Method performed by user equipment, method performed by access network node, user equipment, and access network node

Abstract

The present disclosure relates to methods performed by a user equipment (UE) and an access network node of a communication system for using artificial intelligence and machine learning, AI / ML, models to enhance one or more mobility procedures.

Description

METHOD PERFORMED BY USER EQUIPMENT, METHOD PERFORMED BY ACCESS NETWORK NODE, USER EQUIPMENT, AND ACCESS NETWORK NODE

[0001] The present disclosure relates to a communication system. The disclosure has particular but not exclusive relevance to wireless communication systems and devices thereof operating according to the 3rd Generation Partnership Project (3GPP) standards or equivalents or derivatives thereof (including Long Term Evolution (LTE)-Advanced, Next Generation or 5G networks, future generations, and beyond). The disclosure has particular, although not necessarily exclusive, relevance to the provision of enhanced mobility procedures using an artificial intelligence (AI) and machine learning (ML)('AI / ML') model.

[0002] Earlier developments of the 3GPP standards were referred to as the Long-Term Evolution (LTE) of Evolved Packet Core (EPC) network and Evolved UMTS Terrestrial Radio Access Network (E-UTRAN), also commonly referred as '4G'. More recently, the term '5G' and 'new radio' (NR) is used to refer to an evolving communication technology that supports a variety of applications and services. Various details of 5G networks are described in, for example, the 'NGMN 5G White Paper' V1.0 (NPL 1) by the Next Generation Mobile Networks (NGMN) Alliance, which document is available from https: / / www.ngmn.org / 5g-white-paper.html. 3GPP intends to support 5G by way of the so-called 3GPP Next Generation (NextGen) radio access network (RAN) and the 3GPP NextGen core network.

[0003] Under the 3GPP standards, a NodeB (or an eNB in LTE, and a gNB in 5G) is the radio access network (RAN) node (or simply 'access node', 'access network node' or 'base station') via which communication devices (user equipments or 'UEs') connect to a core network and communicate with other communication devices or remote servers. For simplicity, the present application may use the term access network node, RAN node (or simply RAN) or base station to refer to any such access nodes.

[0004] For simplicity, the present application will use the term mobile device, user device, or UE, to refer to any communication device that is able to connect to the core network via one or more base stations. Although the present application may refer to mobile devices in the description, it will be appreciated that the technology described can be implemented on any communication devices (mobile and / or generally stationary) that can connect to a communication system for sending / receiving data, regardless of whether such communication devices are controlled by human input or software instructions stored in memory.

[0005] In the current 5G architecture, the base station structure may be split into two or more parts. In some RAN implementations there are two parts, known as the Central Unit (CU or gNB-CU) - sometimes referred to as a 'control unit' - and the Distributed Unit (DU or gNB-DU), connected by an F1 interface. This enables the use of a 'split' architecture in which the typically 'higher' CU layers (for example, but not necessarily or exclusively, Packet Data Convergence Protocol (PDCP) and Radio Resource Control (RRC) layers) and the, 'lower' DU layers (for example, but not necessarily or exclusively, Radio Link Control (RLC), Media (sometimes referred to as 'Medium') Access Control (MAC), and Physical (PHY) layers) are separated between a particular CU, and one or more Dus that are connected to and controlled by that CU via the F1 interface. Thus, for example, the higher layer CU functionality for a number of base stations may be implemented centrally (for example, by a single processing unit, or in a cloud-based or virtualised system), whilst retaining the lower layer DU functionality locally separately for each base station.

[0006] In more recently proposed RAN distributed architectures, in addition to the CU and DU, the concept of a Radio Unit (RU) - sometimes referred to as a 'remote unit' - has been introduced. In this architecture the RU is responsible for handling the digital front end (DFE), digital beamforming functionality and, typically, the functionality of the lower parts of the PHY layer, whilst the DU typically handles the higher parts of the PHY layer and the RLC and MAC layers. The CU in this architecture continues to be responsible for controlling one or more DUs (each DU corresponding to a different respective gNB) and to handle higher layer signalling (typically RRC and PDCP layers).

[0007] The actual functional split between the CU and DUs (and potentially RUs where applicable) of these distributed architectures is flexible allowing the functionality to be optimised for different use cases. Effectively, the split architecture enables a 5G network to use a different distribution of protocol stacks between CU and DUs (and potentially RUs) depending on, for example, midhaul availability and network design.

[0008] In 5G, core network entities comprise logical nodes (or 'functions') including control plane functions (CPFs) and one or more user plane functions (UPFs). The CPFs include, amongst other things, one or more Access and Mobility Management Functions (AMFs), a session management function (SMF), an Authentication Server Function (AUSF), a Unified Data Management (UDM) entity for managing user specific data, a Policy Control Function (PCF), an Application Function (AF), a Security Anchor Function (SEAF), an Authentication credential Repository and Processing Function (ARPF), and / or the like. The AMF generally corresponds to the mobility management entity (MME) in 4G and performs many of the functions performed by the MME. Each UPF combines functionality of both the S-GW and P-GW - specifically user plane functionality of the S-GW (SGW-U) and user plane functionality of the P-GW (PGW-U). The SMF provides session management functionality (that formed part of MME functionality in 4G). The SMF also combines the some of the functionality provided by the S-GW and P-GW - specifically control plane functionality of the S-GW (SGW-C) and control plane functionality of the P-GW (PGW-C). The SMF also allocates IP addresses to each UE.

[0009] Historically, mobility between different cells in cellular communications has been based on communication at higher layers, such as layer 3 (e.g., the L3 or radio resource control (RRC) layer) signalling. More recently, with a view to providing enhanced mobility, consideration has given to developing and providing support for layer 1 (e.g., the L1 or physical (PHY) layer) and / or layer 2 (e.g., the L2 or media access control (MAC) layer) centric mobility (also referred to as L1 / L2 centric mobility) rather than at higher layers (e.g., the RRC layer). Such L1 / L2 centric mobility (also referred to as L1 / L2 triggered mobility or 'LTM') has prospects for improving mobility for devices operating both below 7 GHz and in mmWave bands, for example by supporting lower handover latency and improved robustness.

[0010] However, whilst current mobility procedures are generally effective and have been deployed successfully, they are not without potential technical issues. Such issues are particularly prevalent when the UE is moving rapidly and / or is moving in areas where coverage can change dramatically in a relatively short distance (e.g., because of human made structures, or natural physical features of the land, acting as a barrier to radio waves). For example, for L3 triggered mobility, after a decision to trigger handover based on L3 measurements is made, radio signal conditions may change before (or during) handover execution. This could potentially lead to there being a significant communication quality gap between when the measurements were performed and when handover execution occurs (e.g., based on UE and / or cell movement, and / or other factors) thereby increasing the chance of a handover failure or incorrect handover (e.g., to a non-optimum target cell). Similarly, disparities between the radio signal conditions at measurement and the radio signal conditions at handover may lead to handover occurring at a non-optimum time (e.g., too early or too late), or unnecessary handover occurring.

[0011] In respect of LTM based mobility, whilst a cell switch / handover decision is based on more 'real-time' measurement reporting (and hence alleviates some potential issues that may occur in an L3 triggered mobility based handover), the use of L1 measurement reporting causes a relatively large amount of signalling overhead. For example, handover decisions based on an instant L1 measurement report (i.e., a measurement report that has not been subject to L3 filtering by the UE), may be rapidly followed by a similar decision in the new cell to handover back to the previous cell. Hence, unnecessary handovers and so called 'ping-pong' handovers may occur, thereby increasing measurement report and other signalling overhead significantly.

[0012] The disclosure aims to provide one or more apparatus and / or one or more associated methods that overcomes or at least partially ameliorates the above issues.

[0013] In a first aspect, the present disclosure provides a method performed by a user equipment (UE), the method comprising: 　　receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

[0014] In a second aspect, the present disclosure provides a method performed by an access network node, the method comprising: 　　transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

[0015] In a third aspect, the present disclosure provides a user equipment (UE) comprising: 　　means for receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

[0016] In a fourth aspect, the present disclosure provides an access network node comprising: 　　means for transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

[0017] Examples of apparatus and methods will now be described, by way of example, with reference to the accompanying drawings.Fig. 1 schematically illustrates a mobile ('cellular' or 'wireless') communication system.Fig. 2 illustrates a typical frame structure that may be used in the communication system of Fig. 1.Fig. 3 illustrates a functional framework for AI / ML models, and how various entities of the framework may interact with one another, that may be implemented in the communication system of Fig. 1.Fig. 4 schematically illustrates of a method of training an AI / ML model, and of monitoring the performance of the AI / ML model, that may be implemented in the communication system of Fig. 1.Fig. 5 is a simplified sequence diagram illustrating an L3 triggered mobility procedure that may be implemented in the communication system of Fig. 1.Fig. 6 is a simplified sequence diagram illustrating an L1 / L2 triggered mobility (LTM) procedure that may be implemented in the communication system of Fig. 1.Fig. 7 illustrates a hypothetical UE mobility scenario that may occur in the communication system of Fig. 1.Fig. 8 illustrates measurements that may be made by a UE moving in accordance with the mobility scenario of Fig. 7.Fig. 9 is a simplified sequence diagram illustrating an AI / ML enhanced 'predictive' L3 triggered mobility procedure that may be implemented in the communication system of Fig. 1.Fig. 10 illustrates a first example of how periodic predictive measurement reporting may be configured for the exemplary scenario shown in Fig. 7.Fig. 11 illustrates a second example of how periodic predictive measurement reporting may be configured for the exemplary scenario shown in Fig. 7.Fig. 12 is a simplified sequence diagram illustrating an AI / ML enhanced 'predictive' L1 / L2 triggered mobility (LTM) procedure that may be implemented in the communication system of Fig. 1.Fig. 13 is a schematic block diagram illustrating the main components of a UE the communication system of Fig. 1.Fig. 14 is a schematic block diagram illustrating the main components of a RAN node for the communication system of Fig. 1.Description of Example Embodiment

[0018] Overview 　　An exemplary communication system will now be described in general terms, by way of example only, with reference to Figs. 1 to 8.

[0019] Fig. 1 schematically illustrates a mobile ('cellular' or 'wireless') communication system (e.g., communication system 1) to which examples of the present disclosure are applicable.

[0020] In the communication system 1 user equipment (UEs) 3 (3-1, 3-2, 3-3) (e.g., mobile telephones and / or other mobile devices) can communicate with each other via a corresponding radio access network (RAN) node 5-1, 5-2 that operates according to one or more compatible radio access technologies (RATs). In the illustrated example, each RAN node 5 (5-1, 5-2) comprises a base station 5 or 'gNB' 5 that respectively operates one or more associated cells 9 (9-1, 9-2). In the illustrated communication system 1, the coverage provided by each RAN node 5 may be by means of a plurality of beams B (B1, B2… Br, Br+1… BN). It will be appreciated that while, for clarity of illustration, only a selection of possible beams B are shown, the set of beams may include any suitable number of beams and each RAN node 5-1 may operate a respective set of beams or may provide coverage in a non-beamformed manner.

[0021] Communication via each RAN node 5 is typically routed through a core network 7 (e.g., a 5G / 6G or later generations core network or evolved packet core network (EPC)).

[0022] As those skilled in the art will appreciate, whilst three UEs 3 and two RAN nodes 5 are shown in Fig. 1 for illustration purposes, the system, when implemented, will typically include other RAN nodes and UEs.

[0023] Each RAN node 5 controls one or more associated cells 9 either directly, or indirectly via one or more other nodes (such as home base stations, relays, remote radio heads, distributed units, and / or the like). It will be appreciated that the RAN nodes 5 may be configured to support 4G, 5G, 6G, and / or later generations, and / or any other 3GPP or non-3GPP communication protocols.

[0024] The UEs 3 and their serving RAN node 5 are connected via an appropriate air interface (for example the so-called 'Uu' interface and / or the like). Neighbouring RAN nodes 5 may be connected to each other via an appropriate RAN node to RAN node interface (such as the so-called 'X2' interface, 'Xn' interface and / or the like).

[0025] The core network 7 includes a number of logical nodes (or 'functions') for supporting communication in the communication system 1. In this example, the core network 7 comprises control plane functions (CPFs) 10 and one or more network node entities for the communication of user data (e.g., user plane functions (UPFs) 11). The CPFs 10 include one or more network node entities for the communication of control signalling (e.g., Access and Mobility Management Functions (AMFs) 10-1), one or more network node entities for session management (e.g., Session Management Functions (SMFs) 10-2) and a number of other functions 10-n. Additional functions may include, for example: an Authentication Server Function (AUSF) which facilitates security processes; a Unified Data Management (UDM) entity for managing user specific data (e.g., for access authorization, user registration, and data network profiles); a Policy Control Function (PCF); an Application Function (AF); a Security Anchor Function (SEAF) which is in a serving network and acts as a "middleman" during an authentication process between a UE 3 and its home network; an Authentication credential Repository and Processing Function (ARPF) which maintains the authentication credentials; and / or the like. It will be appreciated that the nodes or functions may have different names in different systems.

[0026] Each RAN node 5 is respectively connected to the core network nodes via appropriate interfaces (or 'reference points') such as an N2 reference point between the RAN node 5 and the AMF 10-1 for the communication of control signalling, and an N3 reference point between the RAN node 5 and each UPF 11 for the communication of user data. At least the non-IoT UEs 3 are each connected to the AMF 10-1 via a non-access stratum (NAS) connection over an appropriate interface (e.g., an N1 reference point (analogous to the S1 reference point in LTE)). It will be appreciated, that N1 communications are routed transparently via the RAN node 5.

[0027] Each UPF 11 is respectively connected to an external data network 20 (e.g., an IP network such as the internet) via an appropriate interface (e.g., an N6 reference point) for communication of the user data.

[0028] The AMF 10-1 performs mobility management related functions, maintains the NAS connection with each UE 3 and manages UE registration. The AMF 10-1 is also responsible for managing paging.

[0029] The SMF 10-2 is connected to the AMF 10-1 via an appropriate interface (e.g., an N11 reference point). The SMF 10-2 provides session management functionality (that formed part of MME functionality in LTE) and additionally 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. The SMF 10-2 uses user information provided via the AMF 10-1 to determine what session manager would be best assigned to the user. The SMF 10-2 may be considered effectively to be a gateway from the user plane to the control plane of the network. The SMF 10-2 also allocates IP addresses to each UE 3.

[0030] Each RAN node 5 is also configured for transmission of, and the UEs 3 are configured for the reception of, control information and user data via a number of downlink (DL) physical channels and for transmission of a number of physical signals. The DL physical channels correspond to resource elements (REs) carrying information originated from a higher layer, and the DL physical signals are used in the physical layer and correspond to REs which do not carry information originated from a higher layer.

[0031] The 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 sharing the PDSCH's capacity on a time and frequency basis. The PDSCH can carry a variety of items of data 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) for supporting a number of functions including, for example, scheduling the downlink transmissions on the PDSCH and also the uplink data transmissions on a physical uplink shared channel (PUSCH). The PBCH provides at least the UEs 3 with the Master Information Block (MIB). It also, in conjunction with the PDCCH, supports the synchronisation of time and frequency, which aids cell acquisition, selection and re-selection. Specifically, the UE 3 may receive a Synchronization Signal / physical broadcast channel (PBCH) Block (SSB), and the UE 3 may assume that reception occasions of a PBCH, primary synchronization signal (PSS) and secondary synchronization signal (SSS) are in consecutive symbols and form a SS / PBCH block. The RAN node 5 may transmit a number of SSBs corresponding to different DL beams. The total number of SSBs may be confined, for example, within a 5 ms duration as an SS burst.

[0032] The DL physical signals may include, for example, reference signals (RSs) and synchronization signals (SSs). A reference signal (sometimes known as a pilot signal) is a signal with a predefined special waveform known to both the UE 3 and the RAN node 5. The reference signals may include, for example, cell specific reference signals, UE-specific reference signal (UE-RS), downlink demodulation signals (DMRS), and channel state information reference signal (CSI-RS).

[0033] Similarly, the UEs 3 are configured for transmission of, and the RAN node 5-1 is configured for the reception of, control information and user data via a number of uplink (UL) physical channels corresponding to REs carrying information originated from a higher layer, and UL physical signals which are used in the physical layer and correspond to REs which do not carry information originated from a higher layer. The physical channels may include, for example, the PUSCH, a physical uplink control channel (PUCCH), and / or a physical random-access channel (PRACH). The UL physical signals may include, for example, demodulation reference signals (DMRS) for a UL control / data signal, and / or sounding reference signals (SRS) used for UL channel measurement.

[0034] When the UE 3 initially establishes a radio resource control (RRC) connection with a RAN node 5 via a cell 9 it registers with an appropriate core network node (e.g., AMF 10-1, MME). The UE 3 is in the so-called RRC connected state and an associated UE context is maintained by the network. When the UE 3 is in the so-called RRC idle state, or is in the RRC inactive state, it selects an appropriate cell for camping so that the network is aware of the approximate location of the UE 3 (although not necessarily on a cell level).

[0035] Frame Structure 　　Referring to Fig. 2, which illustrates a typical frame structure that may be used in the communication system 1, the RAN node 5 and UEs 3 of the communication system 1 communicate with one another using resources that are organised, in the time domain, into frames of length 10ms. Each frame comprises ten equally sized subframes of 1 ms length. Each subframe is divided into one or more slots comprising 14 Orthogonal frequency-division multiplexing (OFDM) symbols of equal length.

[0036] As seen in Fig. 2, the communication system 1 supports multiple different numerologies (subcarrier spacing (SCS), slot lengths and hence OFDM symbol lengths). Specifically, each numerology is identified by a parameter, μ, where μ=0 represents 15 kHz (corresponding to the LTE SCS). Currently, the SCS for other values of μ can, in effect, be derived from μ=0 by scaling up in powers of 2 (i.e., SCS = 15 x 2μkHz). The relationship between the parameter, μ, and SCS (Δf) is as shown in Table 1:

[0037]

[0038] Mobility Procedures (without AI / ML enhancement) 　　Each UE 3 and each RAN node 5 are configured for taking its respective part in performing a number of different types of mobility (or 'handover') procedure (depending on requirements), e.g., as the UE 3 moves from cell-to-cell (or beam-to-beam), or as the cells / beams move relative to the UE 3 (in the case of moving cells / beams e.g., in non-terrestrial networks).

[0039] These mobility procedures include, for example, L3 triggered mobility / handover procedures where handover is triggered based on L3 measurement reporting and associated signalling (e.g., radio resource control (RRC) layer signalling).

[0040] These mobility procedures include, for example, L1 / L2 triggered mobility / handover (or 'LTM') procedures where handover is typically triggered by L1 measurement reporting and associated signalling.

[0041] Support for Artificial Intelligence (AI) / Machine Learning (ML) 　　The communication system 1 supports the use of artificial intelligence (AI) and machine learning (ML), often abbreviated to AI / ML in accordance with recent developments in cellular communication technology (e.g., as part of the work of the 3GPP) that those skilled in the art will be familiar with. These AI / ML features make use of trained AI / ML models to make one or more predictions or inferences, from a set of one or more input vectors, that can be used in the network (e.g., for improving the reliability or efficiency of communication in the network).

[0042] In respect of the communication system 1, for example, AI / ML models could potentially be trained and used for predicting the path of a UE 3 based on previous mobility of the UE 3, used for beam management, or used in methods of encoding and transmitting information. An AI / ML model may be hosted at a RAN node 5 (or any other suitable network node), and the RAN node 5 may perform control of communication resources for UEs 3 that it serves, and / or perform control related to the status of a UE 3 (e.g., control of UE mobility, or control of a radio resource control, RRC, state of the UE 3) based on an inference (e.g., determination or prediction) generated using the AI / ML model. The RAN node 5 may also transmit an inference generated using the model to another node in the network, for use at the other node. An AI / ML model may also be hosted the UE 3, or at a plurality of locations within the network, for example at both a RAN node 5 and at a UE 3. For example, the RAN node 5 and the UE 3 may both make determinations and / or predictions using the same model or different models.

[0043] The support for such AI / ML features may involve different levels of collaboration between the network (a RAN node 5 and / or a core network 7) and a UE 3 served by the network when deploying and using such AI / ML features. For example, three possible 'network-UE collaboration levels' that may be supported are: 　　　　Level x: Involving no collaboration between the network and the UE 3. Specifically, level x is an implementation-based AI / ML operation without any dedicated AI / ML-specific enhancement. 　　　　Level y: Signalling-based collaboration without AI / ML model transfer. For example, this level is applicable when model training is performed offline, and models are registered to both a RAN node 5 and the UE 3. Here, the RAN node 5 and the UE 3 are aware of available models (before operation), and the RAN node 5 is only required to activate / deactivate the models residing at the UE 3 when needed. 　　　　Level z: Signalling-based collaboration with AI / ML model transfer (e.g., where an AI / ML model is transferred to the UE 3 when needed).

[0044] The AI / ML model types that are supported in the communication system 1 may include, for example: 　　　　Single-sided model: A single-sided AI / ML model is an AI / ML model that is deployed (hosted) only at the UE side or at the network side. An example of this type of model is an AI / ML model for beam prediction in time, which can be deployed at the UE side. However, even when the model is a single-sided model, it will be appreciated that the model need not necessarily be trained at the node at which it is deployed (e.g., a UE 3 or a RAN node 5). For example, the model could be trained at the RAN node 5 (or at another node in the network such as a core network node / function), and then is transferred to the UE 3 for use at the UE 3. 　　　　Two-sided model: A 'two-sided' model is an AI / ML model (or model pair) that has one AI / ML model hosted at one node (e.g., the UE 3), and a corresponding AI / ML model hosted at another node (e.g., a RAN node 5) - it will be appreciated that any pair of network nodes may be used. Such a two-sided model may also be referred to as a 'paired' AI / ML model. Inference using a two-sided model is performed jointly across the nodes at which the AI / ML models of the two-sided model are deployed. The joint inference may comprise, for example, a first part of the inference being performed at one node (e.g., the UE 3 or RAN node 5), and then the remaining part may be performed by the other (e.g., the RAN node 5 or UE 3). It will be appreciated that whilst the AI / ML model hosted at the different nodes may be the same AI / ML model, they need not necessarily be the same model. One example of this type of model is, for example only, channel state information (CSI) compression, where the UE 3 performs CSI compression and network performs CSI decompression. As with the single-sided model case, the two-sided model (or models) may be trained at any suitable network node, and then transmitted to the UE 3 and the RAN node 5 (or other respective node or nodes).

[0045] A general discussion of how AI / ML may be implemented in the communication system 1 will now be provided, by way of example only, with reference to Figs. 3 and 4.

[0046] Fig. 3 illustrates a functional framework for AI / ML models, and how various entities of the framework may interact with one another, that may be implemented in the communication system 1.

[0047] The entities include a data collection function 341, a model training function 343, a model inference function 345, an actor 347, a management function 349, and a model storage entity 351.

[0048] The model storage entity 351 may be a reference point for protocol terminations for model transfer and delivery. The AI / ML models could be stored at any suitable node in the network.

[0049] The data collection function 341 provides training data to the model training function 343, inference data to the model inference function 345, and monitoring data to the management function 349. The collected data may be, for example, data regarding mobility (e.g., handover of a UE 3, or a location of the UE 3). The data may be obtained, for example, by a UE 3 or a RAN node 5 (e.g., by receiving a measurement report from a UE 3, or by receiving data from another RAN node 5 or a core network node / function) and transmitted to another RAN node 5 or core network node that generates the AI / ML model inference output (or alternatively, the same RAN node 5 that obtains the data may generate the AI / ML model output).

[0050] The model training function 343 performs the ML model training, validation, and testing, and may generate model performance metrics as part of a model testing procedure. The model training function 343 may output a trained AI / ML model to the model storage entity 351 (though it will be appreciated that the output model may be stored at locations other than model storage entity 351).

[0051] The model inference function 345 provides AI / ML model inference output (e.g., predictions or decisions), and the actor 347 is a function or node that receives the output from the model inference function 345 and triggers or performs corresponding actions (e.g., a RAN node 5 that increases / reduces its transmission power, or initiates a handover procedure for a UE 3). The AI / ML model inference output may be, for example, a prediction of mobility (e.g., expected path, route or trajectory, inter-cell, or inter-beam mobility, or expected handover) of the UE 3, or one or more parameters for use in encoding or decoding transmissions between the RAN node 5 and the UE 3. The model inference function 345 may receive an AI / ML model from the model storage entity 351, and inference data from the data collection function 341 for use with the AI / ML model. The model inference function 345 may also output monitoring data for use at the management function 349, and receive information indicating an AI / ML to activate or deactivate from the management function 349.

[0052] The management function 349 receives monitoring data from the data collection function 341, and may also receive monitoring data from the model inference function 345. The management function 349 may transmit, to the model storage entity 351, an indication of an AI / ML model to be transmitted for use at the model inference function 345. The management function 349 may also transmit, to the model training function 343, performance feedback or a retraining request for the AI / ML model.

[0053] The functions illustrated in Fig. 3 may be co-located at a single node of the communication system 1 (e.g., at a RAN node 5 or core network node / function), or may be distributed amongst a plurality of network nodes (e.g., a plurality of RAN nodes 5). By way of example only, terms referred to by 3GPP in the context of this framework include: 　　　　AI / ML model training: A process to train an AI / ML Model [by learning the input / output relationship] in a data driven manner and obtain the trained AI / ML Model for inference. Model training can be performed offline or online or combination of both. 　　　　AI / ML model validation: A subprocess of training, to evaluate the quality of an AI / ML model using a dataset different from one used for model training, that helps selecting model parameters that generalize beyond the dataset used for model training. 　　　　AI / ML model testing: A subprocess of training, to evaluate the performance of a final AI / ML model using a dataset different from one used for model training and validation. Differently from AI / ML model validation, testing does not assume subsequent tuning of the model. 　　　　AI / ML model Inference: A process of using a trained AI / ML model to produce a set of outputs based on a set of inputs. 　　　　Data collection: A process of collecting data by the network nodes, management entity, or UE for the purpose of AI / ML model training, data analytics and inference. 　　　　Model monitoring: A procedure that monitors the inference performance of the AI / ML model. 　　　　Model activation: Enable an AI / ML model for a specific function. 　　　　Model deactivation: Disable an AI / ML model for a specific function. 　　　　Model switching: Deactivating a currently active AI / ML model and activating a different AI / ML model for a specific function. 　　　　Supervised learning: A process of training a model from input and its corresponding labels. 　　　　Unsupervised leaning: A process of training a model without labelled data. 　　　　Semi-supervised learning: A process of training a model with a mix of labelled data and unlabelled data. 　　　　Reinforcement Learning (RL): A process of training an AI / ML model from input (also referred to as 'state') and a feedback signal (also referred to as 'reward') resulting from the model's output (also referred to as 'action') in an environment the model is interacting with.

[0054] The data collection by the data collection function 341 may be performed at various nodes of the communication system 1 (e.g., at one or more RAN nodes 5 or UEs 3). Particularly advantageous methods of obtaining, at a UE 3, data for an AI / ML model, and transmitting the AI / ML data from the UE 3 to a RAN node 5, will be described in more detail later.

[0055] Fig. 4 schematically illustrates of a method of training an AI / ML model, and of monitoring the performance of the AI / ML model. As illustrated in Fig. 4, stored data / features may first be extracted in a data extraction step. In the data validation step, a determination of whether to proceed with training or retraining the AI / ML model is made (e.g., based on the extracted data). In the data preparation stage, the data is prepared for use in training the AI / ML model. For example, the data may be cleaned (e.g., filtered), subject to a transformation, or modified in any other suitable manner. The data may also be divided in training data, validation data and test data sets in the data preparation stage.

[0056] In the model training step, the AI / ML model is trained (or retrained) using training data prepared in the data preparation step. It will be appreciated that any suitable training method can be used to train the AI / ML model (e.g., a method that comprises supervised learning or unsupervised learning). In the model evaluation step, the AI / ML model is evaluated (e.g., a prediction accuracy of the AI / ML model is evaluated) using a test data set (which may be generated in the data preparation step). In the model validation step, a determination of whether the AI / ML model is suitable for deployment in the communication system 1 is made (e.g., based on the results of the model evaluation step).

[0057] In the model serving step, the AI / ML model is deployed for use in the communication system 1. AI / ML model deployment may comprise compiling a trained AI / ML model, packaging the model into an executable format, and delivering the AI / ML model to a target device. For example, the AI / ML model may be transmitted to the RAN node 5 and / or the UE 3, for use at the RAN node 5 and / or the UE 3 to generate predictions or determinations using the AI / ML model as part of a prediction service step, as illustrated in Fig. 4. In the performance monitoring step, the performance of the deployed AI / ML model is monitored. The predictive performance of the AI / ML model may be monitored by comparing predictions generated using the model with one or more measurements. For example, when the AI / ML model is used to predict a location of a UE 3, the prediction accuracy of the AI / ML model may be assessed using a measurement of an actual location of the UE 3. If the AI / ML model is used for predicting future measurement results (e.g., the measured RSRP of reference signals) at some point in time, the prediction accuracy of the AI / ML model may be assessed using actual measurement results acquired by the UE 3 when that point in time is reached. If the AI / ML model is used for determining parameters for use in encoding and decoding data transmitted between a RAN node 5 and a UE 3, the model may be assessed based on the performance of the encoding and / or decoding processes. In the retraining trigger step, retraining of the AI / ML model is triggered (e.g., because the prediction accuracy of the AI / ML model has fallen below an acceptable threshold accuracy, or because a performance of a method that uses inferences from the AI / ML model has fallen below an acceptable threshold performance), and the method returns to the data extraction step.

[0058] As described above with reference to Fig. 3, each step of the method of Fig. 4 may be executed at a single node of the communication system 1 (including at the UE 3), or alternatively steps of the method may be distributed between a plurality of different nodes (or indeed one or more of these steps may be performed online or offline).

[0059] As discussed above with reference to Figs. 3 and 4, information collected by nodes / functions in the communication system 1 (e.g., at a UE 3) can be used as training data for an AI / ML model, and used as inference data for use in generating one or more model inferences using the AI / ML model. The information used as training data, monitoring data, and / or to generate the one or more model inferences may be referred to as 'AI / ML information' or 'AI / ML data'.

[0060] Mobility Procedures - L3 triggered 　　In more detail, the UEs 3 and RAN nodes 5 of the communication system 1 may be mutually configured for performing a RAN centric, L3 triggered, handover, based on direct communication over a RAN node-to-RAN node interface (e.g., X2, Xn or the like), in which the source RAN triggers handover based on an L3 measurement report.

[0061] An exemplary L3 handover procedure that may be used in the communication system 1, will now be described, by way of example only, with reference to Fig. 5.

[0062] Fig. 5 is a simplified sequence diagram illustrating the L3 triggered mobility procedure that may be implemented in the communication system 1.

[0063] Referring to Fig. 5, the L3 triggered mobility procedure in this case concerns a handover of a UE 3 between a source cell of a source RAN node 5-1 and a target cell of a target RAN node 5-2, where a handover decision is made by the source RAN node 5-1 based on a measurement report previously received from the UE 3.

[0064] Before the handover procedure starts, the RAN node 5-1 serving and communicating with the UE 3 (i.e., the source RAN node 5-1 of the handover) is in a measurement phase (S500). The serving RAN node 5-1 will typically have a UE context for the UE 3 stored. This may include, for example, information regarding roaming and access restrictions which were provided either at establishment of the connection between the UE 3 and the serving RAN node 5-1 or at the last tracking area update.

[0065] At the start of this measurement phase, at S502, the serving RAN node 5-1 performs measurement control by sending an appropriate measurement configuration, to the UE 3 (e.g., in an RRC reconfiguration message or the like), to configure the measurement procedures to be performed by the UE 3.

[0066] The measurement configuration typically includes, for example, a list of one or more so called 'measurement objects', which indicate what the UE 3 should measure (i.e., the 'object' or 'target' of the UE measurements). For example, for intra-frequency and inter-frequency measurements, the measurement object may indicate the frequency / time location and subcarrier spacing of the reference signals to be measured. For inter-RAT measurements, a measurement object may be a specific carrier frequency (e.g., a E-UTRA frequency or the like).

[0067] The measurement configuration also typically includes, for example, a list of one or more 'reporting configurations', that configures how the UE 3 performs the measurements and when measurement reports should be sent. There can be one or multiple reporting configurations per measurement object. For example, each measurement reporting configuration typically defines at least one 'reporting criterion' (e.g., a criterion that, when met, triggers the UE 3 to send a measurement report). A reporting criterion may, for example, be time based (e.g., representing a period at which measurement reports may be sent) or may be event based (e.g., defining a single event which, on occurrence, triggers measurement reporting). Each measurement reporting configuration also typically defines at least one reference signal type (i.e., defining the RS that the UE 3 uses for beam and cell measurement results). The reference signal type may, for example, be defined as an SS / PBCH block (SSB) or as CSI-RS. Each measurement reporting configuration also typically defines at least one reporting format that defines the quantity or quantities per cell and / or per beam that the UE 3 is to include in the measurement report (e.g., reference signal received power (RSRP), reference signal received quality (RSRQ), signal to interference plus noise ratio (SINR) and / or the like). Each measurement reporting configuration may also include other associated information such as the maximum number of cells and the maximum number beams per cell to report.

[0068] The serving RAN node 5-1 may, for example, configure the UE 3 to report any of the following list of measurement information based on one or more SS / PBCH blocks (SSBs): ●　　Measurement results per SSB; ●　　Measurement results per cell based on one or more SSBs; and ●　　One or more SSB indexes.

[0069] The serving RAN node 5-1 may, for example, configure the UE 3 to report any of the following measurement information based on CSI-RS resources: ●　　Measurement results per CSI-RS resource; ●　　Measurement results per cell based on one or more CSI-RS resources; and ●　　CSI-RS resource measurement identifiers.

[0070] The UE 3 performs, at S504, the configured measurements and reports them in a measurement report at S506 (e.g., a measurement report that is triggered when a particular configured trigger event occurs, or periodically) according to the measurement configuration.

[0071] A handover preparation phase (S510) then commences when the serving RAN node 5-1 decides to initiate handover at S512. Specifically, the serving RAN node 5-1 makes a decision to handover the UE 3 to the target cell of the target RAN node 5-2, for example based on measurement results received in the measurement report and / or radio resource management (RRM) information. The serving RAN node 5-1 thus begins to operate as a source RAN node 5-1 of the handover.

[0072] The source RAN node 5-1 issues, at S514, a handover request, to the target RAN node 5-2. This message will typically pass the necessary information, to the target RAN node 5-2 in a transparent RRC container, for preparing the handover at the target side. The information may include, for example, the target cell ID, security information, a cell radio network temporary identifier (C-RNTI) of the UE 3 at the source RAN node 5-1, RRM configuration information (e.g., including UE inactive time), basic access stratum (AS) configuration information including antenna information and downlink carrier frequency, current quality of service (QoS) flow to data radio bearer (DRB) mapping rules applied to the UE 3, the SIB1 from the source RAN node 5-1, the UE capabilities for different RATs, protocol data unit (PDU) session related information, and / or UE reported measurement information including beam-related information if available.

[0073] Admission control may then be performed by the target RAN node 5-2 at S515. Slice-aware admission control may, for example, be performed if corresponding slice information is sent to the target RAN node 5-2 and if protocol data unit (PDU) sessions are associated with non-supported slices the target RAN node 5-2 may reject such a PDU session.

[0074] The target RAN node 5-2 prepares handover with its lower layers (L1 and L2) and sends, to the source RAN node 5-1, an appropriate response (e.g., a handover request acknowledge message or the like) at S516. The response includes a transparent container comprising a message (e.g., an RRC message) to be sent to the UE 3 and that is to be used to configure handover (e.g., as a handover command to instruct performance of the handover). The message to be sent to the UE 3 may, for example, be an RRC reconfiguration message or the like.

[0075] The source RAN node 5-1 triggers the handover by sending the handover configuration message (e.g., the RRC reconfiguration message / handover command or the like) to the UE 3 at S518. This message contains the information required to access the target cell (e.g., the target cell ID, the new C-RNTI, the target RAN node security algorithm identifiers for the selected security algorithms and / or the like).

[0076] As soon as the source RAN node 5-1 receives the response (e.g., the handover request acknowledge message or the like), or as soon as the transmission of the handover command (e.g., the RRC reconfiguration message or the like) is initiated in the downlink, data forwarding may be initiated.

[0077] A handover execution phase (S520) is then initiated, and the UE 3 detaches from the source cell of the source RAN node 5-1 and synchronises to the target cell of the target RAN node 5-2 at S526.

[0078] The UE 3 synchronises to the target cell and completes the handover procedure by sending an appropriate message (e.g., an RRC message) to indicate that handover configuration is complete (e.g., an RRC Reconfiguration Complete / handover complete message) to the target RAN node 5-2 (S528).

[0079] The last phase is a handover completion phase (S530) during which the target RAN node 5-2 coordinates with the core network to switch communication to the target RAN node 5-2 at S532. Once communication has been switched the target RAN node 5-2 initiates a UE context release at the source RAN node 5-1 to release the associated resources of the source RAN node 5-1 (e.g., by sending a UE context release message at S534).

[0080] Mobility Procedures - L1 / L2 Triggered Mobility (LTM) 　　The UEs 3 and RAN nodes 5 of the communication system 1 may be mutually configured for performing an L1 / L2 triggered mobility (LTM) mobility procedure, in which the source RAN triggers a change of cell based on an L1 measurement report (that has not been subject to L3 filtering).

[0081] Specifically, LTM is a procedure in which a RAN node 5 receives one or more L1 measurement reports from a UE 3, and on their basis the RAN node 5 changes the UE's serving cell using a cell switch command (e.g., signalled via a MAC control element (CE)). The cell switch command indicates an LTM candidate configuration that the RAN node previously prepared and provided to the UE 3 through appropriate L3 (e.g., RRC) signalling. Then the UE 3 switches to the target configuration according to the cell switch command.

[0082] An exemplary LTM procedure that may be used in the communication system 1, will now be described, by way of example only, with reference to Fig. 6.

[0083] Fig. 6 is a simplified sequence diagram illustrating the LTM procedure that may be implemented in the communication system 1.

[0084] Referring to Fig. 6, the LTM procedure in this case concerns a handover of a UE 3 between a source cell of a source RAN node 5-1 and a target cell of a target RAN node 5-2, where a decision is initially made by the source RAN node 5-1, based on a measurement report previously received from the UE 3, to (pre)configure the UE 3 for handover / cell switch to each of one or more LTM candidate cells / RAN nodes forming an LTM candidate set. The LTM candidate set includes, for example, at least the cell / RAN node 5-2 that will ultimately become the target cell / target RAN node 5-2.

[0085] Before the LTM procedure starts, the serving RAN node 5-1 (i.e., the source RAN node 5-1 of the handover / cell switch) and the UE 3 are in a measurement phase (S600). The serving RAN node 5-1 will typically have a UE context for the UE 3 stored. This may include, for example, information regarding roaming and access restrictions which were provided either at establishment of the connection between the UE 3 and the serving RAN node 5-1 or at the last tracking area update.

[0086] At the start of this measurement phase, at S602, the serving RAN node 5-1 performs measurement control by sending an appropriate measurement configuration, to the UE 3 (e.g., in an RRC reconfiguration message or the like), to configure the (L3) measurement procedures to be performed by the UE 3.

[0087] The measurement configuration typically includes, for example, a list of one or more so called 'measurement objects', which indicate what the UE 3 should measure (i.e., the 'object' or 'target' of the UE measurements). For example, for intra-frequency and inter-frequency measurements, the measurement object may indicate the frequency / time location and subcarrier spacing of the reference signals to be measured. For inter-RAT measurements, a measurement object may be a specific carrier frequency (e.g., a E-UTRA frequency or the like).

[0088] The measurement configuration also typically includes, for example, a list of one or more 'reporting configurations', that configures how the UE 3 performs the measurements and when measurement reports should be sent. There can be one or multiple reporting configurations per measurement object. For example, each measurement reporting configuration typically defines at least one 'reporting criterion' (e.g., a criterion that, when met, triggers the UE 3 to send a measurement report). A reporting criterion may, for example, be time based (e.g., representing a period at which measurement reports may be sent) or may be event based (e.g., defining a single event which, on occurrence, triggers measurement reporting). Each measurement reporting configuration also typically defines at least one reference signal type (i.e., defining the RS that the UE 3 uses for beam and cell measurement results). The reference signal type may, for example, be defined as an SS / PBCH block (SSB) or as CSI-RS. Each measurement reporting configuration also typically defines at least one reporting format that defines the quantity or quantities per cell and / or per beam that the UE 3 is to include in the measurement report (e.g., reference signal received power (RSRP), reference signal received quality (RSRQ), signal to interference plus noise ratio (SINR), and / or the like). Each measurement reporting configuration may also include other associated information such as the maximum number of cells and the maximum number beams per cell to report.

[0089] The serving RAN node 5-1 may, for example, configure the UE 3 to report any of the following list of measurement information based on one or more SS / PBCH blocks (SSBs): ●　　Measurement results per SSB; ●　　Measurement results per cell based on one or more SSBs; and ●　　One or more SSB indexes.

[0090] The serving RAN node 5-1 may, for example, configure the UE 3 to report any of the following measurement information based on CSI-RS resources: ●　　Measurement results per CSI-RS resource; ●　　Measurement results per cell based on one or more CSI-RS resources; and ●　　CSI-RS resource measurement identifiers.

[0091] The UE 3 performs, at S604, the configured measurements and reports them in a measurement report at S606 (e.g., a measurement report that is triggered when a particular configured trigger event occurs, or periodically) according to the measurement configuration.

[0092] An LTM (pre)configuration phase (S610) then commences when the serving RAN node 5-1 decides, based on measurement results, to configure LTM and initiate LTM preparation at S612 (this decision may be referred to as an LTM handover decision). Specifically, the serving RAN node 5-1 makes a decision to (pre)configure the UE 3 for handover / cell switch to each of one or more LTM candidate cells / RAN nodes forming an LTM candidate set. The LTM candidate set includes, for example, at least the cell / RAN node 5-2 that will ultimately become the target cell / target RAN node 5-2. The serving RAN node 5-1 thus begins to operate as a source RAN node 5-1 of the LTM procedure.

[0093] The source RAN node 5-1 issues, at S614, a respective handover request, to each candidate RAN node 5 (i.e., each RAN node 5 that may become a target of the handover / cell switch in the future). In Fig. 6, whilst a single candidate RAN node 5 (the RAN node 5-2 that ultimately becomes the target) is shown there may (but do not have to) be a plurality of candidate RAN nodes 5. The information may include, for example, the target cell ID, security information, a C-RNTI of the UE 3 at the source RAN node 5-1, RRM configuration information (e.g., including UE inactive time), basic AS configuration information including antenna information and downlink carrier frequency, current QoS flow to DRB mapping rules applied to the UE 3, the SIB1 from the source RAN node 5-1, the UE capabilities for different RATs, PDU session related information, and / or UE reported measurement information including beam-related information if available.

[0094] The following procedure will be described from the perspective of the candidate RAN node 5 that ultimately becomes the target RAN node 5-2. It will, nevertheless, be appreciated that a similar procedure will be performed at each candidate RAN node 5 as part of the procedure to configure the UE 3 for LTM.

[0095] Admission control may be performed by the target RAN node 5-2 at S615. Slice-aware admission control may, for example, be performed if corresponding slice information is sent to the target RAN node 5-2 and if protocol data unit (PDU) sessions are associated with non-supported slices the target RAN node 5-2 may reject such a PDU session.

[0096] The target RAN node 5-2 prepares handover with its lower layers (L1 and L2) (e.g., including reserving corresponding resources for the UE 3) and sends, to the source RAN node 5-1, an appropriate response (e.g., a handover request acknowledge message or the like) at S616. The response includes a transparent container comprising a message (e.g., an RRC message) to be sent to the UE 3 and that is to be used as an 'LTM candidate configuration' message to configure LTM handover / cell switch for that specific candidate RAN node 5 (e.g., as a handover command to instruct performance of the handover). The message to be sent to the UE 3 may, for example, be an RRC reconfiguration message or the like.

[0097] The source RAN node 5-1 transmits, at S618, the respective LTM candidate configuration to the UE 3 received from each candidate RAN node 5 in an appropriate (e.g., RRC) message (e.g., an RRC reconfiguration message) comprising an appropriate LTM configuration information element (IE) including the respective LTM candidate configuration for each candidate RAN node 5 (of which there may be one or more). Each LTM candidate configuration in the LTM configuration IE may, for example, be a complete candidate configuration or may be a delta configuration relative to a reference configuration.

[0098] The source RAN node 5-1 may also include as part of the LTM configuration, LTM measurement configuration information for configuring L1 measurements to be reported. The measurement configuration information may, for example, be configured for configuring the UE 3 to provide an SSB based L1-RSRP measurement report for beam selection. The source RAN node 5-1 may also include as part of the LTM configuration, LTM report configuration information for configuring L1 measurement reporting. The report configuration information may, for example, configure reporting to be periodic (on the PUCCH), aperiodic, semipersistent (on the PUCCH or the PUSCH), and / or the like. The report configuration information may, for example, configure the content of the report (e.g., how many cells are reported within a single L1 measurement report instance, how many reference signals per cell are reported within a single L1 measurement report instance, whether the UE 3 should include an L1 measurement report associated to the current special cell, and / or the like).

[0099] The UE 3 stores the LTM candidate configurations and responds to the message carrying the LTM configuration, at S619, with an appropriate response message (e.g., an RRC reconfiguration complete message or the like) to effectively indicate that the LTM configuration has been completed at the UE 3.

[0100] The UE 3 may, at this stage, perform early synchronization, in the downlink, with each candidate cell (i.e., before receiving any corresponding cell switch (or 'handover') command).

[0101] The UE 3 may also, at this stage, perform early synchronization, in the uplink, with each candidate cell. Specifically, when UE-based timing advance (TA) measurement is configured, the UE 3 may acquire a respective TA value of each candidate cell by measurement. The UE 3 may perform early TA acquisition with a candidate cell in accordance with a request by the network (i.e., before receiving any corresponding cell switch (or 'handover') command). This may, for example, be done via a contention free random access (CFRA) triggered by a PDCCH order from the source RAN node 5-1, following which the UE 3 sends preamble towards the indicated candidate cell. In order to minimise the data interruption of the source cell due to CFRA towards a candidate cell, the UE 3 need not receive random access response from the network for the purpose of TA value acquisition and the TA value of the candidate cell may be indicated in any cell switch command.

[0102] An LTM execution / completion phase (S620) is then initiated during which the UE 3 performs, at S621, the configured L1 measurements for the configured candidate cells (where possible) and sends, at S622, a corresponding L1 measurement report to the source RAN node 5-1 in accordance with the report configuration information. L1 measurement may be performed as long as the LTM configuration (i.e., the RRC reconfiguration) provided at S618 is applicable.

[0103] When the UE 3 sends a report configured to provide SSB based L1-RSRP measurements, the L1 measurement report may include, for example, an SSB resource set index ('SSBRI'), which is an index of an SSB resource set configured for L1 mobility measurement reporting. This report may include, for example, a set of one or more L1-RSRP measurement results for each cell. Each reported L1-RSRP value may, for example, be an absolute (e.g., 7-bit) value, or differential reporting may be used in which one or more L1-RSRP values are reported as differential (e.g., 4-bit) values relative to another reported 'reference' absolute (e.g., 7-bit) value of L1-RSRP (e.g., the reference value may be the highest (or lowest) reported L1-RSRP).

[0104] At S623, the source RAN node 5-1 decides to execute cell switch to a target cell (i.e., a cell of the target RAN node 5-2 in this example). The source RAN node 5-1 may then initiate transmission, at S624, of an LTM cell switch command (e.g., as a MAC CE for triggering a cell switch (or handover)) including a candidate configuration index corresponding to the target cell / target RAN node 5-2.

[0105] The UE 3 then, at S626, detaches from the source cell of the source RAN node 5-1 and switches to the target cell by applying the corresponding LTM candidate configuration indicated by candidate configuration index.

[0106] As indicated at S628, the UE 3 can then access the cell using a RACH based or RACH-less procedure. The UE 3 may, for example, perform a random access procedure towards the target cell if the UE 3 does not have valid TA of the target cell. Nevertheless, the UE 3 may access the cell without performing a random access procedure where the UE 3 has a valid TA. The UE 3 can complete the LTM cell switch procedure by sending an appropriate message (e.g., an RRC reconfiguration complete message) to the target RAN node 5-2. If the UE 3 has performed a random access procedure the UE 3 may consider that LTM cell switch execution has been successfully completed when the random access procedure has successfully completed. For RACH-less LTM, on the other hand, the UE 3 may consider that the LTM cell switch execution has successfully completed when the UE 3 determines that the target RAN node 5-2 has successfully received its first uplink data.

[0107] It will be appreciated that the steps following the sending of the message (e.g., RRC reconfiguration complete message) indicating that LTM configuration is complete at S619 (including any early synchronisation) can be performed multiple times for subsequent LTM, for example by using any stored LTM candidate configuration provided at S618 and stored at the UE 3.

[0108] Mobility Procedures (with AI / ML enhancement) 　　Whilst each UE 3 and each RAN node 5 are able to perform these mobility procedures based on real measurements (e.g., of reference signals or the like), each UE 3 and each RAN node 5 are beneficially configured to make use of AI / ML models to provide enhanced 'predictive' mobility procedures based on predicted measurements (possibly in addition to real measurements). Such predictive procedures have the prospect of providing a number of different benefits including a reduction in handover related issues.

[0109] For example, in the L3 triggered mobility procedure described above, after the source RAN node 5-1 makes a decision to trigger handover based on an L3 measurement report, the radio signal conditions may change before (or during) handover execution (S520) - e.g., around step S518. This could potentially lead to there being a significant communication quality gap between when the measurements were performed and when handover execution occurs (e.g., based on UE and / or cell movement, and / or other factors) thereby increasing the chance of a handover failure or incorrect handover (e.g., to a non-optimum target cell) - especially when the UE 3 (or cell) is moving at speed. Similarly, disparities between the radio signal conditions at measurement and the radio signal conditions at handover may lead to handover occurring at a non-optimum time (e.g., too early or too late), or unnecessary handover occurring.

[0110] In respect of LTM based cell switch / handover, whilst the cell switch / handover decision is based on a more 'real-time' measurement reporting (and hence alleviates some potential issues that may occur in an L3 triggered mobility based handover), the use of L1 measurement reporting causes a relatively large amount of signalling overhead. For example, handover decisions based on an instant L1 measurement report (i.e., a measurement report that has not been subject to L3 filtering by the UE), may be rapidly followed by a similar decision in the new cell to handover back to the previous cell. Hence, unnecessary handovers and so called 'ping-pong' handovers may occur, thereby increasing measurement report and other signalling overhead significantly.

[0111] Possible handover issues that may arise from using a mobility procedure as described above can be understood from Fig. 7 which illustrates a hypothetical UE mobility scenario and Fig. 8 which illustrates RSRP measurements that may be made by a UE moving in accordance with the mobility scenario of Fig. 7.

[0112] As seen in Fig. 7, the UE 3 moves along a path, P, in a geographic region covered by three different RAN nodes 5-A, 5-B, and 5-C that each operate a respective cell (Cell A, Cell B, and Cell C) using a corresponding group of beams (beams A1, A2, and A3 in cell A; beams B1, B2, and B3 in cell B; and beams C1, C2, and C3 in cell C). It will be appreciated that only a relatively small number of beams are shown for illustrative purposes.

[0113] As seen in Fig. 7, as the UE 3 travels along the path P, the UE 3 reaches each of a different plurality of locations, L1 to L6, at different respective corresponding reference times, T1 to T6.

[0114] The actual respective measured radio quality for the different cells / beams at each of the different locations L1 to L6 / time points T1 to T6 varies considerably as seen in Fig. 8.

[0115] The hypothetical most appropriate (or 'best') cell and beam for serving the UE 3 at each of the different reference times, based on these measurement results, is illustrated in Table 2.

[0116]

[0117] As seen in Fig. 8, at T3, even though beam C1, of cell C, is hypothetically the best beam, the handover from cell A to cell C turns out to be unnecessary because, almost instantly, after T3 is reached the best cell for serving the UE 3 reverts to Cell A and the radio quality provided by Cell C drops dramatically (e.g., as a result of the UE 3 passing building 625). If the measurement reports are sent / handover decisions made in accordance with the reference timings T1 to T6 (e.g., at T3 and then not until T4), then the network may command the UE 3 to handover to Cell C at T3. The resulting rapid drop off in radio quality in that cell may then cause a failed connection (e.g., a handover failure or radio link failure (RLF)) because the UE 3 is not instructed to handover to a better quality cell sufficiently quickly. Alternatively, if measurement reporting / cell switch decision making is sufficiently 'real-time', then undesirable 'ping-pong' may occur between Cells A and C (i.e., Cell A - Cell C - Cell A) whereas, in reality, the handover from Cell A to Cell C is unnecessary.

[0118] The enhanced 'predictive' mobility procedures implemented in the communication system 1 beneficially allow for a more optimal mobility decision to be made by using knowledge of (i.e., predictions of) the likely future UE radio conditions, UE trajectory, and / or the like, for an appropriate future time span.

[0119] The mobility enhancements described provide benefits in particular for (but not limited to) a UE 3 that is connected (e.g., in an RRC connected mode or state) over the air interface. Beneficially, the mobility enhancements are compatible with mobility procedures based on an existing mobility framework (for example mobility procedures in which a handover / cell switch decision is made at the RAN side). The enhancements are applicable, in particular, to mobility use cases in the context of a standalone primary cell change (but could potentially be adapted for other cell changes if needed). The described enhancements assume that there is at least a UE-sided AI / ML model that can be run by the UE 3 (e.g., to derive a measurement prediction).

[0120] It will be appreciated that whilst the UEs 3 and RAN nodes 5 of the described communication system 1 support a number of different mobility procedures they could be configured to support only one, or a subset of, the mobility procedures (e.g., a single one of the AI / ML enhanced / predictive mobility procedures). Moreover, an AI / ML enhanced / predictive mobility procedure may replace a corresponding non-AI / ML enhanced equivalent procedure.

[0121] L3 Predictive Mobility Procedure 　　As mentioned above, each UE 3 and each RAN node 5 are beneficially configured to make use of AI / ML models to provide one or more enhanced 'predictive' mobility procedures based on predicted measurements. One such procedure will now be described, by way of example only, with reference to Fig. 9 which is a simplified sequence diagram illustrating an AI / ML enhanced 'predictive' L3 triggered mobility procedure that may be implemented in the communication system 1.

[0122] In this example, it is assumed that there is a UE sided AI / ML model run by the UE 3 to derive one or more measurement predictions. The model inference can represent a temporal based, a spatially based and / or a frequency based derivation.

[0123] As seen in Fig. 9, the predictive L3 triggered mobility procedure is broadly similar to that described with reference to Fig. 5 and the description of the steps of Fig. 5 also applies generally to the corresponding steps of Fig. 9. In the interests of clarity and brevity, therefore, the following description therefore focusses on the enhancements introduced in the predictive procedure illustrated in Fig. 9.

[0124] Referring to Fig. 9, the predictive L3 triggered mobility procedure in this case concerns a handover of a UE 3 between a source cell of a source RAN node 5-1 and a target cell of a target RAN node 5-2, where a handover decision is made by the source RAN node 5-1 based on a measurement prediction based measurement report (referred to herein as a 'measurement prediction report') previously received from the UE 3.

[0125] Before any measurement phase for a handover procedure has commenced, at S901, the UE 3 reports its support for AI / ML generally (and / or for AI / ML based measurement prediction specifically) to its serving RAN node 5-1 (i.e., the source RAN node 5-1 of the handover). This may, for example, be reported as part of a UE capability report (e.g., as an indication of capability for AI / ML based measurement prediction and / or its corresponding AI / ML model). As those skilled in the art will be appreciate, such UE capability reporting to the network may be made by means of a UE capability reporting procedure in response to a UE capability enquiry message or similar. Nevertheless, the AI / ML related support capability may be indicated in any suitable way including, for example: explicitly in a message or implicitly (without sending a message); and / or solicited in response to a request, or unsolicited at a timing determined by the UE 3.

[0126] The serving RAN node 5-1 may relay the AI / ML related support capability indication (e.g., the indication of capability for AI / ML based measurement prediction and / or its corresponding AI / ML model) reported by the UE 3, or send other similar information indicating the AI / ML related support capability, to another node of the network (e.g., a node / function of the core network 7), to support predictive mobility related actions. It will be appreciated that the UE capability transfer is shown for completeness, such a transfer need not occur for every handover.

[0127] As seen at S900, before the handover procedure starts, the serving RAN node 5-1 (i.e., the source RAN node 5-1 of the handover) and the UE 3 that it serves are in the measurement phase. At this juncture, the serving RAN node 5-1 will typically have a UE context for the UE 3 stored. This may include, for example, information regarding roaming and access restrictions which were provided either at establishment of the connection between the UE 3 and the serving RAN node 5-1 or at the last tracking area update.

[0128] At the start of this measurement phase, at S902, based on the UE's capability, the serving RAN node 5-1 configures the UE 3 to predict measurement results (i.e., to perform measurement prediction) for the purpose of mobility in connected mode. Specifically, the serving RAN node 5-1 performs measurement control by sending an appropriate measurement prediction configuration, to the UE 3 to configure the measurement prediction procedure to be performed by the UE 3. It will be appreciated that the serving RAN node 5-1 may also (but does not have to) configure real measurements as described in more detail with reference to Fig. 5. The measurement prediction configuration may be provided to the UE 3 using any suitable message (e.g., a dedicated RRC message or an RRC reconfiguration message (which may include a real measurement configuration also)). This procedure is referred to herein as 'measurement prediction configuration'.

[0129] Alternatively, the so called measurement prediction configuration may be carried by a conventional handover command sent from the serving RAN node 5-1 to the UE 3. During a conditional handover, this measurement prediction configuration may be included as part of the conditional handover configuration sent to the UE 3 by the serving RAN node 5-1. In this case, before the serving RAN node 5-1 sends the measurement prediction configuration to the UE 3, it may coordinate with the target RAN node 5-2 to get the measurement prediction configuration beforehand during the handover preparation stage. In this case, the follow-up measurement prediction report as described below may be sent by the UE 3 to the target cell after the completion of the handover (for example, piggybacked within the first RRC message that the UE 3 sends to the target cell).

[0130] The principles of measurement prediction configuration, and specific examples of what the content of the measurement prediction configuration provided at S902 might include are discussed in more detail later.

[0131] After receiving the measurement prediction configuration, as S904, the UE 3 uses the measurement prediction configuration information, possibly together with any current actual radio measurement for serving cells, and neighbouring cells (intra-frequency, inter- frequency, and inter-RAT frequency) as the input for its AI / ML model inference to predict the measurements and to generate a corresponding measurement prediction report which is then sent at S906.

[0132] For example, the UE 3 may include, in the measurement prediction report, one or more predicted measurements according to one or more reporting criteria within the measurement prediction configuration received at S902. For example, the UE 3 may include one or more periodic measurement predictions in the measurement prediction report based on a periodic reporting criterion included in the measurement prediction configuration. Alternatively, or additionally, the UE 3 may include a measurement event prediction in the measurement prediction report indicating when one or more configured conditions for a configured measurement event is predicted to be met.

[0133] It will be appreciated that plural periodic measurement predictions and / or plural measurement event predictions may be included in a single measurement prediction report. Nevertheless, plural measurement prediction reports may be sent e.g., with different reports for reporting different types of measurement predictions (e.g., periodic and / or event based) and / or with different reports for reporting different periodic and / or event based measurement predictions.

[0134] The UE 3 may also include, in the report a probability for each measurement prediction (e.g., a probability that a reported measurement quantity occurs or a probability that one or more criteria for a measurement event are satisfied).

[0135] It will be appreciated that the UE 3 may report the measurement predictions together with normal measurement results e.g., following conventional RRM measurement.

[0136] Measurement prediction reporting, and specific examples of periodic measurement prediction reporting, and event based measurement prediction reporting, will be described in more detail later.

[0137] After receipt of the measurement prediction report (or reports), a handover preparation phase (S910) can commence in which the serving RAN node 5-1 begins preparing for a possible future handover based on the based on the measurement prediction report provided by the UE 3 at S906.

[0138] Hence, at S912, the serving RAN node 5-1 may make a handover decision taking account both any reported real measurement results, and the predicted measurement information indicating what radio conditions the UE 3 might experience in the future (e.g., predicted measurement results, predicted event occurrence, and / or the like). It can be seen, therefore, unlike the handover decision in Fig. 5, the handover decision taken at S912 can be for future mobility. For example, in the example of Figs. 7 and 8 a handover decision may be made to handover at reference time T4 (i.e., effectively not to handover at reference time T3 regardless of the fact that Cell C may appear to provide better radio conditions than Cell A).

[0139] Based on the handover decision, the serving RAN node 5-1 (now operating as a source RAN node 5-1), may coordinate with the target RAN node 5-2 in respect of the handover. Specifically, the source RAN node 5-1 may send, at S914, a handover request, to the target RAN node 5-2 (e.g., including all or a subset of the information described with reference to S514 of Fig. 5). Nevertheless, within this message, the source RAN node 5-1 may include information extracted from (or derived based on) the measurement predictions, for example, the predicted best beam and / or cell that the UE 3 may use to access to the target RAN node 5-2. Moreover, the handover request message may also include a probability of such handover based on the measurement prediction report received from the UE 3 at S906.

[0140] Admission control may then be performed by the target RAN node 5-2 at S915. The target RAN node 5-2 then prepares handover with its lower layers (L1 and L2) and sends, to the source RAN node 5-1, an appropriate response (e.g., a handover request acknowledge message or the like) at S916. The response includes a transparent container comprising a message (e.g., an RRC message) to be sent to the UE 3 and that is to be used to configure handover (e.g., as a handover command to instruct performance of the handover). The message to be sent to the UE 3 may, for example, be an RRC reconfiguration message or the like.

[0141] The source RAN node 5-1 may then trigger handover by sending the handover configuration message (e.g., the RRC reconfiguration message / handover command or the like) to the UE 3 at S918 (e.g., as described with reference to Fig. 5). Nevertheless, the source RAN node 5-1 may, alternatively, send a modified existing RRC (e.g., RRC reconfiguration) message, or a new RRC message, to carry a handover command that is adapted based on one or more measurement predictions. The message may, for example, indicate that the handover command is a 'special' or 'prediction based' handover command, which is based on the UE's measurement prediction. It will be appreciated that the source RAN node 5-1 may employ a similar approach to that used for conditional handover to provide one or more triggering conditions that have to be met at the UE 3 before execution of such a handover command.

[0142] For example, one or more triggering conditions may be based on a comparison of a match between real radio conditions observed at the UE 3, and the UE's previous measurement prediction (e.g., for consecutive reference time points just before the recommended handover). For example, if the real radio conditions match (or are sufficiently close to - e.g., within a (pre)configured offset / hysteresis value from) the UE's earlier prediction of those radio conditions for one or more reference times (e.g., T3 and / or T4) preceding a reference time (e.g., T5) configured for handover execution.

[0143] A measurement event may, alternatively or additionally, be configurable as a triggering condition. For example, the so-called A3 event can be used, to trigger handover when the real radio strength measured for the target cell is an offset better than the serving cell (the A3 event occurs when a measurement result for a neighbour cell (in this example the target cell) becomes better than the corresponding measurement for a special cell (SpCell) (in this case the serving / source cell) by a (pre)configured offset).

[0144] A more detailed example of a conditional handover will be described in more detail later.

[0145] A handover execution / completion phase (S920) is then initiated (e.g., when one or more triggering conditions are met), and the UE 3 detaches from the source cell of the source RAN node 5-1 and synchronises to the target cell of the target RAN node 5-2 at S926.

[0146] The UE 3 can then access the target cell at S928 (e.g., as part of a procedure similar to that described with reference to Fig. 5, S528 to S532).

[0147] Measurement Prediction Configuration Principles and Examples 　　The principles of measurement prediction configuration, and specific examples of what the content of the measurement prediction configuration provided at S902 might include (depending on requirements) will now be discussed in more detail, by way of example only.

[0148] The measurement configuration may configure the UE 3 to predict any suitable measurement results for example one or more measurement predictions corresponding to all, or a subset, of the real measurements configurable by means of a conventional measurement configuration as described with reference to Fig. 5. For example, the network (serving RAN node 5-1) may configure the UE 3 to perform and report measurement prediction results (and / or real measurements) for serving cells, intra-frequency neighbour cells and / or inter-frequency neighbour cells; and / or for inter-RAT neighbour cells. Accordingly, the measurement prediction may be applicable to intra-frequency, inter-frequency and / or inter-RAT frequency.

[0149] As with the real measurement configuration described with reference to Fig. 5, during measurement prediction configuration, the UE 3 may be configured with one or multiple measurement objects to predict the measurements for serving cells, and / or neighbouring cells (intra-frequency, inter-frequency, and inter-RAT frequency). In the context of predictive measurement results a measurement object may be referred to as a 'measurement prediction object' or the like.

[0150] Alternatively (or additionally), the UE 3 may be configured to respectively predict the best cell, or a set of a best cell and corresponding best beam (or beam set) for each of a plurality of reference time points. Predicting the best cell, or a set of a best cell and corresponding best beam (or beam set) for each of a plurality of reference time points has the benefit that when the results of the measurement predictions are reported at S906, the UE 3 need only report this information, and not necessarily any predicted measurement results, potentially with (or separately to) any legacy RRM measurements. Accordingly, the resulting UE measurement prediction report may result in less signalling overhead than would otherwise be the case.

[0151] As another alternative (or addition), during the predicative measurement configuration at S902, the UE 3 may be configured to predict UE movement information (e.g., the UE speed, the UE moving direction, and / or the UE location), respectively for each reference time point. The UE 3 may then report the predicted UE movement information together with (or separately to) any predictive measurements. The provision of such information may be beneficial for helping the network to make an optimum handover decision.

[0152] Similarly, at S902, the measurement prediction configuration may alternatively (or additionally) configure the UE 3 to predict occurrence of an event, for example: a measurement report trigger event (e.g., the so called 'A3' event which occurs when a measurement result for a neighbour cell becomes better than the corresponding measurement for a special cell (SpCell) by a (pre)configured offset); and / or a mobility related mobility ('failure') event (e.g., a beam failure, RLF, a handover failure, and / or the like).

[0153] Periodic Measurement Prediction Configuration 　　The measurement prediction configuration at S902 may configure one or more measurement prediction criterion that may, for example, correspond to a time based prediction criterion (e.g., representing a period for which measurement predictions are to be performed) or may be event based (e.g., defining an event which, on occurrence or predicted occurrence, triggers a measurement prediction).

[0154] For example, the serving RAN node 5-1 may configure the UE 3 to report periodic measurement prediction results (potentially with an associated probability) for serving cells, intra-frequency neighbour cells, inter-frequency neighbour cells, and / or inter-RAT neighbour cells. Specifically, the serving RAN node 5-1 may configure the UE 3 to report the measurement prediction results for each of a plurality of periodic reference times within a fixed (e.g., future) time period. The serving RAN node 5-1 may configure the UE 3 to report the measurement prediction results for each of a plurality of periodic reference times within a certain defined (e.g., future) time period (e.g., between a minimum time period and a maximum time period).

[0155] The serving RAN node 5-1 may, alternatively or additionally, be able to configure a measurement event for the UE 3, for a given measurement object, for a report of (periodic) measurement predictions. During the time period to which the (periodic) measurement prediction report relates, the UE 3 may, for example, predict at which reference time point a particular measurement event will occur (i.e., one or more measurement reporting criteria will be met) for that measurement object.

[0156] Temporal Periodic Measurement Prediction Configuration One or more of the following information elements (IEs) may, for example. be configured within the message for measurement prediction configuration (e.g., as sent at S902) for each 'temporally based' measurement prediction object (e.g., for periodic measurement prediction reporting): ●　　An intra-frequency predictive measurement IE: e.g., including the frequency / time location and subcarrier spacing of reference signals to be measured; ●　　A frequency (e.g., inter-frequency and / or inter-RAT frequency) for the predictive measurement; ●　　A reference signal type (e.g., SS / PBCH block or CSI-RS) for the predictive measurement; ●　　A time interval for the measurement prediction (e.g., 200ms); 　　○　　This IE may, for example, inform the UE 3 of a measurement prediction interval from a temporal perspective (e.g., a time interval between reference times (such as T1 to T2, T2 to T3 etc... in Figs. 8, 10 and 11); ●　　A fixed time period for measurement prediction (e.g., 2000ms); 　　○　　This IE may, for example, inform the UE 3 of a time window (such as T1 to T6 in Figs. 8, 10 and 11 for example) for which the UE 3 needs to report a measurement prediction (where each reference time within the fixed time period is a time for which the UE 3 is to provide a reported measurement prediction); ●　　A minimum time period for measurement prediction (e.g., 2000ms); 　　○　　This IE may, for example, inform the UE 3 of a minimum time window for which the UE 3 needs to report a measurement prediction (where each reference time within the minimum time period is a time for which the UE 3 is to provide a reported measurement prediction); ●　　A maximum time period for measurement prediction (e.g., 40000ms); 　　○　　This IE may, for example, inform the UE 3 of a maximum time window for which the UE 3 needs to report a measurement prediction (where each reference time within the maximum time period is a time for which the UE 3 is to provide a reported measurement prediction); ●　　One or more reporting criteria (e.g., periodic based, single event based (e.g., A3 measurement event), and / or the like); ●　　A reporting format (e.g., RSRP, RSRQ, SINR or the like); ●　　A quantity interval for measurement prediction (e.g., 2dBm for RSRP); 　　○　　This IE may, for example, inform the UE 3 of a quantity interval for the UE 3 to report the measurement prediction; and ●　　A reporting unit (e.g., per cell, or per beam, or both).

[0157] Inter-frequency Periodic Measurement Prediction Configuration 　　Other than the 'temporally based' measurement prediction objects for which the serving RAN node 5-1 configures the UE 3 to perform temporal prediction, the network may also configure one or more specific inter-frequency measurement prediction objects for which the UE 3 is to predict and report one or more inter-frequency measurements, for example, together with one or more (predicted) measurement results for one or more associated measurement (prediction) objects. For example, the inter-frequency measurement prediction objects may be associated with a list of one or more measurement objects for which the UE 3 is to perform real measurement and / or temporal based measurement prediction. It will be appreciated that the inter-frequency measurement prediction objects may be configured by the serving RAN node 5-1, to the UE 3, without a corresponding measurement gap being configured, which indicates that measurement result is to be predicted rather than actually measured.

[0158] One or more of the following information elements (IEs) may, for example, be configured within the message for measurement prediction configuration (e.g., as sent at S902) for each inter-frequency measurement prediction object: ●　　A list of one or more associated measurement prediction object IDs and / or conventional measurement object IDs; 　　○　　This IE may, for example, inform the UE 3 of one or more conventional measurement objects and / or one or more measurement prediction objects the UE 3 should use for predicting the measurement for the current measurement prediction object; ●　　A frequency for pure predictive measurement; ●　　A reference signal type (e.g., SS / PBCH block or CSI-RS) for the predictive measurement; ●　　A time interval for the measurement prediction (e.g., 200ms); ●　　A fixed time period for measurement prediction (e.g., 2000ms); ●　　A minimum time period for measurement prediction (e.g., 2000ms); ●　　A maximum time period for measurement prediction (e.g., 40000ms); ●　　One or more reporting criteria (e.g., periodic based, single event based (e.g., A3 measurement event), and / or the like); ●　　A reporting format (e.g., RSRP, RSRQ, SINR or the like); ●　　A quantity interval for measurement prediction (e.g., 2dBm for RSRP); 　　○　　This IE may, for example, inform the UE 3 of a quantity interval for the UE 3 to report the measurement prediction; and ●　　A reporting unit (e.g., per cell, or per beam, or both).

[0159] Other Periodic Configurations 　　It will be appreciated that the serving RAN node 5-1 may optionally configure the UE 3 to report a measurement prediction for each of a list of discrete reference time points. Moreover, the serving RAN node 5-1 may (alternatively or additionally) configure the UE 3 to report a measurement prediction for when the UE 3 reaches one or more particular locations.

[0160] Within the measurement prediction objects that the network configures the UE 3 to perform temporal measurement prediction for and / or inter-frequency measurement prediction for, the network may also configure one or more specific spatially based real measurement and / or predicted measurements for the UE 3.

[0161] For example, for a particular cell, the network may configure the UE 3 to perform real measurement (or temporally based predictive measurement) for a subset of one or more beams (for example, expressed by one or more SSB indicators / indices), and to predict the measurements of the other beams (for example, expressed by one or more SSB indicators / indices), based on the measured beam or beams. For example, a spatially based measurement prediction may be associated with a list of one or more corresponding beams that the UE 3 is to perform real measurement for (or possibly temporal based measurement prediction for).

[0162] Event based Measurement Prediction Configuration 　　The serving RAN node 5-1 may configure a UE 3 to perform and report the predicted occurrence of a certain event (e.g., an A3 measurement event). For example, the serving RAN node 5-1 may configure the UE 3 to perform and report the predicted satisfaction of that event, with an associated probability (for a given measurement object), at a certain reference time point, or within a time window, which effectively informs the network when the (measurement) event is predicted to occur (i.e., one or more measurement reporting criteria will be met) for that measurement object. This can be referred to as a measurement event prediction or mobility event prediction.

[0163] For an event based report criterion, the measurement prediction report may be triggered in a case where the UE 3 predicts that, as some future reference time point (possibly within a defined time period), the event criterion / criteria will be met.

[0164] For example, if, at a given time reference (e.g., T1), the UE 3 predicts that a measurement event will be met at a future time reference (e.g., T5), then the UE 3 may send the measurement report to the network to report that the measurement event will be met at T5. Accordingly, this may help the network to decide a future handover for T5.

[0165] One or more of the following information elements (IEs) may, for example. be configured within the message for measurement prediction configuration (e.g., as sent at S902) for event based (measurement) prediction reporting: ●　　A list of one or more events for prediction, which may include one or more measurement events (e.g., the so-called 'A3' event), and / or one or more mobility events (e.g., a beam failure, RLF, handover failure, etc.); ●　　A time interval for event based (measurement) prediction (e.g., 200ms); 　　○　　This IE may, for example, inform the UE 3 of a prediction interval from temporal perspective (e.g., a time interval between reference times (such as T1 to T2, T2 to T3 etc... in Figs. 8, 10 and 11); ●　　A fixed time period for event based (measurement) prediction (e.g., 2000ms); and ●　　One or more additional IEs (e.g., as described with reference to the periodic measurement prediction report) may be included in respect of an event based measurement prediction configuration also.

[0166] Measurement Prediction Reporting 　　Measurement prediction reporting, and specific examples of periodic measurement prediction reporting, and event based measurement prediction reporting, will now be described in more detail by way of example only.

[0167] As described above, the UE 3 may be configured (e.g., at S502 in the procedure of Fig. 5 and / or at S902 in the procedure of Fig. 9) to periodically report real measurements that have been recently or currently measured. The UE 3 may also be configured (e.g., at S902 in the procedure of Fig. 9) to report, in a periodic measurement prediction report, periodic measurement predictions (together with or separately from any real measurements). A periodic measurement prediction report may, for example, report the signal quantity of each particular measurement prediction object for each cell (serving cell and / or neighbour cell). Moreover, for each measurement prediction object, a measurement prediction for all, or a subset of one or more, of the associated beams of the cell may be reported.

[0168] Periodic Measurement Prediction Reporting (Serving Cell) 　　For each serving cell, one or more of the following information elements may, for example, be included within a message that provides the measurement prediction report in the context of periodic prediction reporting: ●　　A serving cell index; ●　　A (real) measured quantity (e.g., in RSRP, RSRQ or SINR) of the measurement for the serving cell; ●　　A physical cell ID (PCI) of the best measured neighbour cell (e.g., according to the real measurements); ●　　A list of one or more predicted quantities (e.g., in RSRP, RSRQ or SINR) of each measurement prediction for the serving cell. For example, for each reference time interval; 　　○　　One or more associated probabilities may be included (e.g., a respective probability for each predicted quantity or a single probability applicable to all the predictions); ●　　A PCI of the best predicted neighbour cell (or a respective PCI of the best predicted neighbour cell for each reference time interval); 　　○　　One or more associated probabilities may be included (e.g., a respective probability for each prediction or a single probability applicable to all the predictions); and ●　　A list of one or more predicted quantities (e.g., in RSRP, RSRQ or SINR) of each measurement prediction for the beams (e.g., identified by SSB, or CSI-RS), for each reference time interval, and for the best predicted neighbour cell; 　　○　　One or more associated probabilities may be included (e.g., a respective probability for each predicted quantity or a single probability applicable to all the predictions).

[0169] Periodic Measurement Prediction Reporting (Neighbour Cell) 　　For each neighbour cell, one or more of the following information elements may, for example, be included within a message that provides the measurement prediction report in the context of periodic prediction reporting: ●　　A physical cell ID (PCI) of the neighbour cell; ●　　A list of one or more (real) measured quantities (e.g., in RSRP, RSRQ or SINR) of the measurement for the beams (e.g., identified by SSB, or CSI-RS), for a current reference time interval, for the identified neighbour cell; and ●　　A list of one or more predicted quantities (e.g., in RSRP, RSRQ or SINR) of each measurement prediction for the beams (e.g., identified by SSB, or CSI-RS), for at least a current (and possibly each future) reference time interval, for the identified neighbour cell; 　　○　　One or more associated probabilities may be included (e.g., a respective probability for each prediction or a single probability applicable to all the predictions).

[0170] Periodic Measurement Prediction Reporting (Examples) 　　Examples of how periodic predictive measurement reporting may be configured will now be described, by way of example only, with reference to Figs. 10 and 11.

[0171] Fig. 10 illustrates a first example of how periodic predictive measurement reporting may be configured for the exemplary scenario shown in Fig. 8.

[0172] As seen in Fig. 10, the measurement prediction report for the 'current' time (e.g., reference time T1) may be configured to include current real measurement results for measurements of Cell A, Cell B and Cell C performed at reference time T1. Nevertheless, it will be appreciated that, alternatively, the measurement prediction report may be configured to include current real measurement results for measurements of Cell A and Cell C, whereas a measurement prediction may be included for Cell B.

[0173] As seen in Fig. 10, the measurement prediction report for current time (e.g., reference time T1) may be configured to include temporally based predicted measurements for reference times T2 to T6. Nevertheless, it will be appreciated that, alternatively, the measurement results included in the report for Cell A and Cell C may be temporally based measurement predictions, but the measurement results for Cell B may be inter-frequency measurement predictions based on the real and / or predicted measurements for Cell A, Cell C, or both.

[0174] By way of example only, Table 3 illustrates hypothetical content (in this example cell-level RSRP values) that may be included in the measurement prediction report, for reference time T1, for the exemplary scenario illustrated in Fig. 10.

[0175]

[0176] Fig. 11 illustrates a second example of how periodic predictive measurement reporting may be configured for the exemplary scenario shown in Fig. 8. In this example the predictive measurement reporting is based on inter-frequency measurement predictions.

[0177] As seen in Fig. 11, the periodic measurement report for reference time T1 may be configured to include current real measurement results for measurements of Cell A, Cell B and Cell C performed at reference time T1.

[0178] From reference times T2 to T6, however, respective measurement prediction reports are provided that include real measurement results for Cell A and Cell C and inter-frequency measurement predictions for Cell C based on the real measurement results for Cell A, cell B or both.

[0179] Event Based Measurement Prediction Reporting 　　As mentioned above, an event based measurement prediction report may be sent from the UE 3, to the source RAN node 5-1 (e.g., at S906), that identifies one or more events that are predicted to occur (i.e., based on a prediction of when one or more criteria defining that event will be satisfied).

[0180] An event based measurement prediction report may, for example, be based on a prediction of one or more conditions for one or more mobility events (e.g., a beam failure, RLF, a handover failure, and / or the like) being met. Specifically, in the context of mobility event based measurement prediction, the UE 3 may predict that one or more criteria defining a certain mobility event will be met in a certain reference time, or within a certain time window, according to a prediction made by the AI / ML model being run at the UE 3. In this case, in the UE's report for the predicted event, the UE 3 may notify the source RAN node 5-1 when the mobility event is predicted to occur (e.g., when a corresponding criterion / condition will be met) by including information identifying a certain reference time point, or a certain time window (e.g., by indicating two reference time points delineating the time window).

[0181] Nevertheless, an event based measurement prediction report may, alternatively (or additionally), be based on a prediction of one or more conditions for one or more measurement events (e.g., like event A3 or similar) being met. In the case of a predicted measurement event based reporting, the content of the measurement prediction report may be based on a modified version of a real measurement based measurement report (e.g., as sent at S506 in Fig. 5). Specifically, in the context of measurement event based measurement prediction, the UE 3 may predict that one or more criteria defining a certain measurement event will be met in a certain reference time, or within a certain time window, according to a prediction made by the AI / ML model being run at the UE 3. In this case, in the UE's report for the predicted event, the UE 3 may notify the source RAN node 5-1 when the measurement event is predicted to occur (e.g., when a corresponding criterion / condition will be met) by including information identifying a certain reference time point, or a certain time window (e.g., by indicating two reference time points delineating the time window).

[0182] It will be appreciated that a key difference between an event based measurement prediction report and a conventional event based measurement report (e.g., sent as part of the procedure of Fig. 5) is that the predicted (measurement) event is 'triggered' as a result of the outcome of a UE 3 prediction that a criterion / condition defining that (measurement) event will be met at some (predicted) time point in the future (i.e., rather than by a condition / criterion defining the event already having been met).

[0183] In the context of event based measurement prediction reporting, one or more of the following information elements may, for example, be included within a message that provides the measurement prediction report: ●　　An event Identity (which may, for example, be derived from the measurement prediction configuration); ●　　A reference time point indicating when it is predicted that the event will occur (i.e., on or more associated conditions / criteria will be met) according to the UE's prediction; 　　○　　This may, for example, be a time relative to a reference time (e.g., the current measurement time), which may be expressed as an integer value (e.g., 'N') representing units (or 'multiples') of a defined time interval (e.g., 20ms). For example, a value of N=4 may be used to indicate that the event is predicted to occur (approximately) 80ms after the reference time (e.g., current measurement report time); ●　　A reference time window within which it is predicted that the event will occur (i.e., on or more associated conditions / criteria will be met) according to the UE's prediction; 　　○　　This may, for example, be a time window defined by respective end points of the time window relative to a reference time (e.g., the current measurement time). The end points may, for example, be expressed as integer values (e.g., 'N', 'M') representing units (or 'multiples') of a defined time interval (e.g., 20ms). For example, values of N=4 and M=8) may be used to indicate that the event is predicted to occur within a time window extending from 80ms to 160ms after the reference time (e.g., current measurement report time); and ●　　One or more prediction probabilities (i.e., effectively informing the source RAN node 5-1 of an (estimated) accuracy of the event prediction).

[0184] It will be appreciated that one or more of the other IEs described above for periodic measurement prediction reporting may also be included.

[0185] Conditional Handover Command 　　As mentioned above, when providing a handover command (e.g., at S918), the source RAN node 5-1 may employ a similar approach to that used for conditional handover. Specifically, the handover command may, in effect, be a conditional handover command provided with one or more triggering conditions that have to be met at the UE 3 before the handover command is acted on.

[0186] One example of the use of such a handover command will now be described in more detail, by way of example only.

[0187] In this specific example, the conditional handover command is a handover command that is to be executed conditionally when a specific configured handover execution reference time is reached (e.g., at T5 in Figs. 8, 10 or 11 for handover to cell C).

[0188] In this example, if the real measurements for the neighbour cells performed by the UE 3 at reference times (e.g., T2, T3, T4) that occur before the configured handover execution reference time (e.g., T5) deviate significantly from the corresponding predicted measurements, then this indicates that the UE's prediction was not accurate. As a consequence, it may not be appropriate for the handover command to be executed at the configured handover execution reference time (e.g., T5).

[0189] Accordingly, a handover condition may be configured to ensure that handover is only executed if the UE's real measurements for the neighbour cells at reference times (e.g., T2, T3, T4) that occur before the configured handover execution reference time (e.g., T5) deviate significantly from the corresponding predicted measurements. If, at reference times (e.g., T2, T3, T4) that occur before the configured handover execution reference time, the real measurements deviate significantly from the predicted measurements (e.g., by more than a preconfigured absolute or percentage amount) then the handover command based on the predicted measurements can be cancelled automatically by the UE 3. It will be appreciated that the UE 3 may then report the occurrence of this cancellation of handover to the network.

[0190] Alternatively, or additionally, the UE 3 may report, to the source RAN node 5-1, that a deviation between real measurement and the previous measurement predictions has occurred, and then the source RAN node 5-1 may initiate the handover cancellation by sending a message to the UE 3 to cancel the previously transmitted handover command. This procedure may be considered to be a fallback method for predictive mobility.

[0191] It will be appreciated that a single 'handover command' / 'handover configuration' sent to the UE 3 (e.g., at S918) may include multiple separate handover commands for subsequent handovers, e.g., each for a different reference time point.

[0192] If one or more triggering conditions for handover, provided with the predicative handover command are met, then the UE 3 can proceed to access the new (target) cell (e.g., as seen at S926 and S928).

[0193] Predictive LTM Procedure 　　As mentioned above, each UE 3 and each RAN node 5 are beneficially configured to make use of AI / ML models to provide one or more enhanced 'predictive' mobility procedures based on predicted measurements. One such procedure will now be described, by way of example only, with reference to Fig. 12 which is a simplified sequence diagram illustrating an AI / ML enhanced 'predictive' L1 / L2 triggered mobility procedure that may be implemented in the communication system 1.

[0194] In this example, it is assumed that there is a UE sided AI / ML model run by the UE 3 to derive one or more measurement predictions. The model inference can represent a temporal based, a spatially based and / or a frequency based derivation.

[0195] As seen in Fig. 12, the predictive LTM procedure is broadly similar to that described with reference to Fig. 6 and the description of the steps of Fig. 6 also applies generally to the corresponding steps of Fig. 12. In the interests of clarity and brevity, therefore, the following description therefore focusses on the enhancements introduced in the predictive procedure illustrated in Fig. 12.

[0196] Referring to Fig. 12, the predictive LTM procedure in this case concerns a handover of a UE 3 between a source cell of a source RAN node 5-1 and a target cell of a target RAN node 5-2, where a decision is initially made by the source RAN node 5-1, based on a measurement report previously received from the UE 3, to (pre)configure the UE 3 for handover / cell switch to each of one or more LTM candidate cells / RAN nodes 5 forming an LTM candidate set. The LTM candidate set includes, for example, at least the cell / RAN node 5-2 that will ultimately become the target cell / target RAN node 5-2.

[0197] Before any measurement phase for a handover procedure has commenced, at S1201, the UE 3 reports its support for AI / ML generally (and / or for AI / ML based measurement prediction specifically) to its serving RAN node 5-1 (i.e., the source RAN node 5-1 of the handover). This may, for example, be reported as part of a UE capability report (e.g., as an indication of capability for AI / ML based measurement prediction and / or its corresponding AI / ML model). As those skilled in the art will be appreciate, such UE capability reporting to the network may be made by means of a UE capability reporting procedure in response to a UE capability enquiry message or similar. Nevertheless, the AI / ML related support capability may be indicated in any suitable way including, for example: explicitly in a message or implicitly (without sending a message); and / or solicited in response to a request, or unsolicited at a timing determined by the UE 3.

[0198] The serving RAN node 5-1 may relay the AI / ML related support capability indication (e.g., the indication of capability for AI / ML based measurement prediction and / or its corresponding AI / ML model) reported by the UE 3, or send other similar information indicating the AI / ML related support capability, to another node of the network (e.g., a node / function of the core network 7), to support predictive mobility related actions. It will be appreciated that the UE capability transfer is shown for completeness, such a transfer need not occur for every handover / cell switch.

[0199] As seen at S1200, before the LTM procedure starts, the serving RAN node 5-1 (i.e., the source RAN node 5-1 of the handover / cell switch) and the UE 3 that it serves are in the measurement phase. At this juncture, the serving RAN node 5-1 will typically have a UE context for the UE 3 stored. This may include, for example, information regarding roaming and access restrictions which were provided either at establishment of the connection between the UE 3 and the serving RAN node 5-1 or at the last tracking area update.

[0200] In the illustrated example, at the start of this measurement phase, at S1202, based on the UE's capability, the serving RAN node 5-1 performs measurement control by sending an appropriate measurement configuration, to the UE 3 (e.g., in an RRC reconfiguration message or the like), to configure the (L3) measurement procedures to be performed by the UE 3. The measurement configuration may include, for example, measurement configuration information of the type described with reference to Fig. 6 (S602). Nevertheless, it will be appreciated that the measurement configuration may comprise, for example, a measurement prediction configuration of the type described with reference to Fig. 9 (S902).

[0201] An LTM (pre)configuration phase (S1210) then commences when the serving RAN node 5-1 decides, in the illustrated example, based on the reported real measurement results, to configure LTM and to initiate LTM preparation at S1212 (this decision may be referred to as an LTM handover decision). Specifically, the serving RAN node 5-1 makes a decision to (pre)configure the UE 3 for handover / cell switch to each of one or more LTM candidate cells / RAN nodes 5 forming an LTM candidate set. The LTM candidate set includes, for example, at least the cell / RAN node 5-2 that will ultimately become the target cell / target RAN node 5-2. The serving RAN node 5-1 thus begins to operate as a source RAN node 5-1 of the LTM procedure. Nevertheless, it will be appreciated that the decision to configure LTM and to initiate LTM preparation may be a 'predictive' LTM handover decision based, for example, a measurement predictions of the type described with reference to Fig. 9 (S904 and S906).

[0202] Based on the LTM handover decision (which may be a predictive LTM handover decision) at S1212 The source RAN node 5-1 then begins to coordinate with the target RAN node 5-2 (and other candidate RAN nodes 5) by issuing, at S1214, a respective handover request, to each candidate RAN node 5 (i.e., each RAN node 5 that may become a target of the handover / cell switch in the future). In Fig. 12, whilst a single candidate RAN node 5 (the RAN node 5-2 that ultimately becomes the target) is shown there may (but do not have to) be a plurality of candidate RAN nodes 5. The information may include, for example, the target cell ID, security information, a C-RNTI of the UE 3 at the source RAN node 5-1, RRM configuration information (e.g., including UE inactive time), basic AS configuration information including antenna information and downlink carrier frequency, current QoS flow to DRB mapping rules applied to the UE 3, the SIB1 from the source RAN node 5-1, the UE capabilities for different RATs, PDU session related information, and / or UE reported measurement information including beam-related information if available.

[0203] The following procedure will be described from the perspective of the candidate RAN node 5 that ultimately becomes the target RAN node 5-2. It will, nevertheless, be appreciated that a similar procedure will be performed at each candidate RAN node 5 as part of the procedure to configure the UE 3 for LTM.

[0204] Admission control may be performed by the target RAN node 5-2 at S1215 (as described previously with respect to Fig. 6).

[0205] The target RAN node 5-2 prepares handover with its lower layers (L1 and L2) (e.g., including reserving corresponding resources for the UE 3) and sends, to the source RAN node 5-1, an appropriate response (e.g., a handover request acknowledge message or the like) at S1216. The response includes a transparent container comprising a message (e.g., an RRC message) to be sent to the UE 3 and that is to be used as an 'LTM candidate configuration' message to configure LTM handover / cell switch for that specific candidate RAN node 5 (e.g., as a handover command to instruct performance of the handover). The message to be sent to the UE 3 may, for example, be an RRC reconfiguration message or the like.

[0206] The source RAN node 5-1 transmits, at S1218, the respective LTM candidate configuration to the UE 3 received from each candidate RAN node 5 in an appropriate (e.g., RRC) message (e.g., an RRC reconfiguration message) comprising an appropriate LTM configuration information element (IE) including the respective LTM candidate configuration for each candidate RAN node 5 (of which there may be one or more). Each LTM candidate configuration in the LTM configuration IE may, for example, be a complete candidate configuration or may be a delta configuration relative to a reference configuration.

[0207] In this example, the source RAN node 5-1 also includes, as part of the LTM configuration, LTM measurement prediction configuration information for configuring predictive L1 measurements to be reported. It will be appreciated that the LTM configuration may also include LTM measurement configuration information for configuring real L1 measurements as described with reference to Fig. 6. Nevertheless, instead of reporting real-time L1 measurements (even if configured) an indication may be sent to the UE 3 (e.g., in the RRC message carrying the LTM configuration, and / or as part of DCI sent from the source RAN node 5-1) to indicate that the UE 3 should only report the measurement predictions for LTM handover.

[0208] One or more of the following information elements may, for example, be included within the measurement prediction configuration for predictive L1 measurements: ●　　A report configuration type (e.g., a periodic report, an aperiodic report, a semi-persistent report on PUCCH, a semi-persistent report on PUSCH and / or the like), as specified in TS38.331 for Rel-18 LTM Handover; ●　　An LTM resources for channel measurement IE indicating resources to be used for LTM L1 measurement (e.g., indicating an LTM CSI and / or SSB resource set); ●　　One or more measurement predictions; 　　○　　This IE may also, for example, indicate a probability associated with the measurement prediction; ●　　A measurement prediction time interval (e.g., 20ms); 　　○　　This IE may be used, for example, to define a time gap between each L1 measurement prediction instance; ●　　A quantity interval for the L1 measurement predictions (e.g., 0.5dBm for RSRP predictions); 　　○　　This IE may be used, for example, to inform the UE 3 of a unit for L1 measurement prediction, and may hence allow the L1 measurement prediction to be reported using fewer bits (e.g., for RSRP and / or differential RSRP) than an L1 measurement report based on real L1 measurements; and ●　　A time period for the L1 measurement prediction (e.g., 2000ms); 　　○　　This IE may, for example, be a fixed value, which defines a length of time within which the L1 measurements are to be predicted by the UE 3.

[0209] The UE 3 may the store the LTM candidate configurations and may respond to the message carrying the LTM configuration, at S1219, with an appropriate response message (e.g., an RRC reconfiguration complete message or the like) to effectively indicate that the LTM configuration has been completed at the UE 3.

[0210] The UE 3 may, at this stage, perform early synchronization, in the downlink and or uplink with each candidate cell (e.g., as described previously in respect of Fig. 6).

[0211] An LTM execution / completion phase (S1220) is then initiated during which the UE 3 performs, at S1221, the configured L1 measurement predictions (and possibly some real L1 measurements) for the configured candidate cells (where possible) and sends, at S1222, a corresponding L1 measurement prediction report carrying the measurement predictions to the source RAN node 5-1 in accordance with the report configuration information. By way of example, the UE 3 may periodically report its present L1 measurements and L1 measurement prediction. In another example, the UE 3 may periodically simply report the L1 measurement prediction. The L1 measurement prediction report may, for example, report the (predicted and / or measured) signal strength of each SSB resource set as configured for each LTM candidate.

[0212] By way of example, an L1 measurement prediction report sent at S1222 may comprise a list of one or more of the following: ●　　An SSBRI which is an index of an SSB resource set configured for L1 mobility measurement reporting; ●　　An RSRP prediction (i.e., as an L1 measurement quantity for each beam based on prediction); ●　　A differential RSRP prediction (i.e., as a differential L1 measurement quantity for each beam based on prediction); and ●　　A time period for prediction, which may be expressed as an integer value (e.g., 'N') representing units (or 'multiples') of a defined time interval (e.g., 20ms). For example, a value of N=4 may be used to indicate that the event is predicted to occur (approximately) 80ms after the reference time (e.g., current measurement report time).

[0213] When the source RAN node 5-1 receives an L1 measurement prediction report from the UE 3, it can then make, at S1223, a decision (e.g., an LTM handover decision) to execute cell switch to a target cell based on the measurement predictions. The source RAN node 5-1 may then initiate transmission, at S1224, of an LTM cell switch command (e.g., as a MAC CE for triggering a cell switch (or handover)) including a candidate configuration index corresponding to the target cell / target RAN node 5-2. The LTM cell switch command may, for example, contain multiple subsequent handover commands to different cells (e.g., each for a different respective reference time point). Alternatively, the source RAN node 5-1 may initiate transmission of multiple LTM cell switch commands sequentially based on the L1 measurement prediction report.

[0214] The UE 3 may then access a new cell in accordance with the content of LTM cell switch command at S1228 (e.g., in RACH based or RACH-less manner as described previously).

[0215] User Equipment 　　Fig. 13 is a schematic block diagram illustrating the main components of a UE 3 as shown in Fig. 1.

[0216] As shown in Fig. 13, the UE 3 has a transceiver circuit 31 that is operable to transmit signals to and to receive signals from a RAN node 5 via one or more antennas 33 (e.g., comprising one or more antenna elements). The UE 3 has a controller 37 to control the operation of the UE 3. The controller 37 is associated with a memory 39 and is coupled to the transceiver circuit 31. Although not necessarily required for its operation, the UE 3 might, of course, have all the usual functionality of a conventional UE 3 (e.g., a user interface 35, such as a touch screen / keypad / microphone / speaker and / or the like for, allowing direct control by and interaction with a user) and this may be provided by any one or any combination of hardware, software, and firmware, as appropriate. Software may be pre-installed in the memory 39 and / or may be downloaded via the communication system 1 or from a removable data storage device (RMD), for example.

[0217] The controller 37 is configured to control overall operation of the UE 3 by, in this example, program instructions or software instructions stored within memory 39. As shown in Fig. 13, these software instructions include, among other things, an operating system 41, a communications control module 43, a measurement management module 45, a measurement reporting module 47, and an AI / ML module 49.

[0218] The communication control module 43 is operable to control the communication between the UE 3 and its serving RAN node or RAN nodes 5-1 (and other communication devices connected to the RAN node 5-1, such as further UEs 3 and / or core network nodes). The communication control module 43 is configured for the overall handling of uplink communications via associated uplink channels (e.g., via a physical uplink control channel (PUCCH), random access channel (RACH), and / or a physical uplink shared channel (PUSCH)) including both dynamic and semi-static signalling (e.g., SRS). The communication control module 43 is also configured for the overall handling of receipt of downlink communications via associated downlink channels (e.g., of DCI via a physical downlink control channel (PDCCH) and / or a physical downlink shared channel (PDSCH)) including both dynamic and semi-persistent scheduling (e.g., SPS). The communication control module 43 is responsible, for example: for determining where to monitor for downlink control information; for determining the resources to be used by the UE 3 for transmission / reception of UL / DL communications (including interleaved resources and resources subject to frequency hopping); for managing frequency hopping at the UE side; for determining how slots / symbols are configured (e.g., for UL, DL or full duplex communication, or the like); for determining which bandwidth parts are configured for the UE 3; for determining how uplink transmissions should be encoded and the like.

[0219] It will be appreciated that the communication control module 43 may include a number of sub-modules ('layers' or 'entities') to support specific functionalities. For example, the communication control module 43 may include a PHY sub-module, a MAC sub-module, an RLC sub-module, a PDCP sub-module, an RRC sub-module, etc.

[0220] The communication control module 43 is configured, in particular, to control the UE's communications, where applicable, in accordance with any of the methods described herein.

[0221] The measurement management module 45 is responsible, subject to overall control by the communications control module 43, for managing measurement and measurement prediction related functions of the UE 3 in pursuit of any of the methods described above.

[0222] For example, the measurement management module 45 is responsible for managing tasks related to the reception and measurement of downlink signals for measurement at the UE 3 such as reference signals and / or synchronisation signals (e.g., SSBs, CSI-RS, DMRS, and / or the like) and tasks related to the prediction of measurements using the AI / ML module 49. The measurements and predictions are performed in accordance with measurement (prediction) configuration information received from a RAN node 5 (e.g., information defining one or more CSI reporting configurations in conjunction with information configuring on or more CSI resources or sets of CSI resources). The measurement management module 45 is responsible for managing measurement and / or measurement predictions for different purposes including, but not limited to, CSI reporting, L3 reporting, L1 / L2 reporting of L1 event triggered, periodic and / or semi-persistent reporting, etc.

[0223] The measurement reporting module 47 is responsible, subject to overall control by the communications control module 43, for managing measurement reporting and measurement prediction reporting related functions of the UE 3 in pursuit of any of the methods described above.

[0224] The measurement reporting module 47 is responsible, for example, for generating, and transmitting, appropriate measurement reports (including measurement prediction reports) based on the measurements and / or measurement predictions. The AI / ML module 49 is operable to control the use of one or more AI / ML models at the UE 3 (e.g., to generate one or more inferences using the model). The AI / ML module 49 may be configured to perform any of the AI / ML related functions of the UE 3 of any of the methods described above.

[0225] RAN node 　　Fig. 14 is a schematic block diagram illustrating the main components of the RAN node 5 for the communication system 1 shown in Fig. 1. As shown, the RAN node 5 has a transceiver circuit 51 for transmitting signals to and for receiving signals from the communication devices (such as UEs 3) via one or more antennas 53 (e.g., a single or multi-panel antenna array / massive antenna), and a core network interface 55 (e.g., comprising the N2, N3 and other reference points / interfaces) for transmitting signals to and for receiving signals from network nodes in the core network 7. Although not shown, the RAN node 5 may also be coupled to other RAN nodes 5 via an appropriate interface (e.g., the so-called 'Xn' interface in NR). The RAN node 5 has a controller 57 to control the operation of the RAN node 5. The controller 57 is associated with a memory 59. Software may be pre-installed in the memory 59 and / or may be downloaded via the communication system 1 or from a removable data storage device (RMD), for example. The controller 57 is configured to control the overall operation of the RAN node 5 by, in this example, program instructions or software instructions stored within memory 59.

[0226] As shown in Fig. 14, these software instructions include, among other things, an operating system 61, a communications control module 63, a measurement configuration management module 65, a measurement report management module 67, and a mobility management module 69.

[0227] The communications control module 63 is operable to control the communication between the RAN node 5 and UEs 3 and other network entities that are connected to the RAN node 5. The communications control module 63 is configured for the overall control of the reception and decoding of uplink communications, via associated uplink channels (e.g., via a physical uplink control channel (PUCCH), a random-access channel (RACH), and / or a physical uplink shared channel (PUSCH)) including both dynamic and semi-static signalling (e.g., SRS). The communications control module 63 is also configured for the overall handling the transmission of downlink communications via associated downlink channels (e.g., via a physical downlink control channel (PDCCH) and / or a physical downlink shared channel (PDSCH)) including both dynamic and semi-static signalling (e.g., CSI-RS, SSBs etc.). The communications control module 63 is also responsible, for example, for determining and scheduling the resources to be used by the UE 3 for receiving in DL / transmitting in UL, for configuring slots / symbols appropriately (e.g., for UL, DL, flexible, full duplex communication, or the like), for configuring one or more bandwidth parts for the UE 3, and for providing related configuration signalling to the UE 3.

[0228] It will be appreciated that the communications control module 63 may include a number of sub-modules (or 'layers') to support specific functionalities. For example, the communications control module 63 may include a PHY sub-module, a MAC sub-module, an RLC sub-module, a PDCP sub-module, an SDAP sub-module, an IP sub-module, an RRC sub-module, etc.

[0229] The measurement configuration management module 65 is responsible, subject to overall control by the communications control module 63, for managing measurement configuration and measurement prediction configuration related functions of the UE 3 in pursuit of any of the methods described above.

[0230] For example, the measurement configuration management module 65 is responsible for managing tasks related to the transmission of downlink signals for measurement at the UE 3 such as reference signals and / or synchronisation signals (e.g., SSBs, CSI-RS, DMRS, and / or the like) and the reception and measurement of uplink signals for measurement at the RAN node 5 (e.g., SRS), and tasks related to configuring measurements and the prediction of measurements at the UE 3. The measurement configuration management module 65 is also responsible for configuring appropriate resources for such measurement signals (e.g., CSI-RS resources) and for configuring UE reporting related to the measurement signals (e.g., CSI reports carrying appropriate information such as CQI, PMI, RI, LI, CRI, SSBRI, L1-RSRP, L1-SINR, cri-RSRP, cri-SINR, etc., L3 measurement reports, L1 event triggered, periodic and / or semi-persistent measurement reports, and / or the like).

[0231] The measurement report management module 67 is responsible, subject to overall control by the communications control module 63, for managing the reception of measurement reporting and measurement prediction reporting from the UE 3 in pursuit of any of the methods described above.

[0232] The mobility management module 69 is responsible, subject to overall control by the communications control module 63, for managing mobility related tasks in pursuit of any of the methods described above. The mobility management module 69 is responsible, for example, for L3 triggered mobility, and L1 / L2 triggered mobility, related handover / cell switch decisions and related activities.

[0233] Modifications and Alternatives 　　As those skilled in the art will appreciate, a number of modifications and alternatives can be made to the above embodiments whilst still benefiting from the disclosure embodied therein.

[0234] Whilst the above examples have been described with reference to an AI / ML model, it will be appreciated that the above described methods are advantageous even when the model is not an AI / ML model. Any other suitable type of model or function may be used to generate inferences (e.g., determinations or predictions).

[0235] It will be appreciated, for example, that whilst cellular communication generation (2G, 3G, 4G, 5G, 6G etc.) specific terminology may be used, in the interests of clarity, to refer to specific communication entities, the technical features described for a given entity are not limited to devices of that specific communication generation. The technical features may be implemented in any functionally equivalent communication entity regardless of any differences in the terminology used to refer to them.

[0236] In the above description, the UEs and the RAN node are described for ease of understanding as having a number of discrete functional components or modules. Whilst these modules may be provided in this way for certain applications, for example where an existing system has been modified to implement the disclosure, in other applications, for example in systems designed with the inventive features in mind from the outset, these modules may be built into the overall operating system or code and so these modules may not be discernible as discrete entities.

[0237] In the above example embodiments, a number of software modules were described. As those skilled in the art will appreciate, the software modules may be provided in compiled or un-compiled form and may be supplied as a signal over a computer network, or on a recording medium. Further, the functionality performed by part, or all of this software may be performed using one or more dedicated hardware circuits. However, the use of software modules is preferred as it facilitates the updating of the RAN node or the UE in order to update their functionalities.

[0238] Each controller may comprise any suitable form of processing circuitry including (but not limited to), for example: one or more hardware implemented computer processors; microprocessors; central processing units (CPUs); arithmetic logic units (ALUs); input / output (IO) circuits; internal memories / caches (program and / or data); processing registers; communication buses (e.g., control, data and / or address buses); direct memory access (DMA) functions; hardware or software implemented counters, pointers and / or timers; and / or the like. Various other modifications will be apparent to those skilled in the art and will not be described in further detail here.

[0239] The RAN node may comprise a 'distributed' RAN node having a central unit (CU) and one or more separate distributed units (DUs).

[0240] The User Equipment (or "UE", "mobile station", "mobile device" or "wireless device") in the present disclosure is an entity connected to a network via a wireless interface.

[0241] It should be noted that the present disclosure is not limited to a dedicated communication device and can be applied to any device having a communication function as explained in the following paragraphs.

[0242] The terms "User Equipment" or "UE" (as the term is used by 3GPP), "mobile station", "mobile device", and "wireless device" are generally intended to be synonymous with one another, and include standalone mobile stations, such as terminals, cell phones, smart phones, tablets, cellular IoT devices, IoT devices, and machinery. It will be appreciated that the terms "mobile station" and "mobile device" also encompass devices that remain stationary for a long period of time.

[0243] A UE may, for example, be an item of equipment for production or manufacture and / or an item of energy related machinery (for example equipment or machinery such as: boilers; engines; turbines; solar panels; wind turbines; hydroelectric generators; thermal power generators; nuclear electricity generators; batteries; nuclear systems and / or associated equipment; heavy electrical machinery; pumps including vacuum pumps; compressors; fans; blowers; oil hydraulic equipment; pneumatic equipment; metal working machinery; manipulators; robots and / or their application systems; tools; molds or dies; rolls; conveying equipment; elevating equipment; materials handling equipment; textile machinery; sewing machines; printing and / or related machinery; paper converting machinery; chemical machinery; mining and / or construction machinery and / or related equipment; machinery and / or implements for agriculture, forestry and / or fisheries; safety and / or environment preservation equipment; tractors; precision bearings; chains; gears; power transmission equipment; lubricating equipment; valves; pipe fittings; and / or application systems for any of the previously mentioned equipment or machinery etc.).

[0244] A UE may, for example, be an item of transport equipment (for example transport equipment such as: rolling stocks; motor vehicles; motorcycles; bicycles; trains; buses; carts; rickshaws; ships and other watercraft; aircraft; rockets; satellites; drones; balloons etc.). A UE may, for example, be an item of information and communication equipment (for example information and communication equipment such as: electronic computer and related equipment; communication and related equipment; electronic components etc.).

[0245] A UE may, for example, be a refrigerating machine, a refrigerating machine applied product, an item of trade and / or service industry equipment, a vending machine, an automatic service machine, an office machine or equipment, a consumer electronic and electronic appliance (for example a consumer electronic appliance such as: audio equipment; video equipment; a loud speaker; a radio; a television; a microwave oven; a rice cooker; a coffee machine; a dishwasher; a washing machine; a dryer; an electronic fan or related appliance; a cleaner etc.).

[0246] A UE may, for example, be an electrical application system or equipment (for example an electrical application system or equipment such as: an x-ray system; a particle accelerator; radio isotope equipment; sonic equipment; electromagnetic application equipment; electronic power application equipment etc.).

[0247] A UE may, for example, be an electronic lamp, a luminaire, a measuring instrument, an analyser, a tester, or a surveying or sensing instrument (for example a surveying or sensing instrument such as: a smoke alarm; a human alarm sensor; a motion sensor; a wireless tag etc.), a watch or clock, a laboratory instrument, optical apparatus, medical equipment and / or system, a weapon, an item of cutlery, a hand tool, or the like.

[0248] A UE may, for example, be a wireless-equipped personal digital assistant or related equipment (such as a wireless card or module designed for attachment to or for insertion into another electronic device (for example a personal computer, electrical measuring machine)).

[0249] A UE may be a device or a part of a system that provides applications, services, and solutions described below, as to "internet of things (IoT)", using a variety of wired and / or wireless communication technologies.

[0250] Internet of Things devices (or "things") may be equipped with appropriate electronics, software, sensors, network connectivity, and / or the like, which enable these devices to collect and exchange data with each other and with other communication devices. IoT devices may comprise automated equipment that follow software instructions stored in an internal memory. IoT devices may operate without requiring human supervision or interaction. IoT devices might also remain stationary and / or inactive for a long period of time. IoT devices may be implemented as a part of a (generally) stationary apparatus. IoT devices may also be embedded in non-stationary apparatus (e.g., vehicles) or attached to animals or persons to be monitored / tracked. It will be appreciated that IoT technology can be implemented on any communication devices that can connect to a communication system for sending / receiving data, regardless of whether such communication devices are controlled by human input or software instructions stored in memory.

[0251] It will be appreciated that IoT devices are sometimes also 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 following table. This list is not exhaustive and is intended to be indicative of some examples of machine type communication applications.

[0252]

[0253] Applications, services, and solutions may be an MVNO (Mobile Virtual Network Operator) service, an emergency radio communication system, a PBX (Private Branch eXchange) system, a PHS / Digital Cordless Telecommunications system, a POS (Point of sale) system, an advertise calling system, an MBMS (Multimedia Broadcast and Multicast Service), a V2X (Vehicle to Everything) system, a train radio system, a location related service, a Disaster / Emergency Wireless Communication Service, a community service, a video streaming service, a femto cell application service, a VoLTE (Voice over LTE) service, a charging service, a radio on demand service, a roaming service, an activity monitoring service, a telecom carrier / communication NW selection service, a functional restriction service, a PoC (Proof of Concept) service, a personal information management service, an ad-hoc network / DTN (Delay Tolerant Networking) service, etc.

[0254] Further, the above-described UE categories are merely examples of applications of the technical ideas and example embodiments described in the present document. Needless to say, these technical ideas and example embodiments are not limited to the above-described UE and various modifications can be made thereto.

[0255] Various other modifications will be apparent to those skilled in the art and will not be described in further detail here.

[0256] This application is based upon and claims the benefit of priority from United Kingdom Patent Application No. 2400769.2, filed on January 19, 2024, the disclosure of which is incorporated herein in its entirety by reference.

[0257] Supplementary notes 　　The whole or part of the example Aspects disclosed above can be described as, but not limited to, the following supplementary notes. 　　　　(Supplementary note 1) 　　A method performed by a user equipment (UE), the method comprising: 　　receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point. 　　　　(Supplementary note 2) 　　The method according to supplementary note 1, wherein 　　the configuration information indicates at least one time interval among the at least one future reference time point. 　　　　(Supplementary note 3) 　　The method according to supplementary note 1 or 2, wherein 　　the configuration information indicates at least one time window which includes the at least one future reference time point. 　　　　(Supplementary note 4) 　　The method according to any one of supplementary notes 1 to 3, wherein 　　the configuration information includes information indicating a trigger to perform the prediction of the measurements. 　　　　(Supplementary note 5) 　　The method according to supplementary note 4, wherein 　　the trigger indicates at least one of: 　　　　at least one measurement event; or 　　　　at least one mobility event. 　　　　(Supplementary note 6) 　　The method according to any one of supplementary notes 1 to 5, wherein 　　the configuration information includes information indicating at least one of: 　　　　at least one location where the UE should transmit the measurement prediction report; or 　　　　a quantity interval for the prediction of the measurements. 　　　　(Supplementary note 7) 　　The method according to any one of supplementary notes 1 to 6, wherein 　　the configuration information is included in a Radio Resource Control (RRC) message. 　　　　(Supplementary note 8) 　　The method according to any one of supplementary notes 1 to 7, wherein 　　the measurement prediction report includes at least one of: 　　　　at least one quantity of the prediction of the measurements for each future reference time point; or 　　　　a reference time window in which a particular event will occur. 　　　　(Supplementary note 9) 　　The method according to any one of supplementary notes 1 to 8, wherein 　　the measurement prediction report includes prediction information indicating which of the at least one future reference time point will a particular event occur. 　　　　(Supplementary note 10) 　　The method according to any one of supplementary notes 1 to 9, wherein 　　the measurement prediction report includes information per cell or per beam. 　　　　(Supplementary note 11) 　　The method according to any one of supplementary notes 1 to 10, wherein 　　the measurement prediction report includes information indicating a best predicted neighbour cell. 　　　　(Supplementary note 12) 　　The method according to supplementary note 11, wherein 　　the measurement prediction report includes information indicating a probability corresponding to the best predicted neighbour cell. 　　　　(Supplementary note 13) 　　The method according to any one of supplementary notes 1 to 12, wherein 　　the transmitting the measurement prediction report is performed periodically. 　　　　(Supplementary note 14) 　　The method according to any one of supplementary notes 1 to 13, further comprising: 　　receiving, from the access network node, information for causing the UE to move the UE to another cell; 　　determining whether the prediction of the measurements matches actual measurements; and 　　transmitting, to the access network node, information indicating whether the prediction of the measurements matches the actual measurements. 　　　　(Supplementary note 15) 　　The method according to supplementary note 14, further comprising: 　　cancelling to move the UE to another cell in a case where the prediction of the measurements does not match the actual measurements. 　　　　(Supplementary note 16) 　　A method performed by an access network node, the method comprising: 　　transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point. 　　　　(Supplementary note 17) 　　A user equipment (UE) comprising: 　　means for receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point. 　　　　(Supplementary note 18) 　　An access network node comprising: 　　means for transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

[0258] 1　　COMMUNICATION SYSTEM 3, 3-1, 3-2, 3-3　　USER EQUIPMENT (UE) 5, 5-1, 5-2, 5-A, 5-B, 5-C　　RADIO ACCESS NETWORK (RAN) NODE 7　　CORE NETWORK 9, 9-1, 9-2　　ASSOCIATED CELL 10　　CONTROL PLANE FUNCTION (CPF) 10-1　　ACCESS AND MOBILITY MANAGEMENT FUNCTION (AMF) 10-2　　SESSION MANAGEMENT FUNCTIONS (SMF) 10-n　　OTHER FUNCTIONS 11　　USER PLANE FUNCTION (UPF) 20　　EXTERNAL DATA NETWORK 31, 51　　TRANSCEIVER CIRCUIT 33, 53　　ANTENNA 35　　USER INTERFACE 55　　CORE NETWORK INTERFACE 37, 57　　CONTROLLER 39, 59　　MEMORY 41, 61　　OPERATING SYSTEM 43, 63　　COMMUNICATIONS CONTROL MODULE 45　　MEASUREMENT MANAGEMENT MODULE 47　　MEASUREMENT REPORTING MODULE 49　　AI / ML MODULE 65　　MEASUREMENT CONFIGURATION MANAGEMENT MODULE 67　　MEASUREMENT REPORT MANAGEMENT MODULE 69　　MOBILITY MANAGEMENT MODULE 341　　DATA COLLECTION FUNCTION 343　　MODEL TRAINING FUNCTION 345　　MODEL INFERENCE FUNCTION 347　　ACTOR 349　　MANAGEMENT FUNCTION 351　　MODEL STORAGE ENTITY

Claims

1. A method performed by a user equipment (UE), the method comprising: 　　receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

2. The method according to claim 1, wherein 　　the configuration information indicates at least one time interval among the at least one future reference time point.

3. The method according to claim 1 or 2, wherein 　　the configuration information indicates at least one time window which includes the at least one future reference time point.

4. The method according to any one of claims 1 to 3, wherein 　　the configuration information includes information indicating a trigger to perform the prediction of the measurements.

5. The method according to claim 4, wherein 　　the trigger indicates at least one of: 　　　　at least one measurement event; or 　　　　at least one mobility event.

6. The method according to any one of claims 1 to 5, wherein 　　the configuration information includes information indicating at least one of: 　　　　at least one location where the UE should transmit the measurement prediction report; or 　　　　a quantity interval for the prediction of the measurements.

7. The method according to any one of claims 1 to 6, wherein 　　the configuration information is included in a Radio Resource Control (RRC) message.

8. The method according to any one of claims 1 to 7, wherein 　　the measurement prediction report includes at least one of: 　　　　at least one quantity of the prediction of the measurements for each future reference time point; or 　　　　a reference time window in which a particular event will occur.

9. The method according to any one of claims 1 to 8, wherein 　　the measurement prediction report includes prediction information indicating which of the at least one future reference time point will a particular event occur.

10. The method according to any one of claims 1 to 9, wherein 　　the measurement prediction report includes information per cell or per beam.

11. The method according to any one of claims 1 to 10, wherein 　　the measurement prediction report includes information indicating a best predicted neighbour cell.

12. The method according to claim 11, wherein 　　the measurement prediction report includes information indicating a probability corresponding to the best predicted neighbour cell.

13. The method according to any one of claims 1 to 12, wherein 　　the transmitting the measurement prediction report is performed periodically.

14. The method according to any one of claims 1 to 13, further comprising: 　　receiving, from the access network node, information for causing the UE to move the UE to another cell; 　　determining whether the prediction of the measurements matches actual measurements; and 　　transmitting, to the access network node, information indicating whether the prediction of the measurements matches the actual measurements.

15. The method according to claim 14, further comprising: 　　cancelling to move the UE to another cell in a case where the prediction of the measurements does not match the actual measurements.

16. A method performed by an access network node, the method comprising: 　　transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

17. A user equipment (UE) comprising: 　　means for receiving, from an access network node, configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for transmitting, to the access network node, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

18. An access network node comprising: 　　means for transmitting, to a user equipment (UE), configuration information for configuring a prediction of measurements at least one future reference time point; and 　　means for receiving, from the UE, a measurement prediction report corresponding to the prediction of the measurements at the at least one future reference time point.

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