AI / ML model mobility support method, system and equipment

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 to cause the UE to receive each of an area identifier and a UE identifier from a first radio access network (RAN) node of the RAN when operating in a connected mode. The area identifier corresponds to an area of the RAN comprising a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes comprising the first RAN node. The UE stores each of the area identifier and the UE identifier in a storage device, and in response to returning from an inactive mode or an idle mode to a connected mode, or in response to receiving a radio resource control (RRC) handover command corresponding to a handover to a second RAN node from a first RAN node or a third RAN node, the UE switches the second RAN node to the first RAN node. The region identifier and the UE identifier are transmitted to the second RAN node.

Description

Technical Field

[0001] This specification relates to a method, system, device, and non-transitory computer-readable medium for automatically supporting user equipment (UE) mobility in a telecommunications system, including applying artificial intelligence and machine learning (AI / ML) models. Background Art

[0002] A telecommunications system (such as a cellular system) may include a large number of cells with service coverage provided by multiple vendors. A user equipment (UE) (such as a mobile phone) is typically capable of operating in connected, idle, and inactive modes and often transfers between various cells and multiple vendors. When operating in a given cell, the UE can access and disconnect from the radio access network (RAN) through a network node, and when it switches from the inactive or idle mode to the connected mode, it will actively connect to the RAN. Handover between cells operated by different vendors is typically implemented through handover operations. Summary of the Invention

[0003] In some embodiments, the UE includes: a memory having non-transitory instructions stored therein; and a processor coupled to the memory and configured to execute the instructions to cause the UE: when operating in the connected mode, receive each of a region identifier and a UE identifier from a first RAN node of the RAN, where the region identifier corresponds to a region of the RAN that includes a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the first RAN node; store each of the region identifier and the UE identifier in a storage device of the UE; and in response to returning to the connected mode from the inactive mode or the idle mode, or in response to receiving a radio resource control (RRC) handover command corresponding to a handover to a second RAN node from the first RAN node or a third RAN node, transmit the region identifier and the UE identifier to the second RAN node.

[0004] In some embodiments, a RAN node includes: a memory having non-transitory instructions stored therein; and a processor coupled to the memory and configured to execute the instructions to cause the RAN node to: receive a transmission from a UE as part of establishing a connected-mode session including the RAN node serving the UE; in response to the transmission including a first area identifier and a UE identifier, compare the first area identifier with a second area identifier of an area of the RAN, the area including a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the RAN node; in response to a match between the first area identifier and the second area identifier, retrieve, from a storage device, an existing AI / ML-based model associated with the UE identifier based on a previous session of one of the plurality of RAN nodes serving the UE; or, in response to a mismatch between the first area identifier and the second area identifier or the transmission lacking the first area identifier, generate a new AI / ML-based model; and transmit the corresponding existing or new AI / ML-based model, UE identifier, and second area identifier to the UE.

[0005] In some embodiments, a method of operating a RAN includes: transmitting, from a first node of the RAN to a UE, a UE identifier and an area identifier, where the area identifier corresponds to a first area of the RAN, the first area including a plurality of cells and a plurality of nodes, the plurality of nodes including the first node; storing each of the UE identifier and the area identifier in a storage device of the UE; transmitting the UE identifier and the area identifier from the UE to a second node of the RAN; transmitting an AI / ML-based model and policy parameters from the second node to the UE, where the AI / ML-based model and policy parameters are based on the UE identifier and the area identifier; and applying the AI / ML-based model and policy parameters to operations of the UE. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Aspects of the present disclosure are better understood when the following detailed description is read in conjunction with the accompanying drawings. In accordance with industry standard practice, various features are not drawn to scale. In fact, for the sake of discussion clarity, the dimensions of various features may be arbitrarily increased or decreased.

[0007] Figure 1 is a schematic diagram of a communication system according to some embodiments.

[0008] Figure 2 is a flowchart of a method for AI / ML model mobility support according to some embodiments.

[0009] Figure 3 is a flowchart of a method for AI / ML model mobility support according to some embodiments.

[0010] Figure 4 A flowchart of an AI / ML model mobility support method according to some embodiments.

[0011] Figure 5 A schematic diagram of a processor-based device according to some embodiments. DETAILED DESCRIPTION

[0012] The following disclosure provides many different embodiments or examples for implementing different features of the provided subject matter. To simplify the present disclosure, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to be limiting. For example, in the following description, forming or positioning a first feature above or on a second feature includes embodiments where the first and second features are formed or positioned in direct contact, and embodiments where additional features are formed or positioned between the first and second features such that the first and second features are indirectly in contact. Additionally, the present disclosure repeats reference numerals and / or letters in the various examples. This repetition is for simplicity and clarity and in itself does not determine the relationship between the various embodiments and / or configurations discussed.

[0013] Furthermore, spatial relative terms such as "below", "beneath", "under", "above", "on", etc. are used herein to facilitate describing the relationship between one element or feature and another (or others) element or (or others) feature, as shown in the figures. These spatial relative terms are intended to encompass different orientations of the system or object in use or operation, in addition to the orientation depicted in the figures. If the system is oriented otherwise (rotated 90 degrees or other orientation), the spatial relative descriptors used herein are to be interpreted accordingly.

[0014] In various embodiments, some or all of a method, system, device, and computer-readable medium relate to RAN operations, including: transmitting a UE identifier and a region identifier from a first node of the RAN to a UE, where the region identifier corresponds to a first region of the RAN, the first region including a plurality of cells and a plurality of nodes, the plurality of nodes including the first node; storing each of the UE identifier and the region identifier in a storage device of the UE; transmitting the UE identifier and the region identifier from the UE to a second node of the RAN; transmitting an AI / ML-based model and policy parameters from the second node to the UE, where the AI / ML-based model and policy parameters are based on the UE identifier and the region identifier; and applying the AI / ML-based model and policy parameters to operations of the UE.

[0015] By storing a region identifier and a UE identifier in the UE and by transmitting the region identifier and the UE identifier from the UE to a second node, the second node can determine or retrieve whether previously generated AI / ML-based model information is available for transmission to the UE (e.g., from a database associated with the region identifier). Thereby, the previously generated AI / ML-based model information (e.g., AI / ML-based models and policy parameters) is applied by the UE to operations in scenarios where the previously generated AI / ML-based model information would otherwise not be available, e.g., when the UE transitions from an inactive or idle mode to a connected mode, or as part of a UE handover operation. Compared to methods where the previously generated AI / ML-based model information is not available in these scenarios, the system, UE, and node are thus configured such that UE operations are more efficient by being able to fully utilize the previously generated AI / ML-based model information.

[0016] Figure 1 is a schematic diagram of a telecommunications system 100 (hereinafter simply referred to as "system 100") according to some embodiments. For ease of illustration, Figure 1 simplifications have been made.

[0017] System 100 includes a plurality of interconnected devices 102, which are configured as some or all of network 104. In various embodiments, devices 102 correspond to a combination of computing devices, computing systems, servers, server clusters, and / or multiple server clusters (also referred to as server farms or data centers in some embodiments). In some embodiments, the device 500 discussed below Figure 5 is an example of device 102.

[0018] In some embodiments, one or more of devices 102 are virtualized network components, such as virtualized network functions (VNFs), including software configured to implement one or more network functions by running on one or more hardware devices. In some embodiments, some or all of devices 102 are configured as some or all of the network function virtualization infrastructure (NFVI). Other configurations and / or types of devices 102 are within the scope of the present disclosure.

[0019] Figure 1 An example of device 102, namely device 102N, is depicted, which will be further discussed below.

[0020] In some embodiments, network 104 includes one or more radio access networks (RANs) or portions of a RAN, e.g., regions as will be further discussed below. In some embodiments, a RAN is a mobile telecommunications system that implements a radio access technology (RAT) and resides between instances of user equipment (UE) 112 (such as mobile phones, computers, etc.) and provides a connection to device 102.

[0021] In some embodiments, one or more of devices 102 are configured to perform management functions corresponding to network 104. In various embodiments, one or more of devices 102 are configured as one or more of the following: 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 supporting the operation of network 104.

[0022] In some embodiments, one or more of the interconnecting devices 102 of network 104 are configured as one or more of the following: 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 some embodiments, one or more of the interconnecting devices 102 of network 104 are configured as a backbone network or a core network (CN), a portion of a computer network that provides a path for information exchange between different LANs, WANs, etc.

[0023] In some embodiments, some of the interconnecting devices 102 of network 104 are configured as a server cluster, e.g., included in a data center. In some embodiments, 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, a GSM / EDGE RAN, a Universal Mobile Telecommunications System (UMTS) RAN (UTRAN), an Evolved Universal Terrestrial Radio Access Network (E-UTRAN), an Open RAN (O-RAN), or a Cloud RAN (C-RAN). In some embodiments, network 104 is located between user equipment (UE) 112 and one or more core networks of system 100.

[0025] In some embodiments, network 104 is some or all of the hierarchical telecommunications network (such as system 100), including one or more intermediate links between the RAN and one or more core networks, which is also referred to as the backhaul portion in some embodiments. Non-limiting examples of mobile backhaul implementations include fiber-based backhaul, wireless point-to-point backhaul, copper-based wired lines, 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 Figure 1 the depicted embodiment, network 104 includes cells 106A and 106B, which respectively include base stations 108A and 108B and antennas 110A and 110B. In some embodiments, network 104 includes a plurality of cells, which includes cells 106A and 106B, which are collectively referred to as cell 106 or are referred to as coverage area 106 in some embodiments; a plurality of base stations, which includes base stations 108A and 108B, which are collectively referred to as base station 108; and a plurality of antennas, which includes antennas 110A and 110B, which are collectively referred to as antenna 110.

[0027] In Figure 1 the depicted embodiment, a single base station 108 corresponds to a single instance of each of cell 106 and antenna 110. In various embodiments, a single base station 108 corresponds to more than one instance of cell 106 and / or more than one instance of antenna 110.

[0028] In some embodiments, base station 108 is a lattice or self-standing tower, guyed tower, monopole tower, and stealth tower (e.g., towers designed to resemble trees, cacti, water towers, signs, lamp posts, and other types of structures). In some embodiments, base station 108 is a mobile device site that supports cellular, where antennas and electronic communication equipment are typically placed on radio masts, towers, or other raised structures to create cell 106 (or adjacent cells) in the network. The raised structure typically supports one or more sets of (multiple) antennas 110, as well as transmitters / receivers, transceivers, digital signal processors, control electronics, remote radio heads (RRHs), main power and backup power, and shelters. Base station 108 has other names, such as base station transceiver, mobile phone mast, or cellular tower. In some embodiments, base station 108 is an edge device configured to wirelessly communicate with UE 112. The edge device provides an entry point into the service provider's 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 example of antenna 110 is a sector antenna (e.g., a directional microwave antenna with a sector-shaped radiation pattern), or multiple sector antennas (e.g., configured to have a full-circle coverage area 106). In some embodiments, an example of antenna 110 is a circular antenna. In some embodiments, an example of antenna 110 operates at one or more microwave or ultra-high frequency (UHF) frequencies, such as in a range from 300 megahertz (MHz) to 7.2 gigahertz (GHz). In some embodiments, an example of antenna 110 operates at one or more frequencies in a range from 24.2 GHz to 71.0 GHz.

[0030] In various embodiments, cell 106 is a three-dimensional space, the shape and size of which are based on the configuration of the corresponding base station 108 (e.g., power level) and the configuration of antenna 110 (e.g., number of sectors). In various embodiments, cell 106 has a substantially spherical, hemispherical, conical, cylindrical, circular, or elliptical disk shape, or other shape corresponding to the base station and antenna configuration. In various embodiments, one or both of the shape or size of cell 106 change over time, e.g., based on a variable base station power level and / or a variable number of active antennas and / or antenna sectors. In some embodiments, cell 106 is referred to as a macrocell, microcell, picocell, femtocell, or small cell. In some embodiments, cell 106 is referred to as an indoor small cell (IDSC).

[0031] In some embodiments, an instance of the UE 112 is a computer or computing system. In some embodiments, an instance of the UE 112 has a liquid crystal display (LCD), light emitting diode (LED), or organic light emitting diode (OLED) screen interface, such as providing a touch screen interface with digital buttons and a keyboard or a graphical user interface with physical buttons and a physical keyboard. In some embodiments, an instance of the UE 112 is connected to the Internet and interconnected with other devices. In some embodiments, an instance of the UE 112 incorporates an integrated camera, the ability to make and receive voice and video calls, video games, and global positioning system (GPS) capabilities. In some embodiments, an instance of the UE 112 executes as a virtual machine or allows third-party applications to run as containers. In some embodiments, an instance of the 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 computer, 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 video camera, or a 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, headset, or biometric device), or a smart card).

[0032] The UE 112 is configured to communicate with the base station 108 via signals transmitted to and received from the antenna 110. In some embodiments, the UE 112 is configured to operate in each of an inactive mode, an idle mode, and a connected mode. In the inactive mode, the UE 112 has no active RAN access; in the connected mode, the UE 112 is actively connected to the RAN; in the idle mode, the UE can access the RAN and be accessed from the RAN, but is not actively connected to the RAN. The key difference between the inactive mode and the idle mode is that in the inactive mode, the UE 112 is known to the network, i.e., the context of the UE (which includes its address identifier and session data) is stored both in the UE 112 and in the network; while in the idle mode, the UE 112 is not known to the network.

[0033] Figure 1 An instance of the UE 112, namely the UE 112U, is depicted which will be further discussed below.

[0034] Network 104 includes a plurality of network nodes, which are referred to as nodes or RAN nodes in some embodiments. 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 that is an instance of a device 102.

[0035] In some embodiments, a node corresponds to a device 102 configured as a central unit (CU) and one or more base stations 108 configured as distributed units (DUs). In some embodiments, the node is a next-generation RAN (NG-RAN) node, such as a gNB or NG-eNB according to the 3GPP TS 38.300 specification.

[0036] The nodes are interconnected with each other through various interfaces and are also interconnected with a network management entity (such as an EMS or an AMF). In some embodiments, the interface between a node and a core network element is referred to as an NG interface. In some embodiments, the interface between different nodes (such as NG-RAN nodes) is referred to as an Xn interface.

[0037] In Figure 1 the depicted embodiment, device 102N is a network node that includes mobility support 122N and a storage device 124N, and the storage device 124N is configured to store area and UE identifiers 126N and AI / ML model information 128N. In some embodiments, the mobility support 122N is also referred to as a mobility support algorithm 122N, and / or the AI / ML model information 128N is also referred to as AI / ML-based model and policy parameters 128N.

[0038] In Figure 1 the depicted embodiment, the device 102N including the mobility support 122N is a single instance of the device 102. In some embodiments, the device 102N including the mobility support 122N includes more than one instance of the device 102. The mobility support 122N, the area and UE identifiers 126N, and the multiple model information 128N will be further discussed below.

[0039] A region is part or all of the RAN, including a cell group and a corresponding node group, such as including device 102N. In some embodiments, the region corresponds to a geographical zone, for example, a county, which is bounded by one or more boundaries corresponding to political, physical, and / or geometric configurations. In various embodiments, the region is some, all, or a combination of a town, village, city, county, state, province, country, continent, island, peninsula, isthmus, grid portion (e.g., defined by latitude and longitude standards), circle, polygon, or other zone, etc. In some embodiments, the region is a physically limited portion of a geographical zone, for example, a building (e.g., a hotel or an office building), a building complex, a campus, an industrial park, an urban block, a shopping mall, a town center or a marketplace, a community, a town, a village, etc., some, all, or a combination thereof.

[0040] A storage device (e.g., 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 some embodiments, the storage device includes the memory 504 discussed below with respect to Figure 5 what is discussed.

[0041] In Figure 1 the depicted embodiment, storage device 124N is located on device 102N. In some embodiments, storage device 124N is located external to device 102N, for example, on one or more servers corresponding to device 102.

[0042] In some embodiments, storage device 124N is a database, which in some embodiments is also referred to as a RAN database, that is associated with the region and is thus accessible by each of the nodes in the associated region. In some embodiments, storage device 124N is a database configured to provide storage / read / write services according to service-based architecture principles.

[0043] In some embodiments, the region includes multiple instances of device 102N, each instance of which includes a corresponding mobility support 122N and a storage device 124N, and the storage device 124N is configured to store the corresponding instance of the region and UE identifier 126N and AI / ML model information 128N.

[0044] Mobility support 122N is one or more sets of instructions configured to be executed on device 102N to manage area and UE identifiers 126N and transfer them to and from an instance of UE 112 (e.g., UE 112U), and thus manage AI / ML model information 128N and transfer it to and from an instance of UE 112, each following the AI / ML model mobility support method 200 discussed below. In some embodiments, mobility support 122N is configured to run as a stand-alone program or within one or more sets of instructions. In some embodiments, mobility support 122N is configured to run on one or more devices 102 other than device 102N.

[0045] Mobility support 122N is configured to manage area and UE identifiers 126N in operation, including generating each of the area identifier in area and UE identifiers 126N and the UE identifier in area and UE identifiers 126N.

[0046] The area identifier in area and UE identifiers 126N is a data record configured to be interpreted by devices 102 and UE 112 to identify the area including device 102N. In some embodiments, mobility support 122N is configured to generate the area identifier in operation based on separate information (e.g., information received from device 102 (such as a RAN management system or function)). In some embodiments, mobility support 122N receives the area identifier from device 102 (such as a RAN management system or function).

[0047] In some embodiments, a portion of the area identifier (e.g., a subset of the bits of the data record) is configured to be interpreted by devices 102 and UE 112 to identify a given instance of device 102N. In some embodiments, this portion of the area identifier includes some or all of the address (e.g., IP address) of a given instance of device 102N. In some embodiments, this portion is referred to as an address identifier.

[0048] The UE identifier in area and UE identifiers 126N is a data record configured to be interpreted by devices 102 and UE 112 to identify a given instance of UE 112U over a given time span. In various embodiments, the given time span is a predetermined time span or a variable time span, the length of which is based on one or more criteria, such as a time threshold after the most recent activity within a given area.

[0049] Device 102 and UE 112 are configured to store the area and UE identifier 126N (and the corresponding area and UE identifier 126U discussed below) in a storage device (e.g., storage device 124N) such that the corresponding area identifier and UE identifier are essentially persistent and can be used by device 102 and UE 112 in multiple connection mode sessions involving one or both of device 102 or UE 112 in multiple instances.

[0050] In some embodiments, mobility support 122N is configured to generate a UE identifier in operation based on separate information (e.g., information received from device 102 such as a RAN management system or function). In some embodiments, mobility support 122N receives a UE identifier from device 102 (such as a RAN management system or function). In some embodiments, the UE identifier is a serving temporary mobile subscriber identity (S-TMSI).

[0051] In some embodiments, mobility support 122N is configured to transmit an instance of the area and UE identifier 126N to a given UE 112U in operation in response to receiving a transmission from UE 112U. In some embodiments, the transmission from UE 112U includes an RRC establishment request message or an RRC resume request message, which are received as part of establishing a session in which device 102N acts as a serving node for UE 112U, e.g., establishing a session resulting from a transition of UE 112U from an inactive mode or idle mode to a connection mode. In some embodiments, the transmission includes an indication of a transition of the UE from a connection mode to an inactive mode or idle mode.

[0052] In some embodiments, mobility support 122N is configured to transmit an instance of the area and UE identifier 126N to a given UE 112U in operation corresponding to completion of a connection mode session, e.g., returning UE 112U to an inactive or idle mode.

[0053] In some embodiments, the mobility support 122N is configured to store, in operation, AI / ML model information 128N associated with a region and a UE identifier 126N in one or a combination of a storage device 124N included in the device 102N or a storage device configured as a database associated with a region including the device 102N. In some embodiments, storing the AI / ML model information 128N corresponds to completing a connection mode session with a given UE 112U and storing the generated ML model and policies (e.g., AI / ML model information 128N) in the network. In some embodiments, storing the AI / ML model information 128N includes storing mobility history information (MHI) corresponding to a given UE 112U, e.g., MHI generated by the device 102N or MHI received from the UE 112U and / or other devices 102 other than the device 102N.

[0054] Examples of the AI / ML model information 128N include at least one model generated by performing one or more AI / ML algorithms on training data (e.g., MHI of the UE 112 (including the UE 112U in some embodiments)). The at least one model includes an algorithm configured to generate an output set consisting of prediction information and / or decision parameters based on an input set and is thus configured to be used by the UE 112U during one or more operations (e.g., cell reselection operations).

[0055] In some embodiments, examples of the AI / ML model information 128N include one or more policy parameters, e.g., a speed range of the UE 112U or a signal strength received from the base station 108.

[0056] In some embodiments, the mobility support 122N is further configured to transmit, in operation, an instance of the region and UE identifier 126N to a given UE 112U in response to receiving a transmission from the device 102. In some embodiments, the transmission from the device 102 includes a handover request acknowledgment from the device 102 received as part of establishing a session in which the device 102N acts as a serving node for the UE 112U after the device 102 acts as a serving node for the UE 112U.

[0057] In some embodiments, the mobility support 122N is configured to transmit, in operation, an instance of the region and UE identifier 126N included in a system information block (SIB) to a given UE 112U.

[0058] In some embodiments, in operation, the mobility support 122N is configured to respond to an instance of a received area and UE identifier 126N from a given UE 112U by comparing the received instance of the area and UE identifier 126N with a previously generated instance of the area and UE identifier 126N. In various embodiments, the previously generated instance of the area and UE identifier 126N is stored in one or a combination of a storage device 124N included in the device 102N or a storage device configured as a database associated with the area including the device 102N.

[0059] In some embodiments, an instance of the received area and UE identifier 126N is included in an RRC establishment or resume request message. In some embodiments, an instance of the received area and UE identifier 126N is included in an RRC reconfiguration complete message received as part of a handover operation.

[0060] In some embodiments, the mobility support 122N is configured to, in operation, in response to a match between an instance of the received area and UE identifier 126N and a previously generated instance of the area and UE identifier 126N, retrieve AI / ML model information 128N from one or a combination of a storage device 124N included in the device 102N or a storage device configured as a database associated with the area including the device 102N.

[0061] The previously generated instance of the area and UE identifier 126N is based on one or more previous sessions in which a node in the area (e.g., the device 102N or another device 102 in the area) served as the serving node for the UE 112U.

[0062] In some embodiments, the mobility support 122N is configured to, in operation, respond to a mismatch between an instance of the received area and UE identifier 126N and one or more previously generated instances of the area and UE identifier 126N by generating new AI / ML model information 128N. In some embodiments, the mobility support 122N is configured to respond to a transmission received from the UE 112U (e.g., including an RRC establishment request message or an RRC resume request message) by generating new AI / ML model information 128N.

[0063] In some embodiments, the mobility support 122N is configured to transmit the corresponding previously generated instance of the area and UE identifier 126N and / or the newly generated instance of the area and UE identifier 126N to the UE 112U.

[0064] UE 112U is an instance of UE 112, including mobility support 122U and a storage device 124U, which is configured to store a region and a UE identifier 126U and AI / ML model information 128U. In some embodiments, the mobility support 122U is also referred to as the mobility support algorithm 122U, and / or the AI / ML model information 128U is also referred to as AI / ML-based model and policy parameters 128U.

[0065] The region and UE identifier 126U corresponds to the region and UE identifier 126N received from the device 102N, and the AI / ML model information 128U corresponds to the AI / ML model information 128N received from the device 102N.

[0066] The mobility support 122U is one or more sets of instructions that are configured to be executed on the UE 112U to manage the region and UE identifier 126U and transmit it to an instance of the device 102 (e.g., the device 102N) and be transmitted from an instance of the device 102, and thus the AI / ML model information 128U will be received from an instance of the device 102N and in some embodiments be applied to the operation of the UE 112U, each following the AI / ML model mobility support method 200 discussed below. In some embodiments, the mobility support 122U is configured to run as an independent program or within one or more sets of instructions. In some embodiments, the mobility support 122U is also configured to run on one or more UEs 112 other than the UE 112U.

[0067] The mobility support 122U is configured to receive, in operation, an instance of the region and UE identifier 126U from an instance of the device 102N and store the instance of the region and UE identifier 126U in the storage device 124U. In some embodiments, the instance of the region and UE identifier 126U is included in the SIB received from the device 102N instance.

[0068] In some embodiments, the mobility support 122U is configured to receive, in operation, an instance of the region and UE identifier 126U included in an RRC establishment or resume request message, for example, as part of establishing a session in which the device 102N instance acts as the serving node for the UE 112U, such as establishing a session resulting from the transition of the UE 112U from an inactive or idle mode to a connected mode.

[0069] In some embodiments, the mobility support 122U is configured to receive, in operation, an instance of the region and UE identifier 126U included in an RRC reconfiguration message, which is received as part of completing a connected mode session with the device 102N instance.

[0070] In some embodiments, the mobility support 122U is configured to receive, in operation, an instance of a region and UE identifier 126U included in an RRC reconfiguration message, which is received from an instance of the device 102N as part of a handover operation, where the device 102N acts as a serving node for the UE 112U after acting as a serving node for the UE 112U to another device 102.

[0071] In some embodiments, the mobility support 122U is configured to receive, in operation, an instance of a region and UE identifier 126U included in an RRC reconfiguration message, which is received from the device 102 as part of a handover operation, where the device 102 acts as a serving node for the UE 112U before acting as a serving node for the UE 112U to the device 102N. In some embodiments, the mobility support 122U receives, from the device 102, an instance of a region and UE identifier 126U included in a handover command, which is based on a handover request confirmation sent from the device 102N and includes an instance of a region and UE identifier 126U in, for example, an SIB. In some embodiments, the device 102 corresponds to a different vendor than the vendor corresponding to the device 102N.

[0072] The mobility support 122U is configured to store, in operation, the received region and UE identifier 126U in a storage device 124U. In some embodiments, the mobility support 122U stores the received region and UE identifier 126U before transitioning from a connected mode to an inactive mode or an idle mode and retains the received region and UE identifier 126U in the storage device 124U during subsequent transitions between the modes.

[0073] In some embodiments, the mobility support 122U is configured to transmit, in operation, the stored region and UE identifier 126U to a second instance of the device 102N in response to returning from an inactive mode or an idle mode to a connected mode or in response to receiving an RRC handover command from a device 102 (e.g., a device 102 corresponding to a different vendor than the vendor corresponding to the instance of the device 102N) different from the instance of the device 102N.

[0074] In some embodiments, the mobility support 122U is configured to respond to returning from an inactive mode or an idle mode to a connected mode by transmitting the stored region and UE identifier 126U in an RRC establishment request message or an RRC resume request message.

[0075] In some embodiments, mobility support 122U is configured to respond to receiving an RRC handover command by transmitting stored area and UE identifier 126U in the RRC reconfiguration complete message. In some embodiments, mobility support 122U obtains the area and UE identifier 126U from an instance of a plurality of stored area and UE identifiers 126U.

[0076] In some embodiments, mobility support 122U is configured to receive AI / ML model information 128U from a second instance of device 102N during operation and apply the received AI / ML model information 128U to the operation of UE 112U, such as an idle mode cell reselection operation.

[0077] In various embodiments, the AI / ML model information 128U corresponds to AI / ML model information 128N previously generated and retrieved by a second instance of device 102N, or corresponds to newly generated AI / ML model information 128N by a second instance of device 102N, as discussed above.

[0078] In some embodiments, mobility support 122U is configured to delete, during operation, one or both of the stored area identifier or UE identifier among the plurality of stored area and UE identifiers 126U based on one or more deletion criteria (e.g., after a preconfigured timer expires), and / or by deleting the oldest identifier when a predetermined maximum number of identifiers is reached, or in response to receiving an explicit deletion command or other deletion indication from an instance of device 102N.

[0079] System 100 configured as discussed above, including one or more instances of device 102N and / or one or more instances of UE 112U, is thus configured to perform some or all of the following: transmit area and UE identifier 126N from a first instance of device 102N to UE 112U, where the area identifier corresponds to a first area of network 104, the first area including cell 106 and device 102 including the first instance of device 102N; store area and UE identifier 126U in storage device 124U; transmit area and UE identifier 126U from UE 112U to a second instance of device 102N; send AI / ML model information 128N from a second instance of device 102N to UE 112U, where the AI / ML model information 128N is based on area and UE identifier 126N; and apply AI / ML model information 128U to the operation of UE 112U.

[0080] By storing the area and UE identifier 126U and transferring the area and UE identifier 126U from UE 112U to a second instance of device 102N, the second instance of device 102N can determine whether previously generated AI / ML model information 128N is available for transfer to UE 112U. Thereby, the previously generated AI / ML model information 128N can be used by UE 112U for operations in scenarios where previously generated AI / ML-based model information would otherwise be unavailable, such as when UE 112U transitions from an inactive or idle mode to a connected mode, or as part of a handover operation of UE 112U. Compared to methods where previously generated AI / ML-based model information is unavailable in these scenarios, the system 100, UE 112U, and device 102N are thus configured such that UE operations are more efficient by being able to utilize the previously generated AI / ML model information 128N.

[0081] Figure 2 is a flowchart of an AI / ML model mobility support method 200 according to some embodiments. The AI / ML model mobility support method 200 (also referred to as method 200 or method of operating the RAN in some embodiments) is operable on a telecommunications system (e.g., the telecommunications system 100 discussed above with respect to Figure 1 ).

[0082] Additional operations may be performed before, during, between, and / or after the operations of method 200 depicted in Figure 2 , and some other operations may be described only briefly herein. In some embodiments, other operation sequences of method 200 are within the scope of the present disclosure. In some embodiments, one or more operations of method 200 are not performed.

[0083] In some embodiments, some or all of the operations of method 200 are included in another method, such as a method of operating a telecommunications system. In some embodiments, the operations of method 200 discussed below are repeated, such as as part of operating a telecommunications system.

[0084] In some embodiments, some or all of the operations of method 200 discussed below can be automatically performed, such as by device 102N including mobility support 122N and / or UE 112 including mobility support 122U (each of which has been discussed above with respect to Figure 1 ) and / or by using the processing circuitry 502 discussed below with respect to Figure 5 .

[0085] The operations of method 200 will be discussed below with reference to various features of system 100, which have also been discussed above with respect to Figure 1 .

[0086] Figure 3 and Figure 4 depicts non - limiting examples that illustrate performing some or all of the operations of method 200 using embodiments of system 100, as discussed below.

[0087] In some embodiments, at operation 210, the area and UE identifier are transmitted from a first RAN node to the UE. Transmitting the area and UE identifier from the first RAN node to the UE includes transmitting the area and UE identifier 126N from a first instance of device 102N to UE 112U, as discussed above.

[0088] In some embodiments, at operation 220, AI / ML model information is stored based on the area and UE identifier. Storing AI / ML model information based on the area and UE identifier includes using device 102N to store the AI / ML model information 128N in one or a combination of a storage device 124N included in device 102N or configured to be associated with the area including device 102N, as discussed above.

[0089] In some embodiments, at operation 230, the area and UE identifier are stored in a UE storage device. Storing the area and UE identifier in the UE storage device includes using UE 112U to store the area and UE identifier 126U in storage device 124U, as discussed above.

[0090] In some embodiments, at operation 240, the area and UE identifier are transmitted from the UE to a second RAN node. Transmitting the area and UE identifier from the UE to the second RAN node includes transmitting the area and UE identifier 126U from UE 112U to a second instance of device 102N, as discussed above.

[0091] In some embodiments, at operation 250, AI / ML model information is retrieved or generated based on the area and UE identifier received at the second RAN node. Retrieving or generating AI / ML model information based on the area and UE identifier received at the second RAN node includes using a second instance of device 102N to retrieve or generate the AI / ML model information 128N, as discussed above.

[0092] In some embodiments, at operation 260, the AI / ML model information is transmitted from the second RAN node to the UE. Transmitting the AI / ML model information from the second RAN node to the UE includes transmitting the AI / ML model information 128N from a second instance of device 102N to UE 112U, as discussed above.

[0093] In some embodiments, at operation 270, the operation of applying AI / ML information to the UE. The operation of applying AI / ML information to the UE includes the operation of applying AI / ML model information 128U to UE 112U, as discussed above.

[0094] In some embodiments, at operation 280, the stored area identifier and / or UE identifier are deleted based on one or more deletion criteria. Deleting the stored area identifier and / or UE identifier based on one or more deletion criteria includes using UE 112U to delete some or all instances of the stored area and UE identifier 126U, as discussed above.

[0095] By performing some or all of the operations of method 200, the system (e.g., system 100) automatically performs some or all of the following: transmitting a UE identifier and an area identifier from a first node of the RAN to the UE, where the area identifier corresponds to a first area of the RAN, the first area including a plurality of cells and a plurality of nodes, the plurality of nodes including the first node; storing each of the UE identifier and the area identifier in a storage device of the UE; transmitting the UE identifier and the area identifier from the UE to a second node of the RAN; sending an AI / ML-based model and policy parameters from the second node to the UE, where the AI / ML-based model and policy parameters are based on the UE identifier and the area identifier; and applying the AI / ML-based model and policy parameters to the operation of the UE, thereby enabling the benefits discussed above with respect to system 100.

[0096] Figure 3 is a flowchart of an AI / ML model mobility support method 300 according to some embodiments. The AI / ML model mobility support method 300 (also referred to as method 300 or method of operating the RAN in some embodiments) is a non-limiting example of some or all of method 200 discussed above.

[0097] Method 300 corresponds to a scenario in which an instance of UE 112U transitions into and out of a connection 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 area and UE identifier 128U.

[0098] In Figure 3In the embodiment depicted, in operation 210, a first instance of device 102N transmits a region and UE identifier 128N to UE 112U, and UE 112U transitions from a connected mode to an inactive mode or an idle mode. In operation 230, UE 112U stores the region and UE identifier 128N as region and UE identifier 128U. In operation 220, the first instance of device 102N stores AI / ML model information 128N in the database of device 102. In operation 240, UE 112U returns to the connected mode and transmits the region and UE identifier 128U to a second instance of device 102N. In operation 250, based on the received region and UE identifier 128N, the second instance of device 102N retrieves AI / ML model information 128N from the database of device 102. In operations 260 and 270, the second instance of device 102N transmits the retrieved AI / ML model information 128N to UE 112U, and UE 112U applies the AI / ML model information 128N as AI / ML model information 128U to one or more operations.

[0099] By performing some or all of the operations of method 200 according to the non-limiting example of method 300, the benefits discussed above with respect to Figure 1 and Figure 2 can be achieved.

[0100] Figure 4 is a flowchart of an AI / ML model mobility support method 400 according to some embodiments. The AI / ML model mobility support method 400 (also referred to as method 400 or the method of operating RAN in some embodiments) is a non-limiting example of some or all of method 200 discussed above.

[0101] Method 400 corresponds to a scenario where an instance of UE 112U is included in a handover operation between two instances of device 102N, and AI / ML model information 128N is retrieved from the database on device 102 based on the stored region and UE identifier 128U.

[0102] In Figure 4In the embodiments depicted, in operations 210 through 230, UE 112U stores a region and UE identifier 128U based on a previous connection mode session with an instance (not depicted) of device 102N, where AI / ML model information 128N has been stored in a database on device 102. A handover operation from a first instance of device 102N to a second instance of device 102N is then performed. In operation 240, UE 112U completes the handover operation by transmitting an RRC reconfiguration complete message to the second instance of device 102N that includes the region and UE identifier 128U (corresponding to the stored region and UE identifier 126U). In operation 250, based on the received region and UE identifier 128N, the second instance of device 102N retrieves AI / ML model information 128N from the database on device 102. In operations 260 and 270, the second instance of device 102N transmits the retrieved AI / ML model information 128N to UE 112U, which applies the AI / ML model information 128N as AI / ML model information 128U in one or more operations.

[0103] By performing some or all of the operations of method 200 according to the non - limiting example of method 400, the benefits discussed above with respect to Figure 1 and Figure 2 can be realized.

[0104] Figure 5 is a functional block diagram of a computer or processor - based device 500 on or through which embodiments are implemented.

[0105] The processor - based device 500 is programmed to facilitate the automatic generation and / or modification of a cell reselection policy, as described herein, and includes, for example, a bus 508, processing circuitry 502 (also referred to as processor 502 in some embodiments), and a memory 504 component.

[0106] In some embodiments, 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 circuitry 502 is connected to the bus 508 to obtain instructions for execution and process information stored in, for example, the memory 504. In some embodiments, the processing circuitry 502 is also accompanied by one or more specialized components for performing certain 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 (such as sound) in real time independently of the processing circuitry 502. Similarly, an ASIC can be configured to perform specialized functions that are not easily performed by a more general-purpose processor. Other specialized components for assisting 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 specialized computer chips.

[0107] In one or more embodiments, the processing circuitry (or processors) 502 performs a set of operations on information specified by a set of instructions related to a cell reselection policy stored in the memory 504, for example, corresponding to the mobility support algorithm 516 for mobility support 122N or 122U discussed above with respect to Figure 1 and Figure 2 Execution of these instructions causes the processor to perform the specified functions.

[0108] The processing circuitry 502 and its accompanying components are connected to the memory 504 via the bus 508. The memory 504 includes one or more memories for storing executable instructions, such as static memories (e.g., ROM, CD-ROM, etc.) and dynamic memories (e.g., RAM, disk, writable optical disc, etc.), which, when executed, perform the operations described herein to facilitate automated network configuration. In some embodiments, the memory 504 also stores data associated with or generated by the execution of the operations, such as area and UE identifiers 520 corresponding to area and UE identifiers 126N or 126U, and AI / ML model information 522 corresponding to AI / ML model information 128U or 128N, each of which is discussed above with respect to Figure 1 and Figure 2 and

[0109] In one or more embodiments, the memory 504 (such as random access memory (RAM) or any other dynamic storage device) stores information, which includes processor instructions for facilitating the implementation of network applications. Dynamic memory allows the information stored therein to be changed. RAM allows information units stored at locations called memory addresses to be stored and retrieved independently of the information at adjacent addresses. The memory 504 is also used by the processing circuitry 502 to store temporary values during the execution of the processor instructions. In various embodiments, the memory 504 includes read-only memory (ROM) or any other static storage device coupled to the bus 508 for storing static information (including instructions), which cannot be changed by the processing circuitry 502. Some memories consist of volatile memory, and the information stored therein is lost when power is turned off. In some embodiments, the memory 504 includes non-volatile (persistent) storage devices for storing information (including instructions), such as magnetic disks, optical disks, or flash memory cards, and this information persists even when the device 500 is turned off or otherwise powered down.

[0110] As used herein, the term "computer-readable medium" refers to any medium that participates in providing information (including instructions 506 for execution) to the processing circuitry 502. Such media take many forms, including but 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-ROM, CDRW, DVD, other optical media, punch cards, paper tapes, optical mark sheets, other physical media with hole patterns or other optically recognizable marks, RAM, PROM, EPROM, FLASH-EPROM, EEPROM, flash memory, other memory chips or cartridges, or other media from which a computer reads. The term "computer-readable storage medium" is used herein to refer to computer-readable media.

[0111] The instructions 506 also include a user interface 518, and one or more sets of the instructions are configured to allow a user to effectively operate and control the device 500. In some embodiments, the user interface 518 is configured to operate through one or more layers, including a human-machine interface (HMI) that interfaces the machine with physical input hardware (such as a keyboard, mouse, or gamepad) and output hardware (such as a computer monitor, speakers, printer, and other suitable user interfaces).

[0112] In some embodiments, the UE includes: a memory having non-transitory instructions stored therein; and a processor coupled to the memory and configured to execute the instructions to cause the UE to: when operating in a connected mode, receive each of a region identifier and a UE identifier from a first RAN node of the RAN, where the region identifier corresponds to a region of the RAN that includes a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the first RAN node; store each of the region identifier and the UE identifier in a storage device of the UE; and in response to returning to the connected mode from an inactive mode or an idle mode, or in response to receiving an RRC handover command corresponding to a handover to a second RAN node from the first RAN node or a third RAN node, transmit the region identifier and the UE identifier to the second RAN node. In some embodiments, the instructions are executable by the processor to cause the UE to further: receive an AI / ML-based model and / or policy parameters from the second RAN node, and apply the AI / ML-based model and / or policy parameters to the operation of the UE, where the AI / ML-based model and / or policy parameters include: a previously generated AI / ML-based model and / or policy parameters corresponding to the second RAN node and located in the region corresponding to the stored region identifier, or a newly generated AI / ML-based model and / or policy parameters corresponding to the second RAN node and located in a region other than the region corresponding to the stored region identifier. In some embodiments, the instructions are executable by the processor to cause the UE to, in response to returning to the connected mode from an inactive mode or an idle mode, transmit the region identifier and the UE identifier to the second RAN node included in an RRC establishment request message or an RRC resume request message, and in response to receiving an RRC handover command from the first RAN node or a third RAN node, transmit the region identifier and the UE identifier to the second RAN node included in an RRC reconfiguration complete message. In some embodiments, the instructions are executable by the processor to cause the UE, in response to receiving an RRC handover command from the first RAN node or a third RAN node, further compare the region identifier obtained from the system information broadcast of the second RAN node with a plurality of stored region identifiers, and obtain the UE identifier corresponding to the region identifier from a plurality of stored UE identifiers. In some embodiments, the instructions are executable by the processor to cause the UE to receive, store, and transmit a region identifier including an address identifier of the first RAN node. In some embodiments, the instructions are executable by the processor to cause the UE to receive a new UE identifier and a new region identifier from a third RAN node, thereby indicating that the third RAN node corresponds to a first vendor that is different from a second vendor corresponding to the first RAN node and the second RAN node.In some embodiments, the instructions are executable by a processor to further cause the UE to delete one or both of the stored area identifier or the UE identifier based on one or more deletion criteria or in response to an indication from a first RAN node, a second RAN node, or another RAN node.

[0113] In some embodiments, the RAN node includes: a memory having non-transitory instructions stored thereon, and a processor coupled to the memory and configured to execute the instructions to cause the RAN node to: receive a transmission from a UE as part of establishing a connected mode session that includes the RAN node serving the UE; compare a first area identifier with a second area identifier of an area of the RAN, the area including a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the RAN node, in response to a transmission including the first area identifier and the UE identifier; retrieve an existing artificial intelligence and machine learning (AI / ML)-based model associated with the UE identifier from a storage device based on a previous session of the RAN node among the plurality of RAN nodes serving the UE, in response to a match between the first area identifier and the second area identifier; or generate a new AI / ML-based model and transmit the corresponding existing AI / ML-based model or new AI / ML-based model, the UE identifier, and the second area identifier to the UE, in response to a mismatch between the first area identifier and the second area identifier or a lack of the first area identifier in the transmission. In some embodiments, the instructions are executable by the processor to cause the RAN node to receive the first area identifier and the UE identifier included in a transmission including an RRC establishment request message or an RRC resume request message as part of establishing a connected mode session. In some embodiments, the RAN corresponds to a first vendor, and the instructions are executable by the processor to cause the RAN node to: establish a connected mode session as part of the UE switching from a second vendor different from the first vendor; and receive the first area identifier and the UE identifier included in a transmission including an RRC reconfiguration complete message. In some embodiments, the instructions are executable by the processor to cause the RAN node to retrieve an AI / ML-based model from a storage device including a database associated with an area including a plurality of RAN nodes, the plurality of RAN nodes including the RAN node. In some embodiments, the RAN node is a first RAN node among a plurality of RAN nodes, and the instructions are executable by the processor to cause the first RAN node to receive a first area identifier including an address identifier of a second RAN node among the plurality of RAN nodes and retrieve an AI / ML-based model from a storage device associated with the second RAN node. In some embodiments, the instructions are executable by the processor to cause the RAN node to transmit policy parameters corresponding to an existing AI / ML-based model or a new AI / ML-based model to the UE. In some embodiments, the instructions are executable by the processor to further cause the RAN node to store the corresponding existing AI / ML-based model or new AI / ML-based model as part of completing the connected mode session.

[0114] In some embodiments, a method of operating a RAN includes: transmitting a UE identifier and a region identifier from a first node of the RAN to a UE, where the region identifier corresponds to a first region of the RAN, the first region including a plurality of cells and a plurality of nodes, the plurality of nodes including the first node; storing each of the UE identifier and the region identifier in a storage device of the UE; transmitting the UE identifier and the region identifier from the UE to a second node of the RAN; sending an AI / ML-based model and policy parameters from the second node to the UE, where the AI / ML-based model and policy parameters are based on the UE identifier and the region identifier; and applying the AI / ML-based model and policy parameters to the operation of the UE. In some embodiments, transmitting the UE identifier and the region identifier from the first node to the UE includes: broadcasting a SIB from the first node to the UE, or sending a dedicated message from the first node to the UE. In some embodiments, transmitting the UE identifier and the region identifier from the UE to the second node includes: as part of a transition from an inactive mode or an idle mode to a connected mode, the UE transmitting an RRC establishment request message or an RRC resume request message. In some embodiments, the first node and the second node correspond to a first vendor, and transmitting the UE identifier and the region identifier from the UE to the second node includes: as part of a handover of the UE from a third node corresponding to a second vendor to the second node, the UE transmitting an RRC reconfiguration complete message, the second vendor being different from the first vendor. In some embodiments, transmitting the AI / ML-based model and policy parameters includes: retrieving a previously generated AI / ML-based model and policy parameters from a storage device in response to the second node being located among the plurality of nodes in the first region; or generating new AI / ML-based model and policy parameters in response to the second node being located outside the first region. In some embodiments, retrieving a previously generated AI / ML-based model and policy parameters from a storage device includes: retrieving a previously generated AI / ML-based model and policy parameters from a database associated with the first region, or retrieving a previously generated AI / ML-based model and policy parameters from a storage device associated with the first node, the second node, or the third node among the plurality of nodes in the first region.

[0115] The foregoing has outlined features of several embodiments so that those skilled in the art may better understand the various aspects of the present disclosure. Those skilled in the art will recognize that they can readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and / or achieving the same advantages as the embodiments introduced herein. Those skilled in the art will also recognize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions, and alterations thereto without departing from the spirit and scope of the present disclosure.

Claims

1. A user equipment (UE) comprising: a memory having non-transitory instructions stored therein; and a processor coupled to the memory and configured to execute the instructions to cause the UE to: when operating in a connected mode, receive each of a region identifier and a UE identifier from a first RAN node of a radio access network (RAN), wherein the region identifier corresponds to a region of the RAN, the region including a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the first RAN node; store each of the region identifier and the UE identifier in a storage device of the UE; and in response to: returning from an inactive mode or an 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 a third RAN node, transmit the region identifier and the UE identifier to a second RAN node.

2. The UE according to claim 1, wherein the instructions are executable by the processor to cause the UE to further: receive an artificial intelligence and machine learning (AI / ML) based model and / or policy parameters from the second RAN node; and apply the AI / ML based model and / or policy parameters to the operation of the UE, wherein the AI / ML based model and / or policy parameters include: previously generated AI / ML based model and / or policy parameters corresponding to the second RAN node and located in the region corresponding to the stored region identifier; or newly generated AI / ML based model and / or policy parameters corresponding to the second RAN node and located in a region other than the region corresponding to the stored region identifier.

3. The UE according to claim 1, wherein the instructions are executable by the processor to cause the UE to transmit the region identifier and the UE identifier to the second RAN node, the second RAN node being included in: an RRC establishment request message or an RRC resume request message when responding to a return from the inactive mode or the idle mode to the connected mode; and an RRC reconfiguration complete message when responding to receiving the RRC handover command from the first RAN node or the third RAN node.

4. The UE according to claim 1, wherein the instructions are executable by the processor to cause the UE, in response to receiving the RRC handover command from the first RAN node or the third RAN node, to further: compare the region identifier obtained from a system information broadcast of the second RAN node with a plurality of stored region identifiers, and obtain the UE identifier corresponding to the region identifier from a plurality of stored UE identifiers.

5. The UE according to claim 1, wherein the instruction is executable by the processor to cause the UE to receive, store, and transmit the area identifier including the address identifier of the first RAN node.

6. The UE according to claim 1, wherein the instruction is executable by the processor to cause the UE to receive a new area identifier and a new UE identifier from the third RAN node, thereby indicating that the third RAN node corresponds to a first vendor, the first vendor being different from a second vendor corresponding to the first RAN node and the second RAN node.

7. The UE according to claim 1, wherein the instruction is executable by the processor to further cause the UE to delete one or both of the stored area identifier or the UE identifier based on one or more deletion criteria or in response to an indication received from the first RAN node, the second RAN node, or another RAN node.

8. A radio access network (RAN) node, comprising: a memory having non-transitory instructions stored therein; and a processor coupled to the memory and configured to execute the instructions to cause the RAN node to: receive a transmission from the UE as part of establishing a connection mode session including the RAN node serving the user equipment (UE); compare the first area identifier with a second area identifier of an area of the RAN in response to the transmission including the first area identifier and the UE identifier, the area including a plurality of cells and a plurality of RAN nodes, the plurality of RAN nodes including the RAN node; retrieve, in response to a match between the first area identifier and the second area identifier, an existing artificial intelligence and machine learning (AI / ML)-based model associated with the UE identifier from a storage device based on a previous session including one of the plurality of RAN nodes serving the UE; or generate a new AI / ML-based model in response to a mismatch between the first area identifier and the second area identifier or the transmission lacking the first area identifier; and transmit the corresponding existing AI / ML-based model or the new AI / ML-based model, the UE identifier, and the second area identifier to the UE.

9. The RAN node according to claim 8, wherein the instruction is executable by the processor to cause the RAN node to receive the first area identifier and the UE identifier included in the transmission, the transmission including a radio resource control (RRC) establishment request message or an RRC resume request message as part of establishing the connection mode session.

10. The RAN node according to claim 8, wherein the RAN corresponds to a first vendor, and the instruction is executable by the processor to cause the RAN node to: As part of the UE's handover from a second vendor different from the first vendor, establish the connected-mode session, and Receive the first area identifier and the UE identifier included in the transmission, the transmission including an RRC reconfiguration complete message.

11. The RAN node according to claim 8, wherein the instruction is executable by the processor to cause the RAN node to retrieve the AI / ML-based model from the storage device, the storage device including a database associated with the area including the plurality of RAN nodes, the plurality of RAN nodes including the RAN node.

12. The RAN node according to claim 8, wherein:[[]] The RAN node is a first RAN node among the plurality of RAN nodes, and The instruction is executable by the processor to cause the first RAN node to:[[]] Receive the first area identifier including the address identifier of a second RAN node among the plurality of RAN nodes; and Retrieve the AI / ML-based model from the storage device associated with the second RAN node.

13. The RAN node according to claim 8, wherein the instruction is executable by the processor to cause the RAN node to transmit policy parameters corresponding to the existing AI / ML-based model or the new AI / ML-based model to the UE.

14. The RAN node according to claim 8, wherein the instruction is executable by the processor to further cause the RAN node to store the corresponding existing AI / ML-based model or new AI / ML-based model as part of completing the connected-mode session.

15. A method of operating a radio access network (RAN), the method comprising:[[]] Transmit a UE identifier and an area identifier from a first node of the RAN to a user equipment (UE), wherein the area identifier corresponds to a first area of the RAN, the first area including a plurality of cells and a plurality of nodes, the plurality of nodes including the first node; Store each of the UE identifier and the area identifier in a storage device of the UE; Transmit the UE identifier and the area identifier from the UE to a second node of the RAN; Send an artificial intelligence and machine learning (AI / ML)-based model and policy parameters from the second node to the UE, wherein the AI / ML-based model and policy parameters are based on the UE identifier and the area identifier; And Apply the AI / ML-based model and policy parameters to the operation of the UE.

16. The method according to claim 15, wherein transmitting the UE identifier and the area identifier from the first node to the UE comprises: Broadcast a system information block (SIB) from the first node to the UE, or send a dedicated message from the first node to the UE.

17. The method according to claim 15, wherein transmitting the UE identifier and the area identifier from the UE to the second node comprises: As part of the transition from the inactive mode or idle mode to the connected mode, the UE transmits a radio resource control (RRC) establishment request message or an RRC resume request message.

18. The method according to claim 15, wherein:[[]] The first node and the second node correspond to a first vendor, and transmitting the UE identifier and the area identifier from the UE to the second node includes: as part of a handover of the UE from a third node corresponding to a second vendor to the second node, the UE transmits a Radio Resource Control (RRC) reconfiguration complete message, the second vendor being different from the first vendor.

19. The method according to claim 15, wherein transmitting the AI / ML-based model and policy parameters includes: retrieving a previously generated AI / ML-based model and policy parameters from a storage device in response to the second node being among the plurality of nodes in the first area; or generating new AI / ML-based model and policy parameters in response to the second node being outside the first area.

20. The method according to claim 19, wherein retrieving the previously generated AI / ML-based model and policy parameters from the storage device includes: retrieving the previously generated AI / ML-based model and policy parameters from a database associated with the first area, or retrieving the previously generated AI / ML-based 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 area.

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