WO2020061314A1 - Systems, methods, and apparatuses for self-organizing networks - Google Patents

Abstract

A self-organizing network (SON) function is configured to collect management data, analyze the management data, and generate actions to control a RAN or core network behavior. The SON function may also report an output of management data analysis to other applications. The management data may include performance measurements, alarm information and/or configuration information.

Description

SYSTEMS, METHODS, AND APPARATUSES FOR SELF-ORGANIZING NETWORKS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 62/733,950, filed September 20, 2018, which is hereby incorporated by reference herein in its entirety.

TECHNICAL FIELD

[0002] This application relates generally to wireless communication systems, and more specifically to self-organizing networks for fifth generation (5G) systems.

BACKGROUND

[0003] Wireless mobile communication technology uses various standards and protocols to transmit data between a base station and a wireless mobile device. Wireless communication system standards and protocols can include the 3rd Generation Partnership Project (3GPP) long term evolution (LTE); the Institute of Electrical and Electronics Engineers (IEEE) 802.16 standard, which is commonly known to industry groups as worldwide

interoperability for microwave access (WiMAX); and the IEEE 802.11 standard for wireless local area networks (WLAN), which is commonly known to industry groups as Wi-Fi. In 3GPP radio access networks (RANs) in LTE systems, the base station can include a RAN Node such as a Evolved Universal Terrestrial Radio Access Network (E-UTRAN) Node B (also commonly denoted as evolved Node B, enhanced Node B, eNodeB, or eNB) and/or Radio Network Controller (RNC) in an E-UTRAN, which communicate with a wireless communication device, known as user equipment (UE). In fifth generation (5G) wireless RANs, RAN Nodes can include a 5G Node, new radio (NR) node or g Node B (gNB).

[0004] RANs use a radio access technology (RAT) to communicate between the RAN Node and UE. RANs can include global system for mobile communications (GSM), enhanced data rates for GSM evolution (EDGE) RAN (GERAN), Universal Terrestrial Radio Access Network (UTRAN), and/or E-UTRAN, which provide access to

communication services through a core network. Each of the RANs operates according to a specific 3GPP RAT. For example, the GERAN implements GSM and/or EDGE RAT, the UTRAN implements universal mobile telecommunication system (UMTS) RAT or other 3 GPP RAT, and the E-UTRAN implements LTE RAT.

[0005] A core network can be connected to the UE through the RAN Node. The core network can include a serving gateway (SGW), a packet data network (PDN) gateway (PGW), an access network detection and selection function (ANDSF) server, an enhanced packet data gateway (ePDG) and/or a mobility management entity (MME).

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0006] To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.

[0007] FIG. 1 illustrates an example network in accordance with one embodiment.

[0008] FIG. 2 illustrates an example 5G SON frameworks in accordance with one embodiment.

[0009] FIG. 3 is a flowchart illustrating a method for a SON function in a wireless network in accordance with one embodiment.

[0010] FIG. 4 is a flowchart illustrating a method for an autonomous driving application in accordance with one embodiment.

[0011] FIG. 5 is a flowchart illustrating a method for a SON function to improve resource utilization performance of one or more NSI in accordance with one embodiment.

[0012] FIG. 6 illustrates a system in accordance with one embodiment.

[0013] FIG. 7 illustrates a device in accordance with one embodiment.

[0014] FIG. 8 illustrates example interfaces in accordance with one embodiment.

[0015] FIG. 9 illustrates a system in accordance with one embodiment.

[0016] FIG. 10 illustrates components in accordance with one embodiment.

DETAILED DESCRIPTION

[0017] The present disclosure provides a 5G self-organizing network (SON) overview, management framework, and use cases for a SON to collect and analyze the management data, including performance measurements, alarms, and provisioning data to generate RAN condition data. Embodiments herein define the management data analytical key performance indicators (KPIs) for prediction of traffic volume, resource utilization tendency, and indication of the RAN condition. In certain embodiments, the Management Data Analytics Service uses big data technologies and may assist in the adoption of Artificial Intelligence (AI) in telecommunications.

[0018] In an example embodiment, a SON function is configured to collect management data, analyze the management data, and generate actions to control a RAN or core network behavior. The SON function may also report an output of management data analysis to other applications. The management data may include performance measurements, alarm information and/or configuration information.

[0019] In certain such embodiments, the SON function is also configured to: consume provisioning management services to collect the configuration information for a network function (NF), a network slice instance (NSI), and/or a network slice subnet instance (NS SI); consume a performance data file reporting service to collect the performance data files for the NF, NSI, and/or NSSI; consume a performance data streaming service to collect the real-time performance data for the NF, NSI, and/or NSSI; and/or consume a fault supervision data report management service to receive the alarms for the NF, NSI, and/or NSSI.

[0020] In addition, or in other embodiments, the SON function is configured to analyze a huge number of historical data collected over, for example, hours, days, weeks, months, years, and beyond to predict the traffic demands of 5G networks based on times and locations, and generate an action to automatically control the network behavior to adapt to the changes of the traffic demands in advance. For example, if the SON function detected that there is high volume mMTC (massive Machine Type Communications) traffic at a certain time and location, then the SON function can set up the 5G network in advance to change so as to provide more mMTC capacity at that location (i.e., NR cell) and that time.

[0021] In certain embodiments, the SON function is configured to use a modify managed object instance (MOI) attributes (modifyMOIAttributes) operation in the provisioning management services to apply the actions.

[0022] In certain embodiments, the SON function is configured to analyze the management data and provide services to the other applications. The SON function may be configured to provide services to generate RAN condition data that indicates a condition of an NR cell.

For example, the RAN condition data may include, but is not limited to, one or more of the following values: "0" to indicate healthy; " 1 " to indicate out of service; "2" to indicate a capacity constraint (e.g., overloaded); and/or "3" to indicate a capability constraint (e.g., does not support a latency requirement). The RAN condition data may be consumed by one or more of the other applications, such as internet of things (IoT) applications, edge computing applications, and/or other applications.

[0023] For example, the IoT application may be an autonomous driving application configured to consume the RAN condition data to determine if one or more of the NR cells in a driving route has an issue and to re-route a vehicle accordingly. If, for example, a cell is overloaded with user data traffic, experiencing an outage, or not able to support an ultra-low latency requirement, then this cell is not included in the driving route.

[0024] One of the applications for 5G networks is to support autonomous driving that may require 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 route for a vehicle to reach a destination, according to certain embodiments, the

application avoids directing the vehicle from traveling into the areas that may experience RAN issues in advance.

[0025] For example, FIG. 1 illustrates an example network 100 including a plurality of cells (a cell 102, a cell 104, a cell 106, a cell 108, a cell 1 10, a cell 1 12, a cell 1 14, a cell 1 16, a cell 1 18, and a cell 120). In this example, an autonomous driving application navigates a vehicle 122 from the cell 102 to the cell 1 18. However, it is detected that the cell 112 is either overload with user data traffic, is experiencing an outage, or is not able to support the latency requirement. Thus, the autonomous driving application uses the RAN condition data to detour the driving route of the vehicle 122 to bypass the cell 112 and instead to pass through the cell 1 14 and the cell 1 16.

[0026] 5G SON Overview

[0027] 5G networks and network slicing are designed to support enhanced mobile broadband (eMBB), ultra reliable low latency communications (URLLC), and massive IoT (mloT) or massive machine type communication (mMTC) services, which may be characterized by high speed high data volume, low speed ultra-low latency, and infrequent transmitting low data volume from a huge number of emerging smart devices, respectively. Real-time performance data and/or performance measurements (PM) are collected and used by analytic applications (e.g., network optimization, SON, etc.) to detect the potential issues in advance, and take appropriate actions to prevent or mitigate the issues. The performance data and/or PM may be consumed by multiple analytic applications with specific purposes.

[0028] As the number of mobile users and their demand for data bandwidth increase exponentially generation after generation, 5G is tapping into the millimeter wave above 20 GHz or 30 GHz range to cope with the radio frequency (RF) spectrum shortage. Therefore, SON is playing an even more important role to automatically configure, optimize, and heal 5G network elements for better network performance, efficiency, and reliability, due to the increasing complexity in 5G.

[0029] The raw performance data of the NF(s), NSSI(s) and NSI(s) can be further analyzed, and formed into one or more management analytical KPI(s). The management analytical KPIs can be used to diagnose ongoing issues impacting the NSI/NSSI performance and predict any potential issues (e.g., potential failure and/or performance degradation). For example, the analysis of NSI/NSSI resource usage can form a KPI indicating whether a certain resource is deteriorating. The analysis and correlation of the overall NSI/NSSI performance data may indicate overload situation and potential failure(s). The SON use case of Capacity and Coverage Optimization (CCO) is one typical case for the management data analytics. CCO provides optimal coverage and capacity for the E-UTRAN, which may also be applicable for 5G radio networks. Collecting CCO related performance measurements helps to realize the situation of coverage and capacity or interference which may then trigger corresponding optimization, if needed.

[0030] However, with the introduction of various new services, 5G networks may become more sporadic in that they may have different usage patterns in terms of time, location, UE distribution, and types of applications. For example, most IoT sensor applications may run during off-peak hours or weekends. Special events, such as sport games or concerts, can cause traffic demand to shoot up at certain times and locations. The advances in AI and big data enable SON to analyze a large number of historical data collected over days, weeks, months and beyond to predict the traffic demands of 5G networks based on times and locations, and automatically control the network behavior to adapt to the changes in advance. Therefore, the foresight capability of SON along with network functions virtualization (NFV) and software defined networking (SDN) provides operators additional flexibility to improve network efficiency to maximize the return of investment. The output of SON is not limited to RAN or CN, but can be used to support applications, such as IoT, edge computing, and other applications.

[0031] 5G SON Frameworks

[0032] FIG. 2 illustrates example 5G SON frameworks 200 including a SON function 202 in communication with service consumers 204, an NF management service producer 206, an NSI management service producer 208, and an NSSI management service producer 210. The NF management service producer 206, NSI management service producer 208, and NSSI management service producer 210 respectively include a provisioning management service (shown as (Prov 212), a performance data reporting management service (shown as

(PmData 214), and a fault supervision data reporting management service (shown as FsData 216). The service consumers 204 may include, for example, IoT applications, edge computing applications, and/or other applications.

[0033] In certain embodiments, the 5G SON function 202 consumes the provisioning management services, performance data file services, and fault supervision data report management service to collect the management and network data from the management services produced by the NF management service producer 206, the NSI management service producer 208, and the NSSI management service producer 210. Based on the collected data, the SON function 202 analyzes the network behavior, status, and traffic pattern, among parameters, to determine the actions needed to optimize the networks in terms of performance and efficiency. The SON function 202 may use, for example, the modifyMOIAttributes operation in the provisioning management services to apply the actions. The SON function 202 may produce services for the service consumers 204, such as IoT applications, edge computing applications, etc.

[0034] RAN Condition Data

[0035] In an example embodiment, the SON function 202 has a capability to generate RAN condition data to be consumed by autonomous driving applications. Self-driving vehicles communicate to the applications hosted in edge computing devices with ultra-low latency and high reliability connections, as they travel to respective destinations. Any service interruption in the NR cells along the way where the vehicles are traveling can cause issues, including property damage or even body injury. The SON function 202 can analyze performance data, alarms, and provisioning data of NR cells to generate RAN condition data reporting the issues of an NR cell before the vehicles reach the cells. The applications can consume the RAN condition data to re-route the vehicles when it is determined beforehand that the routes include cells that are experiencing issues. For example, if a cell is overloaded with user traffic, experiencing an outage, or not able to support the ultra-low latency requirement, then this cell should not be in the route.

[0036] As a precondition, in certain embodiments, the SON function 202 is in operation to monitor the NR cells.

[0037] In certain embodiments, the SON function 202 collects and analyzes performance data, alarms, and provisioning data of the NR cells. The SON function 202 generates RAN condition data that may have the following value to represent the condition of a NR cell:

• 0: healthy

• 1 : out of service

• 2: capacity constraint (e.g. overloaded)

• 3 : capability constraint (e.g., does not support ultra-low latency requirement)

[0038] Applications consume the RAN condition data provided by the SON function 202 to assist with vehicle navigation. [0039] As a post-condition, in certain embodiments, the applications use the RAN condition data to assist with vehicle navigation.

[0040] Example NSI Resource Allocation Optimization

[0041] An example embodiment enables an authorized consumer to optimize resource utilization performance of an NSI when, for example one or more NSI(s) have been deployed and the NSI management service producer 208 is in operation. In certain such embodiments for shared NSIs, the NSI management service producer 208 may check policies and resource requirements of several services sharing the NSI.

[0042] Unless there are policies already determining configurations, a SON service provider determines thresholds to trigger NSI optimization (e.g., scale in/out, configure policy), such as network traffic loading, a network resource usage percentage, and available bandwidth, based on policies and requirements of services using the NSI.

[0043] The SON function 202 collects the performance data (related to the data volume, the number of registered UEs, the number of protocol data unit (PDU) sessions, UE behavior statistics based on Charging Data Records information, quality of service (QoS) parameter notifications and UE mobility event notifications from the 5GC, etc.), and utilizes the historical performance data to identify the traffic patterns for the NSIs, and predict the demand for network resources per every NSI for a given time and location. This information may be analyzed, for example, with assistance of the management data analytics service (MDAS), and the information may include data from NSI constituents’ data analytics entities, such as network data analytics function (NWDAF), e.g., regarding the load of some network functions.

[0044] In certain embodiments, based on analytics reports, current situation, and the performance optimization targets, the SON function 202 adjusts the resource allocation (e.g., addition, reduction) for the NSIs. If the NSI needs to be adjusted to optimize performance, e.g., configure policies, scale in or out resources, network slice management systems check the feasibility of the change requirements and initiates the provisioning of changes. The SON function 202 may continue monitoring NSIs to validate the actions being taken, and may perform additional adjustments if necessary.

[0045] FIG. 3 is a flowchart illustrating a method 300 for a SON function in a wireless network according to one embodiment. In block 302, the method 300 collects management data from a management service producer in the wireless network. In block 304, the method 300 performs an analysis of the management data. In block 306, the method 300 generates actions to automatically control one or more behavior of a RAN node or a core network (CN), wherein the one or more behavior is selected from a group comprising a prediction of traffic demands, a tendency of resource utilization, and an indication of a RAN condition.

[0046] FIG. 4 is a flowchart illustrating a method 400 for an autonomous driving application according to one embodiment. In block 402, the method 400 processes RAN condition data from a SON function in a wireless network. In block 404, the method 400 determines, based on the RAN condition data, that a first cell in the wireless network is expected to experience reduced performance during a route driving period. In block 406, based on the reduced performance expected for the first cell during the route drives period, the method 400 routes or re-routes a path of an autonomous vehicle to pass through one or more second cells in the wireless network instead of the first cell.

[0047] FIG. 5 is a flowchart illustrating a method 500 for a SON function to improve resource utilization performance of one or more NSI according to one embodiment. In block 502, method 500 collects performance data. In block 504, the method 500 uses the performance data to identify traffic patterns for one or more NSI. In block 506, the method 500 predicts a demand for network resources per NSI for a given time and location. In block 508, based on the demand, the method 500 adjusts an allocation of the network resources for the one or more NSI.

[0048] Example Systems and Apparatuses

[0049] FIG. 6 illustrates an architecture of a system 600 of a network in accordance with some embodiments. The system 600 is shown to include a UE 602; a 5G access node or RAN node (shown as (R)AN node 608); a Elser Plane Function (shown as ETPF 604); a Data Network (DN 606), which may be, for example, operator services, Internet access or 3rd party services; and a 5G Core Network (5GC) (shown as CN 610).

[0050] The CN 610 may include an Authentication Server Function (AE1SF 614); a Core Access and Mobility Management Function (AMF 612); a Session Management Function (SMF 618); a Network Exposure Function (NEF 616); a Policy Control Function (PCF 622); a Network Function (NF) Repository Function (NRF 620); a Elnified Data Management (E1DM 624); and an Application Function (AF 626). The CN 610 may also include other elements that are not shown, such as a Structured Data Storage network function (SDSF), an Elnstructured Data Storage network function (E1DSF), and the like.

[0051] The ETPF 604 may act as an anchor point for intra-RAT and inter-RAT mobility, an external PDE1 session point of interconnect to DN 606, and a branching point to support multi-homed PDE1 session. The UPF 604 may also perform packet routing and forwarding, packet inspection, enforce user plane part of policy rules, lawfully intercept packets (UP collection); traffic usage reporting, perform QoS handling for user plane (e.g. packet filtering, gating, UL/DL rate enforcement), perform Uplink Traffic verification (e.g., SDF to QoS flow mapping), transport level packet marking in the uplink and downlink, and downlink packet buffering and downlink data notification triggering. UPF 604 may include an uplink classifier to support routing traffic flows to a data network. The DN 606 may represent various network operator services, Internet access, or third party services.

[0052] The AUSF 614 may store data for authentication of UE 602 and handle

authentication related functionality. The AUSF 614 may facilitate a common authentication framework for various access types.

[0053] The AMF 612 may be responsible for registration management (e.g., for registering UE 602, etc.), connection management, reachability management, mobility management, and lawful interception of AMF-related events, and access authentication and

authorization. AMF 612 may provide transport for SM messages for the SMF 618, and act as a transparent proxy for routing SM messages. AMF 612 may also provide transport for short message service (SMS) messages between UE 602 and an SMS function (SMSF) (not shown by FIG. 6). AMF 612 may act as Security Anchor Function (SEA), which may include interaction with the AUSF 614 and the UE 602, receipt of an intermediate key that was established as a result of the UE 602 authentication process. Where USIM based authentication is used, the AMF 612 may retrieve the security material from the AUSF 614. AMF 612 may also include a Security Context Management (SCM) function, which receives a key from the SEA that it uses to derive access-network specific

keys. Furthermore, AMF 612 may be a termination point of RAN CP interface (N2 reference point), a termination point of NAS (NI) signaling, and perform NAS ciphering and integrity protection.

[0054] AMF 612 may also support NAS signaling with a UE 602 over an N3

interworking-function (IWF) interface. The N3IWF may be used to provide access to untrusted entities. N3IWF may be a termination point for the N2 and N3 interfaces for control plane and user plane, respectively, and as such, may handle N2 signaling from SMF and AMF for PDU sessions and QoS, encapsulate/de-encapsulate packets for IPSec and N3 tunneling, mark N3 user-plane packets in the uplink, and enforce QoS corresponding to N3 packet marking taking into account QoS requirements associated to such marking received over N2. N3IWF may also relay uplink and downlink control-plane NAS (NI) signaling between the UE 602 and AMF 612, and relay uplink and downlink user-plane packets between the UE 602 and UPF 604. The N3IWF also provides mechanisms for IPsec tunnel establishment with the UE 602. [0055] The SMF 618 may be responsible for session management (e.g., session establishment, modify and release, including tunnel maintain between UPF and AN node); UE IP address allocation & management (including optional Authorization); Selection and control of UP function; Configures traffic steering at UPF to route traffic to proper destination; termination of interfaces towards Policy control functions; control part of policy enforcement and QoS; lawful intercept (for SM events and interface to LI System);

termination of SM parts of NAS messages; downlink Data Notification; initiator of AN specific SM information, sent via AMF over N2 to AN; determine SSC mode of a

session. The SMF 618 may include the following roaming functionality: handle local enforcement to apply QoS SLAs (VPLMN); charging data collection and charging interface (VPLMN); lawful intercept (in VPLMN for SM events and interface to LI System); support for interaction with external DN for transport of signaling for PDU session

authorization/authentication by external DN.

[0056] The NEF 616 may provide means for securely exposing the services and

capabilities provided by 3 GPP network functions for third party, internal exposure/re- exposure, Application Functions (e.g., AF 626), edge computing or fog computing systems, etc. In such embodiments, the NEF 616 may authenticate, authorize, and/or throttle the AFs. NEF 616 may also translate information exchanged with the AF 626 and information exchanged with internal network functions. For example, the NEF 616 may translate between an AF-Service-Identifier and an internal 5GC information. NEF 616 may also receive information from other network functions (NFs) based on exposed capabilities of other network functions. This information may be stored at the NEF 616 as structured data, or at a data storage NF using a standardized interfaces. The stored information can then be re-exposed by the NEF 616 to other NFs and AFs, and/or used for other purposes such as analytics.

[0057] The NRF 620 may support service discovery functions, receive NF Discovery Requests from NF instances, and provide the information of the discovered NF instances to the NF instances. NRF 620 also maintains information of available NF instances and their supported services.

[0058] The PCF 622 may provide policy rules to control plane function(s) to enforce them, and may also support unified policy framework to govern network behavior. The PCF 622 may also implement a front end (FE) to access subscription information relevant for policy decisions in a UDR of UDM 624.

[0059] The UDM 624 may handle subscription-related information to support the network entities' handling of communication sessions, and may store subscription data of UE 602. The UDM 624 may include two parts, an application FE and a User Data Repository (UDR). The UDM may include a UDM FE, which is in charge of processing of credentials, location management, subscription management and so on. Several different front ends may serve the same user in different transactions. The UDM-FE accesses subscription information stored in the UDR and performs authentication credential processing; user identification handling; access authorization; registration/mobility management; and subscription management. The UDR may interact with PCF 622 . UDM 624 may also support SMS management, wherein an SMS-FE implements the similar application logic as discussed previously.

[0060] The AF 626 may provide application influence on traffic routing, access to the Network Capability Exposure (NCE), and interact with the policy framework for policy control. The NCE may be a mechanism that allows the 5GC and AF 626 to provide information to each other via NEF 616, which may be used for edge computing

implementations. In such implementations, the network operator and third party services may be hosted close to the UE 602 access point of attachment to achieve an efficient service delivery through the reduced end-to-end latency and load on the transport network. For edge computing implementations, the 5GC may select a UPF 604 close to the UE 602 and execute traffic steering from the UPF 604 to DN 606 via the N6 interface. This may be based on the UE subscription data, UE location, and information provided by the AF 626. In this way, the AF 626 may influence UPF (re)selection and traffic routing. Based on operator deployment, when AF 626 is considered to be a trusted entity, the network operator may permit AF 626 to interact directly with relevant NFs.

[0061] As discussed previously, the CN 610 may include an SMSF, which may be responsible for SMS subscription checking and verification, and relaying SM messages to/from the UE 602 to/from other entities, such as an SMS-GMSC/IWMSC/SMS- router. The SMS may also interact with AMF 612 and UDM 624 for notification procedure that the UE 602 is available for SMS transfer (e.g., set a UE not reachable flag, and notifying UDM 624 when UE 602 is available for SMS).

[0062] The system 600 may include the following service-based interfaces: Namf:

Service-based interface exhibited by AMF; Nsmf: Service-based interface exhibited by SMF; Nnef: Service-based interface exhibited by NEF;

Npcf: Service-based interface exhibited by PCF; Nudm: Service-based interface exhibited by UDM; Naf: Service-based interface exhibited by AF; Nnrf: Service-based interface exhibited by NRF; and Nausf: Service-based interface exhibited by AUSF. [0063] The system 600 may include the following reference points: Nl : Reference point between the UE and the AMF; N2: Reference point between the (R)AN and the AMF; N3 : Reference point between the (R)AN and the UPF; N4: Reference point between the SMF and the UPF; and N6: Reference point between the UPF and a Data Network. There may be many more reference points and/or service-based interfaces between the NF services in the NFs, however, these interfaces and reference points have been omitted for clarity. For example, an NS reference point may be between the PCF and the AF; an N7 reference point may be between the PCF and the SMF; an Nl 1 reference point between the AMF and SMF; etc. In some embodiments, the CN 610 may include an Nx interface, which is an inter-CN interface between the mobility management entity (MME) and the AMF 612 in order to enable interworking between CN 610 and other CNs.

[0064] Although not shown by FIG. 6, the system 600 may include multiple RAN nodes (such as (R)AN node 608) wherein an Xn interface is defined between two or more (R)AN node 608 (e.g., gNBs and the like) that connecting to 5GC 410, between a (R)AN node 608 (e.g., gNB) connecting to CN 610 and an eNB, and/or between two eNBs connecting to CN 610.

[0065] In some implementations, the Xn interface may include an Xn user plane (Xn-U) interface and an Xn control plane (Xn-C) interface. The Xn-U may provide non-guaranteed delivery of user plane PDUs and support/provide data forwarding and flow control functionality. The Xn-C may provide management and error handling functionality, functionality to manage the Xn-C interface; mobility support for UE 602 in a connected mode (e.g., CM-CONNECTED) including functionality to manage the UE mobility for connected mode between one or more (R)AN node 608. The mobility support may include context transfer from an old (source) serving (R)AN node 608 to new (target) serving (R)AN node 608; and control of user plane tunnels between old (source) serving (R)AN node 608 to new (target) serving (R)AN node 608.

[0066] A protocol stack of the Xn-U may include a transport network layer built on Internet Protocol (IP) transport layer, and a GTP-U layer on top of a UDP and/or IP layer(s) to carry user plane PDUs. The Xn-C protocol stack may include an application layer signaling protocol (referred to as Xn Application Protocol (Xn-AP)) and a transport network layer that is built on an SCTP layer. The SCTP layer may be on top of an IP layer. The SCTP layer provides the guaranteed delivery of application layer messages. In the transport IP layer point-to-point transmission is used to deliver the signaling PDUs. In other implementations, the Xn-U protocol stack and/or the Xn-C protocol stack may be same or similar to the user plane and/or control plane protocol stack(s) shown and described herein. [0067] FIG. 7 illustrates example components of a device 700 in accordance with some embodiments. In some embodiments, the device 700 may include application circuitry 702, baseband circuitry 704, Radio Frequency (RF) circuitry (shown as RF circuitry 720), front- end module (FEM) circuitry (shown as FEM circuitry 730), one or more antennas 732, and power management circuitry (PMC) (shown as PMC 734) coupled together at least as shown. The components of the illustrated device 700 may be included in a EGE or a RAN node. In some embodiments, the device 700 may include fewer elements (e.g., a RAN node may not utilize application circuitry 702, and instead include a processor/controller to process IP data received from an EPC). In some embodiments, the device 700 may include additional elements such as, for example, memory/storage, display, camera, sensor, or input/output (I/O) interface. In other embodiments, the components described below may be included in more than one device (e.g., said circuitries may be separately included in more than one device for Cloud-RAN (C-RAN) implementations).

[0068] The application circuitry 702 may include one or more application processors. For example, the application circuitry 702 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The processor(s) may include any

combination of general-purpose processors and dedicated processors (e.g., graphics processors, application processors, etc.). The processors may be coupled with or may include memory/storage and may be configured to execute instructions stored in the memory/storage to enable various applications or operating systems to run on the device 700. In some embodiments, processors of application circuitry 702 may process IP data packets received from an EPC.

[0069] The baseband circuitry 704 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The baseband circuitry 704 may include one or more baseband processors or control logic to process baseband signals received from a receive signal path of the RF circuitry 720 and to generate baseband signals for a transmit signal path of the RF circuitry 720. The baseband circuitry 704 may interface with the application circuitry 702 for generation and processing of the baseband signals and for controlling operations of the RF circuitry 720. For example, in some embodiments, the baseband circuitry 704 may include a third generation (3G) baseband processor (3G baseband processor 706), a fourth generation (4G) baseband processor (4G baseband processor 708), a fifth generation (5G) baseband processor (5G baseband processor 710), or other baseband processor(s) 712 for other existing generations, generations in development or to be developed in the future (e.g., second generation (2G), sixth generation (6G), etc.). The baseband circuitry 704 (e.g., one or more of baseband processors) may handle various radio control functions that enable communication with one or more radio networks via the RF circuitry 720. In other embodiments, some or all of the functionality of the illustrated baseband processors may be included in modules stored in the memory 718 and executed via a Central Processing Unit (CPU 714). The radio control functions may include, but are not limited to, signal modulation/demodulation, encoding/decoding, radio frequency shifting, etc. In some embodiments, modulation/demodulation circuitry of the baseband circuitry 704 may include Fast-Fourier Transform (FFT), precoding, or

constellation mapping/demapping functionality. In some embodiments, encoding/decoding circuitry of the baseband circuitry 704 may include convolution, tail-biting convolution, turbo, Viterbi, or Low Density Parity Check (LDPC) encoder/decoder

functionality. Embodiments of modulation/demodulation and encoder/decoder functionality are not limited to these examples and may include other suitable functionality in other embodiments.

[0070] In some embodiments, the baseband circuitry 704 may include a digital signal processor (DSP), such as one or more audio DSP(s) 716. The one or more audio DSP(s) 716 may include elements for compression/decompression and echo cancellation and may include other suitable processing elements in other embodiments. Components of the baseband circuitry may be suitably combined in a single chip, a single chipset, or disposed on a same circuit board in some embodiments. In some embodiments, some or all of the constituent components of the baseband circuitry 704 and the application circuitry 702 may be implemented together such as, for example, on a system on a chip (SOC).

[0071] In some embodiments, the baseband circuitry 704 may provide for communication compatible with one or more radio technologies. For example, in some embodiments, the baseband circuitry 704 may support communication with an evolved universal terrestrial radio access network (EUTRAN) or other wireless metropolitan area networks (WMAN), a wireless local area network (WLAN), or a wireless personal area network

(WPAN). Embodiments in which the baseband circuitry 704 is configured to support radio communications of more than one wireless protocol may be referred to as multi-mode baseband circuitry.

[0072] The RF circuitry 720 may enable communication with wireless networks using modulated electromagnetic radiation through a non-solid medium. In various embodiments, the RF circuitry 720 may include switches, filters, amplifiers, etc. to facilitate the communication with the wireless network. The RF circuitry 720 may include a receive signal path which may include circuitry to down-convert RF signals received from the FEM circuitry 730 and provide baseband signals to the baseband circuitry 704. The RF circuitry 720 may also include a transmit signal path which may include circuitry to up-convert baseband signals provided by the baseband circuitry 704 and provide RF output signals to the FEM circuitry 730 for transmission.

[0073] In some embodiments, the receive signal path of the RF circuitry 720 may include mixer circuitry 722, amplifier circuitry 724 and filter circuitry 726. In some embodiments, the transmit signal path of the RF circuitry 720 may include filter circuitry 726 and mixer circuitry 722. The RF circuitry 720 may also include synthesizer circuitry 728 for synthesizing a frequency for use by the mixer circuitry 722 of the receive signal path and the transmit signal path. In some embodiments, the mixer circuitry 722 of the receive signal path may be configured to down-convert RF signals received from the FEM circuitry 730 based on the synthesized frequency provided by synthesizer circuitry 728. The amplifier circuitry 724 may be configured to amplify the down-converted signals and the filter circuitry 726 may be a low-pass filter (LPF) or band-pass filter (BPF) configured to remove unwanted signals from the down-converted signals to generate output baseband

signals. Output baseband signals may be provided to the baseband circuitry 704 for further processing. In some embodiments, the output baseband signals may be zero-frequency baseband signals, although this is not a requirement. In some embodiments, the mixer circuitry 722 of the receive signal path may comprise passive mixers, although the scope of the embodiments is not limited in this respect.

[0074] In some embodiments, the mixer circuitry 722 of the transmit signal path may be configured to up-convert input baseband signals based on the synthesized frequency provided by the synthesizer circuitry 728 to generate RF output signals for the FEM circuitry 730. The baseband signals may be provided by the baseband circuitry 704 and may be filtered by the filter circuitry 726.

[0075] In some embodiments, the mixer circuitry 722 of the receive signal path and the mixer circuitry 722 of the transmit signal path may include two or more mixers and may be arranged for quadrature downconversion and upconversion, respectively. In some embodiments, the mixer circuitry 722 of the receive signal path and the mixer circuitry 722 of the transmit signal path may include two or more mixers and may be arranged for image rejection (e.g., Hartley image rejection). In some embodiments, the mixer circuitry 722 of the receive signal path and the mixer circuitry 722 may be arranged for direct

downconversion and direct upconversion, respectively. In some embodiments, the mixer circuitry 722 of the receive signal path and the mixer circuitry 722 of the transmit signal path may be configured for super-heterodyne operation. [0076] In some embodiments, the output baseband signals and the input baseband signals may be analog baseband signals, although the scope of the embodiments is not limited in this respect. In some alternate embodiments, the output baseband signals and the input baseband signals may be digital baseband signals. In these alternate embodiments, the RF circuitry 720 may include analog-to-digital converter (ADC) and digital-to-analog converter (DAC) circuitry and the baseband circuitry 704 may include a digital baseband interface to communicate with the RF circuitry 720.

[0077] In some dual-mode embodiments, a separate radio IC circuitry may be provided for processing signals for each spectrum, although the scope of the embodiments is not limited in this respect.

[0078] In some embodiments, the synthesizer circuitry 728 may be a fractional-N synthesizer or a fractional N/N+l synthesizer, although the scope of the embodiments is not limited in this respect as other types of frequency synthesizers may be suitable. For example, synthesizer circuitry 728 may be a delta-sigma synthesizer, a frequency multiplier, or a synthesizer comprising a phase-locked loop with a frequency divider.

[0079] The synthesizer circuitry 728 may be configured to synthesize an output frequency for use by the mixer circuitry 722 of the RF circuitry 720 based on a frequency input and a divider control input. In some embodiments, the synthesizer circuitry 728 may be a fractional N/N+l synthesizer.

[0080] In some embodiments, frequency input may be provided by a voltage controlled oscillator (VCO), although that is not a requirement. Divider control input may be provided by either the baseband circuitry 704 or the application circuitry 702 (such as an applications processor) depending on the desired output frequency. In some embodiments, a divider control input (e.g., N) may be determined from a look-up table based on a channel indicated by the application circuitry 702.

[0081] Synthesizer circuitry 728 of the RF circuitry 720 may include a divider, a delay- locked loop (DLL), a multiplexer and a phase accumulator. In some embodiments, the divider may be a dual modulus divider (DMD) and the phase accumulator may be a digital phase accumulator (DP A). In some embodiments, the DMD may be configured to divide the input signal by either N or N+l (e.g., based on a carry out) to provide a fractional division ratio. In some example embodiments, the DLL may include a set of cascaded, tunable, delay elements, a phase detector, a charge pump and a D-type flip-flop. In these

embodiments, the delay elements may be configured to break a VCO period up into Nd equal packets of phase, where Nd is the number of delay elements in the delay line. In this way, the DLL provides negative feedback to help ensure that the total delay through the delay line is one VCO cycle.

[0082] In some embodiments, the synthesizer circuitry 728 may be configured to generate a carrier frequency as the output frequency, while in other embodiments, the output frequency may be a multiple of the carrier frequency (e.g., twice the carrier frequency, four times the carrier frequency) and used in conjunction with quadrature generator and divider circuitry to generate multiple signals at the carrier frequency with multiple different phases with respect to each other. In some embodiments, the output frequency may be a LO frequency

(fLO). In some embodiments, the RF circuitry 720 may include an IQ/polar converter.

[0083] The FEM circuitry 730 may include a receive signal path which may include circuitry configured to operate on RF signals received from one or more antennas 732, amplify the received signals and provide the amplified versions of the received signals to the RF circuitry 720 for further processing. The FEM circuitry 730 may also include a transmit signal path which may include circuitry configured to amplify signals for transmission provided by the RF circuitry 720 for transmission by one or more of the one or more antennas 732. In various embodiments, the amplification through the transmit or receive signal paths may be done solely in the RF circuitry 720, solely in the FEM circuitry 730, or in both the RF circuitry 720 and the FEM circuitry 730.

[0084] In some embodiments, the FEM circuitry 730 may include a TX/RX switch to switch between transmit mode and receive mode operation. The FEM circuitry 730 may include a receive signal path and a transmit signal path. The receive signal path of the FEM circuitry 730 may include an LNA to amplify received RF signals and provide the amplified received RF signals as an output (e.g., to the RF circuitry 720). The transmit signal path of the FEM circuitry 730 may include a power amplifier (PA) to amplify input RF signals (e.g., provided by the RF circuitry 720), and one or more filters to generate RF signals for subsequent transmission (e.g., by one or more of the one or more antennas 732).

[0085] In some embodiments, the PMC 734 may manage power provided to the baseband circuitry 704. In particular, the PMC 734 may control power-source selection, voltage scaling, battery charging, or DC-to-DC conversion. The PMC 734 may often be included when the device 700 is capable of being powered by a battery, for example, when the device 700 is included in a UE. The PMC 734 may increase the power conversion efficiency while providing desirable implementation size and heat dissipation characteristics.

[0086] FIG. 7 shows the PMC 734 coupled only with the baseband circuitry 704. However, in other embodiments, the PMC 734 may be additionally or alternatively coupled with, and perform similar power management operations for, other components such as, but not limited to, the application circuitry 702, the RF circuitry 720, or the FEM circuitry 730.

[0087] In some embodiments, the PMC 734 may control, or otherwise be part of, various power saving mechanisms of the device 700. For example, if the device 700 is in an

RRC Connected state, where it is still connected to the RAN node as it expects to receive traffic shortly, then it may enter a state known as Discontinuous Reception Mode (DRX) after a period of inactivity. During this state, the device 700 may power down for brief intervals of time and thus save power.

[0088] If there is no data traffic activity for an extended period of time, then the device 700 may transition off to an RRC Idle state, where it disconnects from the network and does not perform operations such as channel quality feedback, handover, etc. The device 700 goes into a very low power state and it performs paging where again it periodically wakes up to listen to the network and then powers down again. The device 700 may not receive data in this state, and in order to receive data, it transitions back to an RRC Connected state.

[0089] An additional power saving mode may allow a device to be unavailable to the network for periods longer than a paging interval (ranging from seconds to a few

hours). During this time, the device is totally unreachable to the network and may power down completely. Any data sent during this time incurs a large delay and it is assumed the delay is acceptable.

[0090] Processors of the application circuitry 702 and processors of the baseband circuitry 704 may be used to execute elements of one or more instances of a protocol stack. For example, processors of the baseband circuitry 704, alone or in combination, may be used to execute Layer 3, Layer 2, or Layer 1 functionality, while processors of the application circuitry 702 may utilize data (e.g., packet data) received from these layers and further execute Layer 4 functionality (e.g., transmission communication protocol (TCP) and user datagram protocol (UDP) layers). As referred to herein, Layer 3 may comprise a radio resource control (RRC) layer, described in further detail below. As referred to herein, Layer 2 may comprise a medium access control (MAC) layer, a radio link control (RLC) layer, and a packet data convergence protocol (PDCP) layer, described in further detail below. As referred to herein, Layer 1 may comprise a physical (PHY) layer of a UE/RAN node, described in further detail below.

[0091] FIG. 8 illustrates example interfaces 800 of baseband circuitry in accordance with some embodiments. As discussed above, the baseband circuitry 704 of FIG. 7 may comprise 3G baseband processor 706, 4G baseband processor 708, 5G baseband processor 710, other baseband processor(s) 712, CPU 714, and a memory 718 utilized by said processors. As illustrated, each of the processors may include a respective memory interface 802 to send/receive data to/from the memory 718.

[0092] The baseband circuitry 704 may further include one or more interfaces to communicatively couple to other circuitries/devices, such as a memory interface 804 (e.g., an interface to send/receive data to/from memory external to the baseband circuitry 704), an application circuitry interface 806 (e.g., an interface to send/receive data to/from the application circuitry 702 of FIG. 7), an RF circuitry interface 808 (e.g., an interface to send/receive data to/from RF circuitry 720 of FIG. 7), a wireless hardware connectivity interface 810 (e.g., an interface to send/receive data to/from Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components), and a power management interface 812 (e.g., an interface to send/receive power or control signals to/from the PMC 734.

[0093] FIG. 9 is a block diagram illustrating components, according to some example embodiments, of a system 900 to support NFV. The system 900 is illustrated as including a virtualized infrastructure manager (shown as VIM 902), a network function virtualization infrastructure (shown as NFVI 904), a VNF manager (shown as VNFM 906), virtualized network functions (shown as VNF 908), an element manager (shown as EM 910), an NFV Orchestrator (shown as NFVO 912), and a network manager (shown as NM 914).

[0094] The VIM 902 manages the resources of the NFVI 904. The NFVI 904 can include physical or virtual resources and applications (including hypervisors) used to execute the system 900. The VIM 902 may manage the life cycle of virtual resources with the NFVI 904 (e.g., creation, maintenance, and tear down of virtual machines (VMs) associated with one or more physical resources), track VM instances, track performance, fault and security of VM instances and associated physical resources, and expose VM instances and associated physical resources to other management systems.

[0095] The VNFM 906 may manage the VNF 908. The VNF 908 may be used to execute EPC components/functions. The VNFM 906 may manage the life cycle of the VNF 908 and track performance, fault and security of the virtual aspects of VNF 908. The EM 910 may track the performance, fault and security of the functional aspects of VNF 908. The tracking data from the VNFM 906 and the EM 910 may comprise, for example, performance measurement (PM) data used by the VIM 902 or the NFVI 904. Both the VNFM 906 and the EM 910 can scale up/down the quantity of VNFs of the system 900. [0096] The NFVO 912 may coordinate, authorize, release and engage resources of the NFVI 904 in order to provide the requested service (e.g., to execute an EPC function, component, or slice). The NM 914 may provide a package of end-user functions with the responsibility for the management of a network, which may include network elements with VNFs, non-virtualized network functions, or both (management of the VNFs may occur via the EM 910).

[0097] FIG. 10 is a block diagram illustrating components 1000, according to some example embodiments, able to read instructions from a machine-readable or computer- readable medium (e.g., a non-transitory machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically, FIG. 10 shows a diagrammatic representation of hardware resources 1002 including one or more processors 1012 (or processor cores), one or more memory/storage devices 1018, and one or more communication resources 1020, each of which may be communicatively coupled via a bus 1022. For embodiments where node virtualization (e.g., NFV) is utilized, a hypervisor 1004 may be executed to provide an execution environment for one or more network slices/sub- slices to utilize the hardware resources 1002.

[0098] The processors 1012 (e.g., a central processing unit (CPET), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPET), a digital signal processor (DSP) such as a baseband processor, an application specific integrated circuit (ASIC), a radio-frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 1014 and a processor 1016.

[0099] The memory/storage devices 1018 may include main memory, disk storage, or any suitable combination thereof. The memory/storage devices 1018 may include, but are not limited to any type of volatile or non-volatile memory such as dynamic random access memory (DRAM), static random-access memory (SRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM),

Flash memory, solid-state storage, etc.

[0100] The communication resources 1020 may include interconnection or network interface components or other suitable devices to communicate with one or more peripheral devices 1006 or one or more databases 1008 via a network 1010. For example, the communication resources 1020 may include wired communication components (e.g., for coupling via a ETniversal Serial Bus (USB)), cellular communication components, NFC components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components. [0101] Instructions 1024 may comprise software, a program, an application, an applet, an app, or other executable code for causing at least any of the processors 1012 to perform any one or more of the methodologies discussed herein. The instructions 1024 may reside, completely or partially, within at least one of the processors 1012 (e.g., within the processor’s cache memory), the memory/storage devices 1018, or any suitable combination thereof. Furthermore, any portion of the instructions 1024 may be transferred to the hardware resources 1002 from any combination of the peripheral devices 1006 or the databases 1008. Accordingly, the memory of the processors 1012, the memory/storage devices 1018, the peripheral devices 1006, and the databases 1008 are examples of computer-readable and machine-readable media.

[0102] For one or more embodiments, at least one of the components set forth in one or more of the preceding figures may be configured to perform one or more operations, techniques, processes, and/or methods as set forth in the example section below. For example, the baseband circuitry as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below. For another example, circuitry associated with a UE, base station, network element, etc. as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below in the example section.

[0103] Example Section

[0104] The following examples pertain to further embodiments.

[0105] Example 1 is an apparatus for a self-organizing network (SON) function in a wireless network. The apparatus includes a memory interface and a processor. The memory interface is to send or receive, to or from a memory device, management data. The processor is to: collect the management data from a management service producer in the wireless network; perform an analysis of the management data; and generate actions to automatically control one or more behavior of a radio access network (RAN) node or a core network, wherein the one or more behavior is selected from a group comprising a prediction of traffic demands, a tendency of resource utilization, and an indication of a RAN condition.

[0106] Example 2 is the apparatus of Example 1, wherein the processor is further configured to report an output of the analysis of the management data to one or more applications in the wireless network.

[0107] Example 3 is the apparatus of Example 1, wherein the management data comprises one of performance measurements, alarm information, and configuration information. [0108] Example 4 is the apparatus of Example 1, wherein to collect the management data from the management service producer comprises to collect the management data from one or more of a network function (NF) management service producer, a network slice instance (NSI) management service producer, and a network slice subnet instance (NSSI).

[0109] Example 5 is the apparatus of Example 4, wherein the processor is further configured to consume provisioning management services to collect configuration information for one or more of the NF, the NSI, and the NSSI.

[0110] Example 6 is the apparatus of Example 5, wherein the processor is further configured to use a modify managed object instance (MOI) attributes

(modifyMOIAttributes) operation in the provisioning management services to apply the actions.

[0111] Example 7 is the apparatus of Example 4, wherein the processor is further configured to consume a performance data file reporting service to collect performance data files for one or more of the NF, the NSI, and the NSSI.

[0112] Example 8 is the apparatus of Example 4, wherein the processor is further configured to consume a performance data streaming service to collect real-time

performance data for one or more of the NF, the NSI, and the NSSI.

[0113] Example 9 is the apparatus of Example 4, wherein the processor is further configured to consume a fault supervision data report management service to receive alarms for one or more of the NF, the NSI, and the NSSI.

[0114] Example 10 is the apparatus of Example 1, wherein to perform the analysis of the management data comprises to analyze historical data collected over a period of time to predict changes in the traffic demands of the wireless network based on times and geographic locations, and wherein to generate the actions to automatically control the one or more behavior comprises adapting to the changes in advance.

[0115] Example 11 is the apparatus of Example 10, wherein the period of time is selected from a group comprising minutes, hours, days, weeks, months, and years.

[0116] Example 12 is the apparatus of Example 10, wherein the processor is further configured to, in response to predicting a high volume of massive machine type

communication (mMTC) traffic at a particular time and a particular geographic location, automatically configure the wireless network to increase mMTC capacity of one or more cells in the wireless network corresponding to the particular geographic location at the particular time. [0117] Example 13 is the apparatus of Example 1, wherein to perform the analysis of the management data comprises to generate RAN condition data to indicate a condition of a cell of the wireless network.

[0118] Example 14 is the apparatus of Example 13, wherein the RAN condition data includes a value to indicate that the cell is healthy, out of service, capacity constrained, or capability constrained.

[0119] Example 15 is the apparatus of Example 13, wherein the processor is further configured to provide the RAN condition data to an application selected from a group comprising an internet of things (IoT) application and an edge computing application.

[0120] Example 16 is the apparatus of Example 15, wherein the IoT application comprises an autonomous driving application configured to use the RAN condition data to change a navigation route of an autonomous vehicle through the wireless network.

[0121] Example 17 is a non-transitory computer-readable storage medium. The computer- readable storage medium includes instructions that when executed by a processor of an autonomous driving application, cause the processor to: process radio access network (RAN) condition data from a self-organizing network (SON) function in a wireless network;

determine, based on the RAN condition data, that a first cell in the wireless network is expected to experience reduced performance during a route driving period; and based on the reduced performance expected for the first cell during the route drive period, route or re route a path of an autonomous vehicle to pass through one or more second cells in the wireless network instead of the first cell.

[0122] Example 18 is the computer-readable storage medium of Example 17, wherein the RAN condition data indicates one or more expected conditions from a group comprising the first cell being overloaded with user data traffic, the first cell experience an outage, and the first cell not being able to support a predetermined latency requirement during at least a first portion of the route driving period associated with the first cell.

[0123] Example 19 is the computer-readable storage medium of Example 18, wherein the RAN condition data indicates that the one or more second cells are not expected to be overloaded with user data traffic, not expected to experience an outage, and are expected to support the predetermined latency requirement at least during respective second portions of the route drive period associated with the one or more second cells.

[0124] Example 20 is a method for a self-organizing network (SON) function to improve resource utilization performance of one or more network slice instance (NSI), the method comprising: collecting performance data; using the performance data to identify traffic patterns for one or more network slice instance (NSI); predicting a demand for network resources per NSI for a given time and location; and based on the demand, adjusting an allocation of the network resources for the one or more NSI.

[0125] Example 21 is the method of Example 20, further comprising monitoring the one or more NSI to validate the adjusting of the allocation of the network resources and to determine whether to perform additional adjustments.

[0126] Example 22 is the method of Example 20, wherein the performance data is selected from a group comprising data volume, a number of registered user equipments (UEs), a number of protocol data unit (PDET) sessions, EGE behavior statistics based on charging data records information, quality of service (QoS) parameter notifications, and EGE mobility event notifications from a core network.

[0127] Any of the above described examples may be combined with any other example (or combination of examples), unless explicitly stated otherwise. The foregoing description of one or more implementations provides illustration and description, but is not intended to be exhaustive or to limit the scope of embodiments to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practice of various embodiments.

[0128] Embodiments and implementations of the systems and methods described herein may include various operations, which may be embodied in machine-executable instructions to be executed by a computer system. A computer system may include one or more general- purpose or special-purpose computers (or other electronic devices). The computer system may include hardware components that include specific logic for performing the operations or may include a combination of hardware, software, and/or firmware.

[0129] It should be recognized that the systems described herein include descriptions of specific embodiments. These embodiments can be combined into single systems, partially combined into other systems, split into multiple systems or divided or combined in other ways. In addition, it is contemplated that parameters/attributes/aspects/etc. of one

embodiment can be used in another embodiment. The parameters/attributes/aspects/etc. are merely described in one or more embodiments for clarity, and it is recognized that the parameters/attributes/aspects/etc. can be combined with or substituted for

parameters/attributes/etc. of another embodiment unless specifically disclaimed herein.

[0130] Although the foregoing has been described in some detail for purposes of clarity, it will be apparent that certain changes and modifications may be made without departing from the principles thereof. It should be noted that there are many alternative ways of implementing both the processes and apparatuses described herein. Accordingly, the present embodiments are to be considered illustrative and not restrictive, and the description is not to be limited to the details given herein, but may be modified within the scope and equivalents of the appended claims.

Claims

1. An apparatus for a self-organizing network (SON) function in a wireless network, the apparatus comprising:

a memory interface to send or receive, to or from a memory device, management data; and

a processor to:

collect the management data from a management service producer in the wireless network;

perform an analysis of the management data; and

generate actions to automatically control one or more behavior of a radio access network (RAN) node or a core network, wherein the one or more behavior is selected from a group comprising a prediction of traffic demands, a tendency of resource utilization, and an indication of a RAN condition.

2. The apparatus of claim 1, wherein the processor is further configured to report an output of the analysis of the management data to one or more applications in the wireless network.

3. The apparatus of claim 1, wherein the management data comprises one of performance measurements, alarm information, and configuration information.

4. The apparatus of claim 1, wherein to collect the management data from the management service producer comprises to collect the management data from one or more of a network function (NF) management service producer, a network slice instance (NSI) management service producer, and a network slice subnet instance (NSSI).

5. The apparatus of claim 4, wherein the processor is further configured to consume provisioning management services to collect configuration information for one or more of the NF, the NSI, and the NSSI.

6. The apparatus of claim 5, wherein the processor is further configured to use a modify managed object instance (MOI) attributes (modifyMOIAttributes) operation in the provisioning management services to apply the actions.

7. The apparatus of claim 4, wherein the processor is further configured to consume a performance data file reporting service to collect performance data files for one or more of the NF, the NSI, and the NSSI.

8. The apparatus of claim 4, wherein the processor is further configured to consume a performance data streaming service to collect real-time performance data for one or more of the NF, the NSI, and the NSSI.

9. The apparatus of claim 4, wherein the processor is further configured to consume a fault supervision data report management service to receive alarms for one or more of the NF, the NSI, and the NSSI.

10. The apparatus of claim 1, wherein to perform the analysis of the management data comprises to analyze historical data collected over a period of time to predict changes in the traffic demands of the wireless network based on times and geographic locations, and wherein to generate the actions to automatically control the one or more behavior comprises adapting to the changes in advance.

11. The apparatus of claim 10, wherein the period of time is selected from a group comprising minutes, hours, days, weeks, months, and years.

12. The apparatus of claim 10, wherein the processor is further configured to, in response to predicting a high volume of massive machine type communication (mMTC) traffic at a particular time and a particular geographic location, automatically configure the wireless network to increase mMTC capacity of one or more cells in the wireless network

corresponding to the particular geographic location at the particular time.

13. The apparatus of claim 1, wherein to perform the analysis of the management data comprises to generate RAN condition data to indicate a condition of a cell of the wireless network.

14. The apparatus of claim 13, wherein the RAN condition data includes a value to indicate that the cell is healthy, out of service, capacity constrained, or capability constrained.

15. The apparatus of claim 13, wherein the processor is further configured to provide the RAN condition data to an application selected from a group comprising an internet of things (IoT) application and an edge computing application.

16. The apparatus of claim 15, wherein the IoT application comprises an autonomous driving application configured to use the RAN condition data to change a navigation route of an autonomous vehicle through the wireless network.

17. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a processor of an autonomous driving application, cause the processor to:

process radio access network (RAN) condition data from a self-organizing network (SON) function in a wireless network;

determine, based on the RAN condition data, that a first cell in the wireless network is expected to experience reduced performance during a route driving period; and based on the reduced performance expected for the first cell during the route drive period, route or re-route a path of an autonomous vehicle to pass through one or more second cells in the wireless network instead of the first cell.

18. The computer-readable storage medium of claim 17, wherein the RAN condition data indicates one or more expected conditions from a group comprising the first cell being overloaded with user data traffic, the first cell experience an outage, and the first cell not being able to support a predetermined latency requirement during at least a first portion of the route driving period associated with the first cell.

19. The computer-readable storage medium of claim 18, wherein the RAN condition data indicates that the one or more second cells are not expected to be overloaded with user data traffic, not expected to experience an outage, and are expected to support the predetermined latency requirement at least during respective second portions of the route drive period associated with the one or more second cells.

20. A method for a self-organizing network (SON) function to improve resource utilization performance of one or more network slice instance (NSI), the method comprising:

collecting performance data;

using the performance data to identify traffic patterns for one or more network slice instance (NSI);

predicting a demand for network resources per NSI for a given time and location; and based on the demand, adjusting an allocation of the network resources for the one or more NSI.

21. The method of claim 20, further comprising monitoring the one or more NSI to validate the adjusting of the allocation of the network resources and to determine whether to perform additional adjustments.

22. The method of claim 20, wherein the performance data is selected from a group comprising data volume, a number of registered user equipments (UEs), a number of protocol data unit (PDU) sessions, UE behavior statistics based on charging data records information, quality of service (QoS) parameter notifications, and EGE mobility event notifications from a core network.