Network node, core network node, mobile device, and method

Abstract

The present disclosure relates to a method in an access network node, the method including: obtaining predicted mobility information indicating predicted mobility of a user equipment (UE); performing a handover procedure for handing over the UE to another access network node; and transmitting the predicted mobility information to the other access network node, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

Description

[Technical Field]

[0001] The present disclosure relates to an access network node, a core network node, a user equipment, and methods thereof. [Background technology]

[0002] This disclosure has particular, though not exclusive, relevance to wireless communication systems and devices thereof that operate in accordance with 3rd Generation Partnership Project (3GPP®) standards or equivalent standards or derivatives thereof (including LTE-Advanced, Next Generation or 5G networks, future generations, and beyond). This disclosure has particular, though not necessarily exclusive, relevance to projections of mobility in so-called "5G" or "New Radio" systems (also referred to as "Next Generation" systems) and similar systems.

[0003] Recent developments in 3GPP standards are referred to as the Long-Term Evolution (LTE) of the Evolved Packet Core (EPC) network and the Evolved Universal Mobile Telecommunications Service (UMTS) Terrestrial Radio Access Network (E-UTRAN), commonly referred to as "4G." Additionally, the terms "5G" and "new radio" (NR) refer to evolving communications technologies expected to support a variety of applications and services. Various details of 5G networks are described, for example, in the "NGMN 5G White Paper" V1.0 by the Next Generation Mobile Network (NGMN) Alliance, available at https: / / www.ngmn.org / 5g-white-paper.html. 3GPP intends to support 5G through the so-called 3GPP Next Generation (NextGen) Radio Access Network (RAN) and 3GPP NextGen Core Network.

[0004] Under 3GPP standards, a NodeB (or eNB in ​​LTE, gNB in ​​5G) is a Radio Access Network (RAN) node (or simply "access node," "access network node," or "base station") through which communication devices (user equipment or "UE") connect to the core network and communicate with other communication devices or remote servers. For simplicity, this application uses the terms RAN node, base station, or access network node to refer to any such access node. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Next Generation Mobile Networks (NGMN) Alliance,'NGMN 5G White Paper',V1.0,17-February-2015 [Non-patent document 2] 3GPP TS 38.331, “NR;Radio Resource Control (RRC) protocol specification”, V17.2.0 (2022-09) Summary of the Invention [Problem to be solved by the invention]

[0006] Some additional developments in 3GPP relate to the use of artificial intelligence (AI) and machine learning (ML), often abbreviated as AI / ML. Several use cases have been proposed for AI / ML, one of which is in the context of UE mobility. AI / ML can be used to predict a UE's path, for example, based on the UE's previous movements between cells. The UE's predicted mobility can then be used to optimize the communication network, resulting in improved efficiency and performance. However, improved methods are needed for sharing information related to UE mobility between nodes in a communication network, so that improved predictions of UE mobility can be made at one or more of the network nodes. For example, if a base station uses AI / ML to predict a UE's mobility, an improved method is needed where information about the UE's actual mobility can be fed back to the base station, thereby improving the AI / ML model based on that feedback. This can be particularly challenging when a UE handover occurs, after which the base station can no longer directly communicate with the UE.

[0007] More generally, improved methods for predicting UE mobility (eg, movement between cells) are needed to enable more efficient and reliable communication networks.

[0008] The present disclosure aims to provide apparatus and methods that at least partially address the above needs and / or problems. [Means for solving the problem]

[0009] A first aspect of the present disclosure is a method for a network node, the method comprising: transmitting a message including predicted mobility information indicating predicted mobility of a user equipment (UE) to another network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides a method comprising at least one of the following steps.

[0010] A second aspect of the present disclosure is a method for a network node, the method comprising: receiving, from another network node, predicted mobility information for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides a method comprising at least one of the following steps.

[0011] A third aspect of the present disclosure is a method for a core network node, the method comprising: receiving predicted mobility information from a network node for mobility of a user equipment (UE), the predicted mobility information indicating a predicted mobility of the UE; transmitting the predicted mobility information to another network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides a method comprising at least one of the following steps.

[0012] A fourth aspect of the present disclosure is a method for a user equipment (UE), the method comprising: sending a first measurement report to a network node indicating results of measurements performed by the UE; receiving, after the first measurement report has been sent to the network node, a notification from the network node to cause the UE to send, in a radio resource control, RRC, reconfiguration complete message, to another network node, a second measurement report indicating a result of a second measurement performed by the UE; sending a second measurement report to another network node; A method is provided in which the second measurement report is used to generate feedback of the predicted mobility of the UE.

[0013] A fifth aspect of the present disclosure is an access network node, comprising: a user equipment, comprising: means for transmitting predicted mobility information indicating predicted mobility of the UE to another network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides an access network node including at least one of:

[0014] A sixth aspect of the present disclosure is an access network node, comprising: means for receiving, from another network node, predicted mobility information for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides an access network node including at least one of:

[0015] A seventh aspect of the present disclosure is a core network node, comprising: means for receiving predicted mobility information from a network node for mobility of a user equipment (UE), the predicted mobility information indicating a predicted mobility of the UE; means for transmitting the predicted mobility information to another access network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. The present invention provides a core network node including at least one of:

[0016] An eighth aspect of the present disclosure is a user equipment (UE), comprising: means for transmitting a first measurement report to a network node, the first measurement report indicating a result of a first measurement performed by the UE; means for receiving, after the first measurement report has been sent to the network node, a notification to cause the UE to send, in a Radio Resource Control, RRC, Reconfiguration Complete message to another network node, a second measurement report indicating a result of a second measurement performed by the UE; means for transmitting a second measurement report to another network node; The second measurement report provides the user equipment with a predicted mobility feedback for the UE. [Brief explanation of the drawings]

[0017] Exemplary embodiments of the present disclosure will now be described, by way of example, with reference to the accompanying drawings, in which: [Figure 1] FIG. 1 is a schematic diagram of a mobile (“cellular” or “wireless”) communications system. [Figure 2] FIG. 2 is a diagram illustrating a typical frame structure that may be used in the communication system of FIG. [Figure 3]FIG. 3 is a schematic block diagram showing the main components of a DU 50 that may be used as part of the RAN equipment 5 for the communication system 1 shown in FIG. [Figure 4] FIG. 4 is a schematic block diagram showing the main components of a CU 60 that may be used as part of the RAN equipment 5 for the communications system 1 shown in FIG. [Figure 5] FIG. 5 illustrates a mobility procedure in which a handover occurs from a source (R)AN node to a target (R)AN node. [Figure 6] FIG. 6 is a diagram illustrating an example of intra-CU inter-DU mobility. [Figure 7] FIG. 7 illustrates a method for L1 / L2-based inter-cell mobility. [Figure 8] FIG. 8 is a diagram illustrating an example of intra-DU mobility. [Figure 9] FIG. 9 illustrates an intra-DU handover to an additional PCI. [Figure 10] FIG. 10 is a diagram illustrating the inter-cell inter-DU method. [Figure 11] FIG. 11 illustrates a base station triggered L1 mobility method including measurement report filtering. [Figure 12] FIG. 12 illustrates an inter-cell inter-DU method including conditional handover. [Figure 13] FIG. 13 illustrates an inter-cell inter-DU method including L1 measurement report reconfiguration. [Figure 14] FIG. 14 is a schematic diagram illustrating the interactions between nodes of the system when using artificial intelligence / machine learning. [Figure 15] FIG. 15 is a diagram showing an example of an AI / ML request and an AI / ML response. [Figure 16] FIG. 16 is a diagram illustrating an example of an AI / ML information update. [Figure 17] FIG. 17 is a diagram illustrating an example of UE mobility information feedback. [Figure 18] FIG. 18 illustrates a further example of UE mobility information feedback. [Figure 19] FIG. 19 is a schematic block diagram illustrating the main components of a UE for the communication system of FIG. [Figure 20] FIG. 20 is a schematic block diagram showing the main components of a base station for the communication system of FIG. [Figure 21] FIG. 21 is a schematic block diagram showing the main components of a core network node or function for the communication system of FIG. DETAILED DESCRIPTION OF THE INVENTION

[0018] <Summary> An exemplary communications system will now be described in general terms, by way of example only, and with reference to FIGS.

[0019] FIG. 1 is a schematic diagram of a mobile ("cellular" or "wireless") communications system 1 to which exemplary embodiments of the present disclosure are applicable.

[0020] In the communication system 1, user equipment (UE) 3-1, 3-2, 3-3 (e.g., mobile phones and / or other mobile devices) can communicate with each other via Radio Access Network (RAN) nodes 5 (base stations 5, RAN equipment 5) that operate according to one or more compatible radio access technologies (RATs). In the illustrated example, the RAN nodes 5 comprise NR / 5G base stations or "gNBs" 5 that operate one or more associated cells 9. Communications via the base stations 5 are typically routed through a core network 7 (e.g., a 5G core network or evolved packet core network (EPC)).

[0021] As one skilled in the art will appreciate, although three UEs 3 and one base station 5 are shown in FIG. 1 for illustrative purposes, the system, when implemented, will typically include other base stations 5 and UEs 3.

[0022] Each base station 5 controls, directly or indirectly via one or more other nodes (e.g., home base stations, repeaters, remote radio heads, distributed units, etc.), one or more associated cells 9. It will be appreciated that the base stations 5 may be configured to support 4G, 5G, 6G, and / or any other 3GPP or non-3GPP communication protocols.

[0023] The UEs 3 and their serving base stations 5 are connected via a suitable air interface (such as, for example, the so-called "Uu" interface). Neighboring base stations 5 may be connected to each other via a suitable inter-base station interface (such as the so-called "X2" interface, "Xn" interface, etc.).

[0024] The core network 7 includes several logical nodes (or "functions") for supporting communications in the communication system 1. In this example, the core network 7 comprises a control plane function (CPF) 10 and one or more user plane functions (UPF) 11. The CPF 10 includes one or more Access and Mobility Management Functions (AMF) 10-1, one or more Session Management Functions (SMF), and several other functions 10-n.

[0025] The base stations 5 are connected to core network nodes via appropriate interfaces (or "reference points"), such as the N2 reference point between the base stations 5 and the AMF 10-1 for communication of control signaling, and the N3 reference point between the base stations 5 and each UPF 11 for communication of user data. The UEs 3 are each connected to the AMF 10-1 via a logical non-access stratum (NAS) connection over the N1 reference point (similar to the S1 reference point in LTE). It will be appreciated that N1 communications are transparently routed via the base stations 5.

[0026] The one or more UPFs 11 are connected to an external data network (eg, an IP network such as the Internet) via a reference point N6 for communication of user data.

[0027] The AMF 10-1 performs mobility management related functions, maintains a NAS signaling connection with each UE 3, and manages UE registration. The AMF 10-1 is also responsible for managing paging. The SMF 10-2 provides session management functions (forming part of the MME function in LTE) and also combines some control plane functions (provided by the Serving Gateway and Packet Data Network Gateway in LTE). The SMF 10-2 also allocates IP addresses to each UE 3.

[0028] The base stations 5 of the communication system 1 are configured to operate at least one cell 9 on an associated TDD carrier operating in unpaired spectrum. It will be appreciated that the base stations 5 may also operate at least one cell 9 on an associated FDD carrier operating in paired spectrum.

[0029] The base station 5 is also configured to transmit control information and user data over several downlink (DL) physical channels and to transmit several physical signals, and the UE 3 is configured to receive control information and user data over several DL physical channels and to transmit several physical signals, where the DL physical channels correspond to resource elements (REs) carrying information originating from higher layers and the DL physical signals correspond to REs used by the physical layer and not carrying information originating from higher layers.

[0030] Physical channels may include, for example, a physical downlink shared channel (PDSCH), a physical broadcast channel (PBCH), and a physical downlink control channel (PDCCH). The PDSCH carries data that shares the capacity of the PDSCH on a time and frequency basis. The PDSCH can carry various data items, including, for example, user data, UE-specific higher-layer control messages mapped down from higher channels, system information blocks (SIBs), and paging. The PDCCH carries downlink control information (DCI) to support several functions, including, for example, scheduling downlink transmissions on the PDSCH and uplink data transmissions on the physical uplink shared channel (PUSCH). The PBCH provides the Master Information Block (MIB) to the UE. The PBCH, in conjunction with the PDCCH, also supports time and frequency synchronization, which aids in cell acquisition, selection, and reselection. The UE 3 may receive a synchronization signal block (SSB), and the UE 3 may assume that the reception opportunities for the PBCH, primary synchronization signal (PSS), and secondary synchronization signal (SSS) are within consecutive symbols, forming an SS / PBCH block. The base station 5 may transmit several synchronization signal (SS) blocks corresponding to different DL beams. The total number of SS blocks may be limited, for example, to a duration of 5 ms as an SS burst. The periodicity of the SSB transmission may be signaled to the UE using any appropriate signaling (e.g., per serving cell using ssb-periodicityServingCell). The periodicity value of the SSB may be, for example, 20 ms or greater. For initial cell selection, the UE 3 may be configured to assume that the SS burst occurs with a periodicity of 2 frames.The UE 3 may also be provided with notification of which SSBs within the 5 ms duration are transmitted (eg, using ssb-PositionsInBurst).

[0031] DL physical signals may include, for example, reference signals (RS) and synchronization signals (SS). A reference signal (sometimes known as a pilot signal) is a signal having a predefined special waveform known to both the UE 3 and the base station 5. Reference signals may include, for example, a cell-specific reference signal, a UE-specific reference signal (UE-RS), a downlink demodulation signal (DMRS), and a channel state information reference signal (CSI-RS).

[0032] Similarly, the UE 3 is configured to transmit control information and user data over several uplink (UL) physical channels corresponding to REs carrying information originated from higher layers and UL physical signals corresponding to REs used at the physical layer that do not carry information originated from higher layers, and the base station 5 is configured to receive control information and user data over several UL physical channels corresponding to REs carrying information originated from higher layers and UL physical signals corresponding to REs used at the physical layer that do not carry information originated from higher layers. The physical channels may include, for example, a PUSCH, a physical uplink control channel (PUCCH), and / or a physical random-access channel (PRACH). The UL physical signals may include, for example, a demodulation reference signal (DMRS) for UL control / data signals and / or a sounding reference signal (SRS) used for UL channel measurement.

[0033] When the UE 3 first establishes a radio resource control (RRC) connection with a base station 5 via a cell, the UE 3 registers with the appropriate core network node (e.g., AMF, MME). The UE 3 is in the so-called RRC connected state, and the associated UE context is maintained by the network. When the UE 3 is in the so-called RRC idle or RRC inactive state, the UE 3 selects a suitable cell for camping, so that the network knows the approximate location (not necessarily at cell level) of the UE 3.

[0034] The base station 5 may be a base station 5 that is split between one or more distributed units (DUs) 50 and a central unit (CU) 60, where the CUs 60 typically perform higher level functions and communication with the next-generation core, and the DUs 50 perform lower level functions and communication over the air interface with nearby UEs 3 (i.e., within the cell operated by the gNB 5). This type of base station may be referred to as a "distributed" base station 5 or gNB 5. A distributed gNB 5 includes the following functional units:

[0035] gNB Central Unit (gNB-CU): A logical node that hosts the Radio Resource Control (RRC), Service Data Adaptation Protocol (SDAP), and Packet Data Convergence Protocol (PDCP) layers of a gNB (or the RRC and PDCP layers of an en-gNB) and controls the operation of one or more gNB-DUs. The gNB-CU terminates the so-called F1 interface connected to the gNB-DU.

[0036] gNB Distributed Unit (gNB-DU): A logical node that hosts the Radio Link Control (RLC), Medium Access Control (MAC), and Physical (PHY) layers of a gNB or en-gNB, and its operation is partially controlled by the gNB-CU. One gNB-DU supports one or more cells. One cell is supported by only one gNB-DU. The gNB-DU terminates the F1 interface connected to the gNB-CU.

[0037] gNB-CU-Control Plane (gNB-CU-CP): A logical node that hosts the control plane part of the RRC and PDCP protocols of the gNB-CU for an en-gNB or gNB. The gNB-CU-CP terminates the so-called E1 interface connected to the gNB-CU-UP and the F1 control plane (F1-C) interface connected to the gNB-DU.

[0038] gNB-CU-User Plane (gNB-CU-UP): A logical node that hosts the user plane portion of the PDCP protocol of the gNB-CU for the en-gNB, and the user plane portions of the PDCP protocol and SDAP protocol of the gNB-CU for the gNB. The gNB-CU-UP terminates the E1 interface connected to the gNB-CU-CP and the F1 user plane (F1-U) interface connected to the gNB-DU.

[0039] It will be appreciated that if a distributed base station or similar control plane-user plane (CP-UP) split is employed, the base station 5 may be split into separate control plane and user plane entities, each of which may include associated transceiver circuitry, antennas, network interfaces, controllers, memory, operating systems, and communication control modules. When the base station 5 comprises a distributed base station, the network interface also includes an E1 interface and an F1 interface (F1-C for the control plane and F1-U for the user plane) for communicating signals between the respective functions of the distributed base station.

[0040] <Frame structure> 2, which illustrates a typical frame structure that may be used in communication system 1, base stations 5 and UEs 3 of communication system 1 communicate with each other in the time domain using resources organized into frames of length 10 ms. Each frame comprises 10 equally sized subframes of length 1 ms. Each subframe is divided into one or more slots of equal length, each comprising 14 Orthogonal Frequency-Division Multiplexing (OFDM) symbols.

[0041] As can be seen in FIG. 2, communication system 1 supports multiple different numerologies (subcarrier spacing (SCS), slot length, and thus OFDM symbol length). Specifically, each numerology is identified by a parameter μ, where μ=0 represents 15 kHz (corresponding to the LTE SCS). Now, the SCS for other values ​​of μ can actually be derived from μ=0 by scaling up by a power of 2 (i.e., SCS=15×2 μ kHz). The relationship between the parameter μ and SCS (Δf) is shown in Table 1. [Table 1]

[0042] <RAN device> DU FIG. 3 is a schematic block diagram showing the main components of the DU 50 that can be used as part of the RAN device 5 for the communication system 1 shown in FIG. 1. As shown, the DU 50 has a transceiver circuit 451 for transmitting signals to and receiving signals from a communication device (such as the UE 3) via a radio unit (RU) and an associated DU-RU interface 453, and for transmitting signals to and receiving signals from the CU 60 of the RAN device 5 via a CU interface 454 (which can be divided into F1-U and F1-C interfaces, for example, for signaling in the user plane and control plane, respectively).

[0043] The DU 50 has a controller 457 for controlling the operation of the DU 50. The controller 457 is associated with a memory 459. Software may be pre-installed in the memory 459 and / or downloaded, for example, via the communication system 1 or from a removable data storage device (RMD). The controller 457 is configured to control the overall operation of the DU 50 by program instructions or software instructions stored in the memory 459 in this example.

[0044] As shown, these software instructions include, among other things, an operating system 461, a communication control module 463, an F1 module 465, a DU-RU module 468, a UE profile management module 473, and a mobility module.

[0045] The communication control module 463 is operable to control communication between the DU 50 and one or more RUs (and thus between the DU 50 and the UE 3) and between the DU 50 and the CU 60. The communication control module 463 is configured to overall control the reception of signals corresponding to uplink communication from the UE 3 and process the transmission of downlink communication to the UE 3.

[0046] The F1 module 465 is responsible for appropriate processing of signals received from or transmitted to the CU 60 via one or more CU (e.g., F1) interfaces 454. These signals may be separated into user plane signals received from or transmitted to the CU-UP portion of the CU 60 via the F1-U interface and control plane signals received from or transmitted to the CU-CP portion of the CU 60 via the F1-C interface.

[0047] The DU-RU module 468 is responsible for the proper processing of signals received from or transmitted to one or more RUs (eg, DU-RU) via interface 453 .

[0048] The DU management module 472 is responsible for managing the overall operation of the DU 50 and the overall performance of tasks required by the DU 50. These tasks include, among other things, the generation and transmission of appropriate messages using appropriate signaling application protocols depending on the functional division between the RU, DU 50, and CU 60, such as interpreting received MAC signaling and generating MAC signaling for transmission.

[0049] The UE profile management module 473 is responsible for performing the following UE profile-related functions: (where applicable) receiving and storing a UE profile or associated assistance / preference information from the UE 3 or from elsewhere in the network; determining an appropriate mobility-specific configuration based on the UE profile / assistance / preference information for implementation in the UE 3 and / or RAN equipment (where applicable); and / or (where applicable) providing configuration information for appropriately configuring the UE in a mobility-based configuration. The UE profile management module 473 may also store previous mobility information for the UE 3 (e.g., previous movements of the UE 3 between different communication cells of the network). The previous mobility information may be for use in any of the AI / ML methods related to the mobility of the UE 3, as described below. It will be understood that, depending on the implementation, the gNB-DU may not implement at least some of these features.

[0050] The mobility module 475 is responsible for controlling mobility procedures for one or more UEs 3. For example, the mobility module 475 may be configured to perform one or more measurements of UE 3 mobility or to select a candidate cell for handover. It will be appreciated that the mobility module 475 may be configured to perform control over any of the mobility methods described below (e.g., handover, etc.).

[0051] CU Figure 4 is a schematic block diagram illustrating the main components of a CU 60 of the RAN equipment for the communications system 1 shown in Figure 1. As shown, the CU 60 has transceiver circuitry 551 for transmitting signals to and receiving signals from the DUs 50 via one or more DU interfaces 554 (e.g., comprising an F1 interface that may be divided into F1-U and F1-C interfaces for user plane and control plane signaling, respectively), and for transmitting signals to and receiving signals from core network 7 functions via one or more core network interfaces 555 (e.g., including N2 and N3 interfaces, etc.).

[0052] The CU 60 has a controller 557 for controlling the operation of the CU 60. The controller 557 is associated with a memory 559. Software may be pre-installed in the memory 559 and / or may be downloaded, for example, via the communication system 1 or from a removable data storage device (RMD). The controller 557 is configured, in this example, to control the overall operation of the CU 60 by means of program or software instructions stored in the memory 559.

[0053] As shown, these software instructions include, among other things, an operating system 561, a communication control module 563, an F1 module 565, an E1 module 566, an N2 module 568, an N3 module 569, a CU-UP management module 571, a CU-CP management module 572, a UE profile management module 573, and a mobility module 575. The functionality of mobility module 575 is as previously described with reference to FIG.

[0054] The communication control module 563 is operable to control communications between the CU 60 and one or more DUs 50 (and thus between the CU 60 and the UE 3), and between the CU 60 and the core network 7. The communication control module 563 is configured to generally control the reception of signals corresponding to uplink communications from the UE 3, and to handle the transmission of downlink communications destined for the UE 3.

[0055] The F1 module 565 is responsible for appropriate processing of signals received from or transmitted to the DU 50 via one or more DU (e.g., F1) interfaces 554. These signals may be separated into user plane signals received at or transmitted by the CU-UP portion of the CU via the F1-U interface and control plane signals received at or transmitted by the CU-CP portion of the CU via the F1-C interface.

[0056] The E1 module 566 is responsible for the proper processing of signals transmitted between the CU-UP portion of the CU 60 and the CU-CP portion of the CU 60 via a corresponding internal CU interface (eg, E1).

[0057] The N2 module 568 is responsible for the appropriate processing of signals received from or sent to the AMF 8-1 via one or more corresponding core network interfaces 555 (eg, N2).

[0058] The N3 module 569 is responsible for the appropriate processing of signals received from or transmitted to one or more core network user plane functions via one or more corresponding core network interfaces 555 (e.g., N3).

[0059] The CU-UP management module 571 is responsible for managing the overall operation of the CU-UP portion of the CU 60 and the overall performance of tasks required for the CU-UP.

[0060] The CU-CP management module 572 is responsible for managing the overall operation of the CU-CP portion of the CU 60 and the overall performance of the tasks required of the CU-CP, including, among other things, the generation and transmission of appropriate messages using the appropriate signaling application protocol depending on the functional division between the RU, the DU 50, and the CU 60, such as interpreting received RRC signaling and generating RRC signaling for transmission.

[0061] The UE profile management module 573 is responsible for performing the following functions related to UE (mobility) profiles: (where applicable) receiving and storing a UE profile or associated assistance / preference information from the UE 3 or from elsewhere in the network; determining an appropriate mobility-specific configuration based on the UE profile / assistance / preference information for implementation in the UE 3 and / or the RAN equipment 5; and / or providing configuration information for appropriately configuring the UE in a mobility-based configuration. The UE profile management module 573 may also store previous mobility information for the UE 3 (e.g., previous movements of the UE 3 between different communication cells of the network). The previous mobility information may be for use in any of the AI / ML methods related to the mobility of the UE 3, as described below. It will be understood that, depending on the implementation, the CU 60 may not implement at least some of these features.

[0062] <System information and SIB> It will be appreciated that transmissions in the cell 9 of the base station 5 may include one or more broadcast transmissions and one or more unicast transmissions for reception by the UEs 3. The system information (SI) transmitted in the cell may include "minimum SI" (MSI) and "other SI" (OSI). The OSI may be broadcast on demand, for example, using the downlink shared channel (DL-SCH). The OSI may be broadcast upon request from a UE 3 in a radio resource control (RRC) idle or RRC inactive state. The OSI may also be requested by a UE 3 in an RRC connected state, for example, via one or more dedicated RRC transmissions.

[0063] The SI may include information to enable (e.g., configure) the UE 3 to complete cell selection, to enable the UE 3 to complete a cell reselection procedure, or to enable the UE 3 to receive one or more paging messages transmitted within the cell. The SI may be broadcast using a Master Information Block (MIB) and one or more System Information Blocks (SIBs).

[0064] The MSI comprises a MIB and a system information block 1 (SIB1). The MIB includes information for the UE 3 to use to receive SIB1, such as the subcarrier spacing of SIB1. The MIB provides information corresponding to the Control Resource Set (CORESET) and the search space. SIB1 may be referred to as the "remaining MSI" (RMSI). SIB1 may be transmitted in a dedicated RRC message, while other SIBs (e.g., SIB2 to SIB9) may be transmitted using one or more other appropriate RRC transmissions. The MIB and SIB1 may provide the UE 3 with notification of scheduling information for receiving and decoding other SIBs, such as SIB2 to SIB9, and may provide information for the UE 3 to use to receive one or more paging messages. The OSI may include, for example, SIB2 to SIB9 transmitted using the DL-SCH in an SI message. Mapping of SIB2 to SIB9 to their corresponding SI messages may be provided to the UE 3 by the base station 5. The MIB and SIB1 to SIB9 are described in more detail, for example, in 3GPP TS 38.331. For example, SIB2 provides information for intra-frequency, inter-frequency, and inter-system cell reselection, SIB3 provides cell-specific information for intra-frequency cell reselection, and SIB4 provides information for inter-frequency cell reselection. SIB5 provides information for inter-system cell reselection for 4G (LTE). SIB6 and SIB7 provide information for the earthquake and tsunami warning system (ETWS). SIB8 provides information for commercial mobile alert service (CMAS) notifications, for example, to provide warning text messages to UE3. SIB9 contains information about harmonized universal time (UTC), global positioning system (GPS) time (e.g., for GPS initialization), and local time.

[0065] The SIBs may be broadcast periodically (e.g., according to a predetermined periodic pattern) or alternatively, may be provided "on-demand," e.g., in response to a request from UE 3. For example, MIB may be transmitted with a period of 80 ms and a repetition occurring within 80 ms, while SIB1 may be transmitted with a period of 160 ms and a variable transmission repetition period (e.g., 20 ms) within 160 ms. SIB1 may be used to indicate to UE 3 which SIBs are transmitted periodically and which SIBs are available on-demand in response to a request from UE 3. UE 3 may be configured to request on-demand SIBs using MSG1 (Random Access Preamble), which may be referred to as an MSG1-based on-demand SI request, or MSG3 (RRC Connection Request), which may be referred to as an MSG3-based on-demand SI request.

[0066] A physical broadcast channel (PBCH) can be used to broadcast the MIB. The base station 5 may transmit the PBCH together with a synchronization signal (SS) (e.g., a primary synchronization signal (PSS) and a secondary synchronization signal (SSS)) in an SS / PBCH block. The SS / PBCH block comprises four orthogonal frequency-division multiplexed (OFDM) symbols that are mapped to the PSS, SSS, and PBCH associated with a demodulation reference signal (DM-RS). In the frequency domain, the SS / PBCH block consists of 240 consecutive subcarriers. When the UE 3 is in RRC connected mode, the base station 5 may provide the UE 3 with notification of the resources used for the SS / PBCH, for example, using dedicated signaling (e.g., for the anchor NES cell or non-anchor NES cell). The SIB1 may be transmitted using a physical downlink shared channel (PDSCH). The OSI may be transmitted similarly, for example, using the PDSCH.

[0067] When one or more beamformed transmissions are transmitted in a cell served by base station 5, only some of the SIs (e.g., some of the SIBs) may be transmitted using a particular beam or using a particular transmission / reception point (TRP).

[0068] <UEモビリティ> Figure 5 shows an overview of mobility procedures that may be performed in a communications system of the type illustrated in Figure 1. In this example, a handover of a UE 3 occurs from a source base station 5 to a target base station 5. However, as will be discussed in more detail later, the handover may also take place between, for example, two DUs 50, or between two cells associated with the same DU 50.

[0069] In optional step S501, the UE 3 performs measurements. The measurements may be measurements of signals transmitted by the source (R)AN node 5 or measurements of signals transmitted by the target (R)AN node 5. The measurements may be measurements of signal strength that can be used to determine that the UE 3 should be handed over from the source (R)AN node 5 to the target (R)AN node. In optional step S501, the UE 3 sends a corresponding measurement report to the source (R)AN node 5. The source (R)AN node can use the information provided in the measurement report to determine that the UE 3 should be handed over to the target (R)AN node 5. However, it will be appreciated that the determination that a handover should be performed may be made based on measurements performed by the source (R)AN node 5 or the target (R)AN node 5. Alternatively, the determination that a handover should be performed may be based on factors other than signal measurements, such as the level of congestion in the cell operated by the source (R)AN node 5.

[0070] In step S502, the source (R)AN node 5 sends a handover request to the target (R)AN node 5. In step S503, the target (R)AN node sends a corresponding acknowledgement of the handover request.

[0071] In step S504, the source (R)AN node sends a configuration for handover to the UE 3. The configuration for handover may be, for example, an RRC configuration sent in an RRC reconfiguration message.

[0072] In step S505, the UE 3 applies the received configuration for the handover and sends a notification to the target (R)AN node that the configuration is complete. The message sent in step S505 may be, for example, an RRC Reconfiguration Complete message.

[0073] Some example types of UE3 mobility procedures that may be performed in a communication system will now be described in more detail.

[0074] Conditional Handover (CHO) Conditional Handover (CHO) is a handover that is executed by the UE 3 when one or more handover execution conditions are met. The UE 3 starts evaluating the one or more execution conditions when it receives a CHO configuration and stops evaluating the one or more execution conditions when the handover is executed. The execution conditions may be based on, for example, measurements of reference signal received power (RSRP), reference signal received quality (RSRQ), RSRP and signal to noise interference ratio (RSRP-SINR) performed by the UE 3. In the case of layer 1 / layer 2 (L1 / L2) mobility, the handover is initiated based on the L1 / L2 measurement results.

[0075] Here, an example of CHO will be described. A "CHO ​​candidate cell" is a candidate cell for CHO and has a corresponding CHO configuration. The CHO configuration includes one or more CHO candidate cell configurations generated by the candidate base station 5 and one or more execution conditions generated by the source base station 5.

[0076] The execution conditions may include, for example, one or two trigger conditions, which may also be referred to as CHO events.

[0077] Similar to intra-NR RAN handover, in intra-NR RAN CHO, the preparation and execution phases of the conditional handover procedure may be performed without involving the core network, i.e., preparation messages are exchanged directly between the base stations 5. The release of resources at the source base station during the conditional handover completion phase is triggered by the target base station 5.

[0078] In the CHO method, the source base station 5 may determine that CHO should be used. The source base station 5 may request CHO for one or more candidate cells belonging to one or more candidate base stations 5. Then, a CHO request message may be sent to each candidate cell.

[0079] The candidate base station 5 sends a CHO response including the configuration of one or more CHO candidate cells to the source base station 5. A CHO response message may be sent for each candidate cell.

[0080] The source base station 5 may send an RRC reconfiguration message to the UE 3, which includes the configuration of one or more CHO candidate cells and one or more CHO execution conditions.

[0081] The UE 3 may send an RRC reconfiguration complete message to the source base station 5 .

[0082] If an initial data transfer is applied, the source base station 5 may send an initial status transfer message.

[0083] After receiving the CHO configuration, the UE 3 maintains connection with the source base station and starts evaluating the CHO execution conditions for one or more candidate cells. If at least one CHO candidate cell satisfies the corresponding CHO execution condition, the UE 3 detaches from the source base station, applies the corresponding configuration stored in the selected candidate cell, synchronizes with the candidate cell, and completes the RRC handover procedure by sending an RRC reconfiguration complete message to the target base station 5. After the RRC handover procedure is successfully completed, the UE 3 releases the stored CHO configuration.

[0084] The target base station 5 sends a handover success message to the source base station 5 to notify that the UE 3 has successfully accessed the target cell. In response, the source base station 5 sends a sequence number status transfer (e.g., SN STATUS TRANSFER) message.

[0085] The source base station 5 can then send a handover cancellation message towards other signaling connections or other candidate target base stations, if any, to cancel the CHO of the UE 3.

[0086] The conditional configuration for a conditional handover may be provided as a "delta configuration" relative to the configuration of the serving cell, in other words, the parameters and settings of the conditional configuration may be indicated by indicating the difference between the conditional configuration and the configuration of the serving cell.

[0087] The UE 3 may be configured to indicate to another entity within the communication system 1 that the UE 3 supports conditional handover, for example by sending a signal that includes a notification in a conditional handover field or information element.

[0088] A CHO candidate cell list may be used to indicate a list of candidate target cells for conditional handover. Candidate target cells for CHO may be referred to as CHO candidates. For example, up to eight candidate cells with associated conditional handover execution conditions may be configured for the UE 3. The number of execution conditions may be two (alternatively, one execution condition, or three or more execution conditions may be used). The UE 3 performs CHO towards the selected target cell if the condition is met by applying the corresponding conditional reconfiguration. This improves mobility robustness because the CHO configuration can be sent before the serving cell quality degrades, and the UE 3 can avoid mobility failure due to missed HO commands.

[0089] Transfer between DUs within a CU FIG. 6 shows an example of intra-CU inter-DU mobility.

[0090] In this case, the current serving cell and the candidate cell share the same CU. Because the source cell and the target cell are located in different DUs, the radio link control (RLC) layer is re-established and the medium access control (MAC) layer is reset.

[0091] 7 shows an exemplary method for inter-DU mobility. The procedure for L1 / L2-based inter-cell mobility from a source DU 50a to a target DU 50b is shown (however, it will be understood that inter-DU mobility does not necessarily have to be L1 / L2-based). As shown in the figure, the method includes a pre-configuration phase, an initial synchronization phase, and a cell switch phase, which will be described later.

[0092] <Pre-configuration> In steps 1 and 2, the UE 3 sends a layer 3 (L3) measurement report to the source DU 50a based on the measurement configuration. The measurement report is forwarded to the CU 60.

[0093] In steps 3-8, the CU 60 determines a candidate set for the UE 3, sends a preparation request to the target DU 50b, and receives a corresponding acknowledgement from the target DU 50b. Then, the CU 60 sends an RRC reconfiguration to the UE 3 via the source DU 50a, and receives a corresponding RRC reconfiguration complete message.

[0094] <Initial synchronization> In steps 9 to 11, the UE 3 performs L1 measurements and reports on reference signals (such as SSB or CSI-RS shown in FIG. 10) corresponding to inter-cell beams based on configuration from the network. Based on the L1 measurement reports, the communication system 1 may activate some transmission configuration information (TCI) states quasi-colocated (QCL-ed) with cells whose physical cell IDs (PCIs) are different from the serving cell. The UE 3 performs synchronization (downlink and optionally uplink) with these cells.

[0095] <Cell switching> In steps 12-13, based on the further L1 report, DU50 may indicate the target cell and beam (TCI state). UE3 applies the target cell configuration. In step 14, if no timing advance (TA) is available, UE3 performs RACH towards the indicated target cell. In steps 15 and 16, UE3 receives PDCCH from the target cell using the new TCI state.

[0096] Intra-DU mobility Figure 8 shows an example of intra-DU mobility, in which the current serving cell and the candidate cell share the same CU and DU, and there is no need to re-establish PDCP and RLC.

[0097] Intra-DU handover to additional PCI Figure 9 shows an example of an intra-DU handover to an additional physical cell ID (PCI). Within the DU, a UE 3 may receive a physical downlink shared channel (PDSCH) from a transmission reception point (TRP) associated with the additional PCI (different from the PCI of the current serving cell). In this scenario, a MAC reset may not be required.

[0098] Between cells and between DUs FIG. 10 shows the inter-cell inter-DU method.

[0099] In step 1, UE Context Setup / Modification is performed (for example, the CU sends a UE Context / Setup Modification Request message to the target DU).

[0100] In step 2, RRC reconfiguration (handover preparation) is performed.

[0101] In step 3, DL synchronization is performed.

[0102] In step 4, the source and target cell L1 measurement reports SSB-RSRP or SSB-SINR are sent from the UE 3 to the source DU 50a.

[0103] In step 5, a determination is made as to whether the HO conditions are met and the best cell / beam for HO is identified.

[0104] In step 6, a physical downlink control channel (PDCCH) for handover to the target cell (which may include a target cell index, a beam index, or a TCI status) is transmitted from the source DU 50a to the UE 3.

[0105] Step 7 involves UL synchronization (which may include transmission of delta timing advance (deltaTA) as described below) and optional RACH procedures.

[0106] Base station triggered L1 mobility FIG. 11 illustrates a base station triggered L1 mobility method including measurement report filtering.

[0107] Steps 1 to 4 in FIG. 11 correspond to steps 1 to 4 in FIG.

[0108] In step 5, the L1 measurement report reconfiguration (which may include one or more filtering parameters) is sent from the CU 60 to the source DU 50a.

[0109] In step 5.1, L1 measurement report filtering is performed at the source DU 50a.

[0110] Step 5.2 in FIG. 11 corresponds to step 5 in FIG.

[0111] Steps 6 and 7 in FIG. 11 correspond to steps 6 and 7 in FIG.

[0112] Inter-cell inter-DU method including conditional handover FIG. 12 illustrates an inter-cell inter-DU method including conditional handover.

[0113] In step 1, UE context setup / modification is performed.

[0114] In step 2, RRC reconfiguration (CHO configuration) is performed.

[0115] In step 3, DL synchronization is performed in UE3.

[0116] In step 4, source and target cell L1 measurement reports are sent from the UE 3 to the source DU 50a.

[0117] In step 5, an L1 measurement report reconfiguration (which may include measurement report filtering parameters) is sent from CU60 to UE3.

[0118] In step 5.1, source and target cell L1 measurement reports are sent from the UE 3 to the source DU 50a.

[0119] In step 6, the UE determines whether one or more CHO conditions are met and identifies the best cell / beam for HO.

[0120] Step 7 in FIG. 12 corresponds to step 7 in FIG.

[0121] Inter-cell inter-DU method including conditional handover Figure 13 shows an inter-cell, inter-DU method including L1 measurement report reconfiguration. As can be seen, Figure 13 shows a variation of the method shown in Figure 12, in which an L1 measurement report reconfiguration (which may include filtering parameters) is sent from the CU 60 to the source DU 50a, and an L1 measurement report reconfiguration (which may include measurement report filtering parameters, as described in more detail below) is sent from the source DU 50a to the UE 3.

[0122] 10 to 13, handover preparation may include measurement configuration and inter-DU synchronization signal block (SSB) SS / PBCH Block Measurement Timing Configuration (SMTC) cooperation. SMTC is an SSB-based measurement timing configuration.

[0123] 10 to 13, the RRC reconfiguration may include measurement configuration, measurement reporting configuration, target cell list and random access channel (RACH) configuration, SMTC (inter-DU) SSB related information of the target cell and associated DU-ID, and inter-frequency measurement gap configuration. If measurement gaps are used, inter-frequency measurements may be performed from OFDM symbols corresponding to the overlapping time span between the SMTC window duration and the measurement gap, as defined by higher layers for the minimum measurement time.

[0124] Regarding step 4 of Figures 10 to 13, note that SSB-based radio link monitoring (RLM), beam management (BM), and beam failure recovery (BFR) can be outside the active bandwidth part (BWP). The beam measurement report may contain candidate cell IDs or may use an implicit mapping of beam indices to neighboring cells and therefore associated DU-IDs.

[0125] If no handover occurs when the timer expires, the source cell may start measurement reporting again via the PDCCH containing a 1-bit "start / stop" indication.

[0126] In Figures 10 to 13, the DCI may indicate a new target beam index or a TCI status.

[0127] <Artificial Intelligence(AI) / Machine Learning(ML)> Figure 14 shows a functional framework for AI / ML and how the various entities of the framework may interact with each other.

[0128] The entities include a data collection function 41, a model training function 43, a model inference function 45, and an actor 47. The data collection function 41 provides input data (training data) to the model training function 43 and the model inference function 45. The collected data may be, for example, data related to mobility (e.g., handover of a UE 3). For example, the data may be collected by a base station 5 (e.g., by receiving measurement reports from the UE 3 or by receiving data from another base station 5 or core network node / function) and transmitted to another base station 5, which generates the AI / ML model inference output (or alternatively, the same base station that obtained the data may generate the AI / ML model output). The model training function 43 performs ML model training, validation, and testing, which may generate model performance metrics as part of a model testing procedure. The model reasoning function 45 provides an AI / ML model inference output (e.g., a prediction or a decision), and the actor 47 is a function or node that receives the output from the model reasoning function 45 and triggers or performs a corresponding action (e.g., the base station 5 increasing / decreasing its transmit power or initiating a handover procedure for the UE 3). The AI / ML model inference output may, for example, be a prediction of the mobility of the UE 3 (e.g., an expected path, route, or trajectory, inter-cell or inter-beam mobility, or an expected handover). The functions shown in FIG. 14 may be co-located at a single node of the communications network (e.g., at a base station 5 or core network node / function) or may be distributed among multiple network nodes (e.g., multiple base stations 5).

[0129] Terms referred to by 3GPP in the context of this framework include: AI / ML Model: A data-driven algorithm that applies machine learning techniques to generate a set of outputs, including predictive information and / or decision parameters, based on a set of inputs. AI / ML training: An online or offline process for training an AI / ML model by learning the features and patterns that best represent the data, and obtaining a trained AI / ML model for inference. AI / ML inference: The process of using a trained AI / ML model to make a prediction or derive a decision (e.g., a handover decision) based on collected data (e.g., UE3 mobility information) and the AI / ML model. Training data: Data used as input to the AI / ML model training function. Inference data: Data to input into the AI / ML model inference function. Model Deployment / Update: Used to initially deploy a trained, validated, and tested AI / ML model to the model inference function, or to transport an updated model to the model inference function.

[0130] As described in more detail below, the data collection function 41 may be performed at various nodes of the communications network (e.g., at one or more base stations 5). Improved methods of collecting data relating to the mobility of one or more UEs 3 are described for use in generating predictions of future UE 3 mobility. Additionally, improved methods of transmitting feedback to one or more nodes of the communications network are described.

[0131] <UEモビリティのためのAI / ML> Next, an improved use of AI / ML to predict the mobility of a UE 3 (e.g., predicted route / path, inter-cell or inter-beam mobility, or handover) will be described. It will be appreciated that the mobility of a UE 3 may include any of the types of handovers described above or any other suitable mobility procedure (e.g., inter-beam mobility). Predicting the location or mobility of a UE 3 advantageously enables more efficient operation of a communications network. For example, the predicted mobility of a UE 3 can be used to more efficiently manage radio resources (e.g., select a target handover cell). The predicted mobility of a UE 3 can also be used for early data forwarding (e.g., for use in a CHO procedure, such as one of the CHO procedures described above).

[0132] As discussed above with reference to Figure 14, information collected by nodes / functions in a communications network can be used as training data for an AI / ML model and can be used as inference data for use in generating one or more model inferences using the AI / ML model. Information used as training data and / or to generate one or more model inferences may be referred to as "AI / ML information." Methods for requesting and transmitting AI / ML information are now described.

[0133] 15 is a diagram showing an example of an AI / ML information request and an AI / ML response. In step S1501, the first base station 5-1 transmits an AI / ML information request to the second base station 5-2. The AI / ML request is a request for AI / ML information (such as information about the actual mobility of the UE 3) from the second base station 5-2.

[0134] After receiving the AI / ML information request in step S1501, the second base station 5-2 transmits an AI / ML information response including the AI / ML information to the first base station 5-1. In addition, the second base station 5-2 may start periodically reporting the AI / ML information to the first base station 5-1 in response to receiving the AI / ML information request. The periodic reporting may be configured using a corresponding AI / ML information reporting configuration indicated by the AI / ML information request (including, for example, the periodicity of the reporting, the number of reports, or the duration / period of the reporting). The AI / ML information request may include an information element (IE) indicating that the second base station 5-2 starts or stops periodically reporting the AI / ML information to the first base station 5-1. Alternatively, the AI / ML information request may be a request for a single report of the AI / ML information from the second base station 5-2, rather than a periodic report.

[0135] If the second base station 5-2 is unable to transmit the requested AI / ML information to the first base station 5-1 (e.g., because the requested information is unavailable at the second base station 5-2), the second base station 5-2 may transmit a corresponding notification, e.g., an AI / ML information failure message, to the first base station 5-1 that the second base station 5-2 is unable to provide the requested information. The AI / ML information failure message may include an indication of the reason (e.g., a cause value) why the second base station 5-2 is unable to provide the requested AI / ML information.

[0136] Upon receiving the AI / ML information, the first base station 5-1 may use the AI / ML information to train (or update) a corresponding AI / ML model (e.g., with respect to the mobility of the UE 3) or to generate a prediction (e.g., a prediction of the mobility of the UE 3). Alternatively, the first base station 5-1 may forward the AI / ML information to another network node for use with an AI / ML model at that network node.

[0137] In the example shown in FIG. 15, the AI / ML information response may include the requested AI / ML information, or alternatively, the AI / ML information response may be a notification that the second base station 5-2 will transmit the AI / ML information in a subsequent AI / ML information update (e.g., an acknowledgment of the AI / ML information request). FIG. 16 is a diagram showing an example of an AI / ML information update. In step S1601, the second base station 5-2 determines to transmit an AI / ML information update to the first base station 5-2. For example, the second base station 5-2 may determine to transmit an AI / ML information update to the first base station 5-2 based on the reporting periodicity received by the second base station 5-2 in step S1501 of FIG. 15, or may determine to transmit an AI / ML information update based on a change in the AI / ML information stored in the second base station 5-2 (or based on new AI / ML information acquired by the second base station 5-2). In step S1602, the second base station 5-2 transmits the AI / ML information to the first base station 5-1 in an AI / ML information update.

[0138] Projected UE Mobility Next, an improved method for transmitting predicted mobility of UE 3 to a node / function in a communication network will be described. The predicted mobility of UE 3 may be generated using an AI / ML model, for example, using the AI / ML information received in step S1602 of FIG. 16. The predicted mobility of UE 3 (which may also be referred to as predicted mobility information or AI / ML model output information) may include a predicted route, path, trajectory, or heading of UE 3, or may be, for example, a notification of predicted inter-cell or inter-beam mobility of UE 3.

[0139] <Base station scenario> In an inter-base station handover scenario (e.g., one of the inter-base station handover methods described above), the inventors have recognized that the predicted mobility of UE3 can be advantageously included in the handover request message (e.g., in step S502 of Figure 5), allowing the target base station 5 to utilize the predicted mobility information of UE3 (e.g., for more efficient configuration of resources at the target base station 5).

[0140] The handover request message sent in step S502 may include predicted UE mobility information (e.g., predicted UE trajectory). As mentioned above, the predicted UE mobility information may indicate a predicted route, path, or future location of the UE 3, or a predicted inter-cell or inter-beam mobility of the UE 3.

[0141] The handover request message may include a predicted UE mobility accuracy indicating the accuracy of the prediction. The predicted UE mobility accuracy may be expressed, for example, as a percentage (e.g., as a percentage probability that the prediction is correct or accurate) or in any other suitable format (e.g., as a number of standard deviations). The prediction accuracy may indicate the accuracy of the prediction of the route, path, or location of the UE 3 and / or the accuracy of the prediction of the duration that the UE 3 will remain in a particular location (e.g., a particular cell).

[0142] The handover request message may include improved UE history information. For example, instead of simply reporting UE history information (e.g., previous location) of UE 3 at the cell level, the UE history information may include the location history of UE 3 at the beam level, tracking area (TA) level, or RAN based notification area (RNA) level.

[0143] The handover request message can include a notification of the identity of the AI / ML model used to generate the predicted UE3 mobility. The handover request message can also include a notification of the input to the AI / ML model used to generate the predicted UE3 mobility. For example, the handover request message can include a notification of the UE mobility type (e.g., high speed, low speed, medium speed, etc.) input to the AI / ML model, the UE type (e.g., Internet of Things (IoT) UE, wearable UE, Redcap UE, fixed UE, etc.), and / or the UE location information or UE fingerprint (e.g., radio frequency fingerprint, etc.).

[0144] This example of UE mobility information and prediction accuracy information is described in reference to the handover request message, but this is not necessarily the case. Alternatively, the UE mobility information and / or prediction accuracy information can be included in any other suitable type of transmission to the target base station (e.g., via the handover configuration completion message for UE3 and step S505).

[0145] The received information can be used, for example, to train or retrain the AI / ML model at the target base station 5, and advantageously enables determining a more accurate prediction of the future mobility of UE3 using the AI / ML model at the target base station 5.

[0146] <Inter-DU scenario> Here, an improved method for inter-DU handover will be described. The inter-DU handover can be, for example, any of the inter-DU handover scenarios described above (e.g., referring to FIG. 6).

[0147] During inter-DU handover, the CU may send a UE context setup / modification request message to the target DU (e.g., as described with reference to step 1 of Figure 10). The UE context setup / modification request message may, for example, enable the target base station 5 to set up signaling radio bearers (SRBs) and data radio bearers (DRBs).

[0148] Advantageously, in this example, the UE context setup / modification request message includes cell-level, beam-level, TA-level or RNA-level UE historical information, enabling the target base station 5-2 to more efficiently configure resources (such as time or frequency radio resources) during the handover procedure.

[0149] The UE context setup / modification request message may advantageously include predicted mobility information for the UE 3, as described above for the inter-base station scenario. Similarly, the UE context setup / modification request message may include AI / ML model identity, prediction accuracy, and / or AI model inputs, as described above for the inter-base station scenario.

[0150] <NGハンドオーバシナリオ> Next, an improved next generation (NG) handover (NGHO) scenario will be described. During NGHO, predicted UE mobility can be transmitted to a target base station via an AMF. In a first example, the predicted UE mobility can be forwarded to the target base station in a transparent container via a source base station (e.g., using a transparent container IE in a next generation application protocol (NGAP) "handover required" message from the source NG-RAN node to the target NG-RAN node). Alternatively, the predicted UE mobility information can be transmitted in an NGAP handover request message using an appropriate AI / ML prediction information element. The information transmitted to the target base station via the AMF can include the UE's predicted mobility information, as described above for the inter-base station scenario. Similarly, the information transmitted to the target base station via the AMF can include an AI / ML model identity, prediction accuracy, and / or AI model input, as described above for the inter-base station scenario.

[0151] As shown in FIG. 14, the feedback may be used to improve the AI / ML model (e.g., by using the feedback to train the AI / ML) or to verify the accuracy of the AI / ML model. For example, the feedback may be used to determine that the AI / ML model should be retrained. In this example, the feedback may be returned to the source base station via the AMF. The feedback information may be forwarded using an NGAP procedure, such as the RAN AI / ML Information Forwarding procedure. Advantageously, the source base station 5 can thus improve the accuracy of the AI / ML model or verify that the AI / ML model is operating as intended (or within an acceptable accuracy range). The feedback sent to the source base station may include, for example, information indicating the actual location / mobility of the UE, or any other suitable mobility information. Similarly, in the inter-base station and inter-DU example described above, the feedback may be sent from the target base station / DU to the source base station / DU (e.g., directly or via an intermediate network node) using any suitable message or transmission.

[0152] <Beam level prediction / feedback information> As described above, the UE mobility prediction may include predicting the mobility of the UE 3 at the cell level. However, alternatively, the mobility prediction may be advantageously performed at the beam level. Mobility prediction at the beam level allows for more efficient configuration of resources implemented at the target base station due to improved prediction accuracy. Similarly, feedback returned to the node operating the AI / ML model may be at the beam level rather than just the cell level, allowing the accuracy of the AI / ML model to be determined at the beam level rather than the cell level. For both the mobility prediction information and the mobility feedback information, the information may be provided at the beam level rather than the cell level, or may be provided in addition to cell-level information. The level of granularity (e.g., cell level, beam level, etc.) may be configurable by the network.

[0153] UE Mobility Feedback We now describe an example in which mobility feedback information (e.g., the actual UE 3 location or mobility, which may be at the cell level or beam level, for example) of the AI / ML model is sent to the source base station 5 (e.g., from the target base station or from another base station) following handover from the source base station 5. As mentioned above, the feedback may be used at the source base station 5 to verify the accuracy of the AI / ML model, to trigger retraining of the AI / ML model, or to generate further predictions using the AI / ML model. However, in this example, since handover of the UE 3 away from the source base station 5 has occurred, the feedback information may not be directly available at the source base station 5 and is sent to the source base station by another node in the communication network (e.g., the target base station or another base station, such as a further base station).

[0154] After receiving the mobility feedback information, the source base station 5 may determine that the prediction accuracy of the AI / ML model is too low and decide to retrain the AI / ML model, thereby advantageously avoiding a scenario in which the AI / ML model becomes unacceptably inaccurate.

[0155] In this example, the source base station 5 is the node in the network where the AI / ML model predictions are generated (and where the AI / ML is retrained, if necessary). Therefore, the source base station 5 may be referred to as the primary base station 5 (or primary RAN node 5). In other words, the AI / ML architecture is centralized in a particular base station 5. However, this need not necessarily be the case; alternatively, the AI / ML architecture may be provided in another node / function within the communications network, such as a core network node / function. The primary base station 5 (or other network node hosting the AI / ML model) may request AI / ML information from other nodes within the communications network (e.g., another base station 5) using the procedures described above with reference to Figures 15 and 16. Alternatively or additionally, other nodes within the network may determine to send AI / ML information to the primary base station without receiving an AI / ML information request from the primary base station 5. For example, the target base station 5 may determine to send AI / ML mobility information to the primary base station 5 in response to a handover of the UE 3 to the target base station (e.g., after a predetermined time after the handover or in response to a further handover of the UE 3 from the target base station).

[0156] The selection of the primary base station 5 may be configurable by the network. The primary base station 5 may be selected for a particular UE 3 based on, for example, one or more characteristics of the UE 3 (e.g., mobility characteristics). As an example, the UE 3 may typically travel between the user's home and the user's office on a particular weekday. The home or office is within the coverage area of ​​a particular base station 5, and this base station may be selected to serve as the primary base station for the UE 3's AI / ML model because it is most likely to have the greatest amount of information about the UE 3's mobility characteristics. When the UE 3 is handed over from the primary base station 5 to a target base station 5 in a handover procedure (e.g., to a base station providing a coverage area for a shopping center the user visits on weekends), the target base station may receive a mobility prediction generated using the AI / ML mobility model from the primary base station 5 during the handover procedure (e.g., in step S502 of FIG. 5). The target base station 5 may also feed back information regarding the actual mobility of the UE 3 (e.g., trajectory, etc.) to the primary base station 5, so that the primary base station 5 has improved knowledge regarding the mobility of the UE 3 (which may be used by the primary base station 5, for example, to verify the accuracy of AI / ML model predictions, as described above).

[0157] 17 shows an example in which UE mobility information is fed back to the source base station 5-1 following handover of the UE 3 to a first target base station 5-2 and subsequently to a second target base station 5-3. In this example, the source base station 5-1 is the primary base station and hosts the AI / ML model for predicting the mobility of the UE 3. Advantageously, information obtained at the second target base station 5-3 regarding the mobility of the UE 3 can be fed back to the source base station 5-1 even if the source base station 5-1 does not have a direct communication link with the second target base station 5-3.

[0158] Steps S1701 and S1702 are the same as steps S501 and S502 in Figure 5, and therefore will not be repeated here. It should be noted that the measurements performed by the UE 3 may be generated in a time to trigger (TTT) manner, and the UE 3 may perform one or more additional measurements (shown in dashed boxes in Figure 17), which may be transmitted to the source base station 5-1 or the target base stations 5-2, 5-3 as needed.

[0159] In step S1703, the source base station 5-1 (which in this example is the primary base station of the AI / ML model) sends a handover request to the first target base station 5-2. Advantageously, the handover request in this example includes a transaction ID (also called an "event ID" and identifies a particular "transaction" of the UE or a particular handover) or a UE ID (which may be an indication of the identity of the UE 3), and an indication of the identity of the primary base station 5-1 (e.g., a primary base station ID or any other suitable type of indication for identifying the node to which feedback is to be sent, such as an indication that a handover request is being sent by the primary base station 5-1 hosting the AI / ML model).

[0160] The transaction ID or UE ID may be used to associate feedback for the AI / ML model with the UE 3. When feedback is returned to the source base station 5-1 in association with the transaction ID or UE ID, the source base station 5-1 can determine that the feedback corresponds to the mobility information of that particular UE 3. The transaction ID may also be used by the target base station to determine that feedback should be sent to the source base station 5-1.

[0161] The notification of the identity of the primary base station can be used by other network nodes (such as the first target base station 5-2 or the second target base station 5-3) to determine which network node to send UE mobility feedback to. The notification of the identity of the primary network node / function enables other network nodes / functions to determine which network node / function is the primary network node / function for the AI / ML model of the UE 3.

[0162] The handover request message sent in step S1703 may also include any of the information related to the predicted mobility of UE 3 for the handover request message described above (e.g., as described above with reference to the inter-base station, inter-DU, and NG handover scenarios). For example, the handover request may include predicted mobility information, AI / ML model identity, prediction accuracy, and / or AI model input.

[0163] In step S1704, the first target base station 5-2 transmits a handover request acknowledgement to the source base station 5-1.

[0164] In step S1705, the source base station 5-1 transmits RRC reconfiguration information (which may be referred to as handover configuration information) to the UE 3 for handover. The RRC reconfiguration information may include a notification to the UE 3 to include a notification of the additional measurement results in a subsequent transmission to the first target base station 5-2 (e.g., in the RRC reconfiguration complete message sent in step S1706). The notification to the UE 3 to include a notification of the additional measurement results may be referred to as an AI mobility enhancement report notification. In this example, the UE 3 includes a notification of the additional measurement results in the RRC reconfiguration complete message of step S1706 if additional measurements were made after the measurement report was sent to the source base station in step S1702 (indicated by the dashed box in Figures 17 and 18). Thus, advantageously, measurement information corresponding to measurements taken by the UE 3 before the handover is transmitted to at least one of the base stations and can be fed back to the primary base station (e.g., to determine whether the decision to hand over the UE to the target base station 5-2 was made, e.g., appropriately or correctly, at the right time) (the target base station 5-2 can advantageously use the information to improve the handover decision process at the target base station 5-2). In this example, the AI ​​mobility enhancement report notification is transmitted to the UE 3 in an RRC reconfiguration message, although the notification may alternatively be transmitted to the UE 3 in any other suitable transmission (e.g., a dedicated transmission after receiving the handover request acknowledgement from the target base station 5-2 and before transmitting the RRC reconfiguration message to the UE 3).

[0165] In step S1706, the UE 3 sends an RRC reconfiguration complete message to the first target base station 5-2, and also includes the additional measurement report as indicated by the source base station 5-1 in the RRC reconfiguration message of step S1705.

[0166] In step S1707, the first target base station 5-2 feeds back mobility information for the AI / ML mobility model to the source base station 5-1 (i.e., the primary base station for the AI / ML mobility model). The information transmitted in step S1701 may be, for example, information indicating the actual mobility (e.g., trajectory) of the UE 3 after handover. As mentioned above, the mobility information fed back to the primary base station 5-1 may be at the cell level, beam level, TA level, RNA level, or any other level of granularity or precision. If a notification of additional measurement results is received at the first target base station 5-2 from the UE 3 in step S1706, the first target base station 5-2 includes the notification of the further measurement results in the information transmitted to the source base station 5-1. In this example, the UE mobility information is transmitted to the source base station 5-1 in association with the transaction ID or UE ID received in step S1703, so that the source base station 5-1 can identify which UE 3 the feedback information relates to.

[0167] In step S1708, the first target base station 5-2 transmits a handover request to the second target base station 5-3. The first target base station 5-2 may determine to transmit the handover request based on, for example, a mobility prediction received from the primary base station 5-1 in step S1703 (e.g., indicating that the UE 3 is likely to move into the area of ​​coverage provided by the cell or beam of the second target base station 5-3). As described above for step S1703, the first target base station 5-2 includes an indication of the identity of the primary base station 5-1 in the handover request message, including a transaction ID or UE ID. Thus, the second target base station 5-2 can advantageously determine which base station is the primary base station 5-1 and can transmit any subsequent feedback information of the AI / ML model of the UE 3 in association with the transaction ID or UE ID (which allows the primary base station 5-1 to determine which UE 3 the feedback relates to). The first target base station 5-2 may also include any other information regarding the AI / ML mobility model (e.g., predicted UE mobility information, model identity, or model input) received from the source base station 5-1 in step S1703.

[0168] In step S1709, in this example, the second target base station 5-3 has a direct communication link (e.g., an Xn interface) to the source base station 5-1 and therefore transmits the UE mobility information feedback directly to the source base station 5-1. The second target base station 5-3 can advantageously identify the source base station 5-1 to send the feedback to based on the indication of the primary base station identity received in step S1708 from the first target base station 5-2. As mentioned above, the mobility information fed back to the source base station 5-1 may include the actual location or mobility of the UE 3 (e.g., at a cell or beam level) or any other suitable information related to the mobility of the UE 3 (e.g., the duration that the UE 3 is at a particular location) that can be used in conjunction with the AI / ML model at the source base station 5-1.

[0169] Figure 18 shows a variation of the method of Figure 17 in which the second target base station 5-3 transmits UE mobility information feedback to the source base station 5-1 via the first target base station 5-2. The second target base station 5-3 may transmit the UE mobility information feedback to the source base station 5-1 via the first target base station 5-2, for example, because the second target base station 5-3 does not have a direct communication link with the source base station 5-1 (e.g., there is no Xn interface with the source base station 5-1).

[0170] Steps S1801 to S1808 are the same as steps S1701 to S1708 described with reference to FIG. 17, and therefore will not be described again here.

[0171] In step S1809, the second target base station 5-3 transmits UE mobility information feedback to the first target base station 5-2. As mentioned above, the information transmitted in step S1809 may be, for example, information indicating the actual mobility (e.g., trajectory) of the UE 3 after handover to the second target base station 5-3, and the feedback information may be transmitted in association with a transaction ID or UE ID (which allows the primary base station 5-1 to determine which UE 3 the feedback relates to). The transmission in step S1809 may also include notification of the identity of the primary base station 5-1 (but this is not necessary, since the first target base station 5-2 has already received notification of the identity of the primary base station 5-1 in step S1803 for the handover of the same UE 3).

[0172] In step S1810, the first target base station 5-2 forwards the UE mobility information feedback to the source base station 5-1. Thus, advantageously, the source base station 5-1 (which is the primary base station in the AI / ML model and generates the mobility prediction) can receive the UE mobility feedback in the AI / ML model from the second target base station 5-3 even if the second target base station 5-3 does not have a direct communication link with the source base station 5-1 (e.g., there is no Xn interface).

[0173] Distributed AI / ML Architecture On the other hand, in the examples described above with reference to Figures 17 and 18, the network may include a primary node / function that hosts the AI / ML model and generates mobility predictions, or the AI / ML model may be distributed among various nodes in the network. For example, multiple base stations 5 may host the AI / ML model and generate mobility predictions. Advantageously, this may increase the processing required in some network nodes, but distributing the AI / ML model among network nodes beneficially reduces the number of mobility predictions transmitted between nodes. For example, with reference to Figure 17, if the first target base station 5-2 is configured to generate a prediction of the mobility of the UE 3 using the AI / ML model, the first target base station 5-2 does not necessarily need to receive the mobility prediction from the source base station 5-1.

[0174] In this example where an AI / ML model (or multiple AI / ML models - not necessarily the same model used at each base station 5) is provided to multiple base stations 5, UE mobility feedback information may still be provided to each base station that generates predictions using the AI / ML model (e.g., to verify the accuracy of the model, as described above).

[0175] As an example, UE 3 may typically travel between a user's home and the user's office on a particular weekday. The home or office is within the coverage area of ​​a first base station 5 that hosts an AI / ML model for predicting the mobility of UE 3. During a handover procedure, UE 3 may be handed over from the first base station 5-1 to a second base station 5-2 (e.g., to a base station that provides a coverage area for a shopping center the user visits on weekends). In this example, the second base station 5-2 also hosts the AI / ML model for predicting the mobility of UE 3. Thus, the second base station 5-2 may use the AI / ML model to generate a prediction of the future mobility of UE 3. The second base station 5-2 may also transmit UE mobility information (e.g., actual UE 3 mobility) to the first base station 5-1, for example, to enable verification of the accuracy of the AI / ML model at the first base station, as described above. In this example, both the first and second base stations 5-1 and 5-2 may use the AI / ML model to generate a prediction of UE 3 mobility, but advantageously, information indicative of the actual mobility of UE 3 (e.g., trajectory) is exchanged between the base stations 5-1 and 5-2, improving the overall accuracy of the AI / ML mobility model used in the system. Even if the second base station 5-2 hosts the AI / ML mobility model, the first base station 5-1 may still send the mobility prediction in the handover request (e.g., as described with reference to step S1703 of FIG. 17 ), since it can use knowledge of the mobility prediction made in the first base station configuration 5-2 to improve the accuracy of the mobility prediction made in the second base station 5-2. In other words, the mobility prediction made in the first base station 5-1 may be used as input to the AI / ML model in the second base station 5-2. Similarly, the inputs used for the AI / ML model in the first base station 5-1, or any other suitable information, such as the type or identity of the AI / ML model used in the first base station 5-1, may be sent to the second base station 5-2 in the handover request.

[0176] If the AI / ML model is provided to multiple base stations 5, the method shown in FIG. 17 may be performed, as described above, by transmitting, in the handover request, information about the AI / ML model used by a particular base station 5 (including the mobility prediction, inputs to the AI / ML model, and type or ID of AI / ML) to other base stations and feeding back UE mobility information for use in validating or refining the model. However, because in this example each base station hosts an AI / ML mobility model and predicts the mobility of UEs 3, in a variation of the method of FIG. 17, the handover request sent by a particular base station includes information about the AI / ML model hosted at that particular base station (including information indicating the mobility prediction, inputs to the AI / ML model, type or ID of AI / ML, the identity of the base station hosting the AI / ML model, and transaction / UE identity). In contrast, for example, the AI / ML model and prediction information included in step S1708 of FIG. 17 corresponds to the AI / ML model hosted at the primary base station 5-1 (because in that example the first target base station 5-2 does not host an AI / ML mobility model). Also, in this case, because the handover request of step S1708 includes information about the AI / ML model of the first target base station 5-2 (including information indicating the mobility prediction, the input to the AI / ML model, the type or ID of the AI / ML, the identity of the first target base station 5-1 hosting the AI / ML model, and the transaction / UE identity), the second target base station 5-3 transmits the UE mobility feedback of step 1709 to the first target base station 5-2 (rather than the source base station 5-1). Nevertheless, the first target base station 5-2 can optionally forward the UE mobility information feedback received from the second target base station 5-3 to the source base station 5-1, for example, for use in verifying the AI / ML model used by the source base station 5-1 as described above.

[0177] AI / ML Configuration Next, some further improvements related to AI / ML models are described. AI / ML model configuration information (e.g., notification of the type of model to use) can be exchanged between base stations (or other communication nodes / functions) using any suitable method. For example, AI / ML model configuration information can be exchanged using Xn setup request / response procedures. Alternatively, dedicated signaling or procedures can be used to transmit the AI / ML model configuration information.

[0178] The AI / ML model configuration information may include a list of supported use cases (the AI / ML model does not necessarily have to be for predicting UE mobility). Supported use cases include, for example, energy saving, traffic steering, anomaly detection, quality of experience (QoE) optimization, mobility robustness optimization (MRO), RAN slice service level agreement (SLA) guarantee, massive multiple-input multiple-output (MIMO) beamforming optimization, network slice subnet instance (NSSI) resource allocation, optimized coverage and capacity optimization (CCO), mobility load balancing (MLB), RACH optimization, or UE transmit power optimization. The AI / ML configuration information may include an indication of the specific AI / ML model to use for a particular use case. For an AI / ML mobility model, the configuration information may include UE mobility prediction granularity (e.g., whether the mobility / trajectory prediction is at the cell level, beam level, or any other level). The AI / ML configuration information may also include an indication of whether feedback is required (e.g., from another network node, as described above with reference to step S1707 of FIG. 17). The feedback may include, for example, UE performance feedback (eg, indicating the communication capabilities of the UE) or UE mobility / trajectory feedback (eg, indicating the actual mobility or location of the UE).

[0179] <User device> FIG. 19 is a schematic block diagram showing the main components of the UE 3 shown in FIG.

[0180] As shown, the UE 3 includes transceiver circuitry 310 operable to transmit signals to and receive signals from a base station 5 via one or more antennas 330 (e.g., comprising one or more antenna elements). The UE 3 includes a controller 370 that controls the operation of the UE 3. The controller 370 is associated with a memory 390 and coupled to the transceiver circuitry 310. Although not necessary for its operation, the UE 3 may, of course, include all the usual functionality of a conventional UE 3 (e.g., a user interface 350, such as a touchscreen / keypad / microphone / speaker, for enabling direct user control and interaction), which may be provided by any one or any combination of hardware, software, and firmware, as appropriate. Software may be pre-installed in the memory 390 and / or downloaded, for example, via a communications network or from a removable data storage device (RMD).

[0181] Controller 370, in this example, is configured to control the overall operation of UE 3 via program or software instructions stored in memory 390. As shown, these software instructions include, among other things, an operating system 410 and a communications control module 430.

[0182] The communications control module 430 is operable to control communications between the UE 3 and its one or more serving base stations 5 (and other communications devices, such as additional UEs and / or core network nodes, connected to the base stations 5). The communications control module 430 is configured to generally handle uplink communications over associated uplink channels (e.g., over the physical uplink control channel (PUCCH), random access channel (RACH), and / or physical uplink shared channel (PUSCH)), including both dynamic and semi-static signaling (e.g., SRS). The communications control module 430 is also configured to generally handle reception of downlink communications over associated downlink channels (e.g., over the physical downlink control channel (PDCCH) and / or physical downlink shared channel (PDSCH)), including both dynamic and semi-static signaling (e.g., CSI-RS). The communications control module 430 is responsible for, for example, determining where to monitor downlink control information (e.g., the locations of the CSS / USS, CORESET, and associated PDCCH candidates to monitor); determining resources (including interleaved resources and resources subject to frequency hopping) to be used by the UE 3 for transmission / reception of UL / DL communications; managing frequency hopping at the UE side; determining how slots / symbols are configured (e.g., for UL, DL, or SBFD communications); determining which bandwidth portion or portions are configured for the UE 3; determining how uplink transmissions should be coded; and appropriately applying any SBFD-specific communications configurations. The communications control module 430 may be configured to control communications (e.g., to send measurement reports according to any of the methods described above) according to any of the methods described above.

[0183] <Base station> FIG. 20 is a schematic block diagram illustrating the main components of a base station 5 for the communication system 1 shown in FIG. 1. As shown, the base station 5 includes a transceiver circuit 510 for transmitting signals to and receiving signals from communication devices (such as UE 3) via one or more antennas 530 (e.g., single or multi-panel antenna arrays / large-scale antennas), and a core network interface 550 (e.g., comprising N2, N3, and other reference points / interfaces) for transmitting signals to and receiving signals from network nodes in the core network 7. Although not shown, the base station 5 may also connect to other base stations via appropriate interfaces (e.g., the so-called "Xn" interface in NR). The base station 5 includes a controller 570 that controls the operation of the base station 5. The controller 570 is associated with a memory 590. Software may be pre-installed in the memory 590 and / or downloaded, for example, via the communication system 1 or from a removable data storage device (RMD). The controller 570 is configured, in this example, to control the overall operation of the base station 5 by means of program or software instructions stored in memory 590 .

[0184] As shown, these software instructions include, among other things, an operating system 610 and a communications control module 630 .

[0185] The communications control module 630 is operable to control communications between the base station 5, the UE 3, and other network entities connected to the base station 5. The communications control module 630 is configured to generally control the reception and decoding of uplink communications over associated uplink channels (e.g., over the physical uplink control channel (PUCCH), random-access channel (RACH), and / or physical uplink shared channel (PUSCH)), including both dynamic and semi-static signaling (e.g., SRS). The communications control module 630 is also configured to generally handle the transmission of downlink communications over associated downlink channels (e.g., over the physical downlink control channel (PDCCH) and / or physical downlink shared channel (PDSCH)), including both dynamic and semi-static signaling (e.g., CSI-RS). The communications control module 630 is responsible for managing full-duplex communications (e.g., SBFD), including separation of UL and DL communications over different physical antenna elements, where appropriate. The communication control module 630 is responsible for, for example: determining where the UE 3 should be configured to monitor downlink control information (e.g., the locations of the CSS / USS, CORESET, and associated PDCCH candidates to monitor); determining resources (including interleaved resources and resources subject to frequency hopping) to be scheduled for UE transmission / reception of UL / DL communications; managing frequency hopping at the base station; configuring slots / symbols appropriately (e.g., for UL, DL, or SBFD communications, etc.); configuring one or more bandwidth portions for the UE 3; providing related configuration signaling to the UE 3; etc. The communication control module 630 may be configured to control communications (e.g., receive or send mobility information of the UE 3, or a handover request) according to any of the methods described above.

[0186] The AI / ML module 650 is operable to use AI / ML to predict the mobility of the UE 3 according to any of the methods described above. The base station 5 may be configured to train or retrain the AI / ML model as described above (e.g., in response to UE mobility information fed back to the base station 5 from another node in the network, such as another base station 5).

[0187] <Core network nodes / functions> 21 is a block diagram illustrating the main components of a core network node or function, such as the AMF, CPF, UPF, SMF, or OAM. As shown, the core network function includes a transceiver circuit 710 operable to transmit signals to and receive signals from other nodes (including UEs 3, base stations 5, and other core network nodes) via a network interface 720. A controller 730 controls the operation of the core network function in accordance with software stored in memory 740. The software may be pre-installed in memory 740 and / or may be downloaded, for example, via the communication system 1 or from a removable data storage device (RMD). The software includes, among other things, an operating system 750 and a communication control module 760.

[0188] The communication control module 760 is responsible for handling (generating / sending / receiving) signaling between core network functions and other nodes such as the UE 3, base station 5, and other core network nodes. The signaling may include, for example, UE context / UE capability notifications for the UE 3 related to energy saving.

[0189] As shown in Figure 21, the core network node / function may also include an AI / ML module 770. If present, the AI / ML module 770 is operable to use AI / ML to predict the mobility of the UE 3 according to any of the methods described above. The core network node / function may be configured to train or retrain the AI / ML model as described above (e.g., in response to UE mobility information being fed back to the core network node / function from another node in the network, such as base station 5).

[0190] <Modifications and Replacements> As those skilled in the art will appreciate, numerous modifications and alternatives can be made to the exemplary embodiments described above while still benefiting from the present disclosure embodied therein.

[0191] Although the AI / ML methods described above are described primarily with reference to UE3 mobility, the improved methods of propagating information and using model outputs to train / update AI / ML models may also be applied to other types of AI / ML models and predictions. For example, an AI / ML model may output model inferences for fault prediction or security. The information used to train the AI / ML model and generate model inferences does not necessarily have to be information about UE3 mobility.

[0192] While the above examples are described with reference to an AI / ML model, it will be appreciated that the above method is advantageous even when the model is not an AI / ML model. Any other suitable type of model or function may be used to predict the mobility of UE 3. For example, the methods shown in FIGS. 17 and 18 are useful for ensuring that mobility information is fed back to a node / function that uses a predictive model to generate mobility prediction information, even when the model is not an AI / ML model (e.g., to verify the accuracy of the model even when the model cannot be trained or retrained). However, the method is particularly advantageous when the model is an AI / ML model, because the information fed back to the primary network node / function can be used to iteratively update / train the model or trigger retraining.

[0193] For example, terms specific to a cellular communication generation (e.g., 2G, 3G, 4G, 5G, 6G, etc.) may be used to refer to a particular communication entity for clarity, but it will be understood that technical features described for a given entity are not limited to devices of that particular communication generation. The technical features may be implemented in any functionally equivalent communication entity regardless of the terms used to refer to them.

[0194] In the above description, the UE and base station have been described for ease of understanding as having several separate functional components or modules. While these modules may be provided in this manner in certain applications, for example, where an existing system is modified to implement the present disclosure, in other applications, for example, in systems designed from the beginning with the features of the present invention in mind, these modules may be incorporated into the overall operating system or code and therefore may not be identifiable as separate entities.

[0195] In the above exemplary embodiments, several software modules have been described. As will be appreciated by those skilled in the art, the software modules may be provided in compiled or non-compiled form, and may be supplied as a signal over a computer network or on a recording medium. Furthermore, the functions performed by some or all of this software may be performed using one or more dedicated hardware circuits. However, the use of software modules is preferred because it facilitates updating the base station or UE to update its functionality.

[0196] Each controller may comprise any suitable form of processing circuitry, including, for example, but not limited to, one or more hardware-implemented computer processors, microprocessors, central processing units (CPUs), arithmetic logic units (ALUs), input / output (IO) circuitry, internal memory / cache (program and / or data), processing registers, communication buses (such as, for example, a control bus, a data bus, and / or an address bus), direct memory access (DMA) facilities, hardware or software-implemented counters, pointers, and / or timers, etc. Various other modifications will be apparent to those skilled in the art and will not be described in further detail herein.

[0197] The base station may comprise a "distributed" base station having a central unit "CU" and one or more individual distributed units (DUs).

[0198] User equipment (or "UE," "mobile station," "mobile device," or "wireless device") in this disclosure is an entity that connects to a network via a wireless interface.

[0199] It should be noted that the present disclosure is not limited to dedicated communication devices, but can be applied to any device having communication capabilities as described in the following paragraphs.

[0200] The terms "user equipment" or "UE" (as this term is used by 3GPP), "mobile station," "mobile device," and "wireless device" are generally intended to be synonymous with each other and include standalone mobile stations such as terminals, cell phones, smartphones, tablets, cellular IoT devices, IoT devices, and machines. It will be understood that the terms "mobile station" and "mobile device" also encompass devices that remain stationary for extended periods of time.

[0201] The UE may be, for example, an item of equipment for production or manufacturing and / or an item of energy-related machinery (such as, for example, equipment or machinery such as boilers, engines, turbines, solar panels, wind turbines, hydroelectric generators, thermal generators, nuclear generators, batteries, nuclear systems and / or related equipment, heavy electrical machinery, pumps including vacuum pumps, compressors, fans, blowers, hydraulic equipment, pneumatic equipment, metalworking machinery, manipulators, robots and / or application systems thereof, tools, dies or molds, rolls, conveying equipment, elevators, material handling equipment, textile machinery, sewing machinery, printing and / or related machinery, paper converting machinery, chemical machinery, mining machinery and / or construction machinery and / or related equipment, machinery and / or implements for the agricultural, forestry, and / or fisheries industries, safety and / or environmental protection equipment, tractors, precision bearings, chains, gears, power transmission equipment, lubrication equipment, valves, pipe fittings, and / or application systems for any of the foregoing equipment or machinery, etc.).

[0202] A UE may be, for example, an item of transportation equipment (e.g., transportation equipment such as rail cars, automobiles, motorcycles, bicycles, trains, buses, carts, rickshaws, ships and other watercraft, aircraft, rockets, satellites, drones, balloons, etc.) A UE may be, for example, an item of information and communications equipment (e.g., information and communications equipment such as electronic computers and related equipment, communications and related equipment, electronic components, etc.).

[0203] The UE may be, for example, a refrigerator, a refrigerator application product, an item of trade and / or service industry equipment, a vending machine, an automated service machine, an office machine or equipment, a home appliance or electronic device (e.g., household appliances such as audio equipment, video equipment, loudspeakers, radios, televisions, microwave ovens, rice cookers, coffee machines, dishwashers, washing machines, dryers, electric fans or related equipment, vacuum cleaners, etc.).

[0204] The UE may be, for example, an electrical application system or device (such as, for example, an electrical application system or device, such as an x-ray system, a particle accelerator, a radioisotope device, a sonic device, an electromagnetic application device, a power application device, etc.).

[0205] The UE may be, for example, an electronic lamp, a lighting fixture, a measuring instrument, an analyzer, a tester, or a surveying or detecting device (such as, for example, a smoke alarm, a human alarm sensor, a motion sensor, a radio tag, or other surveying or detecting device), a watch or clock, laboratory equipment, optical equipment, medical equipment and / or systems, a weapon, an edged item, a hand tool, etc.

[0206] The UE may be, for example, a wirelessly equipped personal digital assistant or related equipment (such as a wireless card or module designed to be attached to or inserted into another electronic device (e.g., a personal computer, an electrical measuring machine, etc.)).

[0207] The UE may be part of a device or system that uses various wired and / or wireless communication technologies to provide the applications, services, and solutions described below with respect to the "internet of things (IoT)."

[0208] Internet of Things devices (or "Things") may be equipped with appropriate electronics, software, sensors, network connections, etc. that enable these devices to collect and exchange data with each other and other communicating devices. IoT devices may comprise automated machines that follow software instructions stored in internal memory. IoT devices may operate without the need for human supervision or interaction. IoT devices may also remain stationary and / or inactive for extended periods of time. IoT devices may be implemented as part of (typically) stationary equipment. IoT devices may also be incorporated into non-stationary equipment (e.g., vehicles) or attached to animals or people being monitored / tracked.

[0209] It will be appreciated that IoT technologies may be implemented on any communication device that can connect to a communication network to send / receive data, whether such communication device is controlled by human input or by software instructions stored in memory.

[0210] It will be appreciated that IoT devices may also be referred to as Machine-Type Communication (MTC) devices or Machine-to-Machine (M2M) communication devices. It will be appreciated that a UE may support one or more IoT or MTC applications. Some examples of MTC applications are listed in the table below. This list is not exhaustive and is intended to inform some examples of machine-type communication applications. [Table 2]

[0211] The applications, services, and solutions may include Mobile Virtual Network Operator (MVNO) services, emergency wireless communication systems, Private Branch eXchange (PBX) systems, PHS / digital cordless telecommunications systems, Point of sale (POS:) systems, incoming advertising systems, Multimedia Broadcast and Multicast Service (MBMS:), Vehicle to Everything (V2X) systems, train radio systems, location-related services, disaster / emergency wireless communication services, community services, video streaming services, femtocell application services, Voice over LTE (VoLTE) services, billing services, wireless on-demand services, roaming services, activity monitoring services, telecommunications carrier / communication network selection services, function restriction services, Proof of Concept (PoC) services, personal information management services, ad hoc networks / Delay Tolerant Networking (DTN) services, and the like.

[0212] Furthermore, the above-mentioned UE categories are merely examples of applications of the concepts and exemplary embodiments described herein, and it should be understood that these concepts and exemplary embodiments are not limited to the above-mentioned UEs and may be modified in various ways.

[0213] Various other modifications will be apparent to those skilled in the art and will not be described in further detail here.

[0214] In a first aspect, the present disclosure provides a method in an access network node, the method comprising: obtaining predicted mobility information indicating predicted mobility of a user equipment (UE); performing a handover procedure for handover of the UE to another access network node; and transmitting the predicted mobility information to the other access network node, wherein the predicted mobility information comprises information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0215] Obtaining the predicted mobility information may include generating, at the access network node, the predicted mobility information using a mobility model.

[0216] The predicted mobility information may include notification of a predicted location, predicted route, or predicted trajectory of the UE, and the predicted mobility accuracy, the precision of the predicted mobility, or the uncertainty associated with the predicted mobility may include spatial accuracy, precision, or uncertainty associated with the predicted location, predicted route, or predicted trajectory of the UE, respectively.

[0217] The predicted mobility information may include an indication of a predicted duration that the UE will be located at a particular location, and the accuracy of the predicted mobility, the precision of the predicted mobility, or the uncertainty associated with the predicted mobility may include a time accuracy, precision, or uncertainty associated with the duration, respectively.

[0218] The predicted mobility information may include at least one of the predicted mobility of the UE at a cell level, a beam level, a tracking area level, or a radio access network based notification area, RNA, level.

[0219] The method may further include sending previous mobility information to another network node notifying the UE of its previous mobility, the previous mobility information indicating at least one of the UE's previous mobility at a beam level, the UE's previous mobility at a tracking area level, or the UE's previous mobility at an RNA level.

[0220] The notification of at least one mobility model input used to generate the predicted mobility using the mobility model may include at least one of a notification of a type of UE mobility, a notification of a speed or velocity of the UE, a notification of a type of UE, or a notification of a previous location of the UE.

[0221] Sending the predicted mobility information to another access network node may include sending the predicted mobility information to another access network node in a handover request message, a UE context setup request message, or a UE context modification request message.

[0222] Sending the predicted mobility information to another access network node may include sending the predicted mobility information to another access network node via a core network node.

[0223] In a second aspect, the present disclosure provides a method in an access network node, the method comprising: performing a handover procedure for handover of a user equipment, UE, from another access network node to the access network node; and receiving, from the other access network node, predicted mobility information indicating predicted mobility of the UE, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0224] The method further includes configuring at least one communication resource for the UE based on the predicted mobility information or performing configuration for a subsequent handover of the UE based on the predicted mobility information.

[0225] The predicted mobility information may be received directly from another access network node or via a core network node.

[0226] In a third aspect, the present disclosure provides a method of a core network node, the method comprising: performing a handover procedure for handover of a user equipment, UE, from a first access network node to a second access network node; receiving predicted mobility information from the first access network node, the predicted mobility information indicating predicted mobility of the user equipment, UE; and transmitting the predicted mobility information to the second access network node, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0227] In a fourth aspect, the present disclosure provides a method in a first access network node, the method comprising: obtaining predicted mobility information indicating a predicted mobility of a user equipment UE; performing a handover procedure for handover of the UE to a second access network node; and transmitting the predicted mobility information to the second access network node, wherein the predicted mobility information comprises information for identifying a network node to which UE mobility feedback corresponding to an actual mobility of the UE after the handover is performed is to be transmitted.

[0228] The information for identifying the network node to which the UE mobility feedback should be sent may include information indicating the identity of the network node that generated the predicted mobility.

[0229] Obtaining the predicted mobility information may include generating, at the first access network node, the predicted mobility information using a mobility model, and the information for identifying a network node to which the UE mobility feedback should be sent may include a notification that the UE mobility feedback should be sent to the first access network node.

[0230] The notification may be the identity of the first access network node.

[0231] The method may further include receiving mobility feedback and using the mobility feedback to determine accuracy of the predicted mobility or using the mobility feedback as input to a mobility model to generate a further predicted mobility for the UE.

[0232] The received mobility feedback may include an indication that the mobility feedback corresponds to the UE.

[0233] The notification that the mobility feedback corresponds to the UE may include a notification of the identity of the UE, a notification identifying a handover of the UE to the second access network node, or a notification identifying the event of a handover of the UE to the second access network node.

[0234] The method may include sending a notification to a second access network node having the predicted mobility information that the mobility feedback corresponds to the UE.

[0235] Obtaining the predicted mobility information may include receiving predicted mobility information generated by a third access network node using a mobility model, and the information for identifying a network node to which the UE mobility feedback should be sent may include a notification that the UE mobility feedback should be sent to the third access network node.

[0236] The method may further include at least one of receiving the predicted mobility information directly from the third access network node and sending the UE mobility feedback directly to the third access network node, or receiving the predicted mobility information directly from a fourth access network node or a core network node and sending the UE mobility feedback to the third access network node via the fourth access network node or via the core network node.

[0237] The mobility feedback may be sent to a third access network node along with an indication that the mobility feedback corresponds to the UE.

[0238] The notification that the mobility feedback corresponds to the UE may include a notification of the identity of the UE, a notification identifying a handover of the UE to the first access network node, or a notification identifying the event of a handover of the UE to the first access network node.

[0239] The method may include receiving a notification that the mobility feedback corresponds to a UE having predicted mobility information.

[0240] The mobility feedback may indicate at least one of the UE's mobility at cell level, the UE's mobility at beam level, the UE's mobility at tracking area level, or the UE's mobility at radio access network based notification area, RNA, level.

[0241] In a fifth aspect, the present disclosure provides a method in a first access network node, the method performing a handover procedure for handover of a UE from a second access network node to the first access network node, and receiving from the second access network node predicted mobility information indicating a predicted mobility of a user equipment, UE, generated by the second access network node using a mobility model, the predicted mobility information including information for identifying that UE mobility feedback corresponding to an actual mobility of the UE after the handover has been performed should be transmitted to the second access network node, the method further including transmitting the UE mobility feedback to the second access network node.

[0242] The information for identifying that the UE mobility feedback should be sent to the second access network node may include an identity of the second access network node.

[0243] In a sixth aspect, the present disclosure provides a method in a first access network node, the method performing a handover procedure for handover of a UE from a second access network node to the first access network node, and receiving from the second access network node predicted mobility information indicating a predicted mobility of a user equipment, UE, generated by a third access network node using a mobility model, the predicted mobility information including information for identifying that UE mobility feedback corresponding to an actual mobility of the UE after the handover is performed should be transmitted to the third access network node, the method further including transmitting the UE mobility feedback to the third access network node.

[0244] The information for identifying that the UE mobility feedback should be sent to a third access network node may include an identity of the third access network node.

[0245] Sending the UE mobility feedback to the third access network node may include sending the UE mobility feedback directly to the third access network node, or sending the UE mobility feedback to the third access network node via the second access network node.

[0246] In a seventh aspect, the present disclosure provides a method in a first access network node, the method including: receiving a measurement report from a user equipment, UE, the measurement report indicating a result of a first measurement performed by the UE in a cell of the first access network node; transmitting to the UE handover configuration information for a handover procedure for handover of the UE from the first access network node to a second access network node, the handover configuration information including a notification that a notification of a result of a second measurement performed by the UE in the cell of the first access network node after the measurement report was transmitted to the first access network node should be transmitted by the UE to the second access network node; and performing the handover procedure for handover of the UE from the first access network node to the second access network node.

[0247] The method may further include receiving information from the second access network node indicative of a result of the second measurement.

[0248] In an eighth aspect, the present disclosure provides a method in a second access network node, the method including: performing a handover procedure for handover of a UE from a first access network node to the second access network node; receiving notification of results of measurements performed by the UE in a cell of the first access network node; and transmitting, to the first access network node, information indicating results of the measurements performed by the UE in the cell of the first access network node.

[0249] In a ninth aspect, the present disclosure provides a method for a user equipment, UE, the method including: transmitting a measurement report to a first access network node, the measurement report indicating a result of a first measurement performed by the UE in a cell of the first access network node; receiving handover configuration information for a handover procedure for handover of the UE from the first access network node to a second access network node, the handover configuration information including a notification that a notification of a result of a second measurement performed by the UE in the cell of the first access network node after the measurement report is sent to the first access network node should be sent by the UE to the second access network node; performing a second measurement in the cell of the first access network node; performing a handover procedure for handover of the UE from the first access network node to the second access network node; and transmitting a notification of the result of the second measurement to the second access network node.

[0250] Sending a notification of the result of the second measurement to the second access network node may include sending the notification of the result of the second measurement to the second access network node in a radio resource control (RRC) reconfiguration complete message.

[0251] In a tenth aspect, the present disclosure provides a method of an access network node in a communications network, the method comprising receiving model configuration information for configuration of a model at the access network node, the model being for generating one or more predictions corresponding to usage or operation of the communications network, the model configuration information comprising at least one of: a notification of supported use of the model; an identity of the model, the model identified by the identity being for use to generate the one or more predictions; and a notification of whether the access network node requests feedback for training the model or from another node in the communications network to which the access network node sends the one or more predictions to determine accuracy of the predictions generated using the model.

[0252] The model may be a mobility model for generating a prediction of the mobility of a user equipment, UE, and the model configuration information may include an indication of whether the mobility prediction should be generated at a cell level, beam level, tracking area level, or radio access network based notification area, RNA, level.

[0253] The method may further include sending a model configuration information request message to the other access network node to request model configuration information from the other access network node, and receiving the model configuration information from the other access network node.

[0254] In an eleventh aspect, the present disclosure provides an access network node, comprising: means for obtaining predicted mobility information indicating predicted mobility of a user equipment (UE); means for performing a handover procedure for handover of the UE to another access network node; and means for transmitting the predicted mobility information to another access network node, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0255] In a twelfth aspect, the present disclosure provides an access network node, comprising: means for performing a handover procedure for handover of a user equipment, UE, from another access network node to the access network node; and means for receiving predicted mobility information from the other access network node, the predicted mobility information indicating predicted mobility of the UE, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0256] In a thirteenth aspect, the present disclosure provides a core network node comprising: means for performing a handover procedure for handover of a user equipment, UE, from a first access network node to a second access network node; means for receiving predicted mobility information from the first access network node, the predicted mobility information indicating predicted mobility of the user equipment, UE; and means for transmitting the predicted mobility information to the second access network node, wherein the predicted mobility information includes information indicating at least one of accuracy of the predicted mobility, accuracy of the predicted mobility, or uncertainty regarding the predicted mobility, an indication of the identity of a mobility model used to generate the predicted mobility, or an indication of at least one mobility model used to generate the predicted mobility using the mobility model.

[0257] In a fourteenth aspect, the present disclosure provides a first access network node, comprising: means for obtaining predicted mobility information indicating predicted mobility of a user equipment (UE); means for performing a handover procedure for handover of the UE to a second access network node; and means for transmitting the predicted mobility information to the second access network node, wherein the predicted mobility information includes information for identifying a network node to which UE mobility feedback corresponding to an actual mobility of the UE after the handover is performed is to be transmitted.

[0258] In a fifteenth aspect, the present disclosure provides a first access network node, further comprising: means for performing a handover procedure for handover of a UE from a second access network node to the first access network node; means for receiving from the second access network node predicted mobility information indicating predicted mobility of a user equipment, UE, generated by the second access network node using a mobility model; the predicted mobility information including information for identifying that UE mobility feedback corresponding to an actual mobility of the UE after the handover is performed should be transmitted to the second access network node; and means for the first access network node to transmit the UE mobility feedback to the second access network node.

[0259] In a sixteenth aspect, the present disclosure provides a first access network node, further comprising: means for performing a handover procedure for handover of a UE from a second access network node to the first access network node; means for receiving from the second access network node predicted mobility information indicating predicted mobility of a user equipment, UE, generated by a third access network node using a mobility model; the predicted mobility information including information for identifying that UE mobility feedback corresponding to an actual mobility of the UE after the handover is performed should be transmitted to the third access network node; and means for the first access network node to transmit the UE mobility feedback to the third access network node.

[0260] In a seventeenth aspect, the present disclosure provides a first access network node, the first access network node comprising: means for receiving a measurement report from a user equipment, UE, the measurement report indicating a result of a first measurement performed by the UE in a cell of the first access network node; means for transmitting to the UE handover configuration information for a handover procedure for handover of the UE from the first access network node to a second access network node, the handover configuration information including a notification that a notification of a result of a second measurement performed by the UE in the cell of the first access network node after the measurement report is transmitted to the first access network node should be transmitted by the UE to the second access network node; and means for performing the handover procedure for handover of the UE from the first access network node to the second access network node.

[0261] In an eighteenth aspect, the present disclosure provides a second access network node, the second access network node including: means for performing a handover procedure for handover of a UE from a first access network node to the second access network node; means for receiving notification of a result of a measurement performed by the UE in a cell of the first access network node; and means for transmitting to the first access network node information indicating a result of the measurement performed by the UE in the cell of the first access network node.

[0262] In a nineteenth aspect, the present disclosure provides a user equipment, UE, comprising: means for transmitting a measurement report to a first access network node, the measurement report indicating a result of a first measurement performed by the UE in a cell of the first access network node; means for receiving handover configuration information for a handover procedure for handover of the UE from the first access network node to a second access network node, the handover configuration information including a notification that a notification of a result of a second measurement performed by the UE in the cell of the first access network node after the measurement report is transmitted to the first access network node should be transmitted by the UE to the second access network node; means for performing a second measurement in the cell of the first access network node; means for performing a handover procedure for handover of the UE from the first access network node to the second access network node; and means for transmitting a notification of the result of the second measurement to the second access network node.

[0263] In a twentieth aspect, the present disclosure provides an access network node in a communications network, the access network node including means for receiving model configuration information for configuration of a model at the access network node, the model for generating one or more predictions corresponding to usage or operation of the communications network, the model configuration information including at least one of: an indication of supported use of the model; an identity of the model, the model identified by the identity is for use to generate the one or more predictions; and an indication of whether the access network node requests feedback for training the model or requests feedback from another node in the communications network to which the access network node sends the one or more predictions for determining accuracy of predictions generated using the model.

[0264] Although the present disclosure has been specifically shown and described with reference to exemplary embodiments thereof, the present disclosure is not limited to these exemplary embodiments. Those skilled in the art will understand that various changes in form and details can be made without departing from the spirit and scope of the present disclosure as defined by the claims. Furthermore, each embodiment can be appropriately combined with at least one of the embodiments.

[0265] All or part of the exemplary embodiments disclosed above can be described as follows, but are not limited to the following:

[0266] (Appendix 1) 1. A method of a network node, comprising: transmitting a message including predicted mobility information indicating predicted mobility of a user equipment (UE) to another network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of method.

[0267] (Appendix 2) Information indicating the accuracy of predicted mobility is Information indicating the accuracy with which the UE will be located at the corresponding position; or Information indicating the accuracy of the duration for which the UE will remain at the corresponding position including at least one of The method described in Appendix 1.

[0268] (Appendix 3) The predicted mobility information includes a predicted trajectory of the UE and information indicating the accuracy of the predicted mobility for each position included in the predicted trajectory. 3. The method according to claim 1 or 2.

[0269] (Appendix 4) The granularity of the information showing the predicted trajectory is Cell level, Beam level, Tracking Area Level, or Notification Area (RNA) level based on Radio Access Network corresponds to at least one of The method described in Appendix 3.

[0270] (Appendix 5) The message includes information indicating a history of the UE's trajectory; The granularity of the information showing the trajectory history of the UE is Cell level, Beam level, Tracking Area Level, or Notification Area (RNA) level based on Radio Access Network corresponds to at least one of 5. The method of any one of appendices 1 to 4.

[0271] (Appendix 6) At least one input of the mobility model is the type of UE mobility, The speed or velocity of the UE, The type of UE, or Previous location of the UE including at least one of 6. The method of any one of appendices 1 to 5.

[0272] (Appendix 7) generating predicted mobility information using the mobility model; 7. The method of any one of appendices 1 to 6.

[0273] (Appendix 8) The message is, a handover request message; UE Context Setup Request message, a UE context modification request message, or Handover Required Message including at least one of 8. The method of any one of appendices 1 to 7.

[0274] (Appendix 9) The predicted mobility information is transmitted to another network node via a core network node. 9. The method of any one of appendices 1 to 8.

[0275] (Appendix 10) The message includes a notification of the network node and a data identity or a UE identifier corresponding to the feedback of the predicted mobility information, and the method comprises: receiving a further message comprising feedback from another network node or a further network node to which the UE has been handed over from the other network node, using the notification and data identity or the UE identifier; 10. The method of any one of appendices 1 to 9.

[0276] (Appendix 11) The feedback is based on measurement reports sent by the UE. 11. The method described in Appendix 10.

[0277] (Appendix 12) sending a report notification to the UE to cause the UE to include the measurement report in a Radio Resource Control (RRC) reconfiguration complete message; The measurement report is sent from the UE based on the report notification; The method described in Appendix 11.

[0278] (Appendix 13) Further messages contain measurement reports, 13. The method according to claim 11 or 12.

[0279] (Appendix 14) The feedback includes the actual trajectory of the UE after the handover is performed. 14. The method of any one of appendices 10 to 13.

[0280] (Appendix 15) using the feedback to determine the accuracy of the predicted mobility or using the feedback as an input to a mobility model to generate a further predicted mobility for the UE. 15. The method of any one of appendices 10 to 14.

[0281] (Appendix 16) The granularity of the feedback is Cell level, Beam level, Tracking Area Level, or Notification Area (RNA) level based on Radio Access Network corresponds to at least one of 16. The method of any one of appendixes 10 to 15.

[0282] (Appendix 17) transmitting the mobility model configuration to another network node; The mobility model is configured as follows: Information indicating at least one use case of the mobility model; a respective framework for at least one mobility model per use case; Including, 17. The method of any one of appendixes 1 to 16.

[0283] (Appendix 18) Each framework is UE trajectory granularity, The need for feedback of the UE's performance, or Need for feedback of UE trajectory accuracy including information indicating at least one of The method described in Appendix 17.

[0284] (Appendix 19) The configuration is a base station interface setup request message; Base station interface setup response message, a base station interface change request message; Base station interface change response message, a mobility model configuration request message, or Mobility Model Configuration Response Message transmitted in at least one of 19. The method according to claim 17 or 18.

[0285] (Appendix 20) 1. A method of a network node, the method comprising: receiving, from another network node, predicted mobility information for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of method.

[0286] (Appendix 21) 1. A method of a core network node, the method comprising: receiving, from a network node, predicted mobility information for a mobility of a user equipment, UE, indicating predicted mobility of the UE; transmitting the predicted mobility information to another network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of method.

[0287] (Appendix 22) 1. A method for a user equipment (UE), comprising: sending a first measurement report to a network node indicating results of measurements performed by the UE; receiving, after the first measurement report has been sent to the network node, a notification from the network node to cause the UE to send, in a radio resource control, RRC, reconfiguration complete message, a second measurement report to another network node, the second measurement report indicating a result of a second measurement performed by the UE; sending a second measurement report to another network node; The second measurement report is used to generate feedback of the predicted mobility of the UE; method.

[0288] (Appendix 23) an access network node, a user equipment, comprising: means for transmitting predicted mobility information indicating predicted mobility of the UE to another network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of Access network node.

[0289] (Appendix 24) an access network node, means for receiving, from another network node, predicted mobility information for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of Access network node.

[0290] (Appendix 25) A core network node, a means for receiving predicted mobility information from a network node, the predicted mobility information indicating a predicted mobility of the UE, for the mobility of the UE; means for transmitting the predicted mobility information to another access network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; Information indicating the mobility model used to generate the predicted mobility; or Information indicative of at least one input to a mobility model for generating a predicted mobility. including at least one of Core network node.

[0291] (Appendix 26) A user equipment (UE), means for transmitting a first measurement report to a network node, the first measurement report indicating a result of a first measurement performed by the UE; means for receiving, after the first measurement report has been sent to the network node, a notification to cause the UE to send, in a Radio Resource Control (RRC) Reconfiguration Complete message to another network node, a second measurement report indicating a result of a second measurement performed by the UE; means for transmitting a second measurement report to another network node; The second measurement report is used to generate feedback of the predicted mobility of the UE; User equipment.

[0292] This application claims the benefit of priority from UK Patent Application No. 2301235.4, filed January 27, 2023, the disclosure of which is incorporated herein by reference in its entirety. [Explanation of symbols]

[0293] 1. Communication Systems 3. User Equipment 5, 5-1, 5-2, 5-3 RAN nodes (base stations, RAN equipment) 7 Core Network 9 cells 10 CPF 10-1 AMF 10-2 SMF 11 UPF 41 Data Collection Function 43 Model training function 45 Model inference function 47 Actors 50, 50a, 50b DU 60 CU 451 Transceiver Circuit 453 RU interface 454 CU interface 457 Controller 459 memory 461 Operating Systems 463 Communication Control Module 465 F1 Module 468 DU-RU module 472 DU Management Module 473 UE Profile Management Module 475 Mobility Module 551 Transceiver Circuit 554 DU interface 555 CU interface 557 Controller 559 memory 561 Operating Systems 563 Communication Control Module 565 F1 Module 566 E1 Module 568 N2 Module 569 N3 Module 571 CU-UP Management Module 572 CU-CP Management Module 573 UE Profile Management Module 575 Mobility Module

Claims

1. 1. A method of a network node, comprising: transmitting a message including predicted mobility information indicating predicted mobility of a user equipment (UE) to another network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of method.

2. The information indicating the accuracy of the predicted mobility is Information indicating the accuracy with which the UE will be located at the corresponding location; or Information indicating the accuracy of the duration for which the UE will remain at the corresponding position. at least one of The method of claim 1.

3. The predicted mobility information includes a predicted trajectory of the UE and the information indicating the accuracy of the predicted mobility for each position included in the predicted trajectory.

3. The method according to claim 1 or 2.

4. The granularity of the information indicating the predicted trajectory is Cell level, Beam level, Tracking Area Level, or Radio access network based notification area (RNA) level corresponding to at least one of The method of claim 3.

5. the message includes information indicating a history of the UE's trajectory; The granularity of the information indicating the history of the trajectory of the UE is Cell level, Beam level, Tracking Area Level, or Radio access network based notification area (RNA) level corresponding to at least one of 5. The method according to any one of claims 1 to 4.

6. The at least one input of the mobility model: the type of mobility of the UE; the speed or velocity of the UE; the type of UE, or The previous location of the UE at least one of 6. The method according to any one of claims 1 to 5.

7. generating the predicted mobility information using the mobility model.

7. The method according to any one of claims 1 to 6.

8. The message is a handover request message; UE context setup request message, a UE Context Modification Request message, or Handover Required Message at least one of 8. The method according to any one of claims 1 to 7.

9. the predicted mobility information is transmitted to the other network node via a core network node.

9. The method according to any one of claims 1 to 8.

10. the message includes a notification of the network node and a data identity or a UE identifier corresponding to the feedback of the predicted mobility information, and the method further comprises: receiving a further message comprising the feedback from the other network node or from a further network node to which the UE has been handed over from the other network node, using the notification and the data identity or the UE identifier.

10. The method according to any one of claims 1 to 9.

11. the feedback is based on measurement reports sent from the UE; The method of claim 10.

12. sending a report indication to the UE to cause the UE to include the measurement report in a Radio Resource Control (RRC) reconfiguration complete message; the measurement report is transmitted from the UE based on the report notification. The method of claim 11.

13. the further message includes the measurement report.

13. The method of claim 11 or 12.

14. the feedback includes the actual trajectory of the UE after a handover is performed.

14. The method according to any one of claims 10 to 13.

15. using the feedback to determine the accuracy of the predicted mobility or using the feedback as the input to the mobility model to generate a further predicted mobility for the UE.

15. The method according to any one of claims 10 to 14.

16. The granularity of the feedback is Cell level, Beam level, Tracking Area Level, or Radio access network based notification area (RNA) level corresponding to at least one of 16. The method according to any one of claims 10 to 15.

17. transmitting the mobility model configuration to the other network node; The configuration of the mobility model: information indicating at least one use case of the mobility model; a respective framework of the mobility model for each of the at least one use case; Including, 17. The method of any one of claims 1 to 16.

18. Each of the above frameworks: the granularity of the UE's trajectory; the need for feedback of the UE's capabilities, or The need for feedback of the accuracy of the UE's trajectory and information indicating at least one of:

18. The method of claim 17.

19. The configuration is a base station interface setup request message; Base station interface setup response message, a base station interface change request message; Base station interface change response message, a mobility model configuration request message, or Mobility Model Configuration Response Message transmitted in at least one of 19. The method of claim 17 or 18.

20. 1. A method of a network node, said method comprising: receiving predicted mobility information from another network node, for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of method.

21. 1. A method of a core network node, said method comprising: receiving, from a network node, predicted mobility information for a mobility of a user equipment (UE), the predicted mobility information indicating a predicted mobility of the UE; transmitting the predicted mobility information to another network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of method.

22. 1. A method for a user equipment (UE), the method comprising: sending a first measurement report to a network node indicating results of measurements performed by the UE; receiving, after the first measurement report has been sent to the network node, a notification from the network node to cause the UE to send a second measurement report, indicating a result of a second measurement performed by the UE, to another network node in a Radio Resource Control (RRC) Reconfiguration Complete message; transmitting the second measurement report to the other network node; the second measurement report is used to generate feedback of the predicted mobility of the UE. method.

23. an access network node, means for transmitting predicted mobility information, indicative of predicted mobility of a user equipment (UE), to the other network node for mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of Access network node.

24. an access network node, means for receiving predicted mobility information from another network node for a mobility of the UE, the predicted mobility information indicating a predicted mobility of the UE; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of Access network node.

25. A core network node, means for receiving predicted mobility information from a network node for mobility of a user equipment (UE), the predicted mobility information indicating a predicted mobility of the UE; means for transmitting the predicted mobility information to another access network node; The predicted mobility information is Information indicating the accuracy of the predicted mobility; information indicative of a mobility model used to generate the predicted mobility; or and information indicative of at least one input to the mobility model for generating the predicted mobility. at least one of Core network node.

26. A user equipment (UE), means for transmitting a first measurement report to a network node, the first measurement report indicating a result of a first measurement performed by the UE; means for receiving, after the first measurement report has been sent to the network node, a notification to cause the UE to send a second measurement report to another network node in a Radio Resource Control (RRC) Reconfiguration Complete message, the second measurement report indicating a result of a second measurement performed by the UE; and means for transmitting the second measurement report to the other network node; the second measurement report is used to generate feedback of the predicted mobility of the UE. User equipment.

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