AI / ML model mobility support methods, systems, and devices

Abstract

A user equipment (UE) includes a memory having non-transitory instructions stored therein and a processor, coupled to the memory and configured to execute the instructions, causing the UE to receive, while operating in a connected mode, each of a zone identifier and a UE identifier from a first RAN node of a radio access network (RAN). The zone identifiers correspond to zones of the RAN that include multiple cells and multiple RAN nodes, including the first RAN node. The UE stores each of the zone identifiers and the UE identifier in a storage device, and transmits the zone identifier and the UE identifier to the second RAN node in response to returning from an inactive mode or an idle mode to a connected mode or receiving, from the first RAN node or a third RAN node, a radio resource control (RRC) handover command corresponding to a handover to the second RAN node.

Description

【Technical Field】 【0001】 This description relates to a method, system, device, and non - transient computer - readable medium for automatically supporting user equipment (UE) mobility in a telecommunications system that includes the application of artificial intelligence and machine learning (AI / ML) models. 【Background Art】 【0002】 A telecommunications system, such as a cellular system, may include a number of cells with service coverage provided by multiple vendors. A user equipment (UE), such as a mobile phone, can typically operate in a connected mode, an idle mode, and a non - active mode and is often transferred between various cells and multiple vendors. When the UE is operating within a given cell, it accesses the radio access network (RAN) through a network node and is accessed by the RAN, and becomes actively connected to the RAN when switching from a non - active or idle mode to a connected mode. The switching between cells operated by different vendors is generally achieved by a handover operation. 【Summary of the Invention】 【0003】 In one embodiment, the UE includes a memory storing non-transient instructions and a processor coupled to the memory and configured to execute instructions, the execution of which causes the processor to perform the following actions: receive a zone identifier and a UE identifier from a first RAN node of the RAN while operating in connected mode, wherein the zone identifier corresponds to a zone of the RAN including a plurality of cells and a plurality of RAN nodes including the first RAN node; store the zone identifier and the UE identifier in the UE's storage device; and transmit the zone identifier and the UE identifier to a second RAN node in response to returning from inactive or idle mode to connected mode, or in response to receiving a Radio Resource Control (RRC) handover command from the first or third RAN node corresponding to a handover to a second RAN node. 【0004】 In one embodiment, a RAN node includes a memory storing non-transient instructions and a processor coupled to the memory and configured to execute the instructions, the execution of which causes the RAN node to receive a transmission from a UE in the process of establishing a connected mode session that includes a RAN node serving the UE, and, in response to a transmission that includes a first zone identifier and a UE identifier, to compare the first zone identifier with a second zone identifier of a zone of the RAN that includes a plurality of RAN nodes, which include a plurality of cells and a plurality of RAN nodes. In response to a match between the first and second zone identifiers, the RAN node retrieves an existing AI / ML base model associated with the UE identifier from a storage device based on a previous session that includes one of the plurality of RAN nodes serving the UE, or, in response to a mismatch between the first and second zone identifiers or a transmission lacking the first zone identifier, generates a new AI / ML base model. The RAN node transmits the corresponding existing or new AI / ML base model, UE identifier, and second zone identifier to the UE. 【0005】 In one embodiment, a method for operating a RAN includes transmitting a UE identifier and a zone identifier from a first node of the RAN to a UE, wherein the zone identifier corresponds to a first zone of the RAN, which includes a plurality of cells and a plurality of nodes including the first node; storing each of the UE identifier and the zone identifier in a storage device of the UE; transmitting the UE identifier and the zone identifier from the UE to a second node of the RAN; sending an AI / ML base model and policy parameters from the second node to the UE, wherein the AI / ML base model and policy parameters are based on the UE identifier and the zone identifier; and applying the AI / ML base model and policy parameters to the operation of the UE. 【0006】 The aspects of this disclosure will be best understood by reading the following detailed description in conjunction with the attached drawings. Following common industry practice, various features are not depicted to a fixed scale. In fact, the dimensions of various features are arbitrarily enlarged or reduced for clarity in the discussion. [Brief explanation of the drawing] 【0007】 [Figure 1] This is a diagram of a communication system according to one embodiment. 【0008】 [Figure 2] This is a flowchart of an AI / ML model mobility support method according to one embodiment. 【0009】 [Figure 3] This is a flowchart of an AI / ML model mobility support method according to one embodiment. 【0010】 [Figure 4] This is a flowchart of an AI / ML model mobility support method according to one embodiment. 【0011】 [Figure 5]This is a diagram of a processor-based device according to one embodiment. [Modes for carrying out the invention] 【0012】 The following disclosure provides many different embodiments or examples for implementing various features of the subject matter provided. For the sake of simplicity, specific examples of components and arrangements are described below. Naturally, these are merely examples and are not intended to be limiting. For example, the formation or positioning of a first feature above or on a second feature in the following description includes embodiments in which the first and second features are formed or arranged in direct contact, and also includes embodiments in which an additional feature is formed or arranged between the first and second features so that they are indirectly in contact. In addition, the disclosure repeats reference numbers and / or letters in various examples. This repetition is for the sake of brevity and clarity and does not in itself determine the relationships between the various embodiments and / or configurations discussed. 【0013】 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 various orientations of the system or object being used or operating, in addition to the orientations shown in the figures. Systems may also be oriented in other directions (rotated by 90 degrees or other directions), and the spatially relative descriptors used herein will be interpreted accordingly. 【0014】 In various embodiments, some or all of the methods, systems, devices, and computer-readable media cover RAN operations that include transmitting a UE identifier and a zone identifier from a first node of the RAN to a UE, wherein the zone identifier corresponds to a first zone of the RAN, which includes a plurality of cells and a plurality of nodes including the first node; storing each of the UE and the zone identifier in a storage device of the UE; transmitting the UE and the zone identifier from the UE to a second node of the RAN; sending an AI / ML base model and policy parameters from the second node to the UE, wherein the AI / ML base model and policy parameters are based on the UE identifier and the zone identifier; and applying the AI / ML base model and policy parameters to the operation of the UE. 【0015】 By storing zone and UE identifiers in the UE and sending them from the UE to a second node, the second node can determine or retrieve, for example, whether previously generated AI / ML base model information to be sent to the UE is available from a database associated with the zone identifier. Therefore, in situations where previously generated AI / ML base model information is unavailable, such as when the UE transitions from inactive or idle mode to connected mode, or during a UE handover operation, previously generated AI / ML base model information to be applied to the UE's operation, such as the AI / ML base model and policy parameters, becomes available. Thus, compared to methods where previously generated AI / ML base model information is unavailable in such situations, the system, UE, and node are configured to operate more efficiently by leveraging previously generated AI / ML base model information. 【0016】 Figure 1 is a diagram of a remote communication system 100 (hereinafter referred to as "System 100") according to one embodiment. Figure 1 is simplified for illustrative purposes. 【0017】 System 100 includes a plurality of interconnected devices 102 configured as part or all of Network 104. In various embodiments, Device 102 corresponds to a computing device, a computing system, a server, a server cluster, and / or a combination of multiple server clusters, also known as a server farm or data center in some embodiments. In one embodiment, Device 500, described later with respect to Figure 5, is one embodiment of Device 102. 【0018】 In one embodiment, one or more of the devices 102 are virtualized network components, such as virtualized network functions (VNFs), which include software configured to perform one or more network functions by operating on one or more hardware devices. In one embodiment, some or all of the devices 102 are configured as part or all of a network function virtualization infrastructure (NFVI). Other configurations and / or types of the devices 102 are within the scope of this disclosure. 【0019】 Figure 1 shows device 102N, which is an instance of device 102, and will be discussed further below. 【0020】 In one embodiment, the network 104 includes one or more radio access networks (RANs), or parts of RANs, such as zones, which are discussed further below. In one embodiment, the RAN is a mobile telecommunications system implementing radio access technology (RAT), which exists between instances of user equipment (UEs) 112, such as mobile phones or computers, and provides connectivity to devices 102. 【0021】 In one embodiment, one or more of the devices 102 are configured to perform management functions corresponding to the network 104. In various embodiments, one or more of the devices 102 are configured as one or more of an operation support system (OSS), an element management system (EMS), a network management system (NMS), an access and mobility management function (AMF), or other systems or functions configured to perform one or more activities that support the operation of the network 104. 【0022】 In one embodiment, one or more of the interconnected devices 102 of the network 104 are configured as one or more of a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), an internet area network (IAN), a campus area network (CAN), or a virtual private network (VPN). In one embodiment, one or more of the interconnected devices 102 of the network 104 are configured as part of a backbone or core network (CN), a computer network that interconnects networks, and provides a path for exchanging information between separate LANs, WANs, etc. 【0023】 In one embodiment, some of the interconnected devices 102 of the network 104 are configured as a server cluster, for example, included in a data center. In one embodiment, the server cluster is part of a cloud computing environment. 【0024】 In some embodiments, network 104 is some or all of a Global System for Mobile Communications (GSM) RAN, GSM / EDGE RAN, Universal Mobile Telecommunications System (UMTS) RAN (UTRAN), Evolved Universal Terrestrial Radio Access Network (E-UTRAN), Open RAN (O-RAN), or Cloud RAN (C-RAN). In some embodiments, network 104 exists between UE 112 and one or more core networks of system 100. 【0025】 In some embodiments, network 104 is a hierarchical telecommunications network, such as part or all of system 100, that includes one or more intermediate links, sometimes referred to in some embodiments as a backhaul portion, between the RAN and one or more core networks. Non-limiting examples of mobile backhaul implementations include fiber-based backhaul, wireless point-to-point backhaul, copper-based wireline, satellite communications, and point-to-multipoint wireless technologies. In some embodiments, the backhaul refers to the side of the network that communicates with the global Internet. 【0026】 In the embodiment shown in FIG. 1, network 104 includes cells 106A and 106B, which include respective base stations 108A and 108B and respective antennas 110A and 110B. In some embodiments, network 104 includes a plurality of cells, collectively referred to as cell 106 or in some embodiments as coverage area 106, including cells 106A and 106B, a plurality of base stations, collectively referred to as base station 108, including base stations 108A and 108B, and a plurality of antennas, collectively referred to as antenna 110, including antennas 110A and 110B. 【0027】 In the embodiment shown in Figure 1, a single base station 108 corresponds to a single instance each of cell 106 and antenna 110. In various embodiments, a single base station 108 corresponds to two or more instances of cell 106 and / or two or more instances of antenna 110. 【0028】 In one embodiment, base station 108 is a grid or freestanding tower, guy tower, monopole tower, and concealed tower (e.g., a tower designed to resemble a tree, cactus, water tower, sign, lighting pole, and other types of structure). In one embodiment, base station 108 is a cellular-enabled mobile device site where antennas and electronic communication equipment are typically located on a radio tower, tower, or other elevated structure to create a cell 106 (or adjacent cell) in the network. The elevated structure typically supports one or more antennas 110 and a transmitter / receiver, transceiver, digital signal processor, control electronics, remote radio head (RRH), primary and backup power sources, and one or more shelters. Base station 108 is also known by other names such as transceiver base station, cell tower, or cell tower. In one embodiment, base station 108 is an edge device configured to communicate wirelessly with a UE 112. The edge device provides an entry point to the service provider core network. Examples include routers, routing switches, integrated access devices (IADs), multiplexers, and various MAN and WAN access devices. 【0029】 In at least one embodiment, an instance of antenna 110 is a sector antenna, for example, a directional microwave antenna having a fan-shaped radiation pattern, or a plurality of sector antennas configured to have, for example, an all-around coverage area 106. In one embodiment, an instance of antenna 110 is a circular antenna. In one embodiment, an instance of antenna 110 operates at one or more microwave or ultra-high frequency (UHF) frequencies in the range of, for example, 300 megahertz (MHz) to 7.2 gigahertz (GHz). In one embodiment, an instance of antenna 110 operates at one or more frequencies in the range of 24.2 GHz to 71.0 GHz. 【0030】 In various embodiments, cell 106 is a three-dimensional space having a shape and size based on the configuration of the corresponding base station 108, e.g., power level, and antenna 110, e.g., the number of sectors. In various embodiments, cell 106 has a substantially spherical, hemispherical, conical, cylindrical, circular, or elliptical disk, or other shape corresponding to the base station and antenna configuration. In various embodiments, one or both of the shape and / or size of cell 106 changes over time, e.g., based on a variable base station power level and / or a variable working antenna and / or the number of antenna sectors. In some embodiments, cell 106 is referred to as a macrocell, microcell, picocell, femtocell, or smallcell. In some embodiments, cell 106 is referred to as an indoor small cell (IDSC). 【0031】 In some embodiments, an instance of UE 112 is a computer or computing system. In some embodiments, UE 112 has a liquid crystal display (LCD), light-emitting diode (LED), or organic light-emitting diode (OLED) screen interface, such as a graphical user interface that provides a touchscreen interface with digital buttons and a keyboard or physical buttons along with a physical keyboard. In some embodiments, an instance of UE 112 connects to the internet and interconnects with other devices. In some embodiments, an instance of UE 112 incorporates a built-in camera, voice and video call capabilities, video games, and Global Positioning System (GPS) functionality. In some embodiments, an instance of UE 112 runs as a virtual machine or allows third-party applications to run as containers. In one embodiment, an instance of UE 112 is a computer (such as a tablet computer, netbook, digital media player, digital assistant, graphing calculator, handheld game console, handheld personal computer (PC), laptop, mobile internet device (MID), personal digital assistant (PDA), pocket calculator, portable media player, or ultra-mobile PC), a mobile phone (such as a camera phone, feature phone, smartphone, or phablet), a digital camera (such as a digital camcorder, or digital still camera (DSC), digital video camera (DVC), or front camera), a pager, a personal navigation device (PND), a wearable computer (such as a calculator watch, smartwatch, head-mounted display, earphone, or biometric device), or a smart card. 【0032】 UE 112 is configured to communicate with base station 108 using signals transmitted to and from antenna 110. In one embodiment, UE 112 is configured to operate in inactive mode, idle mode, and connected mode, respectively. In inactive mode, UE 112 has no active RAN access; in connected mode, UE 112 is actively connected to the RAN; and in idle mode, UE has access to and from the RAN, but is not actively connected to the RAN. The main difference between inactive mode and idle mode is that in inactive mode, UE 112 is known to the network, i.e., the context of the UE, including the UE's address identifier and session data, is stored in both UE 112 and the network, whereas in idle mode, UE 112 is not known to the network. 【0033】 Figure 1 shows an instance of UE 112, namely UE 112U, which will be discussed further below. 【0034】 The network 104 includes a plurality of network nodes, which in some embodiments are called nodes or RAN nodes. In some embodiments, a node corresponds to one or more devices 102, a combination of one or more devices 102 and one or more base stations 108, or one or more base stations 108. In some embodiments, a node corresponds to a base station 108 which is an instance of device 102. 【0035】 In one embodiment, a node corresponds to a device 102 configured as a centralized unit (CU) and one or more base stations 108 configured as distributed units (DUs). In one embodiment, a node is a next-generation RAN (NG-RAN) node, for example, a gNB according to the 3GPP® TS 38.300 specification. or N It is G-eNB. 【0036】 Nodes are interconnected with each other and with network management entities, such as EMS or AMF, through various interfaces. In one embodiment, the interface between a node and a core network element is called an NG interface. In another embodiment, the interface between various nodes, such as between NG-RAN nodes, is called an Xn interface. 【0037】 In the embodiment shown in Figure 1, device 102N is a network node that includes mobility support 122N and a storage device 124N configured to store zone and UE identifiers 126N and AI / ML model information 128N. In one embodiment, mobility support 122N is also called mobility support algorithm 122N, and / or AI / ML model information 128N is also called AI / ML base model and policy parameters 128N. 【0038】 In the embodiment shown in Figure 1, device 102N, which includes mobility support 122N, is a single instance of device 102. In one embodiment, device 102N, which includes mobility support 122N, includes two or more instances of device 102. Mobility support 122N, zone and UE identifier 126N, and AI / ML model information 128N are each discussed further below. 【0039】 A zone is a part or all of a RAN, including a group of cells and a corresponding group of nodes, such as device 102N. In one embodiment, a zone corresponds to a geographical area, e.g., a province, bounded by one or more boundaries corresponding to a political, physical, and / or geometric configuration. In various embodiments, a zone is a part, all, or combination of towns, villages, cities, counties, states, provinces, countries, continents, islands, peninsulas, isthmuses, grid portions bounded by latitude and longitude, circular areas, polygonal areas, or other areas. In one embodiment, a zone is a physically limited portion of a geographical area, e.g., a part, all, or combination of buildings such as a hotel or office building, a mixed-use building, a campus, an industrial park, one or more urban blocks, a shopping center, a town center or mall, a neighborhood, a town, or a village. 【0040】 The storage device, for example, storage device 124N or storage device 124U on UE 112U, is one or more computer-readable non-volatile storage devices, such as a database. In one embodiment, the storage device includes memory 504, which will be described later with respect to Figure 5. 【0041】 In the embodiment shown in Figure 1, the storage device 124N is located on device 102N. In one embodiment, the storage device 124N is located outside of device 102N, for example, on one or more servers corresponding to device 102. 【0042】 In one embodiment, the storage device 124N is a database, also called a RAN database in one embodiment, which is associated with a zone and therefore accessible by each node in the associated zone. In one embodiment, the storage device 124N is a database configured to provide storage / read / write services based on service-based architectural principles. 【0043】 In one embodiment, a zone includes multiple instances of device 102N, each of which includes a corresponding mobility support 122N and a storage device 124N configured to store an instance of the corresponding zone and UE identifier 126N, as well as AI / ML model information 128N. 【0044】 Mobility support 122N is a set of one or more instructions configured to run on device 102N, thereby managing and sending / receiving zones and UE identifiers 126N to and from instances of UE 112, e.g., UE 112U, according to the AI / ML model mobility support method 200 described later, thereby managing and sending / receiving AI / ML model information 128N to and from instances of UE 112. In one embodiment, mobility support 122N is configured to run as a standalone program or within a set of one or more instructions. In one embodiment, mobility support 122N is configured to run on device 102N in addition to one or more of the devices 102. 【0045】 Mobility support 122N is configured to manage zone and UE identifiers 126N during operation, which includes generating the zone identifier for each of the zone and UE identifiers 126N, as well as the UE identifier for each of the zone and UE identifiers 126N. 【0046】 The zone identifier of the zone and UE identifier 126N is used to identify the zone containing device 102N, and device 102 and UE This is a data record configured to be interpreted by 112. In one embodiment, the mobility support 122N is configured to generate a zone identifier during operation based on separate information received from a device 102, such as a RAN management system or function. In one embodiment, the mobility support 122N receives a zone identifier from a device 102, such as a RAN management system or function. 【0047】 In one embodiment, a portion of a zone identifier, for example, a subset of bits in a data record, is used to identify a given instance of device 102N, and device 102 and UE It is configured to be interpreted by 112. In one embodiment, this portion of the zone identifier includes part or all of the address of a given instance of device 102N, for example, an IP address. In one embodiment, this portion is called the address identifier. 【0048】 The zone and UE identifier 126N are used to identify a given instance of UE 112U over a given period of time, with device 102 and UE A data record configured to be interpreted by 112. In various embodiments, a given period is a predetermined period or a variable period of length based on one or more criteria, for example, a time threshold that tracks the most recent activity within a given zone. 【0049】 Device 102 and UE Since 112 is configured to store the zone and UE identifier 126N (and the corresponding zone and UE identifier 126U described later) in a storage device, for example in storage device 124N, the corresponding zone and UE identifiers are essentially persistent, and device 102 or UE Device 102 and UE It can be used by 112. 【0050】 In one embodiment, the mobility support 122N is configured to generate a UE identifier during operation based on separate information received from a device 102, such as a RAN management system or function. In one embodiment, the mobility support 122N receives the UE identifier from a device 102, such as a RAN management system or function. In one embodiment, the UE identifier is Serving Temporary Mobile Subscriber Identification Information (S-TMSI). 【0051】 In one embodiment, the mobility support 122N is configured to send an instance of the zone and UE identifier 126N to a given UE 112U in response to receiving a transmission from the UE 112U during operation. In one embodiment, the transmission from the UE 112U includes an RRC setup request message or an RRC restart request message, which is received in the process of establishing a session in which device 102N acts as a serving node to the UE 112U, for example, in the process of establishing a session due to the UE 112U transitioning from an inactive or idle mode to a connected mode. In one embodiment, this transmission includes an instruction for the UE to transition from a connected mode to an inactive or idle mode. 【0052】 In one embodiment, the mobility support 122N, during operation, confirms that the connected mode session has been completed. Respond For example, if you return the UE 112U to inactive or idle mode... Respond It is configured to send an instance of the zone and UE identifier 126N to a given UE 112U. 【0053】 In one embodiment, the mobility support 122N is configured to store AI / ML model information 128N associated with a zone and a UE identifier 126N in one storage device 124N or a combination of storage devices 124N, which is included in device 102N or configured as a database associated with a zone containing device 102N. In one embodiment, storing the AI / ML model information 128N corresponds to completing a connection mode session with a given UE 112U and storing the generated ML models and policies, for example, the AI / ML model information 128N in the network. In one embodiment, storing the AI / ML model information 128N includes storing mobility history information (MHI) corresponding to a given UE 112U, for example, MHI generated by device 102N or MHI received from UE 112U and / or from a device 102 other than device 102N. 【0054】 An instance of AI / ML model information 128N includes at least one model generated by the execution of one or more AI / ML algorithms on training data, for example, on the MHI of UE 112, including UE 112U in one embodiment. The at least one model includes an algorithm configured to produce a set of outputs consisting of predictive information and / or decision parameters based on a set of inputs, and is therefore configured to be available to UE 112U during one or more operations, for example, during a cell reselection operation. 【0055】 In one embodiment, an instance of AI / ML model information 128N includes one or more policy parameters, for example, the speed range of the UE 112U or the signal strength received from the base station 108. 【0056】 In one embodiment, mobility support 122N is further configured to transmit an instance of zone and UE identifier 126N to a given UE 112U in response to receiving a transmission from device 102 during operation. In one embodiment, the transmission from device 102 includes a handover request acknowledgment from device 102, which is received in the process of establishing a session in which device 102N acts as a serving node for UE 112U after device 102 has acted as a serving node for UE 112U. 【0057】 In one embodiment, the mobility support 122N operates as follows: place To the UE 112U The System Information Block (SIB) It is configured to send instances of the zone and UE identifier 126N. 【0058】 In one embodiment, the mobility support 122N is configured to respond to instances of zone and UE identifiers 126N received from a given UE 112U by comparing the received instances of zone and UE identifiers 126N with previously generated instances of zone and UE identifiers 126N during operation. In various embodiments, previously generated zone and UE identifiers 126N are stored in one storage device 124N or a combination of storage devices 124N, which is contained in device 102N or configured as a database associated with zones containing device 102N. 【0059】 In one embodiment, the received zone and UE identifier 126N instances are included in the RRC setup or restart request message. In another embodiment, the received zone and UE identifier 126N instances are included in the RRC reconfiguration completion message received during the handover operation. 【0060】 In one embodiment, the mobility support 122N is configured to retrieve AI / ML model information 128N from one storage device 124N or a combination of storage devices 124N, which is contained in device 102N or configured as a database associated with zones containing device 102N, in response to a match between an incoming instance of zone and UE identifier 126N and a previously generated zone and UE identifier 126N during operation. 【0061】 The previously generated zone and UE identifier 126N is based on one or more previous sessions in which a node within the zone, for example, device 102N or another device 102 within the zone, acted as a serving node for UE 112U. 【0062】 In one embodiment, the mobility support 122N is configured to respond to a mismatch between an instance of a received zone and UE identifier 126N and one or more previously generated zone and UE identifiers 126N by generating new AI / ML model information 128N during operation. In another embodiment, the mobility support 122N is configured to respond to receiving a transmission from the UE 112U, including, for example, an RRC setup request message or an RRC restart request message, by generating new AI / ML model information 128N. 【0063】 In one embodiment, the mobility support 122N is configured to send the corresponding previously generated zone and UE identifier 126N and / or newly generated zone and UE identifier 126N to the UE 112U. 【0064】 UE 112U is an instance of UE 112 that includes mobility support 122U and a storage device 124U configured to store zone and UE identifiers 126U and AI / ML model information 128U. In one embodiment, mobility support 122U is also called mobility support algorithm 122U, and / or AI / ML model information 128U is also called AI / ML base model and policy parameters 128U. 【0065】 The zone and UE identifier 126U corresponds to the zone and UE identifier 126N received from device 102N, and the AI / ML model information 128U corresponds to the AI / ML model information 128N received from device 102N. 【0066】 Mobility support 122U is a set of instructions configured to run on UE 112U, which manages zones and UE identifiers 126U according to the AI / ML model mobility support method 200 described later, and instances of device 102. (example For example, device 102N ) It is sent and received between, and as a result, AI / ML model information 128U Received from an instance of device 102N and, in one embodiment, applied to the operation of UE 112U 。 In one embodiment, the mobility support 122U is configured to run as a standalone program or within one or more sets of instructions. In one embodiment, the mobility support 122U is configured to run on one or more UEs 112 in addition to the UE 112U. 【0067】 The mobility support 122U is configured to receive instances of zones and UE identifiers 126U from an instance of device 102N during operation, and to store instances of zones and UE identifiers 126U in a storage device 124U. In one embodiment, instances of zones and UE identifiers 126U are included in the SIB received from an instance of device 102N. 【0068】 In one embodiment, the mobility support 122U is configured to receive instances of zone and UE identifier 126U included in RRC setup or restart request messages during operation, for example, in the process of establishing a session in which an instance of device 102N acts as a serving node to UE 112U, or in the process of establishing a session due to, for example, UE 112U transitioning from inactive or idle mode to connected mode. 【0069】 In one embodiment, the mobility support 122U is configured to receive, during operation, an instance of the zone and UE identifier 126U contained in an RRC reconfiguration message received in the process of completing a connection mode session with an instance of device 102N. 【0070】 In one embodiment, the mobility support 122U is configured to receive, during operation, an instance of the zone and UE identifier 126U contained in an RRC reconfiguration message received during the handover operation from an instance of device 102N acting as a serving node for UE 112U after another device 102 has acted as a serving node for UE 112U. 【0071】 In one embodiment, the mobility support 122U is configured to receive, during operation, instances of zone and UE identifier 126U included in RRC reconfiguration messages received during the handover operation from device 102, which is acting as a serving node for UE 112U, before device 102N acts as a serving node for UE 112U. In one embodiment, the mobility support 122U receives instances of zone and UE identifier 126U from device 102, which are included in a handover command, based on a handover request acknowledgment sent from device 102N, for example, which includes instances of zone and UE identifier 126U in an SIB. In one embodiment, device 102 corresponds to a vendor different from the vendor corresponding to device 102N. 【0072】 The mobility support 122U is configured to store the received zone and UE identifiers 126U in a storage device 124U during operation. In one embodiment, the mobility support 122U stores the zone and UE identifiers 126U received before transitioning from connected mode to inactive or idle mode, and retains the zone and UE identifiers 126U received throughout the subsequent inter-mode transitions in the storage device 124U. 【0073】 In one embodiment, the mobility support 122U is configured to send the stored zone and UE identifier 126U to a second instance of device 102N in response to returning from an inactive or idle mode to a connected mode during operation, or in response to receiving an RRC handover command from a device 102 different from the instance of device 102N, for example, from a device 102 corresponding to a vendor different from the vendor corresponding to the instance of device 102N. 【0074】 In one embodiment, the mobility support 122U is configured to respond to a return from inactive or idle mode to connected mode by sending a stored zone and UE identifier 126U in an RRC setup request message or an RRC restart request message. 【0075】 In one embodiment, the mobility support 122U is configured to respond to the receipt of an RRC handover command by sending a stored zone and UE identifier 126U in an RRC reconfiguration complete message. In one embodiment, the mobility support 122U obtains a zone and UE identifier 126U from a plurality of stored instances of zone and UE identifier 126U. 【0076】 In one embodiment, the mobility support 122U is configured to receive AI / ML model information 128U from a second instance of the device 102N during operation and to apply the received AI / ML model information 128U to the operation of the UE 112U, for example, to the idle mode cell reselection operation. 【0077】 In various embodiments, the AI / ML model information 128U corresponds to the AI / ML model information 128N previously generated and acquired by a second instance of device 102N, or to the AI / ML model information 128N newly generated by a second instance of device 102N, as described above. 【0078】 In one embodiment, the mobility support 122U is configured to delete one or both of the stored zones and UE identifiers among the stored zones and UE identifiers 126U during operation by deleting the oldest identifier, for example, after the expiration of a pre-configured timer and / or when a predetermined maximum number of identifiers is reached, or in response to receiving an explicit delete command or other delete instruction from an instance of device 102N. 【0079】 Therefore, a system 100 including one or more instances of device 102N and / or one or more instances of UE 112U configured as described above is configured to perform some or all of the following: transmit a zone and UE identifier 126N from a first instance of device 102N to UE 112U, wherein the zone identifier corresponds to a first zone of network 104 including cell 106 and device 102 including the first instance of device 102N; store the zone and UE identifier 126U in a storage device 124U; transmit the zone and UE identifier 126U from UE 112U to a second instance of device 102N; and send AI / ML model information 128N from the second instance of device 102N to UE 112U, wherein the AI / ML model information 128N is sent based on the zone and UE identifier 126N; and apply the AI / ML model information 128U to the operation of UE 112U. 【0080】 By storing the zone and UE identifier 126U and transmitting the zone and UE identifier 126U from the UE 112U to a second instance of the device 102N, the second instance of the device 102N can determine whether previously generated AI / ML model information 128N to be sent to the UE 112U is available. Thus, for example, while the UE 112U is transitioning from inactive or idle mode to connected mode, or during the UE 112U handover operation, previously generated AI / ML base model information is unavailable, while previously generated AI / ML model information 128N to be applied to the operation by the UE 112U becomes available. Therefore, compared to a method in which previously generated AI / ML base model information is unavailable in such situations, the system 100, UE 112U, and device 102N are configured to make UE operation more efficient by being able to utilize the previously generated AI / ML model information 128N. 【0081】 Figure 2 is a flowchart of the AI / ML model mobility support method 200 according to one embodiment. The AI / ML model mobility support method 200, also called method 200 or method for operating RAN in one embodiment, can operate on a telecommunication system, for example, the telecommunication system 100 described with respect to Figure 1. 【0082】 Additional operations may be performed before, during, between, and / or after the operation of Method 200 shown in Figure 2, and some other operations may only be briefly described herein. In some embodiments, other sequences of operations of Method 200 are within the scope of this disclosure. In some embodiments, one or more operations of Method 200 are not performed. 【0083】 In one embodiment, some or all of the operations of method 200 are included in another method, for example, a method for operating a telecommunications system. In one embodiment, some or all of the operations of method 200 described later are repeated, for example, in the process of operating a telecommunications system. 【0084】 In one embodiment, some or all of the operation of method 200 described later can be performed automatically, for example, by UE 112 including device 102N and / or mobility support 122U, which are described above with respect to Figure 1, and / or by using processing circuit 502 described later with respect to Figure 5. 【0085】 The operation of Method 200 will be described below with reference to the various features of System 100 described above in relation to Figure 1. 【0086】 Figures 3 and 4 illustrate non-limiting examples of how some or all of the operations of Method 200 using an embodiment of System 100 may be performed, as will be described later. 【0087】 In operation 210, in one embodiment, the zone and UE identifier are transmitted from the first RAN node to the UE. Transmitting the zone and UE identifier from the first RAN node to the UE includes, as described above, transmitting the zone and UE identifier 126N from the first instance of device 102N to the UE 112U. 【0088】 In operation 220, in one embodiment, AI / ML model information based on zone and UE identifiers is stored. Storing AI / ML model information based on zone and UE identifiers includes, as described above, using device 102N to store the AI / ML model information 128N in one storage device 124N or a combination of storage devices 124N, which is configured as a database contained in device 102N or associated with zones containing device 102N. 【0089】 In operation 230, in one embodiment, the zone and UE identifier are stored in a UE storage device. Storing the zone and UE identifier in a UE storage device includes, as described above, using UE 112U to store the zone and UE identifier 126U in storage device 124U. 【0090】 In operation 240, in one embodiment, the zone and UE identifier are transmitted from the UE to a second RAN node. Transmitting the zone and UE identifier from the UE to a second RAN node includes, as described above, transmitting the zone and UE identifier 126U from the UE 112U to a second instance of device 102N. 【0091】 In operation 250, in one embodiment, AI / ML model information is acquired or generated based on zone and UE identifiers received at a second RAN node. Acquiring or generating AI / ML model information based on zone and UE identifiers received at a second RAN node includes acquiring or generating AI / ML model information 128N using a second instance of device 102N, as described above. 【0092】 In operation 260, in one embodiment, AI / ML model information is transmitted from the second RAN node to the UE. Transmitting AI / ML model information from the second RAN node to the UE includes transmitting AI / ML model information 128N from the second instance of device 102N to the UE 112U, as described above. 【0093】 In operation 270, in one embodiment, AI / ML information is applied to the operation of the UE. Applying AI / ML information to the operation of the UE includes applying AI / ML model information 128U to the operation of the UE 112U, as described above. 【0094】 In one embodiment, operation 280 deletes stored zones and / or UE identifiers based on one or more deletion criteria. Deleting stored zones and / or UE identifiers based on one or more deletion criteria includes deleting some or all instances of zones and UE identifiers 126U stored using UE 112U, as described above. 【0095】 By performing some or all of the operations of Method 200, a system, for example, System 100, automatically performs some or all of the following: transmitting a UE identifier and a zone identifier from a first node of the RAN to a UE, wherein the zone identifier corresponds to a first zone of the RAN, which includes multiple cells and multiple nodes including the first node; storing each of the UE and the zone identifier in a storage device of the UE; transmitting the UE and the zone identifier from the UE to a second node of the RAN; sending an AI / ML base model and policy parameters from the second node to the UE, wherein the AI / ML base model and policy parameters are based on the UE identifier and the zone identifier; and applying the AI / ML base model and policy parameters to the operation of the UE, thereby realizing the advantages described above with respect to System 100. 【0096】 Figure 3 is a flowchart of the AI / ML model mobility support method 300 according to one embodiment. The AI / ML model mobility support method 300, also called method 300 or method for operating RAN in one embodiment, is a non-limiting example of some or all of the methods 200 described above. 【0097】 Method 300 corresponds to a situation where an instance of UE 112U transitions in and out of a connected mode session with two instances of device 102N, and AI / ML model information 128N is retrieved from a database on device 102 based on the stored zone and UE identifier 128U. 【0098】 In the embodiment shown in Figure 3, in operation 210, the first instance of device 102N sends the zone and UE identifier 128N to UE 112U, and UE 112U transitions from connected mode to inactive or idle mode. In operation 230, UE 112U stores the zone and UE identifier 128N as zone and UE identifier 128U. In operation 220, the first instance of device 102N stores the AI / ML model information 128N in the database on device 102. In operation 240, UE 112U returns to connected mode and sends the zone and UE identifier 128N to the second instance of device 102N. In operation 250, based on the received zone and UE identifier 128N, the second instance of device 102N retrieves the AI / ML model information 128N from the database on device 102. In operations 260 and 270, a second instance of device 102N sends the acquired AI / ML model information 128N to UE 112U, and UE 112U applies AI / ML model information 128N as AI / ML model information 128U in one or more operations. 【0099】 The advantages described above with respect to Figures 1 and 2 can be achieved by performing some or all of the operations of Method 200 according to a non-limiting example of Method 300. 【0100】 Figure 4 is a flowchart of the AI / ML model mobility support method 400 according to one embodiment. The AI / ML model mobility support method 400, also called method 400 or method for operating RAN in one embodiment, is a non-limiting example of some or all of the methods 200 described above. 【0101】 Method 400 addresses a situation where an instance of UE 112U is involved in a handover operation between two instances of device 102N, and AI / ML model information 128N is retrieved from a database on device 102 based on the stored zone and UE identifier 128U. 【0102】 In the embodiment shown in Figure 4, during operations 210-230, the UE 112U stores the zone and UE identifier 128U based on a previous connection mode session (not shown) with an instance of device 102N in which the AI / ML model information 128N is stored in a database on device 102. Subsequent handover operations are performed from the first instance of device 102N to the second instance of device 102N. In operation 240, the UE 112U completes the handover operation by sending an RRC reconfiguration complete message to the second instance of device 102N, which includes the zone and UE identifier 128U (corresponding to the stored zone and UE identifier 126U). In operation 250, based on the received zone and UE identifier 128N, the second instance of device 102N retrieves the AI / ML model information 128N from the database on device 102. In operations 260 and 270, a second instance of device 102N sends the acquired AI / ML model information 128N to UE 112U, and UE 112U applies AI / ML model information 128N as AI / ML model information 128U in one or more operations. 【0103】 The advantages described above with respect to Figures 1 and 2 can be achieved by performing some or all of the operations of Method 200 according to a non-limiting example of Method 400. 【0104】 Figure 5 is a functional block diagram of a computer or processor-based device 500, in which embodiments are carried out on or by the device 500. 【0105】 The processor-based device 500 is programmed to facilitate the automatic generation and / or modification of cell reselection policies, as described herein, and includes, for example, a bus 508, a processing circuit 502 also called a processor 502 in some embodiments, and a memory 504 component. 【0106】 In one embodiment, the processor-based device 500 includes a communication mechanism, such as a bus 508, for transferring information and / or instructions between components of the processor-based device 500. The processing circuit 502 is connected to the bus 508 to obtain instructions to be executed and to process information stored, for example, in memory 504. In one embodiment, the processing circuit 502 also includes one or more specialized components for performing specific processing functions and tasks, such as one or more digital signal processors (DSPs) or one or more application-specific integrated circuits (ASICs). A DSP is typically configured to process real-world signals (e.g., sound) in real time, independently of the processing circuit 502. Similarly, an ASIC can be configured to perform specialized functions that are not readily performed by a more general-purpose processor. Other specialized components that assist in performing the functions described herein optionally include one or more field-programmable gate arrays (FPGAs), one or more controllers, or one or more other dedicated computer chips. 【0107】 In one or more embodiments, the processing circuit (or multiple processors) 502 performs a set of operations on information as specified by a set of instructions stored in memory 504, in relation to a cell reselection policy, for example, a mobility support algorithm 516 corresponding to the mobility support 122N or 122U described above with respect to Figures 1 and 2. By executing the instructions, the processor performs the specified function. 【0108】 The processing circuit 502 and its associated components are connected to the memory 504 via the bus 508. The memory 504 includes one or more dynamic memories (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memories (e.g., ROM, CD-ROM, etc.) that store executable instructions that, when executed, perform the operations described herein to facilitate automatic network configuration. In one embodiment, the memory 504 also stores data related to or generated by the execution of an operation, such as zone and UE identifiers 520 corresponding to zone and UE identifiers 126N or 126U, as described above with respect to Figures 1 and 2, respectively, and AI / ML model information 522 corresponding to AI / ML model information 128U or 128N. 【0109】 In one or more embodiments, memory 504, such as random access memory (RAM) or any other dynamic storage device, stores information including processor instructions to facilitate the implementation of network applications. Dynamic memory allows the stored information to be modified. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at adjacent addresses. Memory 504 is also used by processing circuits 502 to store temporary values ​​during the execution of processor instructions. In various embodiments, memory 504 includes read-only memory (ROM) or any other static storage device coupled to bus 508 to store static information including instructions that cannot be modified by processing circuits 502. Some memory consists of volatile storage, which loses the stored information when power is lost. In some embodiments, memory 504 includes a non-volatile (persistent) storage device, such as a magnetic disk, optical disk, or flash card, which stores information including instructions that remains even if device 500 is turned off or otherwise loses power in any way. 【0110】 As used herein, the term “computer-readable medium” refers to any medium involved in providing information to the processing circuit 502, including the instruction 506 to be executed. Such mediums can take many forms, but are not limited to computer-readable storage media (e.g., non-volatile media, volatile media). Non-volatile media include, for example, optical disks or magnetic disks. Volatile media include, for example, dynamic memory. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, other magnetic media, CD-ROMs, CDRWs, DVDs, other optical media, punch cards, paper tapes, optical mark sheets, other physical media having a pattern of holes or other optically recognizable marks, RAM, PROMs, EPROMs, FLASH-EPROMs, EEPROMs, flash memory, other memory chips or cartridges, or other media that a computer can read. The term computer-readable storage medium is used herein to refer to computer-readable media. 【0111】 Instruction 506 also refers to the user interface 518, and It includes one or more sets of instructions configured to enable the user to effectively operate and control the device 500. In one embodiment, the user interface 518 includes one or more layers, including a human-machine interface (HMI) that connects the machine with physical input hardware such as a keyboard, mouse, or gamepad, as well as output hardware such as a computer monitor, speakers, printer, and other appropriate user interfaces. Move through It is configured to produce. 【0112】 In one embodiment, the UE includes a memory storing non-transient instructions and a processor coupled to the memory and configured to execute instructions, the execution of which causes the UE to receive, while operating in connected mode, a zone identifier and a UE identifier from a first RAN node of the RAN, wherein the zone identifier corresponds to a zone of the RAN including a plurality of cells and a plurality of RAN nodes including the first RAN node; store the zone identifier and the UE identifier in the UE's storage device; and transmit the zone identifier and the UE identifier to a second RAN node in response to returning from inactive or idle mode to connected mode, or in response to receiving an RRC handover command from the first or third RAN node corresponding to a handover to a second RAN node. In one embodiment, the processor can execute instructions to cause the UE to further perform the following actions: receive an AI / ML base model and / or policy parameters from a second RAN node, and apply the AI / ML base model and / or policy parameters to the UE's operation, wherein the AI / ML base model and / or policy parameters include a previously generated AI / ML base model and / or policy parameters corresponding to a second RAN node in a zone corresponding to a stored zone identifier, or a newly generated AI / ML base model and / or policy parameters corresponding to a second RAN node in a zone other than the zone corresponding to a stored zone identifier. In one embodiment, the processor can execute instructions to cause the UE to send a zone identifier and a UE identifier to the second RAN node, which are included in an RRC setup request message or an RRC restart request message in response to a return to connected mode from inactive or idle mode, and in an RRC reconfiguration complete message in response to receiving an RRC handover command from a first or third RAN node.In one embodiment, the processor can execute an instruction to cause the UE to further perform the following actions in response to receiving an RRC handover command from a first or third RAN node: compare a zone identifier obtained from a system information broadcast of a second RAN node with a plurality of stored zone identifiers, and obtain a UE identifier corresponding to the zone identifier from the plurality of stored UE identifiers. In one embodiment, the processor can execute an instruction to cause the UE to receive, store, and transmit a zone identifier including the address identifier of a first RAN node. In one embodiment, the processor can execute an instruction to cause the UE to receive a new zone identifier and a new UE identifier from a third RAN node, thereby instructing the third RAN node to correspond to a first vendor different from the second vendor corresponding to the first and second RAN nodes. In one embodiment, the processor can execute an instruction to further cause the UE to delete one or both of the stored zone identifiers or UE identifiers based on one or more deletion criteria, or in response to instructions from a first, second, or another RAN node. 【0113】 In one embodiment, a RAN node includes a memory storing non-transient instructions and a processor coupled to the memory and configured to execute instructions, the execution of which causes the RAN node to perform the following actions: receive a transmission from a UE in the process of establishing a connected mode session that includes a RAN node serving a UE; in response to a transmission that includes a first zone identifier and a UE identifier, compare the first zone identifier to a second zone identifier of a zone of RAN that includes a plurality of cells and a plurality of RAN nodes that include a plurality of RAN nodes; in response to a match between the first and second zone identifiers, retrieve an existing artificial intelligence and machine learning (AI / ML) base model associated with the UE identifier from a storage device based on a previous session that includes one of the plurality of RAN nodes serving the UE, or in response to a mismatch between the first and second zone identifiers or a transmission lacking the first zone identifier, generate a new AI / ML base model; and transmit the corresponding existing or new AI / ML base model, UE identifier, and second zone identifier to the UE. In one embodiment, the processor can execute instructions to cause a RAN node to receive a first zone identifier and UE identifier included in a transmission including an RRC setup request message or an RRC restart request message during the process of establishing a connected mode session. In another embodiment, the processor can execute instructions to cause a RAN node to establish a connected mode session during a handover of a UE from a second vendor different from the first vendor, and to receive a first zone identifier and UE identifier included in a transmission including an RRC reconfiguration complete message, with the RAN corresponding to a first vendor. In yet another embodiment, the processor can execute instructions to cause a RAN node to retrieve an AI / ML base model from a storage device including a database associated with a zone containing multiple RAN nodes, including the RAN node.In one embodiment, the RAN node is the first of a plurality of RAN nodes, and the processor can execute instructions to cause the first RAN node to receive a first zone identifier which includes the address identifier of a second RAN node among the plurality of RAN nodes, and to retrieve an AI / ML base model from a storage device associated with the second RAN node. In one embodiment, the processor can execute instructions to cause the RAN node to send policy parameters corresponding to an existing or new AI / ML base model to the UE. In one embodiment, the processor can execute instructions to cause the RAN node to further store the corresponding existing or new AI / ML base model in the process of completing a connected mode session. 【0114】 In one embodiment, a method for operating a RAN includes transmitting a UE identifier and a zone identifier from a first node of the RAN to a UE, wherein the zone identifier corresponds to a first zone of the RAN, which includes a plurality of cells and a plurality of nodes including the first node; storing each of the UE identifier and zone identifier in a storage device of the UE; transmitting the UE identifier and zone identifier from the UE to a second node of the RAN; sending an AI / ML base model and policy parameters from the second node to the UE, wherein the AI / ML base model and policy parameters are based on the UE identifier and zone identifier; and applying the AI / ML base model and policy parameters to the operation of the UE. In one embodiment, transmitting the UE identifier and zone identifier from the first node to the UE includes broadcasting an SIB from the first node to the UE, or sending a dedicated message from the first node to the UE. In one embodiment, transmitting the UE identifier and zone identifier from the UE to a second node includes the UE sending an RRC setup request message or an RRC restart request message during the process of transitioning from inactive mode or idle mode to connected mode. In one embodiment, the first and second nodes correspond to a first vendor, and transmitting the UE identifier and zone identifier from the UE to the second node includes the UE transmitting an RRC reconfiguration complete message during the handover of the UE from a third node to the second node, which corresponds to a second vendor different from the first vendor. In one embodiment, transmitting the AI / ML base model and policy parameters includes retrieving previously generated AI / ML base models and policy parameters from a storage device, depending on whether the second node is among multiple nodes in the first zone, or generating new AI / ML base models and policy parameters, depending on whether the second node is outside the first zone.In one embodiment, retrieving previously generated AI / ML base models and policy parameters from a storage device includes retrieving previously generated AI / ML base models and policy parameters from a database associated with a first zone, or retrieving previously generated AI / ML base models and policy parameters from a storage device associated with a first node, a second node, or a third node among multiple nodes of the first zone. 【0115】 The above outlines the features of certain embodiments so that those skilled in the art may better understand aspects of the disclosure. Those skilled in the art will understand that the disclosure may readily be used as a basis for designing or modifying other processes and structures to accomplish the same objectives and / or achieve the same advantages of the embodiments described herein. Those skilled in the art will also recognize that such equivalent configurations will not depart from the spirit and scope of the disclosure, and that those skilled in the art may make various changes, substitutions, and modifications within this specification without departing from the spirit and scope of the disclosure.

Claims

[Claim 1] User equipment (UE), Receiving a zone identifier and a UE identifier from a first RAN node of a wireless access network (RAN) while operating in connected mode, wherein the zone identifier corresponds to a zone of the RAN that includes a plurality of cells and a plurality of RAN nodes including the first RAN node. Each of the aforementioned zone identifier and UE identifier is stored in the UE's storage device, In response to returning from inactive mode or idle mode to the connected mode, Upon receiving a Radio Resource Control (RRC) handover command corresponding to a handover to a second RAN node from the first RAN node or the third RAN node, The system is configured to transmit the zone identifier and the UE identifier to the second RAN node. UE. [Claim 2] Receiving artificial intelligence and machine learning (AI / ML) based models and / or policy parameters from the second RAN node, Applying the aforementioned AI / ML base model and / or policy parameters to the operation of the UE, It is configured to perform further actions, The aforementioned AI / ML base model and / or policy parameters are: The previously generated AI / ML base model and / or policy parameters corresponding to the second RAN node in the zone corresponding to the stored zone identifier, or Includes a newly generated AI / ML base model and / or policy parameters corresponding to the second RAN node located in a zone other than the zone corresponding to the stored zone identifier. The UE according to claim 1. [Claim 3] In response to returning from the inactive mode or idle mode to the connected mode, the following is included in the RRC setup request message or RRC restart request message: In response to receiving the RRC handover command from the first or third RAN node, the RRC reconfiguration completion message includes: The system is configured to transmit the zone identifier and the UE identifier to the second RAN node. The UE according to claim 1. [Claim 4] In response to receiving the RRC handover command from the first or third RAN node, The process involves comparing the zone identifier obtained from the system information broadcast of the second RAN node with a plurality of stored zone identifiers, It is configured to further perform the task of obtaining the UE identifier corresponding to the zone identifier from a plurality of stored UE identifiers. The UE according to claim 1. [Claim 5] The system is configured to receive, store, and transmit the zone identifier, which includes the address identifier of the first RAN node. The UE according to claim 1. [Claim 6] The system is configured to receive a new zone identifier and a new UE identifier from the third RAN node, thereby instructing the third RAN node to correspond to a first vendor different from the second vendor corresponding to the first and second RAN nodes. The UE according to claim 1. [Claim 7] It is further configured to delete one or both of the stored zone identifiers or UE identifiers based on one or more deletion criteria, or in response to instructions received from the first, second, or another RAN node. The UE according to claim 1. [Claim 8] A wireless access network (RAN) node, The system receives a zone identifier and a UE identifier corresponding to a zone of a RAN including multiple cells and the RAN node, from a user device (UE) operating in connected mode, in response to the UE returning to connected mode from inactive mode or idle mode, or in response to the UE receiving a radio resource control (RRC) handover command from another RAN, The system is configured to use the received zone identifier and UE identifier for mobility management of the UE within the zone. RAN node. [Claim 9] Comparing the received zone identifier with the second zone identifier of the RAN node, Depending on whether the received zone identifier matches the second zone identifier, retrieve existing artificial intelligence and machine learning (AI / ML) based models associated with the UE identifier from a storage device based on a previous session including one of a plurality of RAN nodes serving the UE, or If the received zone identifier and the second zone identifier do not match, a new AI / ML base model is generated. It is configured to perform the act of sending an existing or new AI / ML base model, the UE identifier, and the second zone identifier to the UE. The RAN node according to claim 9. [Claim 10] The aforementioned RAN corresponds to the first vendor, Establishing a connected mode operation during the handover process of the UE from a second vendor different from the first vendor, Receiving the first zone identifier and the UE identifier included in the transmission, which includes the RRC reconstruction completion message, Configured to execute The RAN node according to claim 8. [Claim 11] The storage device is configured to retrieve the AI / ML base model from the storage device which includes the database associated with the zone which includes the plurality of RAN nodes, including the RAN node. The RAN node according to claim 9. [Claim 12] The RAN node is the first RAN node among the plurality of RAN nodes, Receiving a first zone identifier that includes the address identifier of the second RAN node among the plurality of RAN nodes, Obtaining the AI / ML base model from the storage device associated with the second RAN node, Configured to execute The RAN node according to claim 9. [Claim 13] It is configured to send policy parameters corresponding to the existing or new AI / ML base model to the UE. The RAN node according to claim 9. [Claim 14] It is configured to further perform the task of storing the existing or new AI / ML base model during the process of completing the connection mode operation. The RAN node according to claim 9. [Claim 15] A method for operating a wireless access network (RAN), The transmission of a UE identifier and a zone identifier from the first RAN node of the RAN to a user device (UE) operating in connection mode, wherein the zone identifier corresponds to a first zone of the RAN, which includes a plurality of cells and a plurality of nodes including the first RAN node. Each of the UE identifier and the zone identifier is stored in the UE's storage device, In response to the UE returning from inactive mode or idle mode to the connected mode, or receiving a radio resource control (RRC) handover command corresponding to a handover to the second RAN node from the first RAN node or the third RAN node, the UE transmits the UE identifier and the zone identifier to the second node of the RAN. Sending artificial intelligence and machine learning (AI / ML) base models and policy parameters from the second node to the UE, wherein the AI / ML base models and policy parameters are sent based on the UE identifier and the zone identifier. Applying the aforementioned AI / ML base model and policy parameters to the operation of the UE, A method that includes this. [Claim 16] The transmission of the UE identifier and the zone identifier from the first node to the UE includes broadcasting a system information block (SIB) from the first node to the UE, or sending a dedicated message from the first node to the UE. The method according to claim 15. [Claim 17] The transmission of the UE identifier and the zone identifier from the UE to the second node includes the UE sending an RRC setup request message or an RRC restart request message during the process of returning from the inactive mode or idle mode to connected mode. The method according to claim 15. [Claim 18] The first and second nodes correspond to the first vendor, The transmission of the UE identifier and the zone identifier from the UE to the second node includes the UE transmitting an RRC reconfiguration completion message during the handover of the UE from a third node corresponding to a second vendor different from the first vendor to the second node. The method according to claim 15. [Claim 19] The transmission of the AI / ML base model and policy parameters is Depending on whether the second node is among the plurality of nodes in the first zone, the AI / ML base model and policy parameters previously generated from the storage device may be retrieved, or Depending on whether the second node is outside the first zone, this includes generating a new AI / ML base model and policy parameters. The method according to claim 15. [Claim 20] The acquisition of the previously generated AI / ML base model and policy parameters from the storage device is as follows: Retrieving previously generated AI / ML base models and policy parameters from the database associated with the first zone, or This includes retrieving the previously generated AI / ML base model and policy parameters from the storage device associated with the first node, the second node, or the third node among the plurality of nodes in the first zone. The method according to claim 19.

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