Intelligent Wireless Access Network (RAN) Optimization Framework and Method

Abstract

1. An intelligent radio access network (RAN) optimization framework. In the case of an E2 node, an optimization service is initiated for processing by a near real-time RAN intelligent controller (RIC) (near-RT RIC). The E2 node compares performance to a first predetermined threshold. In response to performance falling below the first predetermined threshold, the E2 node takes over optimization for the E2 node. Otherwise, the near-RT RIC continues optimization. The E2 node compares performance of the E2 node to a second predetermined threshold. In response to performance falling below the second predetermined threshold, the near-RT RIC takes over optimization. Otherwise, the E2 node continues processing optimization for the E2 node's performance. In the case of an open RAN radio unit (O-RU) node, the O-RU node can perform local optimization of time-critical functions, and a non-RT RIC can perform optimization of non-time-critical functions.

Description

Technical Field

[0001] This specification relates to providing an intelligent radio access network (RAN) optimization framework and a method of using the same.

Background Art

[0002] Network owners, network operators, service and application developers can evaluate how certain applications and services function on a particular network based on configurations using certain parameters or under certain operating conditions. In existing deployments, regardless of 2G, 3G, or 4G, there are algorithms that are executed locally at the eNB or base station. The algorithms provide various optimizations such as energy consumption, throughput, latency, and other KPIs. Network optimization can have a significant impact on the performance of the network.

[0003] As 5G and radio access network (RAN) become open or virtualized, previous monolithic nodes are separated or split into multiple components. 5G RAN is expected to be deployed with algorithms involved in network optimization located in a central controller called a RAN intelligent controller (RIC). Moving the optimization to the RIC provides an overall end-to-end view of the network. An artificial intelligence (AI) / machine learning (ML) framework placed on the RIC platform helps improve the optimization. However, providing AI / ML to local nodes is very expensive.

[0004] In Open RAN (O-RAN), functionality is broken down into the O-RAN Central Unit (O-CU), the O-RAN Distributed Unit (O-DU), and the O-RAN Radio Unit (O-RU). The O-CU is further divided into the O-CU Control Plane (O-CU-CP) and the O-CU User Plane (O-CU-UP). These RAN functionalities are connected to intelligent controllers via open interfaces that can stream telemetry and deploy control actions and policies. The O-RAN architecture includes two RAN intelligent controllers (RICs) that perform network management and control: a Near-Real-time RIC (Near-RT RIC) and a Non-Real-time RIC (Non-RT RIC). The RICs provide an end-to-end view of the network and apply AI / ML. Quasi-RT RICs communicate with E2 nodes via the E2 interface and handle functions that operate in near real-time (e.g., 10 milliseconds to 1 second timescale). Non-RT RICs handle functions that operate in non-real-time (e.g., over 1 second timescale). Optimization can be provided based on quasi-RT RICs exchanging messages with RAN nodes. E2 nodes are terminated at the E2 endpoint and include O-DUs, O-CU-CPs, and O-CU-UPs, as well as Next Generation Node B (O-gNBs) and O-evolved Node B (O-eNBs). O-RUs communicate with non-RT RICs via the Open Fronthaul (FH) Management Plane (M-Plane) and communicate with O-DUs via the Open FH Control, User and Synchronization (CUS) and M-Plane.

[0005] For example, an agreement is reached between next-generation nodes B (gNB), and a service subscription is established between the RAN nodes and the quasi-RT RIC. The quasi-RT RIC determines which parameter and procedural changes to implement on the RAN nodes. The problem with this model is that the quasi-RT RIC cannot provide the best-optimized solution. [Overview of the Initiative] [Means for solving the problem]

[0006] In at least one embodiment, a method for providing intelligent radio access network (RAN) optimization includes provisioning one or more radio access network (RAN) nodes; initiating an optimization subscription service for handling the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switching to performance optimization by the E2 nodes themselves, or otherwise continuing to handle performance optimization by the quasi-RT RIC.

[0007] In at least one embodiment, a radio access network (RAN) node includes a memory for storing computer-readable instructions and a processor connected to the memory, the processor configured to perform operations including: executing computer-readable instructions to provide RAN functionality to one or more RAN nodes in a mobile network; initiating an optimization subscription service for processing the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of an E2 node as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of an E2 node falls below the first predetermined threshold, switching to performance optimization by the E2 node, or otherwise continuing to process the performance optimization by the quasi-RT RIC.

[0008] In at least one embodiment, a non-transient computer-readable medium stores computer-readable instructions that, when executed by the processor, cause the processor to perform operations including: provisioning one or more radio access network (RAN) nodes; initiating an optimization subscription service for handling the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switching to performance optimization by the E2 nodes themselves, or otherwise continuing to handle performance optimization by the quasi-RT RIC.

[0009] The aspects of this disclosure are best understood by reading the following "Modes for Carrying Out the Invention" in conjunction with the accompanying drawings. Note that, in accordance with standard industry practice, various features are not depicted to scale. In fact, the dimensions of various features may be enlarged or reduced for clarity in the description. [Brief explanation of the drawing]

[0010] [Figure 1] A mobile network is shown according to at least one embodiment. [Figure 2] This is a functional block diagram of an O-RAN architecture for implementing an intelligent RAN optimization framework by providing RAN optimization using RIC services or local services, according to at least one embodiment. [Figure 3] This is a block diagram of a quasi-RT RIC architecture according to at least one embodiment. [Figure 4] This is a flowchart of the E2 subscription process according to at least one embodiment. [Figure 5] The information elements of an RIC subscription suspension message according to at least one embodiment are shown. [Figure 6] The information elements of an RIC subscription suspension acknowledgment message according to at least one embodiment are shown. [Figure 7] The information elements of an RIC subscription reactivation message are shown in at least one embodiment. [Figure 8] This is a flowchart of a method for providing RAN optimization using RIC services or local services, according to at least one embodiment. [Figure 8C] This is a flowchart of a method for providing RAN optimization using RIC services or local services, according to at least one embodiment. [Figure 9] This is a high-level functional block diagram of a processor-based system according to at least one embodiment. [Modes for carrying out the invention]

[0011] The embodiments described herein illustrate examples for implementing various features of the subject matter provided. For the sake of simplicity, examples of components, values, actions, materials, arrangements, etc., are described below. Naturally, these are examples and are not intended to be limiting. Other components, values, actions, materials, arrangements, etc., are contemplated. For example, the formation of a first feature on or above a second feature in the following description includes embodiments in which the first and second features are formed in direct contact, and also includes embodiments in which an additional feature is formed between the first and second features so that the first and second features cannot be in direct contact. In addition, this disclosure repeats reference numerals and / or letters in various examples. This repetition is for the sake of brevity and clarity and does not indicate relationships between the various embodiments and / or configurations described.

[0012] Furthermore, spatially relative terms such as “beneath,” “below,” “lower,” “above,” and “upper” are used herein to facilitate descriptions of the relationship between one element or feature and another element or feature, as shown in the figures. Spatially relative terms are intended to encompass different orientations of the device in use or action, in addition to the orientation shown in the figures. If the device is oriented in another direction (rotated 90 degrees or facing another direction), the spatially relative descriptors used herein are similarly interpreted accordingly.

[0013] Terms such as “User equipment,” “Mobile station,” “Mobile,” “Mobile device,” “Subscriber station,” “Subscriber equipment,” “Access terminal,” “Terminal,” and “Handset,” and similar terms, refer to wireless devices used by subscribers or users of wireless communication services to receive or transmit data, control, voice, video, sound, games, data streaming, or signaling streaming. The aforementioned terms are interchangeable in this specification and the related drawings. Terms such as “Access point,” “Base station,” “Node B,” “Evolved Node B (eNode B),” “Next Generation Node B (gNB),” “Enhanced gNB (en-gNB),” “Home Node B (HNB),” and “Home access point (HAP)” refer to components or devices of a wireless network that provide and receive data, control, voice, video, sound, games, data streaming, or signaling streaming to and from the UE.

[0014] In at least one embodiment, the intelligent radio access network (RAN) optimization framework is used to either use a near real-time (near-RT or NRT) RAN intelligent controller (RIC) for centralized optimization, or to switch to using locally supported algorithms, for example, at the RAN node (gNB), which can provide better performance. The framework determines whether the radio access network (RAN) node is an E2 node or an open RAN radio unit (O-RU) node. An optimization subscription service is initiated to handle the performance optimization of the E2 node by the near real-time RAN intelligent controller (RIC) (near-RT RIC). In response to performance falling below a first threshold, the performance optimization of the E2 node is switched to the E2 node. Pausing the processing of E2 performance optimization by the near-RT RIC is based on sending a subscription pause message to the near-RT RIC. The optimization subscription service that was being handled by the near-RT RIC is resumed in response to the E2 performance falling below a second threshold. In response to the determination that a RAN node is an O-RU node, a determination is made as to whether the function is a time-critical or non-critical O-RU function. Based on the determination that the function is a time-critical O-RU function, the O-RU node processes the optimization process. Based on the determination that the function is a non-time-critical O-RU function, the quasi-RT RIC / non-RT RIC processes the optimization process via E2 termination at the O-DU.

[0015] Embodiments described herein provide methods that offer one or more advantages. For example, the Intelligent Radio Access Network (RAN) Optimization Framework provides performance improvements by using a method that achieves optimal performance, whether the method is centralized optimization controlled by a RAN Intelligent Controller (RIC) or localized optimization controlled by RAN nodes via an E2 interface. The Intelligent Radio Access Network (RAN) Optimization Framework provides improved handling of latency-sensitive use cases and RAN optimization functions. The Intelligent Radio Access Network (RAN) Optimization Framework also uses and, as necessary, an RIC for RAN optimization functions.

[0016] Figure 1 shows a mobile network 100 according to at least one embodiment.

[0017] In Figure 1, User Equipment (UE) 1 110, UE2 112, UE3 114, and UE4 116 communicate with Radio Unit (RU) 1 121, RU2 123, RU3 125, and RU4 127, respectively. While Figure 1 shows a one-to-one correspondence between UE1 110, UE2 112, UE3 114, and UE4 116 and RU1 121, RU2 123, RU3 125, and RU4 127, those skilled in the art will understand that this does not mean that the embodiments are limited in this way. For example, more UEs can be connected to RU1 121, RU2 123, RU3 125, and RU4 127. Furthermore, additional RUs can be implemented.

[0018] RU1 121, RU2 123, RU3 125, and RU4 127 are respectively arranged in towers 120, 122, 124, and 126. RU1 121 is shown to communicate with Distributed Unit (DU) 1 130. RU2 123 and RU3 125 are shown to communicate with DU2 132. RU4 127 is shown to communicate with DU3 134. DU1 130 and DU2 132 communicate with Centralized Unit (CU) 1 140. DU3 134 communicates with CU 142. It is shown that CU1 140 has a control plane 142 and a user plane 144. Although not shown in FIG. 1, those skilled in the art will understand that CU2 146 also includes a control plane and a user plane. Towers 120, 122, 124, 126, RU1 121, RU2 123, RU3 125, RU4 127, DU1 130, DU2 132, DU3 134, and CU1 140 and CU2 142 represent one or more Radio Access Networks (RANs) 120.

[0019] RU1 121, RU2 123, RU3 125, RU4 127 and DU1 130, DU2 132, DU3 134 communicate via a fronthaul interface 150. DU1 130, DU2 132, DU3 134 and CU1 140 and CU2 142 communicate via a midhaul interface 152. CU1 140 and CU2 142 are coupled by an Xn interface 156.

[0020] CU1 140 and CU2 142 communicate with a 5G core 160 via a backhaul interface 154. The 5G core 160 provides access for UE1 110, UE2 112, UE3 114, UE4 116 to a data network 170 such as the Internet and a voice network such as a Public Switched Telephone Network 任務を実行する。

[0021] The network management system and the orchestration system 180 can control, manage, and configure the mobile network 100. The network management system and the orchestration system 180 are shown coupled to the 5G core 160. The intelligent RAN optimization framework 182 is directly connected to the RAN 120 to provide intelligent RAN optimization to E2 nodes such as the O-DU 220, O-CU-CP 221, O-CU-UP 222, O-gNB 223, and O-eNB 224. According to at least one embodiment, the network management system and the orchestration system 180 can implement the intelligent RAN optimization framework 182 by providing RAN optimization using RIC services or local services.

[0022] Figure 2 is a functional block diagram of an O-RAN architecture 200 for implementing an intelligent RAN optimization framework by providing RAN optimization using RIC services or local services according to at least one embodiment.

[0023] In Figure 2, the quasi-real-time (RT) RAN intelligent controller (RIC) 210 executes optimization procedures. The quasi-RT RIC 210 and RAN nodes such as E2 nodes 220, 221, 222, 223, 224 have an agreement on centralized optimization control by the quasi-RT RIC 210. The E2 nodes include an ORAN distributed unit (O-DU) 220, an O-centralized unit control plane (O-CU-CP) 221, an O-CU user plane (O-CU-UP) 222, a next-generation node B (O-gNB) 223, and an O-evolved node B (O-eNB) 224. The quasi-RT RIC 210 is coupled to the O-DU 220, O-CU-CP 221, O-CU-UP 222, O-gNB 223, and O-eNB 224 by an E2 interface 230. The E2 nodes are logical nodes that terminate using the E2 interface 230.

[0024] The next-generation NodeB (O-gNB)223 is a radio base station in a 5G NR network. The O-gNB223 includes independent network functions that implement 3rd Generation Partnership Project (3GPP®) compliant 5G New Radio (NR) radio access network (RAN) protocols, including Physical (PHY), Media Access Control (MAC), Radio Link Control (RLC), Packet Data Convergence Protocol (PDCP), Service Data Adaptation Protocol (SDAP), and Radio Resource Control (RRC). The NR RAN protocols can run together or independently and can be deployed on either physical (e.g., small cell chipsets) or virtual resources (e.g., dedicated commercial off-the-shelf (COTS) servers or shared cloud resources).

[0025] Evolved Node B (eNB)224 is an Evolved-UMTS Terrestrial Radio Access Network (E-UTRAN) Node B, which is an evolution of the Node B element in the Universal Mobile Telecommunications System (UMTS) UTRA. E-eNB224 connects to the mobile phone network and communicates wirelessly directly with mobile handsets.

[0026] The service management and orchestration framework 240 includes a non-real-time RIC (non-RT RIC) 242. A quasi-RT RIC 210 communicates with the service management and orchestration framework 240 and the non-RT RIC 242 via the A1 interface 244. The service management and orchestration framework 240 and the non-RT RIC 242 communicate with the O-DU 220, O-CU-CP 221, O-CU-UP 222, O-gNB 223, and O-eNB 224 using the O1 interface 250. The O-DU 220 is coupled to the ORAN radio unit (O-RU) 260 using the open fronthaul M-plane interface 270. The open fronthaul M-plane interface 270 also enables communication between the O-RU 260 and the service management and orchestration framework 240 and the non-RT RIC 242.

[0027] In Figure 2, the quasi-RT RIC210 is the service provider, and E2 nodes 220-224 are the service consumers. Most RAN vendors provide local algorithms that can perform data collection and logging and process the data locally on E2 nodes 220-224 to achieve RAN optimization. Sometimes, algorithms locally supported on E2 nodes, such as O-DU220, O-CU-UP221, O-CU-CP222, O-gNB223, and O-eNB224, can provide better performance. Therefore, improved performance on E2 nodes 220-224 can be achieved by using locally supported algorithms on E2 nodes, rather than following commands from N-RT RIC210 for service optimization.

[0028] One or more of the E2 nodes 220-224 monitor locally collected performance parameters and compare the optimizations provided by the quasi-RT RIC 210 with local optimizations that, for example, E2 node 220 may provide. While the optimizations may be provided by any of the E2 nodes 220-224, the optimizations described herein are explained using O-DU 220. The performance provided by the quasi-RT RIC 210 can be compared using predetermined performance thresholds. E2 node 220 determines that the optimization commands provided by the quasi-RT RIC 210 result in performance below the predetermined threshold. For example, the optimization commands provided by the quasi-RT RIC 210 may generate errors or fail to meet performance indicators such as latency, load balancing, or energy efficiency. E2 node 220 can be configured using a local algorithm or a newer or updated local algorithm that provides better performance optimizations.

[0029] In response to an optimization command provided by the quasi-RT RIC210 that results in performance below a predetermined threshold, the E2 node 220 pauses the optimization performed by the quasi-RT RIC210 on the E2 node 220, and then starts performance optimization using its own local algorithm. The E2 node 220 can also resume or reverse the process of having the quasi-RT RIC210 handle the optimization on the E2 node 220 by resuming its subscription to the optimization commands provided by the quasi-RT RIC210.

[0030] Figure 3 is a block diagram 300 of a quasi-RT RIC architecture according to at least one embodiment.

[0031] In Figure 3, the quasi-RT RIC 310 is shown as a logical network node positioned between the Service Management & Orchestration layer 370 and the E2 node 380. The Service Management & Orchestration (SMO) layer 370 hosts the non-RT RIC 372. The SMO 370 oversees the orchestration, management, and automation of RAN elements. The SMO 370 supports the O1 interface 374 and the A1 interface 376. The non-real-time RAN intelligent controller (Non-RT RIC) 372 is a logical function that enables non-real-time control and optimization of RAN elements and resources, AI / ML workflows including model training and updating, and policy-based guidance of applications / functions within the quasi-RT RIC 310.

[0032] The quasi-RT RIC310 is a logical function that enables near real-time control and optimization of O-RAN elements and resources through granular data acquisition and actions on the E2 interface 320 terminated at the E2 termination 322. The quasi-RT RIC310 provides policy interpretation and enforcement from the non-RT RIC372 and supports enrichment information to optimize control functions.

[0033] The quasi-RT RIC310 includes A1 termination 312 and O1 termination 314. A1 termination 312 terminates the A1 interface 376 from the non-RT RIC372. The A1 interface 376 is used for policy guidance. The SMO370 provides granular policy guidance, such as prompting user equipment to change frequencies, and other data enrichment to RAN functions via the A1 interface 376. O1 termination 312 terminates the O1 interface 374 from the SMO370. The O1 interface 374 supports the management of operation and maintenance (OAM) of multi-vendor open RAN functions, including fault, configuration, accounting, performance and security management, software management, and file management capabilities.

[0034] The quasi-RT RIC API for xApp324 enables RRM control functionality to be performed on the quasi-RT RIC310 and enforced on the E2 node 380 via the E2 interface 320. The quasi-RT RIC API for xApp324 includes xApp1 326, xApp2 327, and xAppN 328. The messaging infrastructure 329 enables message interaction between the internal functions of the quasi-RT RIC310.

[0035] Conflict Mitigation 330 resolves potentially overlapping or conflicting requests from multiple xApps. xApp Subscription Management 331 merges subscriptions from different xApps and provides unified data delivery to the xApp. Management Functions 332, as a service producer, provides fault management, configuration management, and performance management to the SMO 370, captures, monitors, and collects the internal status of the quasi-RT RIC 310, and provides logging, tracing, and metric collection that is forwarded to external systems for further evaluation.

[0036] Security 334 provides the security scheme for xApps. AI / ML 335 provides data pipeline, training, and performance monitoring for xApps. xApp repository function 336 enables the selection of xApps for A1 message routing based on A1 policy type and carrier policy. Quasi-RT RIC 310 acts as an overlay for the underlying database 342 and provides APIs isolated from specific implementation solutions, including a Shared Data Layer (SDL) 340 that enables simplified data access. E2 termination 322 terminates the E2 interface 320 from the E2 node 380.

[0037] The E2 node 380 is a logical function that supports the protocol layers and interfaces defined by 3GPP RAN (eNB for E-UTRAN and gNB / ng-eNB for NG-RAN). One quasi-RT RIC 310 can connect to one or more E2 node 380s via transport functions, while an E2 node 380 can connect to a quasi-RT RIC 310. The quasi-RT RIC 310 uses the A1 interface 376 to receive policies, enrichment data, and ML models from the non-RT RIC 372, and uses the E2 interface 320 to collect quasi-real-time information from the E2 node 380 and perform fine-grained Radio Resource Management (RRM) actions on the E2 node 380. Functions hosted by xApp 326, 327, and 328 enable services to run on the quasi-RT RIC 310 and the results to be sent to the E2 node 380 via the E2 interface 320. API Activation 350 supports capabilities related to API operation of quasi-RT RIC310, such as API repository / registry, authentication, discovery, and generic event subscriptions.

[0038] Figure 4 is a flowchart 400 of the E2 subscription process according to at least one embodiment.

[0039] In Figure 4, the subscription processing between RAN node 410 and quasi-RT RIC 420 includes processing for RIC service initiation 430, RIC service suspension 450, and RIC service resumption 470. The purpose of the subscription processing on quasi-RT RIC 420 is to enable xApps to request subscriptions for REPORT, INSERT, and / or POLICY services (one or more) from RAN node 410 via interfaces such as the E2 interface for E2 nodes or the open fronthaul M-plane interface for O-RU nodes, and to ensure that valid, non-duplicate subscriptions are maintained by quasi-RT RIC 420 via the interface to RAN node 410, and that duplicate subscription request messages from xApps are properly handled.

[0040] RAN node 410 initiates the subscription procedure by sending a setup request message 432 containing appropriate data to quasi-RT RIC 420. For example, the setup request message 432 includes a RAN function definition that defines the RAN functions supported by RAN node 410, node identifier (ID) information, and configurations supported by RAN node 410.

[0041] The quasi-RT RIC420 responds with a setup response message 434 containing appropriate data, such as a list of accepted RAN functions and associated RAN function IDs, as well as a list of rejected RAN functions, associated RAN function IDs, and reasons for rejection. RAN function IDs are indicators of network functions. Subscriptions are associated with network functions related to RAN function IDs.

[0042] The quasi-RT RIC420 can also send an RIC subscription request message 436 to the RAN node. The RIC subscription request message 436 is used to create a new subscription within the RAN node 410 at the request of the quasi-RT RIC420 and includes one or more of the following: RIC request ID, RAN function ID, RIC subscription details, RIC event trigger definition, sequence of actions, RIC action ID, RIC action type, RIC action definition, and RIC subsequent actions.

[0043] RAN node 410 responds by sending RIC subscription response message 438 to quasi-RT RIC 420, accepting the request from quasi-RT RIC 420 to create a new event for RAN node 410. The RIC subscription response message 438 includes one or more of the RIC request ID, RAN function ID, RIC action approval list and associated RIC action IDs, as well as the RIC action disapproval list and associated RIC action IDs, and the cause. Thus, messages 1-4 of the RIC service initiation process are part of the existing interface connection establishment. Messages 1-4 of the RIC service initiation process 430, namely 432, 434, 436, and 438, expose optimization functions, network functions, etc.

[0044] RAN node 410 continues to monitor performance. RAN node 410 determines whether the centralized optimization provided by quasi-RT RIC420 is acceptable. RAN node 410 determines, for example, whether the performance optimization of RAN node 410 by quasi-RT RIC420 is below a first predetermined threshold, whether the local algorithm can provide better performance optimization.

[0045] In response to RAN node 410 determining that the RAN node performance optimization is not below a first predetermined threshold, RAN node 410 continues to monitor the performance optimization of its functions using the quasi-RT RIC420.

[0046] In response to RAN node 410 determining, for example, that a local algorithm can provide better performance optimization based on the performance of the quasi-RT RIC420 optimization being below a predetermined threshold, RAN node 410 executes the RIC service suspension process 450. RAN node 410 sends an RIC subscription suspension message 452 to the quasi-RT RIC420.

[0047] In response, the quasi-RT RIC420 can send an RIC subscription suspension acknowledgment message 454 to the RAN node 410. The RAN node 410 can then take over performance optimization of the RAN node 410 using a local optimization algorithm. For example, the RAN node 410 can determine that subscriptions X, Y, and Z exist, and that subscription X has a problem, but Y and Z do not. Therefore, the RAN node 410 can suspend subscription X. The RIC subscription suspension message 452 can provide the quasi-RT RIC420 with identifying information about why the RAN node 410 is attempting to suspend subscription X. Thus, through the RIC subscription suspension message 452 and the RIC subscription suspension acknowledgment message 454, the RAN node 410 and the quasi-RT RIC420 can reach an agreement on how to optimize the performance optimization of the RAN node 410.

[0048] RAN node 410 continues to monitor performance. RAN node 410 determines whether the performance optimization performed by RAN node 410 is below a second predetermined threshold. In response to the performance optimization not being below the second threshold, RAN node 410 continues to monitor its performance.

[0049] In response to performance optimization being below a second threshold, RAN node 410 can cause quasi-RT RIC 420 to initiate performance optimization. For example, in response to performance changes such as improved coverage or fewer routine failures, RAN node 410 can communicate with quasi-RT RIC 420 / non-RT RIC to cause RAN node 410 to resume performance optimization.

[0050] The RIC service restart process 470 is used to restart the RIC service. The RAN node 410 sends an RIC subscription restart message 472 to the quasi-RT RIC 420. For example, the RAN node 410 sends an RIC subscription restart message 472 that identifies subscription X to be processed again by the quasi-RT RIC 420.

[0051] In response, the quasi-RT RIC420 responds to the RAN node 410 with an RIC subscription request message 474. Again, the RIC subscription request message 474 is used to create a subscription, for example, to reactivate subscription X, and includes one or more of the following: RIC request ID, RAN function ID, RIC subscription details, RIC event trigger definition, sequence of actions, RIC action ID, RIC action type, RIC action definition, and RIC subsequent actions.

[0052] RAN node 410 responds to the subscription request message 474 from quasi-RT RIC420 by sending RIC subscription response message 476 to quasi-RT RIC420, accepting the request from quasi-RT RIC420 to resume subscription X. Thus, through the RIC subscription resume message 472, the RIC subscription request message 474, and the RIC subscription response message 476, RAN node 410 and quasi-RT RIC420 can reach an agreement that quasi-RT RIC420 will resume processing performance optimization for RAN node 410, including agreement on the parameters of subscription X. RAN node 410 then returns to monitoring performance optimization by quasi-RT RIC420.

[0053] In at least one embodiment, the RIC service pause process 450 and the RIC service resume process 470 can be repeated. However, the cycle between the RIC service pause process 450 and the RIC service resume process 470 should not be performed too frequently. Therefore, a timer can be used to control the frequency of transitions between the RIC service pause process 450 and the RIC service resume process 470. For example, before executing the RIC service pause process 450 again, a timer can be used to make the RAN node 410 wait for a predetermined period, such as 1 hour, 4 hours, 10 hours, etc. The timer may depend on the network function involved.

[0054] Figure 5 shows the information elements of an RIC subscription suspension message 500 according to at least one embodiment.

[0055] In Figure 5, an RIC subscription suspension message 500 is sent from the E2 node to the quasi-RT RIC 510. The RIC subscription suspension message 500 includes a message type information element (IE) 520 that uniquely identifies the type of message being sent. The RIC request ID 530 includes the RIC requester ID and the RIC instance ID. The RAN function ID 540 indicates a unique RAN function ID number within a given E2 node.

[0056] Pause reason 550 reports network-level information for pausing the subscription with the quasi-RT RIC for performance optimization. The pause reason provides the quasi-RT RIC with the reason why the E2 node is attempting to pause the subscription. For example, the E2 node may identify, for instance, a message failure at E2 node 552, an error at E2 node 554, and a performance degradation at E2 node 556.

[0057] Therefore, the E2 node identifies issues related to message failures, message errors, and performance degradation through the optimization functions applied by the quasi-RT RIC. The quasi-RT RIC is provided with log information regarding performance parameters, but it does not have direct access to the information that the E2 node can access. Therefore, the E2 node can send an RIC subscription pause message 500 to the quasi-RT RIC to take over performance optimization at the local level, i.e., at the E2 node level.

[0058] Figure 6 shows the information elements of an RIC subscription suspension acknowledgment message 600 according to at least one embodiment.

[0059] In Figure 6, a RIC subscription suspension acknowledgment message 600 is sent from the quasi-RT RIC to the E2 node 610. The RIC subscription suspension acknowledgment message 600 includes a message type information element 620, a RIC request ID information element 630, and a RAN function ID information element 640.

[0060] The Message Type Information Element (IE) 520 uniquely identifies the type of message being sent. The RIC Request ID 630 includes the RIC Requester ID and the RIC Instance ID. The RAN Function ID 640 indicates a unique RAN Function ID number within a given E2 node.

[0061] Next, the E2 node can take over the performance optimization of the E2 node using a local optimization algorithm. Through the RIC subscription suspension message 500 and the RIC subscription suspension acknowledgment message 600, the E2 node and the quasi-RT RIC can reach an agreement on how to optimize the performance optimization of the E2 node.

[0062] Figure 7 shows the information elements of an RIC subscription resumption message 700 according to at least one embodiment.

[0063] In Figure 7, an RIC subscription reactivation message 700 is sent from the E2 node to the quasi-RT RIC710. The RIC subscription reactivation message includes a message type information element (IE) 720 that uniquely identifies the type of message being sent.

[0064] The RIC request ID 730 includes the RIC requester ID and the RIC instance ID. The RAN function ID 740 indicates a unique RAN function ID number within a given E2 node.

[0065] The resumption reason 750 reports network-level information for resuming the subscription with the quasi-RT RIC for performance optimization. The resumption reason identifies to the quasi-RT RIC why the E2 node is attempting to resume the subscription. For example, the E2 node may identify the suspension reason based on message failures 752 at the E2 node due to local optimization, errors 754 at the E2 node due to local optimization, and performance degradation 756 at the E2 node due to local optimization. Thus, the E2 node identifies problems related to message failures, message errors, performance degradation, etc., due to the optimization functions applied by the E2 node. The E2 node may send an RIC subscription resumption message 700 to the quasi-RT RIC so that the quasi-RT RIC resumes performance optimization by the quasi-RT RIC.

[0066] The same framework described above can be extended to non-RT RIC nodes.

[0067] Referring again to Figure 2, the O-Radio Unit (O-RU) 260 is coupled to the O-DU 220 via an open fronthaul M-plane interface 270. The O-RU 260 converts the radio signal transmitted to and from the antenna into a digital signal that can be transmitted to the DU 220 via the fronthaul. The O-RU 260 includes synchronization and fronthaul transport, lower physical layer baseband processing, a digital front end (DFE), and an RF front end (RF FE).

[0068] RIC services are not supported by O-RU260, and due to the time-critical nature of the O-RU260's functions, there is no E2 interface between O-RU260 and the quasi-RT RIC210 or non-RT RIC242. Functions can be divided into time-critical and non-time-critical functions. In at least one embodiment, O-RU260 can perform local optimization of time-critical functions and enable optimization of non-time-critical functions performed by the quasi-RT RIC / non-RT RIC242 via E2 termination at O_DU.

[0069] The non-RT RIC242 is coupled to the quasi-RT RIC210 via the A1 interface 244. The service management and orchestration framework 240 collects data using the FCAPS (Fault Management, Configuration Management, Accounting, Performance Management, Security) interface.

[0070] The O1 interface 250 and the open fronthaul M-plane interface 270 provide an FCAPS interface for exchanging configuration, reconfiguration, registration, security, performance, and monitoring modes with individual nodes such as O-DU220, O-CU-UP221, O-CU-CP222, O-RU260, and non-RT RIC242 and RAN nodes, such as O-gNB223 and O-eNB224.

[0071] The service management and orchestration framework 240 collects data and sets policies to be provided to non-RT RIC 242. For example, a policy can be developed that the number of connected users should not exceed 100 for a particular node, such as O-CU-CP node 222. The policy is based on collected data regarding performance parameters. The policy is then provided to the quasi-RT RIC 210 by the non-RT RIC 242 to optimize several network functions. For example, a policy can be set to limit the number of connected users to 100, which is a critical parameter for the network to operate optimally.

[0072] However, the policy limiting connected users to 100 may not result in optimal performance because O-CU-CP node 222's view is that of an 80-connected-user limit. O-CU-CP node 222 will determine that 80 connected users is the limit because it will experience performance degradation in response to having 100 connected users. Alternatively, O-CU-CP node 222 will determine that the limit is 120 connected users because the allocation on which O-CU-CP node 222's resources are being used is not being fully utilized. Quasi-RT RIC 210 will inform non-RT RIC 242 that quasi-RT RIC 310 is in a better position than non-RT RIC 242, and therefore quasi-RT RIC 210 can make the decision. However, this decision does not involve time-critical functions, but rather non-time-critical functions.

[0073] In at least one other embodiment, the intelligent RAN optimization framework enables the O-RU260 to handle time-critical and non-time-critical functions, as described below, even without a link between the quasi-RT RIC210s. The O-RU260 operates at the 50-200 nanosecond level, compared, for example, to the 1-100 millisecond level of the quasi-RT RIC210. ​​Functions of the O-RU260 do not operate at the 50-200 nanosecond level. There are certain functions that can operate at the 50 millisecond level.

[0074] O-RU260 determines whether an O-RU function is time-critical or non-time-critical. The intelligent RAN optimization framework allows O-RU260 to have quasi-RT RIC210 / non-RT RIC242 process non-time-critical functions via E2 termination in the O-DU, while O-RU260 processes time-critical functions. For example, time-critical functions are latency-sensitive, and using quasi-RT RIC210 / non-RT RIC242 for time-critical functions will affect the performance of O-RU260. Therefore, O-RU260 functions are divided into time-critical functions that are optimized locally by O-RU260 and non-time-critical functions that are centrally optimized by quasi-RT RIC210 / non-RT RIC242. The decision of whether a function is time-critical and should be processed by O-RU260, or non-time-critical and should be processed by non-RT RIC242, is made by O-RU node 260. In response to the non-critical nature of O-RU260's functions, one or more non-RT RIC services are initiated for the non-critical RAN functions of O-RU node 260, and therefore the non-critical RAN functions of O-RU node 260 are handled by the quasi-RT RIC210 / non-RT RIC242. O-RU260 monitors the performance optimization of functions optimized by the quasi-RT RIC210 / non-RT RIC242.

[0075] Figures 8 and 8C (continued) are flowcharts 800 of a method for providing RAN optimization using RIC services or local services according to at least one embodiment.

[0076] In Figures 8 and 8C, the method starts at S802, and one or more RAN nodes are provisioned at S810. Referring to Figure 2, the E2 node includes RAN nodes such as the ORAN Distributed Unit (O-DU) 220, the O-Centralized Unit Control Plane (O-CU-CP) 221, the O-CU User Plane (O-CU-UP) 222, the Next Generation Node B (O-gNB) 223, and the O-Evolutionary Node B (O-eNB) 224. The O-DU 220 is coupled to the ORAN Radio Unit (O-RU) 260 using an open fronthaul M-plane interface 270. The open fronthaul M-plane interface 270 also enables communication between the O-RU 260 and the Service Management and Orchestration Framework 240 and the non-RT RIC 242.

[0077] One or more RAN nodes may be E2 nodes S814 or O-RU nodes S866. The optimization subscription service is initiated S818 to handle the optimization of the performance of one or more RAN nodes' E2 nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC). Referring to Figure 4, RAN node 410 initiates the subscription procedure by sending a setup request message 432 to quasi-RT RIC 420 containing the appropriate data. For example, the setup request message 432 includes RAN function definitions that define the RAN functions supported by RAN node 410, node identifier (ID) information, and configurations supported by RAN node 410. Quasi-RT RIC 420 responds with a setup response message 434 containing the appropriate data, such as a list of accepted RAN functions and their associated RAN function IDs, as well as a list of rejected RAN functions, their associated RAN function IDs, and the reasons for rejection. RAN function IDs are indicators of network functions. The subscription is associated with the network function associated with the RAN function ID. The quasi-RT RIC420 can also send an RIC subscription request message 436 to the RAN node. The RIC subscription request message 436 is used to create a new subscription within the RAN node 410 at the request of the quasi-RT RIC420 and includes one or more of the following: RIC request ID, RAN function ID, RIC subscription details, RIC event trigger definition, sequence of actions, RIC action ID, RIC action type, RIC action definition, and RIC subsequent actions. The RAN node 410 responds by sending an RIC subscription response message 438 to the quasi-RT RIC420, accepting the request from the quasi-RT RIC420 to create a new event in the RAN node 410. The RIC subscription response message 438 includes one or more of the following: RIC request ID, RAN function ID, RIC action approval list and associated RIC action IDs, as well as RIC action disapproval list and associated RIC action IDs, and the cause.Therefore, messages 1-4 of the RIC service initiation process are part of the establishment of an existing interface connection. Messages 1-4 of the RIC service initiation process 430, namely 432, 434, 436, and 438, expose optimization functions, network functions, etc.

[0078] RAN nodes such as the E2 node determined in S814 monitor the performance of the functions optimized by the quasi-RT RIC in S822. Referring to Figure 4, RAN node 410 continues to monitor performance.

[0079] S826 determines whether the performance optimization of the RAN node by the quasi-real-time RIC is below a first predetermined threshold. Referring to Figure 4, the RAN node 410 determines whether the centralized optimization provided by the quasi-RT RIC 420 is acceptable.

[0080] In response to the fact that the performance optimization by the quasi-real-time RIC is not below a first predetermined threshold S830, the process returns to having a RAN node, for example, node E2, continue to monitor the performance of the function optimized by the quasi-real-time RIC S822. Referring to Figure 4, RAN node 410 determines, for example, that the local algorithm can provide better performance optimization based on determining whether the performance optimization of RAN node 410 by the quasi-real-time RIC 420 is below a first predetermined threshold.

[0081] In response to the performance optimization by the quasi-real-time RIC being below a predetermined threshold (S834), the RAN node, for example, the E2 node, suspends the subscription of the quasi-RT RIC service(s)(s)(s)(s)(S838). Referring to Figure 4, in response to the RAN node 410 determining, for example, that the performance of the quasi-RT RIC420 optimization is below a predetermined threshold and that a local algorithm can provide better performance optimization, the RAN node 410 executes the RIC service suspension process 450. The RAN node 410 sends an RIC subscription suspension message 452 to the quasi-RT RIC420.

[0082] The E2 node receives a quasi-RT RIC pause acknowledgment from the quasi-RT RIC in S842. Referring to Figure 4, in response, the quasi-RT RIC 420 may send an RIC subscription pause acknowledgment message 454 to the RAN node 410. The RAN node 410 can then take over the performance optimization of the RAN node 410 using a local optimization algorithm. For example, the RAN node 410 may determine that subscriptions X, Y, and Z exist, and that subscription X has a problem, but Y and Z do not. Therefore, the RAN node 410 can pause subscription X. The RIC subscription pause message 452 may provide the quasi-RT RIC 420 with identifying information on why the RAN node 410 is attempting to pause subscription X. Thus, through the RIC subscription pause message 452 and the RIC subscription pause acknowledgment message 454, the RAN node 410 and the quasi-RT RIC 420 can reach an agreement on how to optimize the performance optimization of the RAN node 410.

[0083] The E2 node monitors the performance of RAN nodes, such as the S846, which is optimized by the E2 node. Referring to Figure 4, RAN node 410 continues to monitor performance.

[0084] S850 determines whether the performance optimization by a RAN node, for example, the E2 node, is below a second predetermined threshold. Referring to Figure 4, RAN node 410 determines whether the performance optimization by RAN node 410 is below a second predetermined threshold.

[0085] In response to the performance optimization by a RAN node, e.g., node E2, not falling below a second predetermined threshold S854, the process returns to having the RAN node, e.g., node E2, continue to monitor the performance of the function optimized by node E2 S846. Referring to Figure 4, in response to the performance optimization not falling below the second threshold, RAN node 410 continues to monitor the performance of RAN node 410.

[0086] In response to the performance optimization by the E2 node being below a second predetermined threshold (S858), the RAN node, for example the E2 node, initiates the resumption of the quasi-RT RIC subscription (S862). Referring to Figure 4, in response to the performance optimization being below a second threshold, the RAN node 410 can cause the quasi-RT RIC 420 to initiate performance optimization processing. For example, in response to a change in performance such as improved coverage or fewer routine failures, the RAN node 410 can communicate with the quasi-RT RIC 420 to cause the quasi-RT RIC 420 to resume performance optimization on the RAN node 410. The RIC service resumption process 470 is used to reactivate RIC services. The RAN node 410 sends an RIC subscription resumption message 472 to the quasi-RT RIC 420. For example, the RAN node 410 sends an RIC subscription resumption message 472 that identifies subscription X to be processed again by the quasi-RT RIC / 420. In response, the quasi-RT RIC 420 responds to the RAN node 410 with an RIC subscription request message 474. Again, the RIC subscription request message 474 is used to create a subscription, for example, to restart subscription X, and includes one or more of the following: RIC request ID, RAN function ID, RIC subscription details, RIC event trigger definition, sequence of actions, RIC action ID, RIC action type, RIC action definition, and RIC subsequent actions. The RAN node 410 responds to the subscription request message 474 from the quasi-RT RIC 420 by sending a RIC subscription response message 476 to the quasi-RT RIC 420, thereby accepting the request from the quasi-RT RIC / non-RT RIC 420 to restart subscription X to the quasi-RT RIC 420.Therefore, via the RIC subscription restart message 472, the RIC subscription request message 474, and the RIC subscription response message 476, the RAN node 410 and the quasi-RT RIC 420 can reach an agreement that the quasi-RT RIC 420 will resume processing the performance optimization of the RAN node 410, including agreement on the parameters of subscription X.

[0087] The process returns to having a RAN node, e.g., E2 node, monitor the performance of the function optimized by an RIC, e.g., a quasi-RT RIC, in S822. Referring to Figure 4, RAN node 410 returns to monitoring the performance optimization by the quasi-RT RIC 420. The RIC service pause process 450 and the RIC service resume process 470 can be repeated. However, the cycle between the RIC service pause process 450 and the RIC service resume process 470 should not be performed too frequently. Therefore, a timer can be used to control the frequency of transitions between the RIC service pause process 450 and the RIC service resume process 470. For example, before executing the RIC service pause process 450 again, a timer can be used to make RAN node 410 wait for a predetermined period, e.g., 1 hour, 4 hours, 10 hours, etc. The timer may depend on the network function involved.

[0088] Based on S866 that the RAN node is an O-RU node, S870 determines whether the performance optimization of the O-RU nodes of one or more RAN nodes involves the optimization of time-critical or non-critical O-RU functions. Referring to Figure 2, the same intelligent RAN optimization framework can be extended to non-RT RIC nodes. RIC services are not supported by O-RU260, and due to the time-critical nature of the O-RU260's functions, there is no E2 interface between O-RU260 and quasi-RT RIC210 or non-RT RIC242. The intelligent RAN optimization framework allows O-RU260 to have quasi-RT RIC210 / non-RT RIC242 handle non-time-critical functions via E2 termination at O-DU, while O-RU260 handles time-critical functions. For example, time-critical functions are latency-sensitive, and using quasi-RT RIC210 / non-RT RIC242 for time-critical functions would affect the performance of O-RU260. Therefore, the functions of O-RU260 can be divided into time-critical functions that are optimized locally by O-RU260 and non-time-critical functions that are centrally optimized by quasi-RT RIC210 / non-RT RIC242. The decision of whether a function is time-critical and should be processed by O-RU260, or non-time-critical and should be processed by quasi-RT RIC210 / non-RT RIC242, is made by O-RU node 260.

[0089] In response to the fact that the functions of a RAN node, for example O-RU, are non-time critical (S874), the non-time critical functions of O-RU are managed by quasi-RT RIC / non-RT RIC services via the E2 interface and E2 termination at O-DU (S878). Referring to Figure 2, in response to the fact that the functions of O-RU260 are non-time critical, one or more non-RT RIC services are initiated for the non-critical RAN functions of O-RU node 260, so that the non-critical RAN functions of O-RU node 260 are handled by quasi-RT RIC210 / non-RT RIC242. O-RU260 monitors the performance optimization of functions optimized by quasi-RT RIC210 / non-RT RIC242.

[0090] The process returns to processing on other RAN nodes (S812).

[0091] In response to S882 that the function of the O-RU node is time-critical, the O-RU processes one or more optimization services for the time-critical RAN function of the O-RU node, S886. Referring to Figure 2, the intelligent RAN optimization framework enables the O-RU260 to process the time-critical function.

[0092] The process returns to processing on other RAN nodes (S812).

[0093] In at least one embodiment, a method for providing intelligent radio access network (RAN) optimization includes provisioning one or more radio access network (RAN) nodes; initiating an optimization subscription service for handling the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switching to performance optimization by the E2 nodes themselves, or otherwise continuing to handle performance optimization by the quasi-RT RIC.

[0094] Figure 9 is a high-level functional block diagram of a processor-based system 900 according to at least one embodiment.

[0095] In at least one embodiment, the processing circuit 900 provides an intelligent RAN optimization framework. The processing circuit 900 implements the intelligent RAN optimization framework using a processor 902. The processing circuit 900 also includes a non-temporary computer-readable storage medium 904 used to implement the intelligent RAN optimization framework. The non-temporary computer-readable storage medium 904 stores, among other things, instructions 906, i.e., computer program code, which are executed by the processor 902 and cause the processor 902 to perform operations to provide RAN optimization using RIC services or local services. The execution of instructions 906 by the processor 902 represents (at least partially) an application that implements at least a portion of the methods described herein (hereinafter, the described processes and / or methods) according to one or more embodiments.

[0096] The processor 902 is electrically coupled to the non-temporary computer-readable storage medium 904 via the bus 908. The processor 902 is electrically coupled to the input / output (I / O) interface 910 via the bus 908. The network interface 912 is also electrically connected to the processor 902 via the bus 908. The network interface 912 is connected to the network 914 so that the processor 902 and the non-temporary computer-readable storage medium 904 connect to external elements via the network 914. The processor 902 is configured to execute instructions 906 encoded in the non-temporary computer-readable storage medium 904, making the processing circuit 900 available for executing at least a portion of a process and / or method. In one or more embodiments, the processor 902 is a central processing unit (CPU), a multiprocessor, a distributed processing system, an application-specific integrated circuit (ASIC), and / or a suitable processing unit.

[0097] The processing circuit 900 includes an I / O interface 910. The I / O interface 910 is coupled to an external circuit. In one or more embodiments, the I / O interface 910 includes a keyboard, keypad, mouse, trackball, trackpad, touchscreen, and / or cursor directional keys for communicating information and commands to the processor 902.

[0098] The processing circuit 900 also includes a network interface 912 coupled to the processor 902. The network interface 912 enables the processing circuit 900 to communicate with a network 914 to which one or more other computer systems are connected. The network interface 912 includes wireless network interfaces such as Bluetooth, Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), General Packet Radio Service (GPRS), or Wideband Code Division Multiple Access (WCDMA®), or wired network interfaces such as Ethernet, Universal Serial Bus (USB), or Institute of Electrical and Electronics Engineers (IEEE) 864.

[0099] The processing circuit 900 is configured to receive information via the I / O interface 910. The information received via the I / O interface 910 includes one or more of the following for processing by the processor 902: instructions, data, design rules, cell libraries, and / or other parameters. The information is transferred to the processor 902 via the bus 908. The processing circuit 900 is configured to receive information related to the user interface (UI) 920 via the I / O interface 910. The information is stored as the UI 920 in the non-temporary computer-readable storage medium 904.

[0100] In one or more embodiments, one or more non-temporary computer-readable storage media 904 store instructions 906 (in compressed or uncompressed form) which may be used to program a computer, processor, or other electronic device to perform the processes or methods described herein. One or more non-temporary computer-readable storage media 904 include one or more of the following: electronic storage media, magnetic storage media, optical storage media, quantum storage media, etc.

[0101] For example, the non-temporary computer-readable storage medium 904 may include, but is not limited to, a hard drive, a floppy diskette, an optical disk, read-only memories (ROMs), random access memories (RAMs), erasable programmable ROMs (EPROMs), electrically erasable programmable ROMs (EEPROMs), flash memory, a magnetic or optical card, a solid-state memory device, or other types of physical media suitable for storing electronic instructions. In one or more embodiments using an optical disk, one or more non-temporary computer-readable storage mediums 904 may include Compact Disk-Read Only Memory (CD-ROM), Compact Disk-Read / Write (CD-R / W), and / or Digital Video Disc (DVD).

[0102] In one or more embodiments, the non-temporary computer-readable storage medium 904 stores instructions 906 configured to cause the processor 902 to execute at least a portion of the process and / or method for implementing the intelligent RAN optimization 922 by providing RAN optimization using RIC services or local services. In one or more embodiments, the non-temporary computer-readable storage medium 904 also stores information such as algorithms that facilitate the execution of at least a portion of the process and / or method for implementing the intelligent RAN optimization 922 by providing RAN optimization using RIC services or local services.

[0103] In at least one embodiment, the processor 902 is configured to provide radio access network (RAN) functionality to a mobile network, provide RAN functionality to one or more RAN nodes in the mobile network, initiate an optimization subscription service for processing the performance optimization of one or more RAN nodes' E2 nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC), determine whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold, and in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switch to performance optimization by the E2 nodes themselves, or otherwise continue to process the performance optimization of the E2 nodes by the quasi-RT RIC. The processor 902 is further configured to determine whether the performance of the E2 node by the E2 node is below a second predetermined threshold, and in response to the performance of the E2 node being below the second predetermined threshold, restart the optimization subscription service for the quasi-RT RIC to process the performance optimization of the E2 node; otherwise, the E2 node continues to process the performance optimization of the E2 node. The processor 902 is further configured to restart the optimization subscription service for the quasi-RT RIC to process the performance optimization of the RAN function by sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart processing the performance optimization of the RAN function, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart processing the performance optimization of the RAN function.The processor 902 is further configured to initiate an optimization subscription service for the quasi-RT RIC to process the optimization of the RAN function performance by sending a setup request to the quasi-RT RIC that identifies at least one function of the RAN function to be optimized, receiving a setup response from the quasi-RT RIC that confirms at least one function of the RAN function to be optimized, receiving a subscription request to cause the quasi-RT RIC to process the optimization of the performance of at least one function of the RAN function, and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC will process the optimization of at least one function. The processor 902 is further configured to switch to the optimization of the RAN function performance by sending a subscription pause message to the quasi-RT RIC that instructs the quasi-RT RIC to pause processing the optimization of the RAN function performance by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC. In response to determining that the RAN function is for an O-RU node, the processor 902 is further configured to determine whether the optimization of the RAN function performance involves the optimization of a time-critical or non-critical RAN function. The processor 902 is further configured to process time-critical RAN function optimizations by the processor in response to determining that optimizing the performance of RAN functions involves optimizing time-critical RAN functions, and to process non-time-critical RAN function optimizations by a non-real-time RIC in response to determining that optimizing the performance of RAN functions involves optimizing non-time-critical RAN functions.

[0104] Embodiments described herein provide methods that offer one or more advantages. For example, the Intelligent Radio Access Network (RAN) Optimization Framework provides performance improvements by using a method that achieves optimal performance, whether the method is centralized optimization controlled by a RAN Intelligent Controller (RIC) or localized optimization controlled by RAN nodes via an E2 interface. The Intelligent Radio Access Network (RAN) Optimization Framework provides improved handling of latency-sensitive use cases and RAN optimization functions. The Intelligent Radio Access Network (RAN) Optimization Framework also uses and, as necessary, an RIC for RAN optimization functions.

[0105] In at least one embodiment, a method for providing intelligent radio access network (RAN) optimization includes provisioning one or more radio access network (RAN) nodes; initiating an optimization subscription service for handling the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switching to performance optimization by the E2 nodes, or otherwise continuing to handle performance optimization by the quasi-RT RIC.

[0106] In at least one embodiment of the method, the method further includes determining whether the performance of the E2 node is below a second predetermined threshold, and in response to the performance of the E2 node being below the second predetermined threshold, restarting an optimization subscription service for processing the performance optimization of the E2 node by a quasi-RT RIC, otherwise continuing to process the performance optimization of the E2 node by the E2 node.

[0107] In at least one embodiment of the method, restarting an optimization subscription service for handling performance optimization of E2 nodes by a quasi-RT RIC includes sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart handling performance optimization of E2 nodes to the quasi-RT RIC, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart handling performance optimization of E2 nodes.

[0108] In at least one embodiment of the method, initiating an optimization subscription service for a quasi-RT RIC to handle performance optimization of an E2 node includes: sending a setup request to the quasi-RT RIC that identifies at least one function of the E2 node to be optimized; receiving a setup response from the quasi-RT RIC that confirms at least one function of the E2 node to be optimized; receiving a subscription request to cause the quasi-RT RIC to handle the optimization of at least one function of the E2 node; and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC will handle performance optimization of at least one function of the E2 node.

[0109] In at least one embodiment of the method, switching to performance optimization of an E2 node by an E2 node includes sending a subscription pause message to a quasi-RT RIC instructing the quasi-RT RIC to pause processing performance optimization of an E2 node by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC.

[0110] In at least one embodiment of the method, it is determined, based on the fact that one or more RAN nodes are O-RU nodes, whether the optimization of the performance of the O-RU nodes of one or more RAN nodes involves the optimization of time-critical or non-critical O-RU functions.

[0111] In at least one embodiment of the method, the method further includes processing the optimization of a time-critical O-RU function by an O-RU in response to determining that the optimization of the performance of the O-RU function involves the optimization of a time-critical O-RU function, and processing the optimization of a non-time-critical O-RU function by a non-real-time RIC in response to determining that the optimization of the performance of the O-RU function involves the optimization of a non-time-critical O-RU function.

[0112] In at least one embodiment, a radio access network (RAN) node includes a memory for storing computer-readable instructions and a processor connected to the memory, the processor being configured to perform operations including: executing computer-readable instructions to provide RAN functionality to one or more RAN nodes in a mobile network; initiating an optimization subscription service for processing the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of an E2 node as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of an E2 node falls below the first predetermined threshold, switching to performance optimization by the E2 node, or otherwise continuing to process the performance optimization by the quasi-RT RIC.

[0113] In at least one embodiment, the processor determines whether the performance of the E2 node by the E2 node is below a second predetermined threshold, and in response to the performance of the E2 node being below the second predetermined threshold, restarts an optimization subscription service for processing the performance optimization of the E2 node by a quasi-RT RIC; otherwise, the processor is further configured to continue processing the performance optimization of the E2 node by the E2 node.

[0114] In at least one embodiment, the processor is further configured to restart the optimization subscription service for processing RAN function performance optimization by the quasi-RT RIC by sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart processing RAN function performance optimization to the quasi-RT RIC, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart processing RAN function performance optimization to the quasi-RT RIC.

[0115] In at least one embodiment, the processor is further configured to initiate an optimization subscription service for the quasi-RT RIC to handle the performance optimization of a RAN function by sending a setup request to the quasi-RT RIC that identifies at least one function of the RAN function to be optimized; receiving a setup response from the quasi-RT RIC that confirms at least one function of the RAN function to be optimized; receiving a subscription request to cause the quasi-RT RIC to handle the performance optimization of at least one function of the RAN function; and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC will handle the optimization of at least one function of the RAN function.

[0116] In at least one embodiment, the processor is further configured to switch back to optimizing the performance of the RAN function by sending a subscription pause message to the quasi-RT RIC instructing the quasi-RT RIC to pause processing the performance optimization of the RAN function, and by receiving a subscription pause acknowledgment message from the quasi-RT RIC.

[0117] In at least one embodiment, the processor is further configured to determine, in response to one or more RAN nodes being O-RU nodes, whether optimizing the performance of an O-RU involves optimizing a time-critical or non-critical RAN function.

[0118] In at least one embodiment, the processor is further configured to process time-critical RAN function optimizations in response to determining that optimizing the performance of a RAN function involves optimizing a time-critical RAN function, and to process non-time-critical RAN function optimizations by a non-real-time RIC in response to determining that optimizing the performance of a RAN function involves optimizing a non-time-critical RAN function.

[0119] In at least one embodiment, a non-transient computer-readable medium stores computer-readable instructions that, when executed by the processor, cause the processor to perform operations including: provisioning one or more radio access network (RAN) nodes; initiating an optimization subscription service for handling the performance optimization of one or more RAN nodes by a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC); determining whether the performance of the E2 nodes as a result of the performance optimization by the quasi-RT RIC falls below a first predetermined threshold; and, in response to determining that the performance of the E2 nodes falls below the first predetermined threshold, switching to performance optimization by the E2 nodes themselves, or otherwise continuing to handle performance optimization by the quasi-RT RIC.

[0120] In a non-transient computer-readable medium according to at least one embodiment, the operation further includes determining whether the performance of the E2 node is below a second predetermined threshold, and in response to the performance of the E2 node being below the second predetermined threshold, restarting an optimization subscription service for processing the performance optimization of the E2 node by a quasi-RT RIC, otherwise continuing to process the performance optimization of the E2 node by the E2 node.

[0121] In at least one embodiment of a non-transient computer-readable medium, restarting an optimization subscription service for handling performance optimization of E2 nodes by a quasi-RT RIC includes sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart handling performance optimization of E2 nodes to the quasi-RT RIC, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart handling performance optimization of E2 nodes.

[0122] In at least one embodiment of a non-transient computer-readable medium, initiating an optimization subscription service for a quasi-RT RIC to handle performance optimization of an E2 node includes sending a setup request to the quasi-RT RIC that identifies at least one function of the E2 node to be optimized; receiving a setup response from the quasi-RT RIC that confirms at least one function of the E2 node to be optimized; receiving a subscription request to cause the quasi-RT RIC to handle the optimization of at least one function of the E2 node; and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC will handle performance optimization of at least one function of the E2 node.

[0123] In at least one embodiment of a non-transient computer-readable medium, switching to performance optimization of an E2 node by an E2 node includes sending a subscription pause message to a quasi-RT RIC instructing the quasi-RT RIC to pause processing the performance optimization of the E2 node by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC.

[0124] In at least one embodiment of a non-temporary computer-readable medium, the operation further includes: determining whether the performance optimization of an O-RU node involves optimizing a time-critical or non-critical O-RU function, in response to the fact that one or more RAN nodes are O-RU nodes; processing the optimization of a time-critical O-RU function by the O-RU, in response to the determination that the performance optimization of an O-RU function involves optimizing a time-critical O-RU function; and processing the optimization of a non-time-critical O-RU function by a non-real-time RIC, in response to the determination that the performance optimization of an O-RU function involves optimizing a non-time-critical O-RU function.

[0125] Separate instances of these programs can run on any number of separate computer systems or be distributed across them. Therefore, while certain steps are described as being performed by a particular device, software program, process, or entity, this is not necessarily required. Various alternative implementations will be understood by those skilled in the art.

[0126] Furthermore, those skilled in the art will readily recognize that the techniques described above can be used in a variety of devices, environments, and situations. While the embodiments are described in language specific to structural features or methodological actions, the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described. Rather, specific features and actions are disclosed as exemplary forms for implementing the claims.

Claims

1. A method for providing intelligent wireless access network (RAN) optimization, Provisioning one or more wireless access network (RAN) nodes, To launch an optimization subscription service for processing the performance optimization of the E2 nodes of one or more RAN nodes using a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC), The determination of whether the performance of the E2 node as a result of the optimization of the performance of the E2 node by the quasi-RT RIC is below a first predetermined threshold, A method comprising: in response to determining that the performance of the E2 node falls below a first predetermined threshold, switching to optimizing the performance of the E2 node by the E2 node; otherwise, continuing to process the optimization of the performance of the E2 node by the quasi-RT RIC.

2. The method according to claim 1, further comprising: determining whether the performance of the E2 node is below a second predetermined threshold; and, in response to the performance of the E2 node being below the second predetermined threshold, restarting the optimization subscription service for processing the optimization of the performance of the E2 node by the quasi-RT RIC; otherwise, continuing to process the optimization of the performance of the E2 node by the E2 node.

3. The method according to claim 2, wherein restarting the optimization subscription service for processing the performance optimization of the E2 node by the quasi-RT RIC includes sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart processing the performance optimization of the E2 node, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart processing the performance optimization of the E2 node.

4. The method according to claim 1, wherein initiating the optimization subscription service for processing the performance optimization of the E2 node by the quasi-RT RIC includes: sending a setup request to the quasi-RT RIC that identifies at least one function of the E2 node to be optimized; receiving a setup response from the quasi-RT RIC that confirms the at least one function of the E2 node to be optimized; receiving a subscription request to cause the quasi-RT RIC to process the optimization of the at least one function of the E2 node; and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC processes the optimization of the performance of the at least one function of the E2 node.

5. The method according to claim 1, wherein switching the E2 node to the optimization of the performance of the E2 node includes sending a subscription pause message to the quasi-RT RIC instructing the quasi-RT RIC to pause processing the optimization of the performance of the E2 node by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC.

6. The method according to claim 1, further comprising determining, based on the fact that one or more RAN nodes are O-RU nodes, whether the optimization of the performance of the O-RU nodes of one or more RAN nodes involves the optimization of time-critical O-RU functions or non-time-critical O-RU functions.

7. In response to determining that the optimization of the performance of the O-RU function involves the optimization of a time-critical O-RU function, the O-RU processes the optimization of the time-critical O-RU function. In response to determining that the optimization of the performance of the O-RU function involves the optimization of a non-time-critical O-RU function, the optimization of the non-time-critical O-RU function is processed by a non-real-time RIC. The method according to claim 6, further comprising:

8. Memory for storing computer-readable instructions, A processor connected to the memory, which executes the computer-readable instructions, To provide RAN functionality to one or more RAN nodes within a mobile network, To launch an optimization subscription service for processing the performance optimization of the E2 nodes of one or more RAN nodes using a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC), The determination of whether the performance of the E2 node as a result of the optimization of the performance of the E2 node by the quasi-RT RIC is below a first predetermined threshold, A processor configured to perform an operation that includes, in response to determining that the performance of the E2 node falls below a first predetermined threshold, switching to optimizing the performance of the E2 node by the E2 node, or otherwise continuing to process the optimization of the performance of the E2 node by the quasi-RT RIC, A wireless access network (RAN) node equipped with [the necessary features].

9. The RAN node according to claim 8, wherein the processor determines whether the performance of the E2 node is below a second predetermined threshold, and in response to the performance of the E2 node being below the second predetermined threshold, restarts the optimization subscription service for processing the optimization of the performance of the E2 node by the quasi-RT RIC, otherwise the processor is further configured to allow the E2 node to continue processing the optimization of the performance of the E2 node.

10. The RAN node according to claim 9, further configured to restart the optimization subscription service for processing the performance optimization of the RAN function by the quasi-RT RIC by sending a subscription restart message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to restart processing the optimization of the performance of the RAN function to the quasi-RT RIC, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will restart processing the optimization of the performance of the RAN function to the quasi-RT RIC.

11. The RAN node according to claim 8, further configured to initiate the optimization subscription service for processing the optimization of the performance of the RAN function by the quasi-RT RIC, by sending a setup request to the quasi-RT RIC that identifies at least one function of the RAN function to be optimized, receiving a setup response from the quasi-RT RIC that confirms the at least one function of the RAN function to be optimized, receiving a subscription request to cause the quasi-RT RIC to process the optimization of the performance of the at least one function of the RAN function, and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC processes the optimization of the performance of the at least one function.

12. The RAN node according to claim 8, further configured to switch to the optimization of the performance of the RAN function by sending a subscription pause message to the quasi-RT RIC instructing the quasi-RT RIC to pause processing the optimization of the performance of the RAN function by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC.

13. The RAN node according to claim 8, wherein the processor is further configured to determine, in response to the one or more RAN nodes being O-RU nodes, whether the optimization of the performance of the O-RU involves the optimization of time-critical RAN functions or non-time-critical RAN functions.

14. In response to the processor determining that the optimization of the performance of the RAN function involves the optimization of a time-critical RAN function, the processor processes the optimization of the time-critical RAN function. The RAN node according to claim 13, further configured to process the optimization of the non-time-critical RAN function by a non-real-time RIC in response to a determination that the optimization of the performance of the RAN function involves the optimization of a non-time-critical RAN function.

15. When executed by the processor, the processor will Provisioning one or more wireless access network (RAN) nodes, To launch an optimization subscription service for processing the performance optimization of the E2 nodes of one or more RAN nodes using a quasi-real-time RAN intelligent controller (RIC) (quasi-RT RIC), The determination of whether the performance of the E2 node as a result of the optimization of the performance of the E2 node by the quasi-RT RIC is below a first predetermined threshold, A non-temporary computer-readable medium for storing computer-readable instructions that causes the medium to perform an operation including, in response to determining that the performance of the E2 node is below a first predetermined threshold, switching to optimizing the performance of the E2 node by the E2 node, or otherwise continuing to process the optimization of the performance of the E2 node by the quasi-RT RIC.

16. The non-temporary computer-readable medium according to claim 15, further comprising: determining by the E2 node whether the performance of the E2 node is below a second predetermined threshold; and, in response to the performance of the E2 node being below the second predetermined threshold, restarting the optimization subscription service for processing the optimization of the performance of the E2 node by the quasi-RT RIC; otherwise, continuing to process the optimization of the performance of the E2 node by the E2 node.

17. The non-temporary computer-readable medium according to claim 16, wherein the resumption of the optimization subscription service for processing the optimization of the performance of the E2 node by the quasi-RT RIC includes sending a subscription resumption message to the quasi-RT RIC, receiving a subscription request from the quasi-RT RIC to cause the quasi-RT RIC to resume processing the optimization of the performance of the E2 node, and sending a subscription response to the quasi-RT RIC confirming that the quasi-RT RIC will resume processing the optimization of the performance of the E2 node.

18. The non-temporary computer-readable medium according to claim 15, wherein initiating the optimization subscription service for processing the performance optimization of the E2 node by the quasi-RT RIC includes: sending a setup request to the quasi-RT RIC that identifies at least one function of the E2 node to be optimized; receiving a setup response from the quasi-RT RIC that confirms the at least one function of the E2 node to be optimized; receiving a subscription request to cause the quasi-RT RIC to process the optimization of the at least one function of the E2 node; and sending a subscription response to the quasi-RT RIC that confirms the quasi-RT RIC processes the optimization of the performance of the at least one function of the E2 node.

19. The non-temporary computer-readable medium according to claim 15, wherein switching by the E2 node to the optimization of the performance of the E2 node includes sending a subscription pause message to the quasi-RT RIC instructing the quasi-RT RIC to pause processing the optimization of the performance of the E2 node by the quasi-RT RIC, and receiving a subscription pause acknowledgment message from the quasi-RT RIC.

20. In response to the fact that one or more of the aforementioned RAN nodes are O-RU nodes, it is determined whether the optimization of the performance of the aforementioned O-RU nodes involves the optimization of time-critical O-RU functions or non-time-critical O-RU functions. In response to determining that the optimization of the performance of the O-RU function involves the optimization of a time-critical O-RU function, the O-RU processes the optimization of the time-critical O-RU function. In response to determining that the optimization of the performance of the O-RU function involves the optimization of a non-time-critical O-RU function, the optimization of the non-time-critical O-RU function is processed by a non-real-time RIC. The non-temporary computer-readable medium according to claim 15, further comprising:

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