AI / ML model mobility support method, system, and device

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 methods, systems, devices, and non-transitory computer-readable media directed to automated support of user equipment (UE) mobility in telecommunications systems involving the application of artificial intelligence and machine learning (AI / ML) models. [Background technology]

[0002] Telecommunications, e.g., cellular systems, may include multiple cells with service coverage provided by multiple vendors. User equipment (UE), e.g., mobile phones, can typically operate in connected, idle, and inactive modes and are often transferred between different cells and multiple vendors. When operating within a given cell, the UE accesses and is accessed by a radio access network (RAN) through a network node, and becomes actively connected to the RAN when it switches from an inactive or idle mode to a connected mode. Switching between cells operated by different vendors is typically accomplished by a handover operation. Summary of the Invention

[0003] In an embodiment, a UE includes a memory having non-transitory instructions stored therein; and a processor, coupled to the memory and configured to execute the instructions, where execution of the instructions causes the processor to: receive, while operating in a connected mode, a zone identifier and a UE identifier from a first RAN node of a RAN, where 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 each of the zone identifiers and the UE identifier in a storage device of the UE; and transmit the zone identifier and the UE identifier to the second RAN node in response to returning to the connected mode from an inactive mode or an idle mode or in response to receiving a Radio Resource Control (RRC) handover command from the first RAN node or a third RAN node corresponding to a handover to the second RAN node.

[0004] In one embodiment, 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, causing the RAN node to: receive a transmission from a UE in the course of establishing a connected mode session including a RAN node serving the UE; and, in response to the transmission including a first zone identifier and a UE identifier, compare the first zone identifier to a second zone identifier of a zone of the RAN including a plurality of RAN nodes, including a plurality of cells and the RAN node. In response to a match between the first and second zone identifiers, the RAN node retrieves from a storage device an existing AI / ML-based model associated with the UE identifier based on a previous session including one of the plurality of RAN nodes serving the UE, or generates a new AI / ML-based model in response to a mismatch between the first and second zone identifiers or a transmission lacking the first zone identifier. The RAN node transmits the corresponding existing or new AI / ML-based model, the UE identifier, and the second zone identifier to the UE.

[0005] In an embodiment, a method of operating a RAN includes transmitting a UE identifier and a zone identifier from a first node of the RAN to a UE, the zone identifier corresponding to a first zone of the RAN including 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-based model and policy parameters from the second node to the UE, the AI / ML-based model and policy parameters based on the UE identifier and the zone identifier; and applying the AI / ML-based model and policy parameters to operation of the UE.

[0006] Aspects of the present disclosure are best understood from the following detailed description when read in conjunction with the accompanying drawings. In accordance with common practice in the industry, various features have not been drawn to scale. In fact, the dimensions of various features have been arbitrarily expanded or reduced for clarity of discussion. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a diagram of a communication system, according to an embodiment.

[0008] [Figure 2] 1 is a flowchart of an AI / ML model mobility support method, according to an embodiment.

[0009] [Figure 3] 1 is a flowchart of an AI / ML model mobility support method, according to an embodiment.

[0010] [Figure 4] 1 is a flowchart of an AI / ML model mobility support method, according to an embodiment.

[0011] [Figure 5]FIG. 1 is a diagram of a processor-based device, according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] The following disclosure provides many different embodiments or examples for implementing various features of the provided subject matter. To simplify the 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, the formation or location 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 with each other, and also includes embodiments in which an additional feature is formed or arranged between the first and second features such that the first and second features are in indirect contact with each other. Additionally, the disclosure repeats reference numerals and / or letters in various examples. This repetition is for the purposes of brevity and clarity and does not, in itself, dictate a relationship between the various embodiments and / or configurations discussed.

[0013] Additionally, spatially relative terms such as "beneath," "below," "lower," "above," and "upper" are used herein for ease of description to describe the relationship of one element or feature to another element(s) or feature(s), as shown in the figures. Spatially relative terms are intended to encompass various orientations of a system or object in use or operation in addition to the orientation shown in the figures. Systems may be oriented in other directions (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

[0014] In various embodiments, some or all of the methods, systems, devices, and computer-readable media are directed to RAN operations including: transmitting a UE identifier and a zone identifier from a first node of a RAN to a UE, the zone identifier corresponding to a first zone of the RAN including a plurality of cells and a plurality of nodes including the first node; storing each of the UE and zone identifiers in a storage device of the UE; transmitting the UE and zone 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, the AI / ML-based model and policy parameters based on the UE identifier and the zone identifier; and applying the AI / ML-based model and policy parameters to operation of the UE.

[0015] By storing the zone and UE identifier in the UE and transmitting the zone and UE identifier from the UE to the second node, the second node can determine or obtain, for example, from a database associated with the zone identifier, whether previously generated AI / ML-based model information is available to be transmitted to the UE. Thus, in situations where the previously generated AI / ML-based model information is unavailable, such as during a UE transition from an inactive or idle mode to a connected mode or during a UE handover operation, the previously generated AI / ML-based model information, e.g., AI / ML-based model and policy parameters, to be applied to operation by the UE becomes available. Thus, compared to approaches where the previously generated AI / ML-based model information is unavailable in such situations, the system, UE, and node are configured to utilize the previously generated AI / ML-based model information to enable more efficient UE operation.

[0016] Figure 1 is a diagram of a telecommunications system 100 (hereinafter "system 100") according to one embodiment. Figure 1 is simplified for illustrative purposes.

[0017] System 100 includes multiple interconnected devices 102 configured as part or all of network 104. In various embodiments, device 102 represents a computing device, a computing system, a server, a server cluster, and / or a combination of multiple server clusters, also referred to in some embodiments as a server farm or data center. In some embodiments, device 500, described below with reference to FIG. 5, is one embodiment of device 102.

[0018] In one embodiment, one or more of the devices 102 are virtualized network components, e.g., virtualized network functions (VNFs), that include software configured to implement one or more network functions by running 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 functions virtualization infrastructure (NFVI). Other configurations and / or types of devices 102 are within the scope of this disclosure.

[0019] FIG. 1 shows device 102N, which is an instance of device 102, which is discussed further below.

[0020] In one embodiment, the network 104 includes one or more radio access networks (RANs), or portions of a RAN, such as zones, discussed further below. In one embodiment, the RAN is a mobile telecommunications system that implements a radio access technology (RAT) and exists between instances of user equipment (UE) 112, such as mobile phones or computers, to provide connectivity to the devices 102.

[0021] In an 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 operations 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 in support of 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 pathway 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 server clusters, for example, contained in a data center. In one embodiment, the server clusters are part of a cloud computing environment.

[0024] In one embodiment, the 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 one embodiment, the network 104 resides between the UE 112 and one or more core networks of the system 100.

[0025] In one embodiment, network 104 is a hierarchical telecommunications network, such as part or all of system 100, that includes one or more intermediate links, also referred to in one embodiment as backhaul portions, 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 one embodiment, backhaul refers to the side of the network that communicates with the global Internet.

[0026] 1, network 104 includes cells 106A and 106B, which include respective base stations 108A and 108B and respective antennas 110A and 110B. In one embodiment, network 104 includes multiple cells, collectively referred to as cells 106, including cells 106A and 106B, or in one embodiment, referred to as coverage area 106; multiple base stations, collectively referred to as base stations 108, including base stations 108A and 108B; and multiple antennas, collectively referred to as antennas 110, including antennas 110A and 110B.

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

[0028] In one embodiment, the base station 108 is a lattice or freestanding tower, a guy tower, a monopole tower, and a hidden tower (e.g., a tower designed to resemble a tree, a cactus, a water tower, a sign, a light pole, and other types of structures). In one embodiment, the base station 108 is a cellular-enabled mobile device site where antennas and electronic communication equipment are typically located on a radio mast, tower, or other elevated structure to create a cell 106 (or adjacent cells) in the network. The elevated structure typically supports antenna(s) 110 and one or more sets of transmitters / receivers, transceivers, digital signal processors, control electronics, remote radio heads (RRHs), primary and backup power sources, and shelters. The base station 108 is known by other names, such as a base transceiver station, a cellular phone mast, or a cell tower. In one embodiment, the base station 108 is an edge device configured to wirelessly communicate with the UE 112. The edge device provides an entry point into 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, e.g., a directional microwave antenna having a sector-shaped radiation pattern, or a multiple sector antenna configured to have, e.g., a full-circle coverage area 106. In some embodiments, an instance of antenna 110 is a circular antenna. In some embodiments, an instance of antenna 110 operates at one or more microwave or ultra-high frequency (UHF) frequencies, e.g., in the 300 megahertz (MHz) to 7.2 gigahertz (GHz) range. In some embodiments, an instance of antenna 110 operates at one or more frequencies in the 24.2 GHz to 71.0 GHz range.

[0030] In various embodiments, a cell 106 is a three-dimensional space having a shape and size based on the configuration, e.g., power level, and number of antennas 110, e.g., sectors, of the corresponding base station 108. In various embodiments, a 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 size of a cell 106 changes over time, for example, based on variable base station power levels and / or variable number of active antennas and / or antenna sectors. In one embodiment, a cell 106 is referred to as a macrocell, microcell, picocell, femtocell, or small cell. In one embodiment, a cell 106 is referred to as an indoor small cell (IDSC).

[0031] In one embodiment, an instance of UE 112 is a computer or computing system. In one embodiment, 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 one embodiment, an instance of UE 112 connects to the Internet and interconnects with other devices. In one embodiment, an instance of UE 112 incorporates a built-in camera, voice and video calling capabilities, video games, and global positioning system (GPS) functionality. In one embodiment, an instance of UE 112 runs as a virtual machine or allows third-party apps 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, personal navigation device (PND), a wearable computer (such as a calculator watch, smart watch, head-mounted display, earphones, 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 one embodiment, the UE 112 is configured to operate in each of an inactive mode, an idle mode, and a connected mode. In an inactive mode of operation, the UE 112 does not have active RAN access; in a connected mode of operation, the UE 112 is actively connected to the RAN; and in an idle mode of operation, the UE has access to and from the RAN but is not actively connected to the RAN. The primary 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 UE's context, including the UE's address identifier and session data, is stored in both the UE 112 and the network; but in the idle mode, the UE 112 is unknown to the network.

[0033] FIG. 1 shows an instance of UE 112, UE 112U, discussed further below.

[0034] The network 104 includes multiple network nodes, referred to in one embodiment as nodes or RAN nodes. In one embodiment, 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 one embodiment, a node corresponds to a base station 108 that is an instance of a device 102.

[0035] In one embodiment, the 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, the node is a Next Generation RAN (NG-RAN) node, such as a gNB NG-eNB according to the 3GPP TS 38.300 specification.

[0036] The nodes are interconnected to each other and to network management entities, such as the EMS or AMF, through various interfaces. In one embodiment, the interfaces between the nodes and core network elements are referred to as NG interfaces. In one embodiment, the interfaces between various nodes, such as between NG-RAN nodes, are referred to as Xn interfaces.

[0037] 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 referred to as mobility support algorithms 122N and / or AI / ML model information 128N is also referred to as AI / ML base model and policy parameters 128N.

[0038] 1, the device 102N that includes the mobility support 122N is a single instance of the device 102. In an embodiment, the device 102N that includes the mobility support 122N includes two or more instances of the device 102. Each of the mobility support 122N, the zone and UE identifiers 126N, and the AI / ML model information 128N is discussed further below.

[0039] A zone is a portion or all of a RAN, including a group of cells and a corresponding group of nodes, including, for example, device 102N. In one embodiment, a zone corresponds to a geographic area, e.g., a prefecture, bounded by one or more boundaries corresponding to political, physical, and / or geometric configurations. In various embodiments, a zone is a portion, all, or combination of a town, village, city, county, state, province, country, continent, island, peninsula, isthmus, grid portion bounded by latitude and longitude criteria, a circular area, a polygonal area, or other area. In one embodiment, a zone is a physically bounded portion of a geographic area, e.g., a portion, all, or combination of a hotel or office building, a complex, a campus, an industrial park, one or more city blocks, a shopping center, town center or mall, a neighborhood, a town, a village, etc.

[0040] The storage device, e.g., storage device 124N or storage device 124U on UE 112U, is one or more computer-readable non-volatile storage devices, e.g., a database. In one embodiment, the storage device includes memory 504, which is described below with respect to FIG.

[0041] 1, 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 102N.

[0042] In one embodiment, the storage device 124N is a database, also referred to in one embodiment as a RAN database, that 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 architecture 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 corresponding instances of zone and UE identifier 126N and AI / ML model information 128N.

[0044] Mobility support 122N is one or more sets of instructions configured to execute on device 102N to manage zone and UE identifiers 126N to be transmitted to and received from instances of UE 112, e.g., UE 112U, and to manage AI / ML model information 128N to and received from instances of UE 112, in accordance with an AI / ML model mobility support method 200, described below. In one embodiment, mobility support 122N is configured to execute as a standalone program or in one or more sets of instructions. In one embodiment, mobility support 122N is configured to execute on one or more of devices 102 in addition to device 102N.

[0045] During operation, the mobility support 122N is configured to manage the zone and UE identifiers 126N, which includes generating each of the zone identifiers of the zone and UE identifiers 126N and the UE identifiers of the zone and UE identifiers 126N.

[0046] The zone identifier of the zone and UE identifier 126N is a data record configured to be interpreted by the device 102 and the UE 112 to identify the zone that contains the device 102N. In one embodiment, the mobility support 122N is configured to generate the zone identifier during operation based on separate information received from the device 102, such as a RAN management system or function. In one embodiment, the mobility support 122N receives the zone identifier from the device 102, such as a RAN management system or function.

[0047] In one embodiment, a portion of the zone identifier, e.g., a subset of bits of the data record, is configured to be interpreted by the device 102 and the Ue 112 to identify a given instance of the device 102N. In one embodiment, this portion of the zone identifier includes part or all of an address, e.g., an IP address, of the given instance of the device 102N. In one embodiment, this portion is referred to as an address identifier.

[0048] The UE identifier of the zone and UE identifier 126N is a data record configured to be interpreted by the device 102 and the Ue 112 to identify a given instance of the UE 112U over a given period of time. In various embodiments, the given period of time is a predetermined period of time or a variable period of time having a length based on one or more criteria, for example, a time threshold that tracks recent activity within a given zone.

[0049] The device 102 and the Ue 112 are configured to store the zone and UE identifier 126N (and the corresponding zone and UE identifier 126U described below) in a storage device, for example, in the storage device 124N, so that the corresponding zone identifier and UE identifier are persistent in nature and can be used by the device 102 and the Ue 112 across multiple connected mode sessions involving multiple instances of either or both of the device 102 or the Ue 112.

[0050] In one embodiment, the mobility support 122N is configured, during operation, to generate a UE identifier based on separate information received from the device 102, such as a RAN management system or function. In one embodiment, the mobility support 122N receives the UE identifier from the device 102, such as a RAN management system or function. In one embodiment, the UE identifier is a Serving Temporary Mobile Subscriber Identity (S-TMSI).

[0051] In one embodiment, the mobility support 122N is configured, during operation, to transmit an instance of the zone and UE identifier 126N to a given UE 112U in response to receiving a transmission from the UE 112U. In one embodiment, the transmission from the UE 112U comprises an RRC Setup Request message or an RRC Resume Request message received in the course of establishing a session in which the device 102N acts as a serving node for the UE 112U, e.g., establishing a session due to the UE 112U transitioning from an inactive or idle mode to a connected mode. In one embodiment, the transmission comprises an indication of the UE transitioning from a connected mode to an inactive or idle mode.

[0052] In one embodiment, the mobility support 122N is configured, during operation, to send an instance of the zone and UE identifier 126N to a given UE 112U in response to completing a connected mode session, for example, in response to returning the UE 112U to an inactive or idle mode.

[0053] In one embodiment, the mobility support 122N is configured, during operation, to store AI / ML model information 128N associated with a zone and a UE identifier 126N in one or a combination of storage devices 124N included in the device 102N or configured as a database associated with a zone that includes the device 102N. In one embodiment, storing the AI / ML model information 128N corresponds to completing a connected mode session with a given UE 112U and storing the generated ML models and policies, e.g., 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 the given UE 112U, e.g., an MHI generated by the device 102N or an MHI received from a device 102 other than the UE 112U and / or the device 102N.

[0054] An instance of AI / ML model information 128N includes at least one model generated by execution of one or more AI / ML algorithms on training data, e.g., on the MHI of UE 112, which in one embodiment includes UE 112U. The at least one model includes an algorithm configured to generate a set of outputs consisting of prediction information and / or decision parameters based on a set of inputs, and is thus configured to be usable by UE 112U during one or more operations, e.g., 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, a range of speeds of UE 112U or a strength of a signal received from base station 108.

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

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

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

[0059] In one embodiment, the received instance of the zone and UE identifier 126N is included in an RRC setup or resume request message. In one embodiment, the received instance of the zone and UE identifier 126N is included in an RRC reconfiguration complete message received during a handover operation.

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

[0061] The previously generated zone and UE identifier 126N is based on one or more previous sessions in which a node in the zone, for example, device 102N or another device 102 in the zone, acted as a serving node for the UE 112U.

[0062] In one embodiment, the mobility support 122N is configured, during operation, to respond to a mismatch between a received instance of a zone and UE identifier 126N and one or more previously generated zone and UE identifiers 126N by generating new AI / ML model information 128N. In one 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 resume request message, by generating new AI / ML model information 128N.

[0063] In one embodiment, the mobility support 122N is configured to transmit the corresponding previously generated zone and UE identifier 126N and / or the 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 an embodiment, mobility support 122U is also referred to as mobility support algorithms 122U and / or AI / ML model information 128U is also referred to as 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 the device 102N, and the AI / ML model information 128U corresponds to the AI / ML model information 128N received from the device 102N.

[0066] Mobility support 122U is one or more sets of instructions configured to execute on UE 112U, whereby zone and UE identifiers 126U are managed and transmitted to and from an instance of device 102, such as device 102N, and whereby AI / ML model information 128U is received from the instance of device 102N and, in one embodiment, applied to the operation of UE 112U, in accordance with AI / ML model mobility support method 200, described below. In one embodiment, mobility support 122U is configured to execute as a standalone program or in one or more sets of instructions. In one embodiment, mobility support 122U is configured to execute on one or more UEs 112 in addition to UE 112U.

[0067] During operation, the mobility support 122U is configured to receive an instance of the zone and UE identifier 126U from the instance of the device 102N and to store the instance of the zone and UE identifier 126U in the storage device 124U. In one embodiment, the instance of the zone and UE identifier 126U is included in a SIB received from the instance of the device 102N.

[0068] In one embodiment, the mobility support 122U is configured to receive, during operation, an instance of the zone and UE identifier 126U included in an RRC setup or resume request message, for example, in the course of establishing a session in which an instance of the device 102N acts as a serving node for the UE 112U, for example, in the course of establishing a session due to the UE 112U transitioning from an inactive or idle mode to a connected mode.

[0069] In one embodiment, mobility support 122U is configured, during operation, to receive an instance of zone and UE identifier 126U included in an RRC reconfiguration message received in the course of completing a connected mode session with an instance of device 102N.

[0070] In one embodiment, the mobility support 122U is configured, during operation, to receive an instance of the zone and UE identifier 126U included in an RRC reconfiguration message received in the course of a handover operation from an instance of the device 102N that serves as a serving node for the UE 112U after another device 102 serves as a serving node for the UE 112U.

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

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

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

[0074] In one embodiment, the mobility support 122U is configured to respond to a return to a connected mode from an inactive or idle mode by sending the stored zone and UE identifier 126U in an RRC setup request message or an RRC resume request message.

[0075] In one embodiment, the mobility support 122U is configured to respond to receiving the RRC handover command by sending the stored zone and UE identifier 126U in an RRC reconfiguration complete message. In one embodiment, the mobility support 122U obtains the zone and UE identifier 126U from a plurality of stored instances of the zone and UE identifier 126U.

[0076] In one embodiment, mobility support 122U is configured, during operation, to receive AI / ML model information 128U from the second instance of device 102N and apply the received AI / ML model information 128U to operation of UE 112U, for example, to 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 obtained by the second instance of the device 102N, or AI / ML model information 128N newly generated by the second instance of the device 102N, as described above.

[0078] In one embodiment, the mobility support 122U is configured, during operation, to delete one or both of the stored zones or UE identifiers of the stored zones and UE identifiers 126U based on one or more deletion criteria, for example, by deleting the oldest identifier after expiration of a preconfigured timer and / or 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 the device 102N.

[0079] Thus, 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: transmitting a zone and UE identifier 126N from a first instance of device 102N to the UE 112U, where the zone identifier corresponds to a first zone of the network 104 including the cell 106 and the device 102 including the first instance of device 102N; storing the zone and UE identifier 126U in a storage device 124U; transmitting the zone and UE identifier 126U from the UE 112U to a second instance of device 102N; sending AI / ML model information 128N from the second instance of device 102N to the UE 112U, where the AI / ML model information 128N is based on the zone and UE identifier 126N; and applying the AI / ML model information 128U to the operation of the UE 112U.

[0080] By storing the zone and UE identifier 126U and transmitting the zone and UE identifier 126U from the UE 112U to the second instance of the device 102N, the second instance of the device 102N can determine whether previously generated AI / ML model information 128N is available to be transmitted to the UE 112U. Thus, in situations where previously generated AI / ML base model information is unavailable, such as while the UE 112U transitions from an inactive or idle mode to a connected mode or during a UE 112U handover operation, the previously generated AI / ML model information 128N is available to be applied to operation by the UE 112U. Thus, compared to approaches where previously generated AI / ML base model information is unavailable in such situations, the system 100, the UE 112U, and the device 102N are configured to utilize the previously generated AI / ML model information 128N to enable more efficient UE operation.

[0081] 2 is a flowchart of an AI / ML model mobility support method 200, according to one embodiment. In one embodiment, the AI / ML model mobility support method 200, also referred to as method 200 or method of operating a RAN, is operable on a telecommunications system, such as the telecommunications system 100 described above with respect to FIG.

[0082] 2, additional operations may be performed before, during, between, and / or after the operations of method 200, and some other operations may only be briefly described herein. In certain embodiments, other orders of the operations of method 200 are within the scope of the present disclosure. In certain 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, for example, a method of operating a telecommunications system. In some embodiments, some or all of the operations of method 200 described below are repeated, for example, in the course of operating a telecommunications system.

[0084] In an embodiment, some or all of the operations of method 200 described below may be performed automatically, for example, by device 102N including mobility support 122N and / or UE 112 including mobility support 122U, each described above with respect to FIG. 1, and / or by using processing circuitry 502 described below with respect to FIG. 5.

[0085] The operation of the method 200 is described below with reference to various features of the system 100 described above with respect to FIG.

[0086] 3 and 4 show non-limiting examples illustrating the performance of some or all of the operations of method 200 using an embodiment of system 100, as described below.

[0087] In an embodiment, the zone and UE identifier are transmitted from the first RAN node to the UE at operation 210. Transmitting the zone and UE identifier from the first RAN node to the UE includes transmitting the zone and UE identifier 126N from the first instance of the device 102N to the UE 112U, as described above.

[0088] In an embodiment, the AI / ML model information based on the zone and the UE identifier is stored in operation 220. Storing the AI / ML model information based on the zone and the UE identifier includes storing the AI / ML model information 128N using the device 102N in one or a combination of storage devices 124N included in the device 102N or configured as a database associated with the zone that includes the device 102N, as described above.

[0089] In an embodiment, the zone and UE identifier are stored in a UE storage device at operation 230. Storing the zone and UE identifier in a UE storage device includes using the UE 112U to store the zone and UE identifier 126U in a storage device 124U, as described above.

[0090] In an operation 240, in one embodiment, the zone and UE identifier are transmitted from the UE to the second RAN node. Transmitting the zone and UE identifier from the UE to the second RAN node includes transmitting the zone and UE identifier 126U from the UE 112U to the second instance of the device 102N, as described above.

[0091] In operation 250, in one embodiment, AI / ML model information based on the zone and UE identifier received at the second RAN node is obtained or generated. Obtaining or generating the AI / ML model information based on the zone and UE identifier received at the second RAN node includes obtaining or generating the AI / ML model information 128N using the second instance of device 102N, as described above.

[0092] In an operation 260, in one embodiment, 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 the second instance of the device 102N to the UE 112U, as described above.

[0093] In an operation 270, in one embodiment, the AI / ML information is applied to the operation of the UE. Applying the AI / ML information to the operation of the UE includes applying the AI / ML model information 128U to the operation of the UE 112U, as described above.

[0094] In an embodiment, stored zones and / or UE identifiers are deleted based on one or more deletion criteria at operation 280. Deleting stored zones and / or UE identifiers based on one or more deletion criteria may include deleting some or all of the 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, such as system 100, can automatically perform some or all of the following: transmitting a UE identifier and a zone identifier from a first node in the RAN to a UE, where the zone identifier corresponds to a first zone of the RAN that includes a plurality of cells and a plurality of nodes including the first node; storing each of the UE and zone identifiers in a storage device of the UE; transmitting the UE and zone identifier from the UE to a second node in 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 zone identifier; and applying the AI / ML-based model and policy parameters to operation of the UE, thereby achieving the advantages described above for system 100.

[0096] 3 is a flowchart of an AI / ML model mobility support method 300, according to one embodiment. The AI / ML model mobility support method 300, also referred to in one embodiment as method 300 or a method of operating a RAN, is one non-limiting example of some or all of method 200 described above.

[0097] Method 300 corresponds to a situation in which 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 obtained from a database on device 102 based on stored zone and UE identifier 128U.

[0098] 3, in operation 210, the first instance of the device 102N transmits the zone and UE identifier 128N to the UE 112U, and the UE 112U transitions from a connected mode to an inactive or idle mode. In operation 230, the UE 112U stores the zone and UE identifier 128N as the zone and UE identifier 128U. In operation 220, the first instance of the device 102N stores the AI / ML model information 128N in a database on the device 102. In operation 240, the UE 112U returns to connected mode and transmits the zone and UE identifier 128U to the second instance of the device 102N. In operation 250, the second instance of the device 102N retrieves the AI / ML model information 128N from the database on the device 102 based on the received zone and UE identifier 128N. In operations 260 and 270, the second instance of the device 102N sends the obtained AI / ML model information 128N to the UE 112U, and the UE 112U applies the AI / ML model information 128N as the AI / ML model information 128U in 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 advantages discussed above with respect to FIGS. 1 and 2 may be realized.

[0100] 4 is a flowchart of an AI / ML model mobility support method 400, according to one embodiment. The AI / ML model mobility support method 400, also referred to in one embodiment as method 400 or a method of operating a RAN, is one non-limiting example of some or all of method 200 described above.

[0101] The method 400 corresponds to a situation in which an instance of the UE 112U is involved in a handover operation between two instances of the device 102N and AI / ML model information 128N is obtained from a database on the device 102 based on a stored zone and UE identifier 128U.

[0102] 4, in operations 210-230, the UE 112U stores a zone and UE identifier 128U based on a previous connected mode session (not shown) with an instance of device 102N for which AI / ML model information 128N was stored in a database on the device 102. A subsequent handover operation is 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, including the zone and UE identifier 128U (corresponding to the stored zone and UE identifier 126U). In operation 250, the second instance of device 102N retrieves the AI / ML model information 128N from the database on the device 102 based on the received zone and UE identifier 128N. In operations 260 and 270, the second instance of the device 102N sends the obtained AI / ML model information 128N to the UE 112U, and the UE 112U applies the AI / ML model information 128N as the 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 advantages discussed above with respect to FIGS. 1 and 2 may be realized.

[0104] FIG. 5 is a functional block diagram of a computer or processor-based device 500 on or by which embodiments may be implemented.

[0105] The processor-based device 500 is programmed to facilitate automatic generation and / or modification of cell reselection policies as described herein and includes, for example, a bus 508, processing circuitry 502, also referred to in one embodiment as a processor 502, and memory 504 components.

[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 circuitry 502 is coupled to the bus 508 to receive instructions to execute and to process information stored, for example, in memory 504. In one embodiment, the processing circuitry 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). DSPs are typically configured to process real-world signals (e.g., sound) in real time, independently of the processing circuitry 502. Similarly, ASICs can be configured to perform specialized functions not easily performed by more general-purpose processors. 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 processors) 502 performs a set of operations on the information as specified by a set of instructions stored in memory 504 in connection with a cell reselection policy, e.g., a mobility support algorithm 516 corresponding to mobility support 122N or 122U described above with respect to Figures 1 and 2. Execution of the instructions causes the processor to perform the specified function.

[0108] The processing circuit 502 and associated components are coupled to memory 504 via bus 508. The memory 504 includes one or more of dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (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 performance of the operations, such as zone and UE identifiers 520 corresponding to zone and UE identifiers 126N or 126U and AI / ML model information 522 corresponding to AI / ML model information 128U or 128N, as described above with respect to FIGS. 1 and 2, respectively.

[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 implementation of network applications. Dynamic memory allows stored information to be changed. 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 circuit 502 to store temporary values ​​during 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 changed by processing circuit 502. Some memory consists of volatile storage, which loses stored information when power is lost. In certain embodiments, memory 504 includes a non-volatile (persistent) storage device, such as a magnetic disk, optical disk, or flash card, that stores information, including instructions, that remains even when device 500 is turned off or otherwise loses power.

[0110] The term "computer-readable medium" as used herein refers to any medium that participates in providing information to the processing circuit 502, including the instructions 506 to be executed. 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 or magnetic disks. Volatile media include, for example, dynamic memory. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, a hard disk, magnetic tape, another magnetic medium, a CD-ROM, a CDRW, a DVD, another optical medium, a punch card, a paper tape, an optical mark sheet, another physical medium having a pattern of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, another memory chip or cartridge, or another medium readable by a computer. The term computer-readable storage medium is used herein to refer to a computer-readable medium.

[0111] The instructions 506 also include a user interface 518, one or more sets of instructions configured to enable a user to effectively operate and control the device 500. In one embodiment, 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 an embodiment, a 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, while operating in a connected mode, to receive, from a first RAN node of a RAN, a zone identifier and a UE identifier, respectively, 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; storing, in a storage device of the UE, each of the zone identifiers and the UE identifier; and transmitting, in response to returning from an inactive mode or an idle mode to a connected mode or in response to receiving, from the first RAN node or a third RAN node, an RRC handover command corresponding to a handover to the second RAN node. In an embodiment, the instructions are executable by the processor to further cause the UE to: 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 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 in a zone corresponding to the stored zone identifier or a newly generated AI / ML-based model and / or policy parameters corresponding to the second RAN node in a zone other than the zone corresponding to the stored zone identifier. In an embodiment, the instructions are executable by the processor to cause the UE to send a zone identifier and a UE identifier to the second RAN node in an RRC Setup Request message or an RRC Resume Request message in response to returning to a connected mode from an inactive mode or an idle mode, and in an RRC Reconfiguration Complete message in response to receiving an RRC handover command from the first or third RAN node.In one embodiment, the instructions are executable by a processor to further cause the UE to: compare a zone identifier obtained from a system information broadcast of a second RAN node to a plurality of stored zone identifiers in response to receiving an RRC handover command from the first or third RAN node; and obtain a UE identifier corresponding to the zone identifier from the plurality of stored UE identifiers. In one embodiment, the instructions are executable by a processor to cause the UE to receive, store, and transmit a zone identifier including an address identifier of the first RAN node. In one embodiment, the instructions are executable by a processor to cause the UE to receive a new zone identifier and a new UE identifier from a third RAN node, thereby indicating that the third RAN node corresponds to a first vendor different from a second vendor corresponding to the first and second RAN nodes. In one embodiment, the instructions are executable by a processor 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 an instruction from the first, second, or another RAN node.

[0113] In an embodiment, 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, wherein execution of the instructions causes the RAN node to: receive a transmission from a UE in the course of establishing a connected mode session including a RAN node serving the UE; in response to the transmission including a first zone identifier and a UE identifier, compare the first zone identifier to a second zone identifier of a zone of the RAN including a plurality of RAN nodes, the zone including a plurality of cells and the RAN node; in response to a match of the first and second zone identifiers, retrieve from a storage device an existing artificial intelligence and machine learning (AI / ML)-based model associated with the UE identifier based on a previous session including one of the plurality of RAN nodes serving the UE, or in response to a mismatch of the first and second zone identifiers or a transmission lacking the first zone identifier, generate a new AI / ML-based model; and transmit the corresponding existing or new AI / ML-based model, the UE identifier, and the second zone identifier to the UE. In one embodiment, the instructions are executable by a processor to cause the RAN node to receive, during the process of establishing a connected mode session, a first zone identifier and a UE identifier included in a transmission comprising an RRC Setup Request message or an RRC Resume Request message. In one embodiment, the RAN corresponds to a first vendor, and the instructions are executable by a processor to cause the 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, during the process of handing over a UE from a second vendor different from the first vendor, a first zone identifier and a UE identifier included in a transmission comprising an RRC Reconfiguration Complete message. In one embodiment, the instructions are executable by a processor to cause the RAN node to retrieve the AI / ML-based model from a storage device comprising a database associated with a zone including a plurality of RAN nodes including the RAN node.In one embodiment, the RAN node is a first RAN node of a plurality of RAN nodes, and the instructions are executable by a processor to cause the first RAN node to: receive a first zone identifier including an address identifier of a second RAN node of the plurality of RAN nodes; and retrieve the AI / ML-based model from a storage device associated with the second RAN node. In one embodiment, the instructions are executable by a processor to cause the RAN node to send policy parameters corresponding to the existing or new AI / ML-based model to the UE. In one embodiment, the instructions are executable by a processor to further cause the RAN node to store the corresponding existing or new AI / ML-based model in the course 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 in the RAN to a UE, the zone identifier corresponding to a first zone of the RAN including 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 in the RAN; sending an AI / ML-based model and policy parameters from the second node to the UE, the AI / ML-based model and policy parameters being based on the UE identifier and the zone identifier; and applying the AI / ML-based model and policy parameters to operation of the UE. In one embodiment, transmitting the UE identifier and the zone identifier from the first node to the UE includes broadcasting a signaling information base (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 the zone identifier from the UE to the second node includes sending an RRC setup request message or an RRC resumption request message when the UE is in the process of transitioning from an inactive mode or an idle mode to a connected mode. In one embodiment, the first and second nodes correspond to a first vendor, and transmitting the UE identifier and the zone identifier from the UE to the second node includes transmitting an RRC reconfiguration complete message by the UE during a handover of the UE from a third node corresponding to a second vendor different from the first vendor to the second node. In one embodiment, transmitting the AI / ML-based model and policy parameters includes retrieving 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 zone, or generating new AI / ML-based model and policy parameters in response to the second node being outside the first zone.In an embodiment, retrieving the previously generated AI / ML-based model and policy parameters from a storage device includes retrieving the previously generated AI / ML-based model and policy parameters from a database associated with the first zone, or retrieving the previously generated AI / ML-based model and policy parameters from a storage device associated with a first node, a second node, or a third node of the plurality of nodes in the first zone.

[0115] The foregoing outlines features of certain embodiments so that those skilled in the art may better understand the aspects of the present disclosure. Those skilled in the art will readily appreciate that they may use this disclosure as a basis for designing or modifying other processes and structures which carry out the same purposes and / or achieve the same advantages of 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 those skilled in the art will be able to make various changes, substitutions, and alterations herein without departing from the spirit and scope of the present disclosure.

Claims

1. a memory having non-transitory instructions stored therein; a processor coupled to the memory and configured to execute the instructions. A user equipment (UE), Execution of the instructions causes the processor to receiving, 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 identifier corresponding to a zone of the RAN that includes a plurality of cells and a plurality of RAN nodes including the first RAN node; storing each of the zone identifier and the UE identifier in a storage device of the UE; upon returning to said connected mode from an inactive or idle mode, or in response to receiving a Radio Resource Control (RRC) handover command from the first RAN node or a third RAN node corresponding to a handover to a second RAN node; transmitting the zone identifier and the UE identifier to the second RAN node. UE.

2. receiving artificial intelligence and machine learning (AI / ML) based models and / or policy parameters from the second RAN node; applying the AI / ML-based model and / or policy parameters to the operation of the UE; the instructions are executable by the processor to cause the UE to further perform The AI / ML based model and / or policy parameters include: a previously generated AI / ML base model and / or policy parameters corresponding to the second RAN node that is within the zone corresponding to the stored zone identifier; or a newly generated AI / ML base model and / or policy parameters corresponding to the second RAN node in a zone other than the zone corresponding to the stored zone identifier; The UE of claim 1.

3. In response to returning from the inactive mode or the idle mode to the connected mode, the RRC setup request message or the RRC resumption request message is included, in an RRC reconfiguration complete message in response to receiving the RRC handover command from the first or third RAN node; The instructions are executable by the processor to cause the UE to transmit the zone identifier and the UE identifier to the second RAN node. The UE of claim 1.

4. in response to receiving the RRC handover command from the first or the third RAN node; comparing the zone identifier obtained from the second RAN node's system information broadcast to a plurality of stored zone identifiers; and obtaining the UE identifier corresponding to the zone identifier from a plurality of stored UE identifiers. The UE of claim 1.

5. The instructions are executable by the processor to cause the UE to receive, store, and transmit the zone identifier, the zone identifier including an address identifier of the first RAN node. The UE of claim 1.

6. The instructions are executable by the processor to cause the UE to receive a new zone identifier and a new UE identifier from the third RAN node, thereby indicating that the third RAN node corresponds to a first vendor that is different from a second vendor that corresponds to the first and second RAN nodes. The UE of claim 1.

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

8. A radio access network (RAN) node, comprising: a memory having non-transitory instructions stored therein; a processor coupled to the memory and configured to execute the instructions, wherein execution of the instructions causes the processor to receiving a transmission from a user equipment (UE) in the course of establishing a connected mode session involving the RAN node serving the UE; In response to the transmission including a first zone identifier and a UE identifier, comparing the first zone identifier to a second zone identifier for a zone of a RAN including a plurality of cells and a plurality of RAN nodes including the RAN node; responsive to a match between the first and second zone identifiers, retrieving from a storage device an existing artificial intelligence and machine learning (AI / ML) based model associated with the UE identifier based on a previous session involving one of the plurality of RAN nodes serving the UE; or generating a new AI / ML based model in response to a mismatch between the first and second zone identifiers or the transmission lacking the first zone identifier; transmitting the corresponding existing or new AI / ML base model, the UE identifier, and the second zone identifier to the UE. RAN node.

9. The instructions are executable by the processor to cause the RAN node to receive, in the course of establishing the connected mode session, the first zone identifier and the UE identifier included in the transmission, including a Radio Resource Control (RRC) Setup Request message or an RRC Resume Request message.

9. The RAN node of claim 8.

10. the RAN corresponds to a first vendor; establishing the connected mode session during a handover 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 comprising an RRC reconfiguration complete message; The instructions are executable by the processor to cause the RAN node to perform 9. The RAN node of claim 8.

11. The instructions are executable by the processor to cause the RAN node to retrieve the AI / ML-based model from the storage device including a database associated with the zone including the plurality of RAN nodes, the RAN node including the RAN node.

9. The RAN node of claim 8.

12. the RAN node is a first RAN node of the plurality of RAN nodes; receiving the first zone identifier including an address identifier of a second RAN node of the plurality of RAN nodes; retrieving the AI / ML base model from the storage device associated with the second RAN node; The instructions are executable by the processor to cause the first RAN node to perform 9. The RAN node of claim 8.

13. The instructions are executable by the processor to cause the RAN node to send policy parameters corresponding to the existing or new AI / ML-based model to the UE.

9. The RAN node of claim 8.

14. The instructions are executable by the processor to further cause the RAN node to store the corresponding existing or new AI / ML-based model in the course of completing the connected mode session.

9. The RAN node of claim 8.

15. 1. A method of operating a radio access network (RAN), comprising: transmitting a UE identifier and a zone identifier from a first node of the RAN to a user equipment (UE), the zone identifier corresponding to a first zone of the RAN comprising 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 artificial intelligence and machine learning (AI / ML) based models and policy parameters from the second node to the UE, the AI / ML based models and policy parameters being based on the UE identifier and the zone identifier; applying the AI / ML-based model and policy parameters to the operation of the UE; A method comprising:

16. The transmitting 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.

16. The method of claim 15.

17. The transmitting of the UE identifier and the zone identifier from the UE to the second node includes transmitting a Radio Resource Control (RRC) Setup Request message or an RRC Resume Request message during a transition of the UE from an inactive mode or an idle mode to a connected mode.

16. The method of claim 15.

18. the first and second nodes correspond to a first vendor; the transmitting of the UE identifier and the zone identifier from the UE to the second node includes the UE transmitting a Radio Resource Control (RRC) Reconfiguration Complete message during a handover of the UE from a third node corresponding to a second vendor different from the first vendor to the second node.

16. The method of claim 15.

19. The transmitting the AI / ML base model and policy parameters includes: retrieving a previously generated AI / ML base model and policy parameters from a storage device in response to the second node being among the plurality of nodes in the first zone; or generating a new AI / ML base model and policy parameters in response to the second node being outside the first zone.

16. The method of claim 15.

20. The retrieving of the previously generated AI / ML base 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 zone; or and obtaining the previously generated AI / ML base model and policy parameters from the storage device associated with the first node, the second node, or a third node of the plurality of nodes in the first zone.

20. The method of claim 19.

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