Non-real-time RIC architecture supporting cooperative RAN and core information sharing and control

Abstract

A method for policy / control implementation includes: acquiring, by a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC), first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; and implementing, by the NRT RIC, the at least one policy / control in the RAN.

Description

[Technical Field]

[0001] [CROSS REFERENCE TO RELATED APPLICATIONS] This application claims priority from Indian Patent Application No. 202241058574, filed with the Indian Patent Office on October 13, 2022, the disclosure of which is incorporated herein by reference in its entirety.

[0002] [Technical field] Apparatus and methods consistent with embodiments of the present disclosure relate to policy / control implementation in a service management and orchestration (SMO) framework. [Background technology]

[0003] The Radio Access Network (RAN) is a critical component in a communication system that connects end-user devices (or user equipment) to the rest of the network. The RAN includes a combination of various network elements (NEs) that connect end-user devices to the core network. Traditionally, the hardware and / or software of a particular RAN has been vendor-specific.

[0004] The emergence of Open RAN (O-RAN) technology allows multiple vendors to provide hardware and / or software for communication systems. To this end, O-RAN decomposes RAN functions into a centralized unit (CU), a distributed unit (DU), and a radio unit (RU). The CU is a logical node for hosting the RAN sublayers of Radio Resource Control (RRC), Service Data Adaptation Protocol (SDAP), and / or Packet Data Convergence Protocol (PDCP). The DU is a logical node for hosting the RAN sublayers of Radio Link Control (RLC), Medium Access Control (MAC), and Physical (PHY). The RU is a physical node that converts radio signals from the antenna into digital signals that can be transmitted over the fronthaul to the DU. These entities can be developed by different vendors because they have open protocols and interfaces between them.

[0005] FIG. 1 is a diagram of an O-RAN architecture in the related art, FIG. 2 is a diagram of a Service Management and Orchestration (SMO) framework with a non-real-time (NRT) RAN intelligent controller (RIC) architecture in the related art from a functional perspective, and FIG. 3 is a diagram of the SMO framework with an NRT RIC in the related art from a service perspective. Referring to FIGS. 1 to 3, RAN functions in the O-RAN architecture are controlled and optimized by the RIC. The RIC is a software-defined component that implements modular applications to realize the multi-vendor operability required in the O-RAN system and automate and optimize RAN operations. RICs are divided into two types: NRT RICs and near real-time RICs (nRT RICs).

[0006] The NRT RIC is the control point for non-real-time control loops and operates within the SMO framework on timescales longer than one second. Its functions are implemented through modular applications called rApps (rApp 1, ..., rApp N in Figures 1-3) and include providing policy-based guidance and enrichment over the A1 interface, which is the interface enabling communication between the NRT RIC and the nRT RIC; performing data analytics; artificial intelligence / machine learning (AI / ML) training and inference for RAN optimization; and / or recommending configuration management actions over the O1 interface, which is the interface connecting the SMO to RAN management elements (e.g., nRT RIC, O-RAN aggregation unit (O-CU), O-RAN distributed unit (O-DU), etc.).

[0007] The nRT RIC operates on a time scale between 10 milliseconds and 1 second and connects to the O-DU, O-CU (decomposed into the O-CU control plane (O-CU-CP) and the O-CU user plane (O-CU-UP)), and the "open evolved NodeB" (O-eNB) via the E2 interface. The nRT RIC uses the E2 interface to control the underlying RAN elements (E2 nodes / network functions (NFs)) in a near-real-time control loop. The nRT RIC monitors, suspends / stops, overrides, and controls the E2 nodes (O-CU, O-DU, and O-eNB) through policies. For example, the nRT sets policy parameters on the activated functions of the E2 nodes. Furthermore, the nRT RIC hosts xApps for implementing functions such as quality of service (QoS) optimization, mobility optimization, slicing optimization, interference mitigation, load balancing, and security. The two types of RICs work together to optimize the O-RAN. For example, the NRT RIC provides policies, data, and artificial intelligence (AI) / machine learning (ML) models over the A1 interface that are enabled and used by the nRT RIC for RAN optimization, and the nRT returns policy feedback (i.e., how the policies set by the NRT RIC are working).

[0008] The SMO framework in which the NRT RIC resides manages and coordinates RAN elements. Specifically, the SMO manages and coordinates what is referred to as the O-RAN Cloud (O-Cloud). The O-Cloud is a collection of physical RAN nodes that host the RIC, O-CU, and O-DU, supporting software components (e.g., operating systems and runtime environments), and the SMO itself. In other words, the SMO manages the O-Cloud from within. The O2 interface is the interface between the SMO and the O-Cloud in which it resides. The SMO provides Infrastructure Management Services (IMS) and Deployment Management Services (DMS) through the O2 interface. Summary of the Invention [Problem to be solved by the invention]

[0009] In the related art, the NRT RIC can only control RAN parameters. The related art NRT RIC architecture cannot control other parameters of the network, such as parameters for the core network (e.g., 4th generation (4G) "long term evolution" (LTE) "evolved packet core" (EPC), 5th generation (5G) "new radio" (NR) core, etc.), inventory, or geolocation information. Furthermore, the intelligent controller for the RAN layer and the core network may move. Thus, the lack of coordination between the RAN and the core controller can lead to serious conflicts and performance degradation in the network.

[0010] Additionally, related art systems do not provide for enrichment of AI / ML models in the NRT RIC with inventory, geolocation, and user equipment (UE) specific configuration from the core network (or other external sources) and / or planning data. Furthermore, related art systems have difficulty accessing parameter, context, and event information in the core network. [Means for solving the problem]

[0011] According to embodiments, a system and method are provided for policy / control implementation in a service management and orchestration (SMO) framework and core network based on externally obtained enrichment data and information sharing between the core network and the SMO.

[0012] According to one aspect of the disclosure, a method for policy / control implementation may include obtaining, by a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC), first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; and implementing, by the NRT RIC, the at least one policy / control in the RAN.

[0013] According to one aspect of the disclosure, a system for policy / control implementation may include a memory storing instructions; and a processor configured to execute the instructions to: obtain, by an NRT RIC, first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determine, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; and implement, by the NRT RIC, the at least one policy / control in the RAN.

[0014] According to one aspect of the disclosure, a non-transitory computer-readable storage medium may store instructions that, when executed by at least one processor, cause the at least one processor to: acquire, by the NRT RIC, first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determine, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; and implement, by the NRT RIC, the at least one policy / control in the RAN.

[0015] According to one aspect of the disclosure, a method for policy / control implementation may include: obtaining, by a core network, first enrichment data corresponding to RAN information from an NRT RIC external to the core network via a first external interface; determining, by the core network, at least one policy / control to be implemented in the core network based on the first enrichment data; and implementing, by the core network, the at least one policy / control in the core network.

[0016] Additional aspects will be set forth in part in the description that follows, and in part will be obvious from the description, or may be realized by practice of presented embodiments of the disclosure. [Brief explanation of the drawings]

[0017] The features, advantages and significance of exemplary embodiments of the disclosure will be described below with reference to the accompanying drawings, in which like numerals represent like elements and in which:

[0018] FIG. 1 is a diagram of an open radio access network (O-RAN) architecture according to the related art.

[0019] FIG. 2 is a functional view of a Service Management and Orchestration (SMO) framework with a non-real-time (NRT) RAN intelligent controller (RIC) architecture according to the related art.

[0020] FIG. 3 is a related art diagram of a service perspective of a SMO framework with an NRT RIC in the related art.

[0021] FIG. 4 is a diagram of an O-RAN architecture according to one embodiment.

[0022] FIG. 5 is a flowchart of a method for policy / control implementation in an O-RAN architecture according to one embodiment.

[0023] FIG. 6 is a diagram of an example environment in which the systems and / or methods described herein may be implemented.

[0024] FIG. 7 is a diagram of example components of a device, according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0025] The following detailed description of the embodiments refers to the accompanying drawings, in which the same reference numbers in different drawings may identify the same or similar elements.

[0026] The foregoing disclosure provides illustrations and descriptions, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the foregoing disclosure or may be acquired from practice of the implementations. Furthermore, one or more features or components of one embodiment may be combined or combined with other embodiments (or one or more features of other embodiments). Additionally, in the flowcharts and operational descriptions provided below, it is understood that one or more operations may be omitted, one or more operations may be added, one or more operations may be performed concurrently (at least in part), and the order of one or more operations may be rearranged.

[0027] It will be apparent that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specific control hardware or software code used to implement these systems and / or methods is not a limitation of the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It will be understood that software and hardware may be designed to implement the systems and / or methods based on the description herein.

[0028] Although particular feature combinations are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. Indeed, many of these features may be combined in ways other than those specifically recited in the claims and / or specifically disclosed in the specification. Although each dependent claim listed below may depend directly on only one claim, the disclosure of possible implementations includes each dependent claim in combination with all other claims in the claim group.

[0029] No element, act, or instruction used herein should be construed as critical or required unless explicitly stated otherwise. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Where only one item is intended, the term "one" or similar words are used. Also, as used herein, the terms "has," "have," "having," "include," "including," etc. are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based, at least in part, on," unless expressly stated otherwise. Furthermore, phrases such as "at least one of A and B" or "at least one of A or B" are understood to include A only, B only, or both A and B.

[0030] Embodiments provide systems, methods, networks, and devices that enable a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC) to control both the RAN and core network in a coordinated manner and to access data from both the RAN and core network through the network interface disclosed herein. The data sharing and coordinated control of the provided systems, methods, networks, and devices significantly mitigates conflicts between the RAN and core state machines and solves performance degradation issues. Furthermore, the provided systems, methods, networks, and devices include the ability to access enriched information from the core network in the NRT RIC, enabling artificial intelligence (AI) / machine learning (ML) models in rApps or xApps to make more accurate decisions based on the enriched data inputs, improving end-to-end network performance.

[0031] Thus, a method and system are provided for: acquiring, by an NRT RIC, first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; and implementing, by the NRT RIC, the at least one policy / control in the RAN. The first enrichment data may include at least one of user level information, subscription priority information, network slice registration information, and device capability information. The method and system may also include acquiring, by the NRT RIC, second enrichment data corresponding to inventory information of devices connected to the RAN from an inventory database external to the NRT RIC via a second external interface. Here, the at least one policy / control is further determined based on the second enrichment data.

[0032] The method and system may also include having the NRT RIC obtain, via a third external interface, third enrichment data corresponding to RAN location information from a geolocation database external to the NRT RIC, where at least one policy / control is further determined based on the third enrichment data. The method and system may also include having the NRT RIC access, via a fourth external interface, at least one AI / ML / AN engine external to the NRT RIC to perform at least one processing task related to at least one of AI / ML model training, evolution, testing, and performance assurance. The method and system may also obtain, via a fifth external interface, fourth enrichment data corresponding to network planning data from a planning database external to the NRT RIC, where at least one policy / control is further determined based on the fourth enrichment data. The method and system may further include acquiring, by the NRT RIC, fifth enrichment data corresponding to the new core network information from a core network external to the NRT RIC via the first external interface; updating, by the NRT RIC, at least one policy / control based on the fifth enrichment data; and implementing, by the NRT RIC, the updated at least one policy / control in the RAN.

[0033] Further provided is a method and system for policy / control implementation, which may include: acquiring, by a core network, first enrichment data corresponding to RAN information from an NRT RIC outside the core network via a first external interface; determining, by the core network, at least one policy / control to be implemented in the core network based on the first enrichment data; and implementing, by the core network, the at least one policy / control in the core network.

[0034] 4 is a diagram of an open RAN (O-RAN) architecture 400, according to one embodiment. The O-RAN architecture 400 may include a service management and orchestration (SMO) framework 402 with an NRT RIC 404, a near real-time (nRT) RIC 406, an “open evolved NodeB” (O-eNB) 408, an O-RAN aggregation unit (O-CU) control plane (O-CU-CP) 410, an O-CU user plane (O-CU-UP) 412, an O-RAN distributed unit (O-DU) 414, an O-RAN radio unit (O-RU) 416, and an O-RAN cloud (O-Cloud) 418. The O-RAN architecture 400 may include a core network 420 configured to interface with the SMO framework 402, the O-CU-CP 410, and the O-CU-UP 412.

[0035] As shown in FIG. 4 , an interface (e.g., a novel open or standardized interface) is provided between the SMO framework 402 and the core network 420. Through the novel interface according to an embodiment, the SMO framework 402 or the NRT RIC 404 may access data from the core network 420 (e.g., a fourth-generation (4G) “long term evolution” (LTE) “evolved packet core” (EPC), a fifth-generation (5G) “new radio” (NR) core, other next-generation cores, etc.). Through this interface, user equipment (UE)-specific core network information may be accessed, including registration information, UE identifiers (IDs), and more. The architecture 400 may include separate interfaces for inventory data, geolocation data, planning data, and externally or remotely hosted AI, ML, or autonomous network (AN) engines (e.g., AI / ML / AN may be implemented at different sites). This enrichment data may be used to configure policies and cloud-related functions in the SMO framework 402. Planning data, inventory data, geolocation data (e.g., geolocation data of deployed network elements), and core data (e.g., data UE or user-specific subscriptions and IDs, data regarding user subscription priorities, data regarding device priorities, etc.) may be used for anomaly detection and training of AI / ML models for cases where sufficient recent data is not available.

[0036] The NRT RIC 404 may configure and control both the core network 420 and the RAN in a coordinated manner through interfaces for conflict mitigation and performance enhancement. Thus, interfaces are provided, including an interface I1 between the NRT RIC 404 and the core network 420, an interface I2 between the NRT RIC 404 and the inventory database 422, an interface I3 between the NRT RIC 404 and the geolocation database 424, an interface I4 between the NRT RIC 404 and the external AL / ML / AN engine 426, and an interface I5 between the NRT RIC 404 and the network planning database 428. Although interfaces I1-I5 are shown, additional interfaces may be provided without departing from the scope of the disclosure.

[0037] With respect to the interface I1 with the core network 420, the core network may operate in a non-standalone (NSA) mode, a standalone (SA) mode, a dual mode, etc. The NRT RIC 404 may be configured to obtain user-level information including UE ID, subscription priority, network slice registration details, device capability information, etc. through the interface I1 with the core network 420. The NRT RIC 404 may be configured to obtain fault, configuration, accounting, performance, and security (FCAPS) data, etc. through the interface I1 with the core network 420. The NRT RIC 404 may be configured to update policies and configurations using information obtained from the core network 420 via the interface I1. The NRT RIC 404 may decide not to present the obtained information to the rApp. However, a general framework for working with rApps may be implemented that can handle user priorities without disclosing user subscription information or other sensitive information to the application.

[0038] Through an interface I2 with inventory database 422, interface I2 with inventory database 422 may provide access to NRT RIC 404 for information regarding the complete network inventory. If a particular existing configuration, configuration change, and / or configuration update is not valid, as may be determined based on the inventory information from inventory database 422, NRT RIC 404 may be configured to handle the invalid configuration based on the inventory information.

[0039] Through an interface I3 with the geolocation database 424, the NRT RIC 404 may access geolocation information for a complete inventory (e.g., all devices accessing the network) or a partial inventory of deployed devices. Based on the geolocation information, the NRT RIC 404 may configure policies for network nodes based on the geolocation of the devices. For example, if a particular area is affected by a natural disaster or some other type of network failure event, the NRT RIC 404 may configure different priorities and resources for that area for a predetermined period of time or for the duration of the network failure event. Access to the geolocation information may be full or partial, and the accessed geolocation information may be provided to the rApp based on subscription information and permissions.

[0040] Through interface 14 with AI / ML / AN engine 426, NRT RIC 404 may access an external AI / ML / AN engine. SMO framework 402 may access both an external AI / ML / AN engine and an internal AI / ML / AN engine 430 via interface 14 so that selective workloads are distributed based on accuracy needs and latency (i.e., SMO framework 402 may determine which of an external AI / ML / AN engine and an internal AI / ML / AN engine to use to perform processing tasks required for, for example, training, evolution, testing, and performance assurance of an AI / ML model, and may further divide the processing tasks between both the external AI / ML / AN engine and the internal AI / ML / AN engine as needed). The engines may include evolution engines, digital twins, and / or AI / ML models.

[0041] Through an interface 15 with a network planning database 428, the NRT RIC 404 may access network planning data including RAN node planning data, transport planning data, etc. Using the network planning data, the NRT RIC 404 may be configured to adjust / update existing policies, implement new policies / controls, and / or generate new policies / controls, as needed.

[0042] Thus, the presently disclosed O-RAN architecture 400 introduces interfaces between the SMO framework 402 / NRT RIC 404 and the core network 420, the inventory database 422, the geolocation database 424, the AI / ML / AN engine 426, and the network planning database 428 to enable data sharing and coordinated control between the SMO framework 402 / NRT RIC 404 and the core network 420, the inventory database 422, the geolocation database 424, the AI / ML / AN engine 426, and the network planning database 428. Through the interfaces, the NRT RIC 404 may access inventory data, geolocation data, planning data, and data from the core network 420 in conjunction with an external or remotely hosted AI / ML engine. This data may be utilized to configure policy and cloud-related functions in the NRT RIC 404. Planning data, inventory data, geolocation data, and core data (e.g., about UE / user-specific subscriptions and IDs) may be used for anomaly detection and training of AI / ML / AN models for cases where sufficient data is not available. Additionally, the NRT RIC 404 may configure and control both the core network 420 and the RAN in a coordinated manner using interfaces I1-I5 for conflict mitigation and performance improvement.

[0043] 5 is a flowchart of a method for policy / control implementation in an O-RAN architecture, according to one embodiment. In operation 502, the system may, by an NRT RIC, obtain first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface. In operation 504, the system may, by the NRT RIC, determine at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data. In operation 506, the system may, by the NRT RIC, implement the at least one policy / control in the RAN.

[0044] 6 is a diagram of an example environment 600 in which the systems and / or methods described herein may be implemented. As shown in FIG. 6, environment 600 may include a user device 610, a platform 620, and a network 630. The devices of environment 600 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections. In an embodiment, any of the functions and operations described above with reference to FIG. 1 may be performed by any combination of elements illustrated in FIG. 6.

[0045] User device 610 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information related to platform 620. For example, user device 610 may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a smart speaker, a server, etc.), a mobile phone (e.g., a smartphone, a wireless phone, etc.), a wearable device (e.g., smart glasses or a smart watch), or a similar device. In some implementations, user device 610 may receive information from platform 620 and / or send information to platform 620.

[0046] Platform 620 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information. In some implementations, platform 620 may include a cloud server or a group of cloud servers. In some implementations, platform 620 may be designed to be modular, such that particular software components may be swapped in or out depending on particular needs. In this manner, platform 620 may be easily and / or quickly reconfigured for different uses.

[0047] In some implementations, as shown, platform 620 may be hosted in a cloud computing environment 622. Note that although the implementations described herein describe platform 620 as being hosted in a cloud computing environment 622, in some implementations platform 620 may not be cloud-based (i.e., may be implemented outside of a cloud computing environment) or may be partially cloud-based.

[0048] Cloud computing environment 622 includes an environment that hosts platform 620. Cloud computing environment 622 may provide services such as computation, software, data access, storage, etc., without requiring end-user (e.g., user device 610) knowledge of the physical location and configuration of the systems and / or devices that host platform 620. As shown, cloud computing environment 622 may include a group of computing resources 624 (collectively referred to as “computing resources 624” and individually referred to as “computing resource 624”).

[0049] Computing resources 624 include one or more personal computers, clusters of computing devices, workstation computers, server devices, or other types of computation and / or communication devices. In some implementations, computing resources 624 may host platform 620. Cloud resources may include compute instances executing on computing resources 624, storage devices provided on computing resources 624, data transfer devices provided by computing resources 624, etc. In some implementations, computing resources 624 may communicate with other computing resources 624 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0050] As further shown in FIG. 6, computing resources 624 include a group of cloud resources such as one or more applications (“APP”) 624-1, one or more virtual machines (“VM”) 624-2, virtualized storage (“VS”) 624-3, and one or more hypervisors (“HYP”) 624-4.

[0051] The application 624-1 includes one or more software applications that may be provided to or accessed by the user device 610. The application 624-1 may obviate the need to install and run a software application on the user device 610. For example, the application 624-1 may include software associated with the platform 620 and / or any other software that may be provided via the cloud computing environment 622. In some implementations, one application 624-1 may send and receive information to one or more other applications 624-1 via the virtual machine 624-2.

[0052] Virtual machine 624-2 includes a software implementation of a device (e.g., a computer) that executes programs like a physical device. Virtual machine 624-2 may be a system virtual machine or a process virtual machine, depending on the use by virtual machine 624-2 and the degree of correspondence with any real-world device. A system virtual machine may provide a complete system platform that supports the execution of a complete operating system (“OS”). A process virtual machine may execute a single program or support a single process. In some implementations, virtual machine 624-2 may execute on behalf of a user (e.g., user device 610) and manage the infrastructure of cloud computing environment 622, such as data management, synchronization, or long-term data transfer.

[0053] Virtualized storage 624-3 includes one or more storage systems and / or one or more devices or computing resources 624 that use virtualization technology within a storage system. In some implementations, within the context of a storage system, types of virtualization may include block virtualization and file virtualization. Block virtualization may represent the abstraction (or separation) of logical storage from physical storage so that the storage system may be accessed without consideration of the physical storage or heterogeneous structure. The separation may provide storage system administrators with flexibility in managing storage for end users. File virtualization may remove the dependency between data accessed at the file level and where the file is physically stored. This may enable storage usage optimization, server consolidation, and / or non-disruptive file migration performance.

[0054] The hypervisor 624-4 may provide hardware virtualization technology that allows multiple operating systems (e.g., "guest operating systems") to run simultaneously on a host computer, such as computing resource 624. The hypervisor 624-4 may present a virtual operating platform to the guest operating systems and may manage the execution of the guest operating systems. Multiple instances of different operating systems may share virtualized hardware resources.

[0055] The network 630 may include one or more wired and / or RANs. For example, the network 630 may include a cellular network (e.g., a fifth-generation (5G) network, a long-term evolution (LTE) network, a third-generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN), a private network, an ad hoc network, an intranet, the Internet, an optical fiber-based network, etc.), and / or a combination of these or other types of networks.

[0056] The number and arrangement of devices and networks shown in Figure 6 are provided as an example. In practice, there may be additional, fewer, different, or differently arranged devices and / or networks than those shown in Figure 6. Furthermore, two or more devices shown in Figure 6 may be implemented within a single device, and a single device shown in Figure 6 may be implemented as multiple distributed devices. Additionally or alternatively, a set of devices in environment 600 (e.g., one or more devices) may perform one or more functions described as being performed by other sets of devices in environment 600.

[0057] 7 is a diagram of example components of a device 700. The device 700 may correspond to a user device 610 and / or a platform 620. As shown in FIG. 7, the device 700 may include a bus 710, a processor 720, a memory 730, a storage component 740, an input component 750, an output component 760, and a communication interface 770.

[0058] The bus 710 includes components that enable communication between the components of the device 700. The processor 720 may be implemented in hardware, firmware, or a combination of hardware and software. The processor 720 may be a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or other type of processing component. In some implementations, the processor 720 includes one or more processors that are programmable to perform functions. The memory 730 includes random access memory (RAM), read-only memory (ROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) that store information and / or instructions for use by the processor 720.

[0059] The storage component 740 stores information and / or software related to the operation and use of the device 700. For example, the storage component 740 may include a hard disk (e.g., a magnetic disk, optical disk, magneto-optical disk, and / or solid-state disk), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or other type of non-transitory computer-readable medium, along with a corresponding drive. The input component 750 includes components that enable the device 700 to receive information, such as via user input (e.g., a touchscreen display, a keyboard, a keypad, a mouse, buttons, switches, and / or a microphone). Additionally or alternatively, the input component 750 may include sensors for measuring information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and / or an actuator). The output component 760 includes components that provide output information from the device 700 (e.g., a display, a speaker, and / or one or more light-emitting diodes (LEDs)).

[0060] The communication interface 770 includes transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that allow the device 700 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communication interface 770 allows the device 700 to receive information from and / or provide information to other devices. For example, the communication interface 770 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, etc.

[0061] Device 700 may perform one or more processes described herein. Device 700 may perform these processes in response to processor 720 executing software instructions stored by a non-transitory computer-readable medium, such as memory 730 and / or storage component 740. The computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space distributed across multiple physical storage devices.

[0062] The software instructions may be loaded into memory 730 and / or storage component 740 from other computer-readable media or other devices via communications interface 770. When executed, the software instructions stored in memory 730 and / or storage component 740 may cause processor 720 to perform one or more of the processes described herein.

[0063] Additionally or alternatively, hardwired circuitry may be used in place of, or in combination with, software instructions to implement one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

[0064] The number and arrangement of components shown in Figure 7 are provided as an example. In practice, device 700 may include additional, fewer, different, or differently arranged components than those shown in Figure 7. Additionally or alternatively, a set of components (e.g., one or more components) of device 700 may perform one or more functions that are described as being performed by other sets of components of device 700.

[0065] In embodiments, any operation or process of Figures 4-5 may be implemented by or using any of the elements illustrated in Figures 6 and 7. It is understood that other embodiments are not so limited and may be implemented in a variety of different architectures (e.g., bare metal architectures, any cloud-based architectures or deployment architectures such as Kubernetes, Docker, OpenStack, etc.).

[0066] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the foregoing disclosure or may be acquired from practice of the implementations.

[0067] Some embodiments may relate to systems, methods, and / or computer-readable media at any possible level of technical detail of integration. Furthermore, one or more of the above-described components may be implemented as instructions stored on a computer-readable medium and executable by at least one processor (and / or may include at least one processor). The computer-readable medium may include a computer-readable non-transitory storage medium (or medium) having computer-readable program instructions stored thereon for causing a processor to perform operations.

[0068] A computer-readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or raised structures in grooves in which instructions are recorded, and any suitable combination thereof. As used herein, computer-readable storage medium is not to be understood as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted over a wire.

[0069] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium into each computing / processing device, or may be downloaded to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and transfers the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing / processing device.

[0070] The computer-readable program code / instructions for carrying out operations may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for an integrated circuit, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and procedural programming languages ​​such as the "C" programming language, or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server, as a standalone software package. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be to an external computer (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform a certain aspect or operation.

[0071] These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce an apparatus, such that the instructions, when executed by the processor of the computer or other programmable data processing apparatus, produce means for implementing the functions / acts set forth in the flowcharts and / or block diagrams (one or more blocks). These computer-readable program instructions may be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium on which the instructions are stored comprises an article including instructions that implement aspects of the functions / acts set forth in the flowcharts and / or block diagrams (one or more blocks).

[0072] The computer-readable program instructions may be loaded onto a computer, other programmable data processing apparatus, or other device such that a series of operational steps are performed on the computer, other programmable apparatus, or other device to generate a computer-implemented process such that the instructions, executed on the computer, other programmable apparatus, or other device, implement the functions / acts described in the flowcharts and / or block diagrams (one or more blocks).

[0073] The illustrated flowcharts and block diagrams illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. Each block in a flowchart or block diagram may represent a microservice, module, segment, or portion of instructions, comprising one or more executable instructions for implementing specific logical functions. The methods, computer systems, and computer-readable media may include additional, fewer, different, or differently arranged blocks than those shown in the figures. In some alternative implementations, the functions shown in the blocks may occur out of the order shown in the figures. For example, two blocks shown in succession may, in fact, be executed concurrently or substantially concurrently, depending on the functionality involved, or the blocks may be executed in the reverse order. Note that each block of the block diagram and / or flowchart illustrations, and combinations of blocks in the block diagram and / or flowchart illustrations, may be implemented by a dedicated hardware-based system that performs specific functions or acts, or by executing a combination of dedicated hardware and computer instructions.

[0074] It will be apparent that the systems and / or methods described herein may be implemented in different forms, such as hardware, firmware, or a combination of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods does not limit the implementation. As such, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It will be understood that software and hardware may be designed to implement the systems and / or methods based on the description herein.

Claims

1. acquiring, by a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC), first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; implementing, by the NRT RIC, the at least one policy / control in the RAN; A method for policy / control implementation comprising:

2. 2. The method of claim 1, wherein the first enrichment data comprises at least one of user level information, subscription priority information, network slice registration information, and device capability information.

3. and further comprising: acquiring, by the NRT RIC, second enrichment data corresponding to inventory information of devices connected to the RAN from an inventory database external to the NRT RIC via a second external interface; the at least one policy / control is determined further based on the second enrichment data. The method of claim 1.

4. and acquiring, by the NRT RIC, third enrichment data corresponding to location information of the RAN from a geolocation database external to the NRT RIC via a third external interface; the at least one policy / control is determined further based on the third enrichment data. The method of claim 1.

5. 10. The method of claim 1, further comprising accessing, by the NRT RIC via a fourth external interface, at least one artificial intelligence (AI) / machine learning (ML) / autonomous network (AN) engine external to the NRT RIC to perform at least one processing task related to at least one of AI / ML model training, evolution, testing, and performance assurance.

6. and acquiring, by the NRT RIC, fourth enrichment data corresponding to the network planning data from a planning database external to the NRT RIC via a fifth external interface; the at least one policy / control is determined further based on the fourth enrichment data. The method of claim 1.

7. After implementing the determined at least one policy / control in the RAN, Acquiring, by the NRT RIC, fifth enrichment data corresponding to new core network information from the core network external to the NRT RIC via the first external interface; updating, by the NRT RIC, the at least one policy / control based on the fifth enrichment data; Implementing, by the NRT RIC, the updated at least one policy / control in the RAN; The method of claim 1 further comprising:

8. a memory for storing instructions; acquiring, by a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC), first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; implementing, by the NRT RIC, the at least one policy / control in the RAN; a processor configured to execute the instructions to perform the A system for policy / control implementation comprising:

9. 9. The system of claim 8, wherein the first enrichment data comprises at least one of user level information, subscription priority information, network slice registration information, and device capability information.

10. The processor is further configured to execute the instructions to perform: acquiring, by the NRT RIC, second enrichment data corresponding to inventory information of devices connected to the RAN from an inventory database external to the NRT RIC via a second external interface; the at least one policy / control is determined further based on the second enrichment data. The system of claim 8.

11. The processor is further configured to execute the instructions to perform: acquiring, by the NRT RIC, third enrichment data corresponding to location information of the RAN from a geolocation database external to the NRT RIC via a third external interface; the at least one policy / control is determined further based on the third enrichment data. The system of claim 8.

12. 10. The system of claim 8, wherein the processor is further configured to execute the instructions to cause the NRT RIC to access, via a fourth external interface, at least one artificial intelligence (AI) / machine learning (ML) / autonomous network (AN) engine external to the NRT RIC to perform at least one processing task related to at least one of AI / ML model training, evolution, testing, and performance assurance.

13. The processor is further configured to execute the instructions to perform: obtaining, by the NRT RIC, fourth enrichment data corresponding to network planning data from a planning database external to the NRT RIC via a fifth external interface; the at least one policy / control is determined further based on the fourth enrichment data. The system of claim 8.

14. After implementing the determined at least one policy / control in the RAN, the processor: Acquiring, by the NRT RIC, fifth enrichment data corresponding to new core network information from the core network external to the NRT RIC via the first external interface; updating, by the NRT RIC, the at least one policy / control based on the fifth enrichment data; Implementing, by the NRT RIC, the updated at least one policy / control in the RAN; 9. The system of claim 8, further configured to execute the instructions to perform:

15. When executed by at least one processor, acquiring, by a non-real-time (NRT) radio access network (RAN) intelligent controller (RIC), first enrichment data corresponding to core network information from a core network external to the NRT RIC via a first external interface; determining, by the NRT RIC, at least one policy / control to be implemented in a RAN including the NRT RIC based on the first enrichment data; implementing, by the NRT RIC, the at least one policy / control in the RAN; a non-transitory computer-readable storage medium storing instructions for causing the at least one processor to execute the

16. 16. The storage medium of claim 15, wherein the first enrichment data comprises at least one of user level information, subscription priority information, network slice registration information, and device capability information.

17. The instructions, when executed, further cause the at least one processor to obtain, by the NRT RIC, second enrichment data corresponding to inventory information of devices connected to the RAN from an inventory database external to the NRT RIC via a second external interface; the at least one policy / control is determined further based on the second enrichment data.

16. The storage medium of claim 15.

18. The instructions, when executed, further cause the at least one processor to obtain, by the NRT RIC, third enrichment data corresponding to location information of the RAN from a geolocation database external to the NRT RIC via a third external interface; the at least one policy / control is determined further based on the third enrichment data.

16. The storage medium of claim 15.

19. 16. The storage medium of claim 15, wherein the instructions, when executed, further cause the at least one processor to access, by the NRT RIC, via a fourth external interface, at least one artificial intelligence (AI) engine external to the NRT RIC to perform at least one processing task related to the at least one policy / control determination.

20. The instructions, when executed, further cause the at least one processor to obtain, by the NRT RIC, fourth enrichment data corresponding to network planning data from a planning database external to the NRT RIC via a fifth external interface; the at least one policy / control is determined further based on the fourth enrichment data.

16. The storage medium of claim 15.

21. obtaining, by a core network, first enrichment data corresponding to RAN information from a non-real-time (NRT) Radio Access Network (RAN) intelligent controller (RIC) external to the core network via a first external interface; determining, by the core network, at least one policy / control to be implemented in the core network based on the first enrichment data; implementing, by the core network, the at least one policy / control in the core network; A method for policy / control implementation comprising:

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