relation between cells  406424 . Based on the cell where the car is located, the autonomous driving application (or a navigation application) knows the RAN condition of neighboring cells along a planned route, and may change the route accordingly, as the RAN conditions may change along the way when the car is traveling. 
     For example,  FIG.  4    illustrates a vehicle traveling from position  402 A in cell  406  to position  402 B in cell  422 . It may be detected (e.g., via a received RAN condition KPI) that cell  416  is either overloaded with user traffic, is experiencing an outage, or it is not able to support the latency requirement of the traveling vehicle. Therefore, the auto navigation application plans the navigation route to detour and pass through cells  414  and  420 . In some aspects, the data analytic function  193  can generate a cell composite load KPI, which can include an uplink (UL) cell composite load KPI and/or a downlink (DL) cell composite load KPI, which KPIs can be described using the following subsections a)—j) of the above mentioned template: 
     UL Cell Composite Load KPI. 
     a) This KPI is intended to be used to analyze the traffic trend of 5G networks. b) This KPI describes the ULcomposite load of a NR cell. c) This KPI is generated from the analysis of management data such as performance measurements, alerts, and configuration information (e.g. PRB usage, an average number of active UEs, IP/data throughput in the UL, resource usage, and so forth). d) ulCellCompositeLoad. e) The specific performance measurements used for deriving this KPI are up to implementation. f) 5GS. g) Condition. h) Integer. i) N/A. j) This KPI can be used to understand the status and traffic patterns of 5G networks. 
     DL Cell Composite Load KPI. 
     a) This KPI is intended to be used to analyze the traffic trend of 5G networks. b) This KPI describes the DLcomposite load of a NR cell. c) This KPI is generated from the analysis of management data such as performance measurements, alerts, and configuration information (e.g., PRB usage, an average number of active UEs, IP/data throughput in the DL, resource usage, and so forth). d) dlCellCompositeLoad. e) The specific performance measurements used for deriving this KPI are up to implementation. f) 5GS. g) Condition. h) Integer. i) N/A. j) This KPI can be used to understand the status and traffic patterns of 5G networks. 
     In some aspects, with the advances of AI and big data, cell composite load KPIs can be collected and analyzed to understand the status and traffic patterns of 5G networks, based on time and locations when and where the KPI is collected to enable analytic applications to predict the potential issues, and to plan a solution in advance to resolve the issues before happening. 
     A service producer supported by one or more processors is configured to obtain management data, analyze the management data, generate the management data analytical KPI(s), and/or report the management data analytical KPI(s). The management data includes performance measurements, alarm information, and/or configuration information. The management data analytical KPI is a RAN condition KPI that indicates the RAN condition for a cell. The RAN condition KPI is generated from the management data, including, but not limited to, performance measurements, alarms, and/or configuration data related to the condition of a cell. The RAN condition KPI includes, but is not limited to, the following values: 0: healthy cell; 1: out of service cell; 2: capacity constraint (e.g., overloaded cell); and 3: capability constraint (e.g., the cell does not support latency requirement). The uplink cell composite load KPI is generated from the management data (e.g., PRB usage, an average active UE, IP throughput in the uplink, resource usages, and so forth). The downlink cell composite load KPI is generated from management data (e.g., PRB usage, average number of active UEs, IP throughput in the downlink, resource usage, and so forth). The downlink cell composite load KPI and uplink cell composite load KPI can be used by analytic applications to predict the potential issues, and to plan a solution in advance to resolve the issues before happening. 
     An analytic application acting as the service consumer supported by one or more processors, is configured to receive an analytic KPI, analyze the analytic KPI, and perform an action to mitigate an issue handled by the application. The analytic application is aware of a neighbor relation between cells. Based on the cell where the car is located, the analytic application knows the RAN condition of the neighboring cells, and may change the route, based on the RAN condition determined based on a received KPI. The analytic application can be configured to avoid cells with RAN condition of out of service, capacity constraint (e.g., overloaded), or capability constraint (e.g., does not support latency requirement). The analytic application can be configured to analyze the uplink cell composite load KPI and downlink cell composite load KPI to understand the status and traffic patterns of 5G networks, based on time and locations when and where the KPI is collected. The analytic application can be configured to generate a prediction of potential issues, and plan a solution in advance to resolve the issues before happening (e.g., dynamically change a navigation route for a self-driving vehicle based on received KPIs associated with condition of one or more cells the planned navigation route is passing through). 
       FIG.  5    illustrates a block diagram of a communication device such as an evolved Node-B (eNB), a next generation Node-B (gNB), an access point (AP), a wireless station (STA), a mobile station (MS), or a user equipment (UE), in accordance with some aspects and to perform one or more of the techniques disclosed herein. In alternative aspects, the communication device  500  may operate as a standalone device or may be connected (e.g., networked) to other communication devices. 
     Circuitry (e.g., processing circuitry) is a collection of circuits implemented intangible entities of the device  500  that include hardware (e.g., simple circuits, gates, logic, etc.). Circuitry membership may be flexible over time. Circuitries include members that may, alone or in combination, perform specified operations when operating. In an example, the hardware of the circuitry may be immutably designed to carry out a specific operation (e.g., hardwired). In an example, the hardware of the circuitry may include variably connected physical components (e.g., execution units, transistors, simple circuits, etc.) including a machine-readable medium physically modified (e.g., magnetically, electrically, moveable placement of invariant massed particles, etc.) to encode instructions of the specific operation. 
     In connecting the physical components, the underlying electrical properties of a hardware constituent are changed, for example, from an insulator to a conductor or vice versa. The instructions enable embedded hardware (e.g., the execution units or a loading mechanism) to create members of the circuitry in hardware via the variable connections to carry out portions of the specific operation when in operation. Accordingly, in an example, the machine-readable medium elements are part of the circuitry or are communicatively coupled to the other components of the circuitry when the device is operating. In an example, any of the physical components may be used in more than one member of more than one circuitry. For example, under operation, execution units may be used in a first circuit of a first circuitry at one point in time and reused by a second circuit in the first circuitry, or by a third circuit in a second circuitry at a different time. Additional examples of these components with respect to the device  500  follow. 
     In some aspects, the device  500  may operate as a standalone device or may be connected (e.g., networked) to other devices. In a networked deployment, the communication device  500  may operate in the capacity of a server communication device, a client communication device, or both in server-client network environments. In an example, the communication device  500  may act as a peer communication device in peer-to-peer (P2P) (or other distributed) network environment. The communication device  500  may be a UE, eNB, PC, a tablet PC, a STB, a PDA, a mobile telephone, a smartphone, a web appliance, a network router, switch or bridge, or any communication device capable of executing instructions (sequential or otherwise) that specify actions to be taken by that communication device. Further, while only a single communication device is illustrated, the term “communication device” shall also be taken to include any collection of communication devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein, such as cloud computing, software as a service (SaaS), and other computer cluster configurations. 
     Examples, as described herein, may include, or may operate on, logic or a number of components, modules, or mechanisms. Modules are tangible entities (e.g., hardware) capable of performing specified operations and may be configured or arranged in a certain manner. In an example, circuits may be arranged (e.g., internally or with respect to external entities such as other circuits) in a specified manner as a module. In an example, the whole or part of one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware processors may be configured by firmware or software (e.g., instructions, an application portion, or an application) as a module that operates to perform specified operations. In an example, the software may reside on a communication device-readable medium. In an example, the software, when executed by the underlying hardware of the module, causes the hardware to perform the specified operations. Accordingly, the term “module” is understood to encompass a tangible entity, be that an entity that is physically constructed, specifically configured (e.g., hardwired), or temporarily (e.g., transitorily) configured (e.g., programmed) to operate in a specified manner or to perform part or all of any operation described herein. Considering examples in which modules are temporarily configured, each of the modules need not be instantiated at any one moment in time. For example, where the modules comprise a general-purpose hardware processor configured using software, the general-purpose hardware processor may be configured as respective different modules at different times. The software may accordingly configure a hardware processor, for example, to constitute a particular module at one instance of time and to constitute a different module at a different instance of time. 
     Communication device (e.g., UE)  500  may include a hardware processor  502  (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory  504 , a static memory  506 , and mass storage  507  (e.g., hard drive, tape drive, flash storage, or other block or storage devices), some or all of which may communicate with each other via an interlink (e.g., bus)  508 . 
     The communication device  500  may further include a display device  510 , an alphanumeric input device  512  (e.g., a keyboard), and a user interface (UI) navigation device  514  (e.g., a mouse). In an example, the display device  510 , input device  512  and UI navigation device  514  may be a touchscreen display. The communication device  500  may additionally include a signal generation device  518  (e.g., a speaker), a network interface device  520 , and one or more sensors  521 , such as a global positioning system (GPS) sensor, compass, accelerometer, or another sensor. The communication device  500  may include an output controller  528 , such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc.). 
     The storage device  507  may include a communication device-readable medium  522 , on which is stored one or more sets of data structures or instructions  524  (e.g., software) embodying or utilized by any one or more of the techniques or functions described herein. In some aspects, registers of the processor  502 , the main memory  504 , the static memory  506 , and/or the mass storage  507  may be, or include (completely or at least partially), the device-readable medium  522 , on which is stored the one or more sets of data structures or instructions  524 , embodying or utilized by any one or more of the techniques or functions described herein. In an example, one or any combination of the hardware processor  502 , the main memory  504 , the static memory  506 , or the mass storage  516  may constitute the device-readable medium  522 . 
     As used herein, the term “device-readable medium” is interchangeable with “computer-readable medium” or “machine-readable medium”. While the communication device-readable medium  522  is illustrated as a single medium, the term “communication device-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) configured to store the one or more instructions  524 . The term “communication device-readable medium” is inclusive of the terms “machine-readable medium” or “computer-readable medium”, and may include any medium that is capable of storing, encoding, or carrying instructions (e.g., instructions  524 ) for execution by the communication device  500  and that cause the communication device  500  to perform any one or more of the techniques of the present disclosure, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. Non-limiting communication device-readable medium examples may include solid-state memories and optical and magnetic media. Specific examples of communication device-readable media may include: non-volatile memory, such as semiconductor memory devices (e.g., Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; Random Access Memory (RAM); and CD-ROM and DVD-ROM disks. In some examples, communication device-readable media may include non-transitory communication device-readable media. In some examples, communication device-readable media may include communication device-readable media that is not a transitory propagating signal. 
     The instructions  524  may further be transmitted or received over a communications network  526  using a transmission medium via the network interface device  520  utilizing any one of a number of transfer protocols. In an example, the network interface device  520  may include one or more physical jacks (e.g., Ethernet, coaxial, or phone jacks) or one or more antennas to connect to the communications network  526 . In an example, the network interface device  520  may include a plurality of antennas to wirelessly communicate using at least one of single-input-multiple-output (SIMO), MIMO, or multiple-input-single-output (MISO) techniques. In some examples, the network interface device  520  may wirelessly communicate using Multiple User MIMO techniques. 
     The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the communication device  500 , and includes digital or analog communications signals or another intangible medium to facilitate communication of such software. In this regard, a transmission medium in the context of this disclosure is a device-readable medium. 
     A communication device-readable medium may be provided by a storage device or other apparatus which is capable of hosting data in a non-transitory format. In an example, information stored or otherwise provided on a communication device-readable medium may be representative of instructions, such as instructions themselves or a format from which the instructions may be derived. This format from which the instructions may be derived may include source code, encoded instructions (e.g., in compressed or encrypted form), packaged instructions (e.g., split into multiple packages), or the like. The information representative of the instructions in the communication device-readable medium may be processed by processing circuitry into the instructions to implement any of the operations discussed herein. For example, deriving the instructions from the information (e.g., processing by the processing circuitry) may include: compiling (e.g., from source code, object code, etc.), interpreting, loading, organizing (e.g., dynamically or statically linking), encoding, decoding, encrypting, unencrypting, packaging, unpackaging, or otherwise manipulating the information into the instructions. 
     In an example, the derivation of the instructions may include assembly, compilation, or interpretation of the information (e.g., by the processing circuitry) to create the instructions from some intermediate or preprocessed format provided by the machine-readable medium. The information, when provided in multiple parts, may be combined, unpacked, and modified to create the instructions. For example, the information may be in multiple compressed source code packages (or object code, or binary executable code, etc.) on one or several remote servers. The source code packages may be encrypted when in transit over a network and decrypted, uncompressed, assembled (e.g., linked) if necessary, and compiled or interpreted (e.g., into a library, stand-alone executable etc.) at a local machine, and executed by the local machine. 
     Although an aspect has been described with reference to specific exemplary aspects, it will be evident that various modifications and changes may be made to these aspects without departing from the broader scope of the present disclosure. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various aspects is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

Metadata:
Filing Date: 20230622
Publication Date: 20240806
Grant Date: 20240806
Priority Date: 20180809
Inventors: CHOU, JOEY
Yao, Yizhi
Assignee: APPLE INC
CPC Classifications: [{"code": "H04W88/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W84/042", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W74/0833", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W24/04", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W36/0079", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W76/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W24/08", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W88/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04L43/0876", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W24/04", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W24/08", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04W24/04", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04W88/18", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04W88/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W84/042", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W76/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W74/0833", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W36/0079", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W24/04", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W24/08", "inventive": true, "first": true, "tree": "[]"}]
Family ID: 69415134