Time-domain predictions in measurement reports for cho configuration

Abstract

According to an aspect, there is provided method performed by a user equipment, UE The UE is being served by a first cell of a source network node. The method comprises transmitting (602), to the source network node, a first message comprising time-domain prediction information for a second cell; receiving, from the source network node, a conditional handover, CHO, configuration comprising a CHO execution condition and a CHO candidate configuration for the second cell; and evaluating the CHO execution condition associated with the second cell.

Description

[0001] Time-domain predictions in measurement reports for CHO configuration

[0002] Technical Field

[0003] This disclosure relates to time-domain prediction information.

[0004] Background

[0005] Conditional handover (CHO) has been introduced in Release 16 (Rel-16) for New Radio (NR) to improve the mobility robustness i.e. reduce the amount of Radio Link Failure(s) (RLF) and / or Handover failure(s) (HOF) in the user equipment (UE). Failures could be caused by the fact that when the UE is in the cell border, and close to be triggered by the network to perform a handover (HO), the UE may try to send a Layer 3 (L3) Measurement Report (MR) to the network which is either not received by the source gNodeB (gNB) (e.g. due to some interference in the UL and / or poor coverage) or, even if the source gNodeB receives the Measurement Report, the UE does not receive the Handover Command in response to it (e.g. an RRCReconfiguration message including a ReconfigurationWithSync) to trigger the Handover (e.g. due to some interference in the downlink (DL) and / or poor DL coverage). Due to HOF and RLF, the UE would trigger an RRC Re-establishment procedure, which leads to more signaling exchanged between the UE and the network, and higher interruption time, since there is no service continuity. This is illustrated in Fig. 1. Fig. 1 shows two signaling diagrams which depict how a lack of mobility robustness may lead to RLFs and / or HOFs, which leads to RRC Re-establishment i.e. higher signaling and interruption time.

[0006] To improve mobility robustness, the 3rd Generation Partnership Project (3GPP) introduced in Rel-16 the feature called CHO, which may be defined as a handover that is executed by the UE when one or more handover execution conditions are met. When configured with CHO, the UE starts evaluating the execution condition(s) upon receiving the CHO configuration and stops evaluating the execution condition(s) once a handover is executed.

[0007] The following principles apply to CHO:

[0008] • The CHO configuration contains the configuration of CHO candidate cell(s) generated by the candidate gNB(s) and execution condition(s) generated by the source gNB.

[0009] • An execution condition may consist of one or two trigger condition(s) (CHO events A3 / A5). Only single Reference Signal (RS) type is supported and at most two different trigger quantities (e.g. reference signal received power (RSRP) and reference signal received quality (RSRQ), RSRP and signal-to-noise and interference ratio (SINR), etc.) can be configured simultaneously for the evaluation of CHO execution condition of a single candidate cell.

[0010] • Before any CHO execution condition is satisfied, upon reception of HO command (without CHO configuration), the UE executes the HO procedure as described in clause 9.2.3.2 of 3GPP Technical Specification (TS) 38.300 version 17.4.0, regardless of any previously received CHO configuration.

[0011] • While executing CHO, i.e. from the time when the UE starts synchronization with target cell, the UE does not monitor source cell.

[0012] Fig. 2 is a signalling diagram showing a signalling flow for CHO. The signals and events labelled 0 through to 8c are described below.

[0013] 0. The UE context within the source gNB contains information regarding roaming and access restrictions which were provided either at connection establishment or at the last tracking area (TA) update.

[0014] 1. The source gNB configures the UE measurement procedures and the UE reports according to the measurement configuration.

[0015] 2. The source gNB decides to use CHO e.g., based on Measurement Report(s) and Radio Resource Management (RRM) information.

[0016] 3. The source gNB requests CHO for one or more candidate cells belonging to one or more candidate gNBs. A CHO request message is sent for each candidate cell.

[0017] 4. Admission Control may be performed by the target gNB (and the candidate gNB(s)). Slice-aware admission control shall be performed if the slice information is sent to the target gNB. If the protocol data unit (PDU) sessions are associated with non-supported slices the target gNB shall reject such PDU Sessions.

[0018] 5. The candidate gNB(s) sends CHO response (HO REQUEST ACKNOWLEDGE) including configuration of CHO candidate cell(s) to the source gNB. The CHO response message is sent for each candidate cell.

[0019] 6. The source gNB sends an RRCReconfiguration message to the UE, containing the configuration of CHO candidate cell(s) and CHO execution condition(s).

[0020] NOTE 1 : CHO configuration of candidate cells can be followed by other reconfiguration from the source gNB.

[0021] NOTE 1a: A configuration of a CHO candidate cell cannot contain a DAPS handover configuration.

[0022] 7. The UE sends an RRCReconfigurationComplete message to the source gNB.

[0023] 7a. If early data forwarding is applied, the source gNB sends the EARLY STATUS TRANSFER message. 8. The UE maintains connection with the source gNB after receiving CHO configuration, and starts evaluating the CHO execution conditions for the candidate cell(s). If at least one CHO candidate cell satisfies the corresponding CHO execution condition, the UE detaches from the source gNB, applies the stored corresponding configuration for that selected candidate cell, synchronises to that candidate cell and completes the RRC handover procedure by sending RRCReconfigurationComplete message to the target gNB. The UE releases stored CHO configurations after successful completion of the RRC handover procedure.

[0024] 8a / b. The target gNB sends the HANDOVER SUCCESS message to the source gNB to inform that the UE has successfully accessed the target cell. In return, the source gNB sends the SN STATUS TRANSFER message following the principles described in step 7 of Intra-AMF / UPF Handover in clause 9.2.3.2.1 of 3GPP TS 38.300 version 17.4.0.

[0025] NOTE 2: Late data forwarding may be initiated as soon as the source gNB receives the HANDOVER SUCCESS message.

[0026] 8c. The source gNB sends the HANDOVER CANCEL message toward the other signalling connections or other candidate target gNBs, if any, to cancel CHO for the UE.

[0027] Artificial Intelligence (Al) / Machine Learning (ML) for PHY Study Item Rel-18

[0028] Artificial Intelligence (Al) and Machine Learning (ML) have been investigated as promising tools to optimize the design of air-interface in wireless communication networks in both academia and industry. Example use cases include using autoencoders for Channel State Information (CSI) compression to reduce the feedback overhead and improve channel prediction accuracy; using deep neural networks for classifying Line of Sight (LOS) and Non-LOS (NLOS) conditions to enhance the positioning accuracy; and using reinforcement learning for beam selection at the network side and / or the UE side to reduce the signaling overhead and beam alignment latency; using deep reinforcement learning to learn an optimal precoding policy for complex Multiple Input and Multiple Output (MIMO) precoding problems.

[0029] In 3GPP NR standardization work, a new release 18 study item on AI / ML for NR air interface has started since May 2022. This study item will explore the benefits of augmenting the airinterface with features enabling improved support of AI / ML based algorithms for enhanced performance and / or reduced complexity / overhead.

[0030] AI / ML for beam management is a use case that is particularly relevant to the present disclosure. AI / ML for beam management includes predicting the channel in respect of a beam for a certain time-frequency resource. In other words, the beam management use case for AI / ML includes beam prediction in time and / or spatial domain for overhead and latency reduction, beam selection accuracy improvement. The expected performance of such predictor depends on several different aspects, for example time / frequency variation of channel due to UE mobility or changes in the environment. Due to the inherent correlation in time, frequency and the spatial domain of the channel, an ML-model can be trained to exploit such correlations. The spatial domain can comprise of different beams, where the correlation properties partly depend on the how the gNB antennas forms the different beams, and how UE forms the receiver beams.

[0031] In the latest agreements from 3GPP RAN1 , the one use case for Beam Management based on AI / ML that is of particular interest is called “Temporal Downlink beam prediction”, as described below.

[0032] • BM-Case1 : Spatial-domain Downlink beam prediction for Set A of beams based on measurement results of Set B of beams o Consider: Alt. 1): AI / ML model training and inference at NW side. Alt. 2): AI / ML model training and inference at UE side. o Consider: Alt. i): Set A and Set B are different (Set B is NOT a subset of Set A). Alt. ii): Set B is a subset of Set A. Note: Set A is for DL beam prediction and Set B is for DL beam measurement. The beam patterns of Set A and Set B can be clarified by companies. o AI / ML model input: Alt 1): Only L1-RSRP measurement based on Set B; Alt.2): L1-RSRP measurement based on Set B and assistance information; Alt. 3): CIR based on Set B; Alt. 4): L1-RSRP measurement based on Set B and the corresponding DL Tx and / or Rx beam ID.

[0033] • BM-Case2: Temporal Downlink beam prediction for Set A of beams based on the historic measurement results of Set B of beams o Consider: Alt. 1): AI / ML model training and inference at NW side. Alt. 2): AI / ML model training and inference at UE side. o Consider: Alt. i): Set A and Set B are different (Set B is NOT a subset of Set A). Alt. ii): Set B is a subset of Set A (Set A and Set B are not the same). Alt. iii): Set A and Set B are the same. o AI / ML model input: measurement results of K (K>1) latest measurement instances with the following alternatives: Alt. 1): Only L1-RSRP measurement based on Set B; Alt 2): L1-RSRP measurement based on Set B and assistance information; Alt. 3): L1-RSRP measurement based on Set B and the corresponding DL Tx and / or Rx beam ID. o [AI / ML model output]: F predictions for F future time instances, where each prediction is for each time instance. At least F=1. Set B is a set of beams whose measurements are taken as inputs of the AI / ML model. Note: Beams in Set A and Set B can be in the same Frequency Range.

[0034] For both sub-use cases, the following alternatives are studied for the predicted beams:

[0035] • Alt.1 : DL Tx beam prediction

[0036] • Alt.2: DL Rx beam prediction (deprioritized)

[0037] • Alt.3: Beam pair prediction (a beam pair consists of a DL Tx beam and a corresponding DL Rx beam)

[0038] Note: DL Rx beam prediction may or may not have spec impact.

[0039] The following alternatives for [AI / ML model output] are defined:

[0040] • Alt.1 : Tx and / or Rx Beam ID(s) and / or the predicted L1-RSRP of the N predicted DL Tx and / or Rx beams o e.g., N predicted beams can be the top-N predicted beams

[0041] • Alt.2: Tx and / or Rx Beam ID(s) of the N predicted DL Tx and / or Rx beams and other information o e.g., N predicted beams can be the top-N predicted beams

[0042] • Alt.3: Tx and / or Rx Beam angle(s) and / or the predicted L1-RSRP of the N predicted DL Tx and / or Rx beams o e.g., N predicted beams can be the top-N predicted beams

[0043] All of the outputs in the above alternatives may vary based on whether the AI / ML model inference is at UE side or gNB side. The Top-N beam IDs might have been derived via postprocessing of the ML-model output.

[0044] Fig. 3 provides a summary of the assumptions for AI / ML for Beam Management, as described above.

[0045] Al / ML for Mobility in Rel-19

[0046] The AI / ML for PHY work in Rel-18 has been limited to lower layer features, such as Beam Management, which is sometimes referred to as intra-cell mobility. Other features, such as L3 handovers, RRC measurements, L1 / L2 triggered mobility (LTM), RRC measurement reporting and Conditional Handover has not been of the Rel-18, but initial discussions for Rel-19 seemed to indicate that higher layer features, specified by RAN2, might leverage on AI / ML functions to be possibly specified. Summary

[0047] There currently exist certain challenge(s). Existing CHO procedures can result in many cells being configured as CHO candidates, which is problematic in various ways.

[0048] For example, under existing CHO procedures, the UE is configured by the source gNodeB with one or more CHO candidate cells based on RRC Measurement Reports transmitted by the UE to the source gNodeB, and CHO is triggered by the fulfillment of the entry condition, e.g., of an Event A3 (Neighbor becomes offset better than SpCell), which is specified as follows in 3GPP TS 38.331 V17.4.0:

[0049] 5.5.4 Measurement report triggering

[0050] 5.5.4.1 General

[0051] If AS security has been activated successfully, the UE shall:

[0052] 1> for each measld included in the measIdList within VarMeasConfig'.

[0053] 2> if the corresponding reportConfig includes a reportType set to eventTriggered or periodical'.

[0054] 3> if the corresponding measObject concerns NR:

[0055] [...]

[0056] 4> if the eventA3 or eventA5 is configured in the corresponding reportConfig'.

[0057] 5> if a serving cell is associated with a measObjectNR and neighbors are associated with another measObjectNR, consider any serving cell associated with the other measObjectNR to be a neighboring cell as well;

[0058] [...]

[0059] 2> if the reportType is set to eventTriggered and if the entry condition applicable for this event, i.e. the event corresponding with the eventld of the corresponding reportConfig within VarMeasConfig, is fulfilled for one or more applicable cells for all measurements after layer 3 filtering taken during timeToTrigger defined for this event within the VarMeasConfig, while the VarMeasReportList does not include a measurement reporting entry for this measld (a first cell triggers the event):

[0060] 3> include a measurement reporting entry within the VarMeasReportList for this measld',

[0061] 3> set the numberOfReportsSent defined within the VarMeasReportList for this measld to 0;

[0062] 3> include the concerned cell(s) in the cellsTriggeredList defined within the VarMeasReportList for this measld',

[0063] 3> initiate the measurement reporting procedure, as specified in 5.5.5;

[0064] [...]

[0065] 2> upon expiry of the periodical reporting timer for this measld'.

[0066] 3> initiate the measurement reporting procedure, as specified in 5.5.5. [...]

[0067] 5.5.4.4 Event A3 (Neighbor becomes offset better than SpCell)

[0068] The UE shall:

[0069] 1> consider the entering condition for this event to be satisfied when condition A3-1, as specified below, is fulfilled;

[0070] [ .]

[0071] 1> use the SpCell for Mp, Ofp and Ocp.

[0072] NOTE The cell(s) that triggers the event has reference signals indicated in the measObjectNR associated to this event which may be different from the NR SpCell measObjectNR.

[0073] [■••]

[0074] Inequality A3-1 (Entering condition)

[0075] Mn + Ofn + Ocn - Hys > Mp + Ofp + Ocp + Off

[0076] [ .]

[0077] The variables in the formula are defined as follows:

[0078] Mn is the measurement result of the neighboring cell, not taking into account any offsets.

[0079] Ofn is the measurement object specific offset of the reference signal of the neighbor cell (i.e. offsetMO as defined within measObjectNR corresponding to the neighbor cell).

[0080] Ocn is the cell specific offset of the neighbor cell (i.e. celllndividualOffset as defined within measObjectNR corresponding to the frequency of the neighbor cell), and set to zero if not configured for the neighbor cell.

[0081] Mp is the measurement result of the SpCell, not taking into account any offsets.

[0082] Ofp is the measurement object specific offset of the SpCell (i.e. offsetMO as defined within measObjectNR corresponding to the SpCell).

[0083] Ocp is the cell specific offset of the SpCell (i.e. celllndividualOffset as defined within measObjectNR corresponding to the SpCell), and is set to zero if not configured for the SpCell.

[0084] Hys is the hysteresis parameter for this event (i.e. hysteresis as defined within reportConfigNR for this event).

[0085] Off is the offset parameter for this event (i.e. a3-Offset as defined within reportConfigNR for this event).

[0086] Mn, Mp are expressed in dBm in case of RSRP, or in dB in case of RSRQ and RS-SINR.

[0087] Ofn, Ocn, Ofp, Ocp, Hys, Off are expressed in dB.

[0088] An Event A3 may be triggered by the UE when the UE gets closer to the cell border and / or when one or multiple neighbor cells Reference Signal Received Power (RSRP) and / or Reference Signal Received Quality (RSRQ) and / or Signal to Interference-Noise Ratio (SI NR) start to become an offset better than the corresponding RSRP and / or RSRQ and / or SINR of current Primary Cell (PCell). For the purpose of identifying CHO candidate cells, such an Event A3 is configured at the UE with offset(s) not very close to the actual condition in which a handover or conditional handover is supposed to be triggered / executed, otherwise it is too close to the time in which a handover occurs, and perhaps there is no time to configure CHO until an actual HO needs to be triggered. For that reason, the Event A3 event offset and other parameters may be configured further from the actual condition in which a handover or CHO needs to be triggered / executed, which can mean that multiple neighbor cell(s) fulfil the Event A3 condition, which leads to a Measurement Report with various neighbor cells as triggered cells (i.e. fulfilling entering conditions of Event A3) for the source gNodeB to select as CHO candidates.

[0089] CHO effectively reduces handover failure rate especially in the scenario where the performance is challenging to guarantee. However, it has been found that most of the gains are achieved even with a single candidate target cell, and allowing more candidates leads to additional, but only moderate, gains. Thus, it is important how the network selects the CHO candidate cells.

[0090] As noted above, configuring many neighbor cells as CHO candidates is problematic in various ways. Firstly, the maximum number is limited to 8. Secondly, it leads to an increase in the number of measurements the UE needs to perform which increases UE energy consumption, and, especially in the case of inter-frequency measurements, which may require measurement gaps, throughput in the PCell may be reduced.

[0091] Thirdly, it represents a waste of resources at the network side, since CHO candidate cells would need to reserve resources for a possibly incoming UE, and, when CHO execution occurs (CHO execution condition is fulfilled), the UE only selects one of the CHO candidate cells, i.e., the resources reserved by the other candidate cells are wasted from the time the UE has been monitoring the execution conditions until the time the UE executes CHO with one of the candidate(s) (this can be seen in step 8c of Fig. 2, in which the source gNB sends a HANDOVER CANCEL message toward the other signalling connections or other candidate target gNBs, if any, to cancel CHO for the UE).

[0092] Fig. 4 depicts a scenario in which an Event A3 offset has an early setting when configured for identifying neighbor cells which are potential CHO candidate cells. In the example illustrated in Fig. 4, a neighbor cell is a triggered cell for Event A3 based on an A3 offset (early offset) and is configured as a CHO candidate under the expectation that there is some likelihood that the measurements of such a neighbor cell (e.g. RSRP) would become even larger than the PCell’s RSRP, up to the A3 offset configured for the CHO execution, however, that does not happen.

[0093] A fourth problem associated with configuring many neighbor cells as CHO candidates, also related to CHO resources, arises when the network wants to trigger Early Data Forwarding (EDF). When the source gNodeB wants to trigger EDF, it sends an EARLY STATUS TRANSFER message to each CHO candidate gNodeB (concerning one or more CHO candidates) and starts data forwarding to them. This causes a waste of reserved CHO resources if the configured CHO candidate gNodeBs are not selected by the UE.

[0094] A fifth problem, also related to CHO resources, arises when the candidate network node needs to determine how to configure Contention Free Random Access (CFRA) for a candidate cell configured for CHO. The problem is that in legacy handover, the target network node receives beam measurements (e.g. L3 filtered Synchronization Signal Block (SSB) measurement, like filtered Synchronization Signal Reference Signal Received Power (SS-RSRP) values) based on which the target network node can configure CFRA at least for beams reported as good e.g. RSRP above a threshold the target cell would define for selecting an SSB and / or Channel State Information Reference Signal (CSI-RS) before random access resource selection. However, in CHO, the time instant in which the candidate network node (e.g. candidate gNodeB) needs to configure CFRA resources and the time instant in which the UE needs to execute CHO and perform random access may differ significantly, so that CFRA resources configured when CHO is configured may not even be associated to SSBs and / or CSI-RS resources which the UE is able to detect during CHO execution.

[0095] Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. The techniques disclosed herein thereby improve the performance of Conditional Handovers.

[0096] The present disclosure comprises a method at a User Equipment (UE) in which the UE transmits a first message (e.g. RRC Measurement Report) including prediction information (such as time-domain prediction information derived based on time-domain predictions of measurements) for a neighbor cell (and / or a serving cell) and receives a Conditional Handover (CHO) candidate configuration of the neighbor cell (to be applied upon CHO execution). The neighbour cell is also referred to herein as a second cell, and the serving cell of the UE is also referred to herein as the first cell. In some embodiments, the first message corresponds to a MeasurementReport message in RRC (e.g. triggered by the fulfillment of an Event A3 when the neighbor cell becomes an offset better than the PCell or an Event A4 when the neighbour cell becomes offset better than a threshold). The UE can include in the MeasurementReport measurement and prediction information of the neighbor cell and / or the PCell, before it receives the CHO candidate configuration of the neighbor cell.

[0097] The present disclosure also comprises a method at a UE comprising receiving a Conditional Handover (CHO) candidate configuration of a neighbor cell (to be applied upon CHO execution) and, afterwards, transmitting a first message (e.g. RRC Measurement Report) including prediction information (such as time-domain prediction information derived based on time-domain predictions of measurements) for the neighbor cell configured as a CHO candidate (and / or a serving cell), evaluating the CHO execution condition associated to the at least one neighbor cell and executing CHO to the at least one neighbor cell of a candidate network node. When the UE accesses the at least one neighbor cell in CHO execution, downlink data is available at the candidate network node to be scheduled to the UE. In other words, due to the reported first and / or second prediction information, Early Data Forwarding is triggered by the source network node, so that data is available at the candidate network node when the UE performs CHO execution.

[0098] The present disclosure also comprises a method at a source network node. The UE transmits the first message including the prediction information of the neighbor cell (and / or prediction information on a serving cell) to a source network node and, the source network node determines to configure the UE with that neighbor cell as a CHO candidate cell in response to the reported information. In a network implementation step, the source network node configures the neighbor cell as a CHO candidate cell when the prediction information indicates that the neighbor cell is a likely candidate the UE would execute CHO e.g. time domain predictions show that the RSRP of the neighbor cell develops such a way that it further increases while the RSRP of the PCell further decreases.

[0099] The present disclosure also comprises a method at a candidate network node, which is also referred to herein as a second network node. The source network node transmits to a candidate network node, associated to the neighbor cell, a CHO request (e.g. Handover Request message including an Information Element indicating a CHO request). The CHO request includes the predicted information from the UE (or some post-processed information based on the predicted information received from the UE). In response to it, the candidate network node transmits a CHO Request Ack (e.g. Handover Request Acknowledge message) including the Conditional Handover (CHO) candidate configuration of the for the neighbor cell. As a network implementation step, the candidate network node accepts the requested neighbor cell as a CHO candidate cell when the prediction information indicates that the neighbor cell is a likely candidate the UE would execute CHO e.g. time domain predictions show that the RSRP of the neighbor cell develops such a way that it further increases while the RSRP of the PCell further decreases. As a network implementation step, the candidate network node configures the CFRA resources (part of CHO candidate configuration message) associated to one or more SSBs where the prediction information indicates that the SSB(s) is / are likely to be selected when the UE execute CHO.

[0100] According to a first aspect, there is provided a method performed by a user equipment (UE) being served by a first cell of a source network node. The method comprises: transmitting, to the source network node, a first message comprising time-domain prediction information for a second cell; receiving, from the source network node, a conditional handover (CHO) configuration comprising a CHO execution condition and a CHO candidate configuration for the second cell; and evaluating the CHO execution condition associated with the second cell.

[0101] According to a second aspect, there is provided a method performed by a source network node. A user equipment (UE) is being served by a first cell of the source network node. The method comprises: receiving, from the UE, a first message comprising time-domain prediction information for a second cell; and transmitting, to the UE, a conditional handover (CHO) configuration comprising a CHO candidate configuration for the second cell and a CHO execution condition for the second cell.

[0102] According to a third aspect, there is provided a method performed by a second network node. A user equipment (UE) is being served by a first cell of a source network node. The method comprises: receiving, from the source network node, a conditional handover request for configuring a conditional handover for a second cell, wherein the second cell is a cell of a second network node, and the conditional handover request comprises time-domain prediction information for the second cell or information derived therefrom.

[0103] According to a fourth aspect, there is provided a computer program product comprising a computer readable medium having computer readable code embodied therein, the computer readable code being configured such that, on execution by a suitable computer or processor, the computer or processor is caused to perform the method according to the first aspect, the second aspect, the third aspect or any embodiment thereof.

[0104] According to a fifth aspect, there is provided a user equipment (UE) configured to perform the method according to the first aspect or any embodiment thereof.

[0105] According to a sixth aspect, there is provided a user equipment (UE) comprising a processor and a memory, said memory containing instructions executable by said processor whereby said UE is operative to perform the method according to the first aspect or any embodiment thereof.

[0106] According to a seventh aspect, there is provided a first radio access network (RAN) node, configured to perform the method according to the second aspect, the third aspect, or any embodiment thereof.

[0107] According to an eighth aspect, there is provided a first radio access network (RAN) node comprising a processor and a memory, said memory containing instructions executable by said processor whereby said first RAN node is operative to perform the method according to the second aspect, the third aspect, or any embodiment thereof.

[0108] Certain embodiments may provide one or more of the following technical advantage(s).

[0109] A benefit of the present disclosure is that due to the reported predictions (e.g. time-domain predictions), the UE may be configured with fewer CHO candidates, in which there is more certainty (i.e., an increased likelihood) that one of these fewer CHO candidates is the one the UE is likely to execute CHO in a successful manner.

[0110] Having fewer neighbor cells configured as CHO candidates has various benefits. First, there is no need to fill in the maximum number, which is limited to 8. Second, it reduces the number of measurements the UE needs to perform for CHO, which reduces UE energy consumption, and, especially in the case of inter-frequency measurements, may require shorter measurement gaps (or no measurement gaps), which means less degradation in throughout in the PCell due to measurements the UE needs to perform. Third, it enables a better resource usage at the network, since only the most probable CHO candidate cells would need to reserve resources for a possibly incoming UE i.e. there would be fewer cells for which the resources reserved by the other candidate cells were wasted from the time the UE has been monitoring the execution conditions until the time the UE executes CHO with one of the candidate(s) (see step 8c in Figure 2, in which the source gNB sends the HANDOVER CANCEL message toward the other signaling connections or other candidate target gNBs, if any, to cancel CHO for the UE.

[0111] Another benefit of the present disclosure is that the source gNodeB can trigger Early Data Forwarding (EDF) with more certainty, to fewer candidate cells, which means the mobility interruption time at the UE due to a CHO execution would be reduced, also improving the user experience.

[0112] For the case predictions of L3 filtered beam measurements are included in the measurement reports, based on which the Candidate Network node (e.g. candidate gNodeB) configured CFRA resources for beams reported to remain good in future time instances, one advantage is that the UE may be actually configured with CFRA which improves the delay in accessing the target candidate cell in CHO execution (as only two steps would be required instead of 4, and contention is prevented). At the network side, that also represents a benefit in terms of resource usage, as the network would not need to configure too many CFRA resources unnecessarily.

[0113] Brief Description of the Drawings

[0114] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings, in which:

[0115] Fig. 1 shows two signalling diagrams which depict how a lack of mobility robustness may lead to higher signalling and interruption time;

[0116] Fig. 2 is a signalling diagram showing a signalling flow for conditional handover;

[0117] Fig. 3 illustrates the assumptions for AI / ML for Beam Management;

[0118] Fig. 4 depicts a scenario in which an Event A3 offset has an early setting;

[0119] Fig. 5 is a signalling diagram showing techniques according to the present disclosure; Fig. 6 is a flow chart illustrating a method in accordance with some embodiments;

[0120] Fig. 7 is a flow chart illustrating a method in accordance with some embodiments;

[0121] Fig. 8 is a flow chart illustrating a method in accordance with some embodiments;

[0122] Fig. 9 shows an example AI / ML model;

[0123] Fig. 10 shows an example AI / ML model;

[0124] Fig. 11 shows an example of time domain cell prediction derivation;

[0125] Fig. 12 shows an example of time domain cell prediction derivation;

[0126] Fig. 13 shows an example of time domain cell prediction derivation;

[0127] Fig. 14 shows two examples of model architectures;

[0128] Fig. 15 shows an example of AI / ML model input and output fortime domain beam prediction;

[0129] Fig. 16 depicts a source decision not to configure CHO for a neighbour cell according to some embodiments;

[0130] Fig. 17 depicts a source decision to configure CHO for a neighbour cell according to some embodiments;

[0131] Fig. 18 is a signalling diagram according to some embodiments;

[0132] Fig. 19 is a signalling diagram according to some embodiments;

[0133] Fig. 20 is a signalling diagram according to some embodiments;

[0134] Fig. 21 shows an example of a communication system in accordance with some embodiments;

[0135] Fig. 22 shows a UE in accordance with some embodiments;

[0136] Fig. 23 shows a RAN network node in accordance with some embodiments; and

[0137] Fig. 24 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized.

[0138] Detailed Description

[0139] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0140] Fig. 5 is a signalling diagram showing techniques according to the present disclosure at the UE, source network node and candidate network node.

[0141] As shown in Fig. 5, the UE sends a first message to the Source Network Node that includes first prediction information for at least one neighbour cell. The Source Network Node sends a Handover Request for CHO to the Candidate Network Node associated to the reported neighbour cell. The Candidate Network Node responds to the Source Network Node with a Handover Request Acknowledge for CHO including the CHO candidate configuration of the neighbour cell. The Source Network Node sends a CHO configuration to the UE that includes the CHO candidate configuration for the neighbour cell and CHO execution condition. The UE evaluates the CHO execution condition associated to the at least one neighbour cell. Also at the UE, the CHO execution condition associated to the at least one neighbour cell is fulfilled and the UE accesses the neighbour cell. CHO execution then occurs with the neighbour cell.

[0142] In the context of the present disclosure, the term “ML-model” or “Al-model”, “Model Inference”, “Model Inference function” or “AI / ML model” are used interchangeable. An AI / ML model can be defined, in the context of the present disclosure, as a functionality or be part of a functionality that is deployed / implemented in the UE. An AI / ML model can be defined as a feature or part of a feature that is implemented / supported in a UE. An ML-model (or Model Inference function) may correspond to a function which receives one or more inputs (e.g. measurements performed on reference signal(s) of a neighbor cell, such as SSBs and / or CSI-RSs) and provide as outcome one or more prediction(s) / estimates / decisions of a certain type e.g. values of a measurements in the future, such as predicted RSRP values in a future time instance. It may be said that an ML model or Model Inference is a function that provides AI / ML model inference output (e.g. predictions or decisions). The Model inference function may also responsible for data preparation (e.g. data pre-processing and cleaning, formatting, and transformation) based on Inference Data delivered by a Data Collection function. The output may correspond to the inference output of the AI / ML model produced by a Model Inference function.

[0143] In the context of this present disclosure, the predictions are time-domain predictions: thus, the input of the ML-model comprises at least one or more measurements at (or starting at) a time instance to (and / or a timer interval such as T1 or tO+T 1 , which may comprise one or more samples or measurement time occasions, from 1 to K time occasions) of at least one neighbor cell, and the output of the ML-model comprises one or more predicted measurements at (or starting at) a future time instance e.g. to + T, possibly comprising future time instances within a time window of duration T2 and having F predictions. Further terminology may refer to an “actor”, as a function that receives the output from the Model inference function and triggers or performs corresponding actions. The Actor may trigger actions directed to other entities or to itself. In the context of this particular present disclosure, one actor may correspond to CSI / beam prediction reporting (or CSI prediction reporting) functionality at the UE, and / or the functionality at the UE responsible for generating the data structure to transmit the one or more information derived based on the one or more time-domain predictions. In one example, an ML-model may correspond to a function receiving as input one or more measurements of at least one DL RS at time instance to (or a time interval starting or ending at tO), after at least one measurement period, (e.g. transmitted in beam- X, SSB-x, CSI-RS resource index x) and provide as output the prediction of the RS measurement(s) in time instance tO+T (or a time interval starting or ending at tO+T, until tO+T+T2). This future time instance tO+T, obtained at to, may be in different time units such as in number of slots (frames, sub-frames, OFDM symbols, etc.) after the UE has performed the last measurement or targeting a specific slot in time within the future.

[0144] In the context of the present disclosure, a measurement may correspond to one or more of:

[0145] • A radio measurement i.e. a measurement performed on reference signal(s) received by the UE over the radio interface

[0146] • An RRM measurement, since they assist Radio Resource Management decisions at the network side and / or Layer 3 (L3) or higher layer measurements, since these measurements would be the responsibility of the RRC protocol, also called L3 in the Control Plane RAN protocol stack.

[0147] • A NR measurement and / or an Inter-RAT measurement of E-UTRA frequencies and / or 6G measurements (i.e. performed over the 6G air interface on 6G reference signal(s))

[0148] • A measurement performed on one or more reference signal(s) of a reference signal type e.g. SSB or Channel State Information - Reference Signal (CSI-RS). For example: o In the case of SSBs these measurements (or in more general terms, measurement information) are:

[0149] ■ Measurement results per SSB, such as:

[0150] • SS reference signal received power (SS-RSRP) o In one option this may be defined as the linear average over the power contributions (in [W]) of the resource elements that carry secondary synchronization signals (SS).

[0151] • SS reference signal received quality (SS-RSRQ): o In one option this may be defined as the ratio of NxSS- RSRP I NR carrier RSSI, where N is the number of resource blocks in the NR carrier RSSI measurement bandwidth. The measurements in the numerator and denominator shall be made over the same set of resource blocks.

[0152] • SS signal-to-noise and interference ratio (SS-SINR): o In one option this may defined as the linear average over the power contribution (in [W]) of the resource elements carrying secondary synchronisation signals divided by the linear average of the noise and interference power contribution (in [W]) over the resource elements carrying secondary synchronization signals within the same frequency bandwidth.

[0153] ■ Measurement results per cell based on SSBs, for example:

[0154] • A cell-based measurement quantity (e.g. cell based RSRP, cell based RSRQ, cell based SINR)

[0155] • A cell-based measurement quantity derived as the highest beam measurement quantity value e.g. highest SS-RSRP of the cell, highest SS-RSRQ of the cell, highest SS-SINR of the cell

[0156] • A cell-based measurement quantity derived as the linear power scale average of the highest beam measurement quantity values above a threshold (e.g. absThreshSS-BlocksConsolidation) where the total number of averaged beams shall not exceed an integer threshold (e.g. nrofSS-BlocksToAverage) e.g. average of SS-RSRP values of the cell.

[0157] ■ SSB indexes (derived based on SSB measurements).

[0158] • SSB indexes of one or more SSBs whose SSB based measurement quantity (e.g. SS-RSRP, SS-RSRQ, SS-SINR) is above a threshold

[0159] ■ cell identification (derived based on cell-based measurement quality) In the case of CSI-RS these measurements (or in more general terms, measurement information) are:

[0160] ■ Measurement results per CSI-RS resource, such as:

[0161] • CSI reference signal received power (CSI-RSRP): o In one option this may be defined as the linear average over the power contributions (in [W]) of the resource elements of the antenna port(s) that carry CSI reference signals configured for RSRP measurements within the considered measurement frequency bandwidth in the configured CSI-RS occasions.

[0162] • CSI reference signal received quality (CSI-RSRQ) o In one option this may be defined as CSI reference signal received quality (CSI-RSRQ) is defined as the ratio of NxQSI-RSRP to CSI-RSSI, where N is the number of resource blocks in the CSI-RSSI measurement bandwidth. The measurements in the numerator and denominator shall be made over the same set of resource blocks.

[0163] • CSI signal-to-noise and interference ratio (CSI-SINR) o In one option this may defined as the linear average over the power contribution (in [W]) of the resource elements carrying CSI reference signals divided by the linear average of the noise and interference power contribution (in [W]) over the resource elements carrying CSI reference signals reference signals within the same frequency bandwidth.

[0164] ■ Measurement results per cell based on CSI-RS resource(s);

[0165] • A cell-based measurement quantity (e.g. cell based RSRP, cell based RSRQ, cell based SINR)

[0166] • A cell-based measurement quantity derived as the highest beam measurement quantity value e.g. highest CSI-RSRP of the cell, highest CSI-RSRQ of the cell, highest CSI-SINR of the cell

[0167] • A cell-based measurement quantity derived as the linear power scale average of the highest beam measurement quantity values above a threshold (e.g. absThreshSS-BlocksConsolidation) where the total number of averaged beams shall not exceed an integer threshold (e.g. nrofSS-BlocksToAverage) e.g. average of CSI-RSRP values of the cell.

[0168] ■ CSI-RS resource measurement identifiers.

[0169] • CSI-RS resource measurement identifiers of one or more CSI- RS resources whose CSI-RS based measurement quantity (e.g. CSI-RSRP, CSI-RSRQ, CSI-SINR) is above a threshold

[0170] ■ Cell identification (derived based on cell-based measurements quality) A measurement which may be associated to a measurement quantity, such as RSRP, RSRQ or SINR. For example, one may say that a “measurement” corresponds to an RSRP value, so that a measurement of a neighbor cell corresponds to an RSRP value of the neighbor cell.

[0171] A measurement of a cell (which may also be called cell quality or cell measurement result), where the measurement of a cell may be performed based on one or more beam measurements.

[0172] • A measurement which is filtered according to one or more filter parameters configured by the network e.g. a L3 filtered measurement, with a time-domain filtered.

[0173] • A measurement quantity, such as an RSRP and / or RSRQ and / or SINR and / or RSSI value in dB and / or dBm.

[0174] • A cell-based measurement result or cell measurement, where a measurement value represents a cell quality e.g. RSRP of a cell, RSRQ of a cell

[0175] • A beam-based measurement result or beam measurement, where a measurement value represents a beam quality e.g. RSRP of a beam, RSRQ of a beam, SINR of a beam. A beam-based measurement may also be a RS based measurement when the RS is transmitted on a spatial direction or beam e.g. SSB measurement may correspond to a measurement associated to an SSB index, like an SS-RSRP value; CSI-RS measurement may correspond to a measurement associated to an CSI-RS resource index / identifier, like an CSI-RSRP value.

[0176] In the context of the present disclosure, the source network node (and / or the candidate network node) may correspond to one or more of:

[0177] • A Radio Access Network (RAN) node

[0178] • A gNodeB (gNB)

[0179] • A 6G RAN node

[0180] • A Centralized Unit gNodeB

[0181] • A distributed Unit gNodeB

[0182] • A Cloud-RAN centralized unit

[0183] The method includes the possibility in which the source network node and the candidate network node are different nodes, or the same. The source network node may also be referred to herein as the serving network node or the network node of the serving cell.

[0184] A neighbor cell in this may be characterized as a cell which is not configured at the UE as a serving cell. In the context of the present disclosure, the at least one neighbor cell for which the UE includes prediction information and / or one or more measurements in the first message corresponds to one or more of:

[0185] • A neighbor cell which is an intra-frequency neighbor

[0186] • A neighbor cell on the same Synchronization Signal Block (SSB) frequency as the PCell

[0187] • A neighbor cell with the same subcarrier spacing as the PCell • A neighbor cell which is an inter-frequency neighbor

[0188] • A neighbor cell on a different SSB frequency as the PCell

[0189] • A neighbor cell with a different subcarrier spacing as the PCell

[0190] • A neighbor cell on an SSB frequency indicated in a Measurement Object which the UE is configured with e.g. IE MeasObjectNR

[0191] • A neighbor cell on the same SSB frequency as the SSB frequency of a Secondary Cell (SCell) of the Master Cell Group (MCG)

[0192] • A neighbor cell with the same subcarrier spacing as the subcarrier spacing of an SCell of the MCG

[0193] • A neighbor cell on a different SSB frequency as the SSB frequency of an SCell of the MCG

[0194] • A neighbor cell with a different subcarrier spacing as the subcarrier spacing of an SCell of the MCG

[0195] • A neighbor cell which is configured at the UE, for example, upon reception of a cell identifier (e.g. physical cell identity) and a frequency information (e.g. SSB frequency in a Measurement Object).

[0196] • A “best” neighbor cell on a serving frequency e.g. in terms of RSRP, RSRQ, SINR and / or in terms of predicted information. o For example, the UE includes in the first message predicted information of one or more number of neighbor cell(s) with the same SSB frequency as one of the SCell(s) of the MCG and with highest RSRP values. o For example, the UE includes in the first message predicted information of one or more number of neighbor cell(s) with the same SSB frequency as the PCell and with highest RSRP values. o For example, the UE includes in the first message predicted information of the neighbor cell with the same SSB frequency as each of the SCell(s) of the MCG and with the highest RSRP value.

[0197] A neighbor cell may also be called CHO candidate cell (or simply a CHO candidate or candidate) when that cell is configured as a candidate cell for CHO at the UE. The neighbour cell is also referred to herein as a second cell.

[0198] In the context of the present disclosure, the at least one serving cell for which the UE includes prediction information in the first message may correspond to one or more of:

[0199] • For a UE in RRC_CONNECTED not configured with Carrier Aggregation (CA) / Dual Connectivity (DC) there is one serving cell comprising of the primary cell (e.g. PCell). For a UE in RRC_CONNECTED configured with CA / DC the term 'serving cell' is used to denote the set of cells comprising of the Special Cell(s) and all secondary cells.

[0200] • A Primary Cell (PCell), also called the Master Cell Group (MCG) cell, operating on the primary frequency (e.g. an SSB frequency), in which the UE either performs the initial connection establishment procedure, resume procedure or initiates the connection reestablishment procedure.

[0201] • A Secondary Cell (SCell): For a UE configured with CA, a cell providing additional radio resources on top of Special Cell (SpCell). The SCell may be associated to a cell group e.g. Scell of the MCG, or SCell of the SCG.

[0202] • A Special Cell (SpCell): For DC operation the term Special Cell refers to the PCell of the MCG or the PSCell of the Secondary Cell Group (SCG), otherwise the term Special Cell refers to the PCell.

[0203] In the context of the present disclosure, the term Conditional Handover (CHO) may also be considered as a kind of Conditional Reconfiguration in which the UE receives and stores an RRCReconfiguration message associated to a CHO candidate cell. The RRCReconfiguration may include Reconfiguration with sync for the Master Cell Group (MCG). The UE may apply the stored RRCReconfiguration when the CHO execution condition for the corresponding candidate is fulfilled.

[0204] AI / ML models applied for the NR / 6G air interface use cases or NR / 6G higher-layer use cases can be categorized into three types:

[0205] 1) one-sided UE-sided AI / ML models whose inference is performed entirely at the UE-side;

[0206] 2) one-sided NW-sided AI / ML models whose inference is performed entirely at the NW side,

[0207] 3) two-sided AI / ML models, which refers to a paired AI / ML Model(s) over which joint inference is performed, where joint inference comprises AI / ML Inference whose inference is performed jointly across the UE and the network, i.e., the first part of inference is firstly performed by UE and then the remaining part is performed by gNB, or vice versa.

[0208] Here, model inference refers to a process of using a trained AI / ML model to produce a set of outputs based on a set of inputs. In the context of the present disclosure, the time-domain prediction of one or more measurements of one or more neighboring cell(s) and / or one or more serving cell(s) is achieved via one or more AI / ML model(s), whose inference is performed entirely at the UE. Hence, these models can be referred to as UE-sided AI / ML models.

[0209] Fig. 6 depicts a method in accordance with particular embodiments. The method in Fig. 6 may be performed by a User Equipment (UE) or wireless device (e.g. the UE 2112 or UE 2200 as described later with reference to Figs. 21 and 22 respectively). The UE is being served by a first cell of a source network node. The method begins at step 602 with transmitting, to the source network node, a first message comprising time-domain prediction information for a second cell. The time-domain prediction information is also referred to herein as prediction information. The first message may be a RRC measurement report message.

[0210] The method performed by the UE also comprises receiving a CHO configuration from the source network node. The CHO configuration comprises a CHO execution condition and a CHO candidate configuration for the second cell. The UE evaluates the CHO execution condition associated with the second cell.

[0211] In some embodiments, step 602 is performed prior to receiving the CHO configuration and evaluating the CHO execution condition. In other embodiments, step 602 is performed after receiving the CHO configuration and after evaluating the CHO execution condition.

[0212] The time-domain prediction information for the second cell may comprise an indication of a likelihood of a conditional handover of the UE to the second cell.

[0213] The second cell may be one of the first cell, another cell of the source network node, and a cell of a second network node.

[0214] The time-domain prediction information for the second cell may be based on, or comprise, at least one prediction of a measurement of the first cell and / or at least one prediction of a measurement of the second cell.

[0215] The time-domain prediction information for the second cell comprises one or more of: a predicted signal strength or quality value for the second cell at a future time instance; a predicted cell identifier for the second cell at a future time instance; a cell identifier based on a predicted signal strength or quality value for the second cell at a future time instance; a predicted RSRP of the second cell at a future time instance; a predicted RSRQ of the second cell at a future time instance; a predicted SI NR of the second cell at a future time instance; a predicted beam index and / or beam identifier of the second cell at a future time instance; a SSB index of the second cell at a future time instance; a corresponding confidence indicator of a predicted value for the second cell; a corresponding time duration for which a predicted value for the second cell is expected to be valid; and a corresponding time duration for which a predicted value for the second cell is expected to satisfy a condition.

[0216] The time-domain prediction information for the second cell may be based on a prediction for fulfilment of an event trigger for the second cell. The event trigger may comprise an event or condition that triggers transmission by the UE of measurements of the second cell, and / or an event or condition that triggers conditional handover of the UE to the second cell. The timedomain prediction information for the second cell may comprise one or more of: a flag indicating that the event trigger is predicted to remain fulfilled; an indication of a period of time for which the event trigger is predicted to remain fulfilled; and a cell identifier of the second cell as the cell which triggered the event.

[0217] The time-domain prediction information for the second cell may be based on a difference between a prediction of a measurement of the second cell and a prediction of a measurement of the first cell.

[0218] The time-domain prediction information for the second cell may comprise one or more of: a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a cell identifier based on a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a cell identifier based on a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a corresponding confidence indicator for the predicted difference; a corresponding confidence indicator for the cell identifier; a corresponding time duration for which the predicted difference is expected to be valid; a corresponding time duration for which the cell identifier is expected to be valid; and a corresponding time duration for which the predicted difference is expected to satisfy a condition.

[0219] Responsive to determining that the conditional handover execution condition associated with the second cell is satisfied, the UE may execute the conditional handover to the second cell. In some embodiments, the method is for assisting the triggering of Early Data Forwarding (EDF) and data continuity at the UE upon CHO execution.

[0220] The method may further comprise, prior to transmitting the first message in step 602, receiving an indication of a property of the time-domain prediction information that the UE can transmit in the first message. The indication may be received from the source network node. The property of the time-domain prediction information may be a quantity of the time-domain prediction information that the UE can transmit in the first message. The quantity of the timedomain prediction information comprises one or more of: a number of cells, a number of predicted SSBs, and a number of Channel State Information Reference Signals.

[0221] The first message may further comprise time-domain prediction information for a third cell. The third cell is one of: the first cell, another cell of the source network node, and a cell of a third network node.

[0222] The first message may be transmitted according to one or more parameters which the UE received, prior to transmitting the first message in step 602, in a measurement configuration and / or a prediction configuration.

[0223] Complementary methods performed by a source network node and a second network node (also referred to herein as a candidate network node or potential target network node, e.g., candidate gNB or potential target gNB) are described with respect to Figs. 7 and 8 respectively. Further detail regarding the method in Fig. 6 and other methods performed by the UE is set out below in the sections “Embodiments in a UE”, “Further embodiments in a UE” and “Detailed embodiments”.

[0224] The UE may perform the method in response to executing suitably formulated computer readable code. The computer readable code may be embodied or stored on a computer readable medium, such as a memory chip, optical disc, or other storage medium. The computer readable medium may be part of a computer program product.

[0225] Fig. 7 depicts a method in accordance with particular embodiments. The method in Fig. 7 is performed by a source network node. A user equipment is being served by a first cell of the source network node. The source network node may be a RAN network node (e.g. the RAN network node 2110 or RAN network node 2300 as described later with reference to Fig. 21 and 23 respectively). The source network node may also be referred to herein as a serving network node. The method begins at step 702 with receiving, from the UE, a first message comprising time-domain prediction information for a second cell. The time-domain prediction information is also referred to herein as prediction information.

[0226] The method also comprises the source network node transmitting a CHO configuration to the UE. The CHO configuration comprises a CHO candidate configuration for the second cell and a CHO execution condition for the second cell.

[0227] The CHO configuration may be based on the time-domain prediction information for the second cell. The method may further comprise determining, based on the time-domain prediction information for the second cell, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE. In this case, transmitting the CHO configuration to the UE is responsive to the determined likelihood indication satisfying a criterion.

[0228] The method may further comprise triggering Early Data Forwarding (EDF) for the second cell based on the time-domain prediction information for the second cell.

[0229] The method may further comprise configuring fast failure recovery based on the timedomain prediction information for the second cell. Configuring fast failure recovery can comprise determining to include a ‘attemptCondReconfig’ field set to ‘true’ in a conditional handover configuration for the second cell. The second cell may be a cell of a second network node, and the method can further comprise: after receiving the first message, transmitting, to the second network node, a conditional handover request for configuring a conditional handover for the second cell. The conditional handover request may further comprise the time-domain prediction information for the second cell or information derived therefrom. The derived information is one of: part of the timedomain prediction information for the second cell received from the UE; and post-processed information based on the time-domain prediction information for the second cell received from the UE. The method further comprises, after transmitting the conditional handover request, receiving a conditional handover candidate configuration for the second cell from the second network node.

[0230] The second cell may be one of: the first cell, another cell of the source network node, and a cell of a second network node.

[0231] The method may further comprise, prior to receiving the first message in step 702, transmitting, to the UE, an indication of a property of the time-domain prediction information that the UE can transmit in the first message.

[0232] Complementary methods performed by a UE and a second network node (also referred to herein as a candidate network node, a candidate gNB, a potential target network node, a potential target gNB, a target network node, or a target gNB) are described with respect to Figs. 6 and 8 respectively. Further detail regarding the method in Fig. 7 and other methods performed by the network node is set out below in the sections “Embodiments in a source network node” and “Detailed embodiments”.

[0233] The source network node may perform the method in response to executing suitably formulated computer readable code. The computer readable code may be embodied or stored on a computer readable medium, such as a memory chip, optical disc, or other storage medium. The computer readable medium may be part of a computer program product.

[0234] UE 8 depicts a method in accordance with particular embodiments. The method in Fig. 8 is performed by a second network node. A user equipment is being served by a first cell of a source network node. The second network node may be performed by a RAN network node (e.g. the RAN network node 2110 or RAN network node 2300 as described later with reference to Figs. 21 and 23 respectively). The second network node may also be referred to herein as a candidate network node, a candidate gNB, a potential target network node, a potential target gNB, a target network node, a target gNB, or a network node of a neighbour cell. The method begins at step 802 with receiving, from the source network node, a conditional handover request for configuring a conditional handover for a second cell. The second cell is a cell of a second network node. The conditional handover request comprises time-domain prediction information for the second cell or information derived therefrom. The time-domain prediction information is also referred to herein as prediction information.

[0235] The derived information may be one of: part of the time-domain prediction information for the second cell; and post-processed information based on the time-domain prediction information for the second cell.

[0236] The time-domain prediction information for the second cell or information derived therefrom that is comprised in the conditional handover request may further comprise time-domain prediction information for a third cell or information derived therefrom. The third cell is one of: the first cell, and another cell of the source network node.

[0237] The method further comprises, based on the prediction information, determining whether to accept or reject the conditional handover request for configuring the conditional handover for the second cell. Determining whether to accept or reject the conditional handover request can comprise: determining, based on the time-domain prediction information for the second cell or information derived therefrom, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE; and responsive to the determined likelihood indication satisfying a criterion, accepting the conditional handover request for configuring the conditional handover for the second cell; and responsive to the determined likelihood indication failing to satisfy the criterion, rejecting the conditional handover request for configuring the conditional handover for the second cell.

[0238] Accepting the conditional handover request can comprise transmitting, to the source network node, a handover request acknowledge message.

[0239] The method may further comprise, based on the time-domain prediction information for the second cell or information derived therefrom, configuring Contention-Free Random-Access resources per beam for the second cell, wherein the second cell is a conditional handover candidate for the UE.

[0240] Complementary methods performed by a UE and a source network node are described with respect to Figs. 6 and 7 respectively. Further detail regarding the method in Fig. 8 and other methods performed by the second network node is set out below in the sections “Embodiments in a candidate network node” and “Detailed embodiments”. The second network node may correspond to the candidate network node described therein.

[0241] The second network node may perform the method in response to executing suitably formulated computer readable code. The computer readable code may be embodied or stored on a computer readable medium, such as a memory chip, optical disc, or other storage medium. The computer readable medium may be part of a computer program product. Embodiments in a UE

[0242] The present disclosure includes a method at a User Equipment (UE) for CHO, the method can comprise one or more of:

[0243] • Transmitting to a source network node, a first message including a first prediction information for at least one neighbor cell and, after transmitting the first message,

[0244] • Receiving a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell, and

[0245] • Evaluating the CHO execution condition associated to the at least one neighbor cell.

[0246] The UE may be configured by a source network node (e.g. with RRCReconfiguration message) with an indication of a number of prediction information (e.g. number of cells and / or predicted SSBs / CSI-RSs per cell) the UE can include in a first message.

[0247] The first message (e.g. RRC MeasurementReport message) may also comprise a second prediction information for at least a serving cell.

[0248] The first prediction information for the at least one neighbor cell may be based on at least one time-domain prediction of a measurement of the at least one neighbor cell. The first prediction information may correspond to:

[0249] • a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0250] • a predicted cell identifier at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted).

[0251] • a cell identifier derived based on the predicted RSRP value (or predicted RSRQ, predicted SI NR) of the neighbor cell at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted).

[0252] • a predicted beam index and / or beam identifier (e.g. SSB index) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). The beam index may be derived based on a time-domain index and / or a L3 filtered timedomain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam.

[0253] • a confidence level / indicator of the predicted value of the measurement quantity (e.g. RSRP value, RSRQ value, SINR value), the predicted cell identifier, or the derived cell identifier.

[0254] • a time duration under which the predicted measurement quantity (e.g. RSRP, RSRQ, SINR) of the neighbour cell is expected to be valid according to a condition. For example, the predicted RSRP value of the neighbour cell above a threshold for a number of future time instances and / or the predicted RSRP value of the neighbour cell an offset better than the predicted RSRP value of the PCell for a number of future time instances.

[0255] The second prediction information for the at least a serving cell may be based on at least one time-domain prediction of a measurement of the at least a serving cell. The second prediction information may correspond to:

[0256] • a predicted RSRP value of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0257] • a predicted cell identifier at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0258] • a cell identifier derived based on the predicted RSRP value of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0259] • a confidence level / indicator for the predicted RSRP value, the predicted cell identifier, or the derived cell identifier.

[0260] • a time duration under which the predicted measurement quantity (e.g. RSRP, RSRQ, SINR) of the serving cell (e.g. PCell) is expected to be valid according to a condition.

[0261] The first prediction information for the at least one neighbor cell can be based on at least one time-domain prediction of a measurement of the at least one neighbor cell AND at least one time-domain prediction of a measurement of the at least a serving cell. The first prediction information may correspond to:

[0262] • a difference between “a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0263] • a cell identifier derived based on a difference between “a predicted RSRP value of the neighbor cell at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0264] • a predicted cell identifier at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted).

[0265] • a predicted beam index and / or beam identifier (e.g. SSB index) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)., The beam index may be derived based on a time-domain index and / or a L3 filtered time-domain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam. • a confidence level(s) / indicator(s) for the derived measurement quantity (e.g. RSRP) difference or / and the derived cell identifier.

[0266] • a time duration under which the derived measurement quantity (e.g. RSRP) difference or / and the derived cell identifier is / are expected to be valid or fulfilled according to a condition.

[0267] The first prediction information for the at least one neighbor cell in relation to the at least a serving cell may be based on at least one time-domain prediction of a measurement value difference between a measurement of the at least one neighbor cell and a measurement of at least a serving cell. The First prediction information may correspond to:

[0268] • a predicted measurement quantity difference (e.g., RSRP difference) between the measurement quantity of the neighbor cell and the measurement quantity of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0269] • a cell identifier derived based on a predicted measurement quantity difference between the neighbor cell and the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0270] • a predicted SSB index of the neighbor cell at a future time instance f” (e.g. in relation to the timing in which first message is transmitted). The beam index may be derived based on a time-domain index and / or a L3 filtered time-domain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam.

[0271] • a predicted cell identifier at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted).

[0272] • a confidence level(s) / indicator(s) for the predicted measurement quantity difference or / and the derived cell identifier.

[0273] • a time duration under which the predicted measurement quantity difference or / and the derived cell identifier is / are expected to be valid.

[0274] The first prediction information for the at least one neighbor cell may be based on the prediction of the fulfillment duration of the event triggering of the at least one neighbor cell. The first prediction information may correspond to:

[0275] • a flag indicating that the condition which triggered the event (e.g. Event A3 when the neighbor cell becomes an offset better than the PCell) is predicted to remain fulfilled.

[0276] • the period of time T (in relation to the timing in which first message is transmitted), indicating for how long time the condition which triggered the event (e.g. Event A3 when the neighbor cell becomes an offset better than the PCell) is predicted to remain fulfilled • a cell identifier of a neighbor cell which triggered the event.

[0277] The first message may also include one or more measurement(s) of the at least one neighbor cell and / or one or more measurements of the at least one serving cell. In other words, the CHO execution condition may be based on measurements of the PCell and / or prediction of the PCell and / or measurements of the neighbor cell configured as CHO candidate and the predictions of the neighbor cell configured as CHO candidate.

[0278] The first prediction information or / and the second prediction information may include multiple measurement quantity predictions. The measurement quantity predictions may correspond to:

[0279] • Time-domain predictions of L3 filtered SSB / CSI-RS beam level measurement quantities or / and cell-level measurement quantities of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0280] • Time-domain predictions of L3 filtered SSB / CSI-RS beam level measurement quantities or / and cell-level measurement quantities of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0281] • Time-domain predictions of L3 filtered SSB / CSI-RS beam level measurement quantity or / and a cell-level measurement quantity of the neighbor cell at one or more multiple future time instance “f1 , f2, ...” (e.g. in relation to the timing in which first message is transmitted)

[0282] • Time-domain predictions of L3 filtered SSB / CSI-RS beam level measurement quantity or / and a cell-level measurement quantity of the serving cell at one or more multiple future time instance “f1 , f2, ...” (e.g. in relation to the timing in which first message is transmitted)

[0283] • any combination of the above bullets

[0284] The first message may be transmitted in response to one or more measurements, such as upon fulfillment of an entry condition of an Event A3: neighbor cell measurement quantity (e.g. RSRP) an offset better than the measurement quantity of the PCell.

[0285] The first message may be transmitted in response to one or more measurements, such as upon fulfillment of an entry condition of an Event A4: neighbor cell measurement quantity (e.g. RSRP) better than an absolute threshold.

[0286] The first message may be transmitted according to one or more parameters which the UE receives in a measurement configuration and / or a prediction configuration. The UE may receive the measurement configuration and / or the prediction configuration in a message the UE receives before it transmits the first message.

[0287] The first message may be transmitted in response to the first prediction information for at least one neighbor cell and / or the second prediction information for at least a serving cell, such as upon fulfillment of an entry condition related to an Event A3: time-domain prediction(s) of a neighbor cell measurement quantity (e.g. RSRP) on at least a time instance “f” is an offset better than time-domain prediction(s) of the PCell’s measurement quantity (e.g. RSRP) on at least the time instance “f”.

[0288] The method may further comprise the UE applying the stored CHO candidate configuration for the at least one neighbor cell and accessing the at least one neighbor cell when the CHO execution condition is fulfilled.

[0289] Accessing the at least one neighbor cell when the CHO execution condition is fulfilled may comprise the UE transmitting a random-access preamble to the neighbor cell, receiving a Random Access Response from the neighbor cell and transmitting an RRC Reconfiguration Complete message to the neighbor cell.

[0290] The UE may transmit a complete message (e.g. RRC Reconfiguration Complete) to the source network node in response to receiving a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0291] The UE may receive the CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell further comprises a Contention- Free Random Access (CFRA) resource configuration. The CFRA resource configuration may be associated to at least one beam of the neighbor cell (e.g. SSB index, CSI-RS identifier) mapped to the CFRA resource (SSB index=X, mapped to the CFRA resource with preamble index Y, Time / Frequency Physical Random Access Channel (PRACH) resource Z), the UE has transmitted in the first message prediction information for the at least one beam of the neighbor cell e.g. L3 filtered predicted RSRP values of that beam indicating that close a CHO execution the beam would have a L3 filtered predicted RSRP value above a threshold (thus it would be a good beam for CFRA configuration).

[0292] The CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell may further comprise an indication that the cell is configured for a fast recovery procedure (e.g. attemptCondReconfig set to ‘true’) in which upon a failure detection (e.g. Radio Link Failure, Handover Failure, CHO Failure) the UE initiates reestablishment, selects the neighbor cell and performs CHO execution (i.e. the UE applies the stored CHO candidate configuration of the at least one neighbor cell).

[0293] Further embodiments in a UE

[0294] The present disclosure also includes a method at a UE for CHO, to assist the triggering of Early Data Forwarding (EDF) and data continuity at the UE upon CHO execution, the method comprising one or more of: • Receiving from a source network node a CHO configuration including a CHO execution condition and a CHO candidate configuration for at least one neighbor cell and

[0295] • Evaluating the CHO execution condition associated to the at least one neighbor cell

[0296] • Transmitting to a source network node, a first message including a first prediction information for the at least one neighbor cell

[0297] • Executing CHO to the at least one neighbor cell of a candidate network node When the UE accesses the at least one neighbor cell in CHO execution, downlink data may be available at the candidate network node to be scheduled to the UE.

[0298] The first message (e.g. RRC MeasurementReport message) may also comprise a second prediction information for at least a serving cell.

[0299] The first prediction information for the at least one neighbor cell may be based on at least one time-domain prediction of a measurement of the at least one neighbor cell. The first prediction information may correspond to:

[0300] • a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0301] • a cell identifier derived based on the predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0302] The second prediction information for the at least a serving cell may be based on at least one time-domain prediction of a measurement of the at least a serving cell. The second prediction information may correspond to:

[0303] • a predicted RSRP value of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0304] • a cell identifier derived based on the predicted RSRP value of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0305] The first prediction information for the at least one neighbor cell may be based on at least one time-domain prediction of a measurement of the at least one neighbor cell AND at least one time-domain prediction of a measurement of the at least a serving cell. The first prediction information may correspond to:

[0306] • a difference between “a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0307] • a cell identifier derived based on a difference between “a predicted RSRP value of the neighbor cell at a future time instance “f’ (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0308] The first prediction information for the at least one neighbor cell may be based on the prediction of the fulfillment duration of the event triggering of the at least one neighbor cell. The first prediction information may correspond to:

[0309] • a flag indicating that the condition which triggered the event (e.g. Event A3 when the neighbor cell becomes an offset better than the PCell) is predicted to remain fulfilled.

[0310] • the period of time T (in relation to the timing in which first message is transmitted), indicating for how long time the condition which triggered the event (e.g. Event A3 when the neighbor cell becomes an offset better than the PCell) is predicted to remain fulfilled

[0311] • a cell identifier of a neighbor cell which triggered the event.

[0312] The first message may also include one or more measurement(s) of the at least one neighbor cell and / or one or more measurements of the at least one serving cell.

[0313] The first message may be transmitted in response to one or more measurements, such as upon fulfillment of an entry condition of an Event A3: neighbor cell measurement quantity (e.g. RSRP) an offset better than the measurement quantity of the PCell.

[0314] The first message may be transmitted according to one or more parameters which the UE receives in a measurement configuration and / or a prediction configuration. The UE may receive the measurement configuration and / or the prediction configuration in a message the UE receives before it transmits the first message.

[0315] Embodiments in a Source network node

[0316] The present disclosure includes a method at a source network node for CHO, the method comprising one or more of:

[0317] • Receiving from a UE, a first message including a first prediction information for at least one neighbor cell and, after receiving the first message,

[0318] • Transmitting a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0319] Before the source network node transmits the CHO configuration for the at least one neighbor cell to the UE, the source network node may transmit a CHO request to a candidate network node for configuring a CHO for the at least one neighbor cell and receive in response the CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0320] As an alternative, before the source network node transmits the CHO configuration for the at least one neighbor cell to the UE, the source network node may transmit a CHO request to a candidate network node including a first prediction information for configuring a CHO for the at least one neighbor cell and receive in response the CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0321] A first prediction information for configuring a CHO for the at least one neighbor cell, included in the CHO request, can be the predictions received from the UE in the first message, or can be a part of the prediction information that is relevant to this neighbor cell for the CHO candidate configuration or, alternatively can be a post-processed information based on the predicted information received from the UE.

[0322] The first message (e.g. RRC MeasurementReport message) may also comprise a second prediction information for at least a serving cell.

[0323] The first message may also include one or more measurement(s) of the at least one neighbor cell and / or one or more measurements of the at least one serving cell.

[0324] The source network node may transmit the CHO configuration for the at least one neighbor cell to the UE based on the first prediction information for the at least one neighbor cell.

[0325] The source network node may determine to trigger one or more actions based on the first prediction information and / or the second prediction information which has been received. The one or more actions may comprise:

[0326] • A) Configuring a neighbor as a CHO candidate based on the first and / or second prediction information of the serving and / or the neighbor cell(s) and / or

[0327] • B) Triggering Early Data Forward (EDF) for a neighbor cell (of a candidate network node) which is configured (or it is to be configured at a UE as a CHO candidate cell) and / or

[0328] • C) Configuring fast failure recovery by determining to include in a CHO configuration the ‘attemptCondReconfig’ field set to ‘true’

[0329] Embodiments in a candidate network node

[0330] The present disclosure includes a method at a candidate network node for CHO, the method comprising one or more of:

[0331] • Receiving from a source network node a CHO request for configuring CHO for the at least one neighbor cell. The CHO request may include a first prediction information for at least one neighbor cell,

[0332] • Transmitting to the source network node a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0333] The candidate network node may accept the CHO request from the source network node based on the first prediction information for the at least one neighbor cell. A first prediction information for configuring a CHO for the at least one neighbor cell, received in the CHO request, can be the predictions sent by the UE in the first message, or can be a part of the prediction information that is relevant to this neighbor cell for the CHO candidate configuration or, alternatively can be a post-processed information based on the predicted information received from the UE.

[0334] The candidate network node may receive from the UE a random access preamble, transmit a Random Access Response and receive a Reconfiguration complete during CHO execution of the UE to the neighbor cell.

[0335] The candidate network node may determine to trigger one or more actions based on the first prediction information and / or the second prediction information which has been received from the source network node (e.g. in the CHO request). The one or more actions may comprise:

[0336] • D) Accepting or rejecting a CHO request for a neighbor cell based on the first and / or second prediction information of the serving and / or the neighbor cell(s). o In one option, the candidate network node accepts the requested neighbor cell as a CHO candidate cell and transmits to the source network candidate node a CHO candidate configuration for the neighbor cell (e.g. in a Handover Request Acknowledge message) when the first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell. First and / or second prediction information may comprise time domain prediction of cell measurement quantities e.g. predicted RSRP values for one or more future time instances (f=1 , ... , F) for the neighbor cell and the PCell, or another indication of that, e.g., a neighbor cell ID, validation time of the predicted information, confidence level / indication of the predicted information, etc. (see previous embodiments for other alternatives). o In one option, the candidate network node rejects the requested neighbor cell as a CHO candidate cell when the first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition would likely NOT be fulfilled after some time in the future for that neighbor cell.

[0337] • E) Configuring Contention-Free Random Access resources per beam for a neighbor cell accepted as CHO candidate based on the first prediction information of the neighbor cell(s). The first prediction information may comprise time-domain prediction(s) of at least one L3 filtered beam measurement of the neighbor cell e.g. L3 filtered predicted RSRP value(s) for one or more time instances for one or more beams of the neighbor cell accepted as a CHO candidate cell (like L3 filtered predicted SS-RSRP values). o For example, let us assume that the following Layer 3 (L3) filtered measurements has been reported by the UE and is available at the candidate network node (e.g. included in the CHO request):

[0338] ■ For future time instance f=1 ;

[0339] • SS-RSRP=x1 , for SSB(1);

[0340] • SS-RSRP=x2, for SSB(2);

[0341] • SS-RSRP=x3, for SSB(3);

[0342] • SS-RSRP=x4, for SSB(4);

[0343] ■ For future time instance f=2;

[0344] • SS-RSRP=x1*, for SSB(1);

[0345] • SS-RSRP=x2*, for SSB(2);

[0346] • SS-RSRP=x3*, for SSB(3);

[0347] • SS-RSRP=x4*, for SSB(4);

[0348] ■ For future time instance f=3;

[0349] • SS-RSRP=x1**, for SSB(1);

[0350] • SS-RSRP=x2**, for SSB(2);

[0351] • SS-RSRP=x3**, for SSB(3);

[0352] • SS-RSRP=x4**, for SSB(4);

[0353] ■ For future time instance f=4;

[0354] • SS-RSRP=x1***, for SSB(1);

[0355] • SS-RSRP=x2***, for SSB(2);

[0356] • SS-RSRP=x3***, for SSB(3);

[0357] • SS-RSRP=x4***, for SSB(4);

[0358] Assume that only SSB(3) and SSB(4), for the future time instances, have L3 filtered predicted RSRP values above the SSB threshold for determining an SSB which may be selected in a random access resource selection procedure (as defined in 3GPP TS 38.331).

[0359] The candidate network cell may configure CFRA resources within the CHO candidate configuration only for SSB(3) and SSB(4), assuming that CFRA resources for SSB(1) and SSB(2) would be wasted, as assuming predictions were right, these would not be suitable SSBs at the time the UE needs to perform random access during CHO execution.

[0360] Detailed embodiments

[0361] In a set of embodiments, the UE can transmit to a source network node, a first message including a first prediction information for at least one neighbor cell and, after transmitting the first message, the UE can receive a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell. In response to receiving the CHO configuration the UE can evaluate the CHO execution condition associated to the at least one neighbor cell.

[0362] In a set of embodiments, the first message which the UE transmits can correspond to one or more of the following:

[0363] • An RRC Measurement Report (e.g. MeasurementReport message) used for the indication of measurement results and the indication of prediction information.

[0364] • An RRC Measurement Report (e.g. MeasurementReport message) used for the indication of prediction information (not necessarily including actual measurements).

[0365] • A UE Assistance Information message (e.g. U EAssistanceinformation message) used for the indication of UE assistance information to the network.

[0366] • Another type of RRC report or / and message used for indication of prediction information for at least one neighbor cell and / or a serving cell. That RRC may comprise one or more of the following features: o Transmitted by the UE over a Signaling Radio Bearer (e.g. SRB1 , SRB2, SRB3) o Transmitted by the UE in Acknowledge Mode (AM) for the Radio Link Control (RLC) layer, for increases robustness o Transmitted by the UE over a logical channel, such as Dedicated Control Channel (DCCH) o Transmitted by the UE including one or more measurements (e.g. of a neighbor and serving cell) in addition to prediction information e.g. when configured by the network. o Transmitted by the UE based on a prediction configuration. o Transmitted by the UE based on a measurement configuration. o Transmitted by the UE after security is activated. o Transmitted by the UE encrypted and / or integrity protected according to one or more security key(s).

[0367] In the method the UE can receive a CHO configuration including a CHO execution condition according to any of:

[0368] • The UE can receive the CHO configuration in a first RRCReconfiguration and, in response to it, the UE transmits an RRCReconfigurationComplete. • The CHO configuration can contain the configuration of CHO candidate cell(s) generated by the candidate network node(s) e.g. candidate gNB(s) and CHO execution condition(s) generated by the source network node e.g. source gNB.

[0369] • The CHO execution condition (or simply execution condition) may consist of one or two trigger condition(s) each configured as a Measurement ID associated to a reporting / trigger configuration (i.e. CHO events A3 / A5, as defined in TS 38.331).

[0370] • When the UE executes CHO, i.e. the UE may apply a stored RRCReconfiguration message and starts synchronization with a candidate cell which fulfills the CHO execution condition, and transmits an RRCReconfigurationComplete.

[0371] Prediction information

[0372] In a set of embodiments, the UE can include in the first message (e.g. RRC MeasurementReport message) a second prediction information for at least a serving cell in addition to the first prediction information for at least one neighbor cell. That enables the source network node receiving the first message to make a comparison, and understand how the timedomain predictions of the neighbor cell (e.g. predicted RSRP) in one or more future time instances is in relation to the PCell e.g. whether the neighbor cell is better than the PCell in future time instances, which in turn it indicates whether the neighbor cell is a good CHO candidate or not and whether it should be configured or not. For example, a neighbor cell would be a good CHO candidate when the first prediction information for at least one neighbor cell in one or more time instance (e.g. prediction RSRP value(s)) is / are an offset better than the second prediction information for the PCell (e.g. predicted RSRP value). Or, a neighbor cell would not be a good CHO candidate when the first prediction information for at least one neighbor cell in various time instance (e.g. prediction RSRP value(s)) are not an offset better than the second prediction information for the PCell (e.g. predicted RSRP value).

[0373] • Further details about options for the first and / or second prediction information are provided in the ‘Further Details about the prediction information’ section below.

[0374] In a set of embodiments, the first prediction information for the at least one neighbor cell may be based on at least one time-domain prediction of a measurement of the at least one neighbor cell. The first prediction information may correspond to one or more of the following:

[0375] • At least one predicted measurement quantity (e.g. predicted RSRP value, predicted RSRQ value, predicted SINR value) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). In one option, the UE includes in the first message multiple predicted measurement quantity values (e.g. multiple predicted RSRP values) for the neighbor cell e.g. each predicted RSRP value associated to a future time instance “f”.

[0376] • At least a cell identifier (e.g. Cell ID, PCI + SSB frequency) derived based on the predicted measurement quantity (e.g. predicted RSRP value) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). In one option, the UE includes in the first message multiple times the cell identity of the neighbor cell e.g. each time the cell ID is included is associated to a future time instance “f”, to possibly indicate that the cell fulfills a criteria.

[0377] • At least a predicted cell identifier at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0378] • a predicted beam index and / or beam identifier (e.g. SSB index) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). The beam index can be derived based on a time-domain index and / or a L3 filtered timedomain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam. The information can be used to assist the candidate network node to configure for the neighbor cell CFRA resources for the CHO candidate configuration.

[0379] • a confidence level / indicator of the predicted value of the measurement quantity (e.g. RSRP value, RSRQ value, SINR value), the predicted cell identifier, or the derived cell identifier.

[0380] • a time duration under which the predicted measurement quantity (e.g. RSRP, RSRQ, SINR) of the neighbour cell is expected to be valid according to a condition. For example, the predicted RSRP value of the neighbour cell above a threshold for a number of future time instances and / or the predicted RSRP value of the neighbour cell an offset better than the predicted RSRP value of the PCell for a number of future time instances.

[0381] • Further details about the prediction information are provided in the ‘Further Details about the prediction information’ section below.

[0382] In a set of embodiments, the second prediction information for the at least a serving cell can be based on at least one time-domain prediction of a measurement of the at least a serving cell. The second prediction information may correspond to one or more of the following:

[0383] • At least one predicted measurement quantity (e.g. predicted RSRP value, predicted RSRQ value, predicted SINR value) of the serving cell (e.g. PCell) at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). In one option, the UE includes in the first message multiple predicted measurement quantity values (e.g. multiple predicted RSRP values) for the serving cell e.g. each predicted RSRP value associated to a future time instance “f”.

[0384] • at least a cell identifier (e.g. Cell ID, PCI + SSB frequency) derived based on the predicted measurement quantity (e.g. predicted RSRP value) of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). In one option, the UE includes in the first message multiple times the cell identity of the serving cell e.g. each time the cell ID is included is associated to a future time instance “f”.

[0385] • at least a predicted cell identifier at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0386] • at least a confidence level / indicator for the predicted measurement quantity, the predicted cell identifier, or the derived cell identifier.

[0387] • at least a time duration under which the predicted measurement quantity / cell-identifier is expected to be valid

[0388] • Further details about the prediction information are provided in the ‘Further Details about the prediction information’ section below.

[0389] In a set of embodiments, the UE can include in the first message a first prediction information for the at least one neighbor cell which is based on at least one time-domain prediction of a measurement of the at least one neighbor cell and at least a time-domain prediction of a measurement of the at least a serving cell. The first prediction information may correspond to:

[0390] • At least a difference (or delta) between a predicted measurement quantity for neighbor and serving for a future time instance, such as “a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0391] • At least a cell identifier derived based on a difference between a predicted measurement quantity for neighbor and serving for a future time instance, such as “a predicted RSRP value of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)” minus a predicted RSRP value of the serving cell at the future time instance “f’ (e.g. in relation to the timing in which first message is transmitted).

[0392] • at least a predicted cell identifier at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0393] • At least a predicted SSB index of the neighbor cell at a future time instance f” (e.g. in relation to the timing in which first message is transmitted). This information can be used to assist the neighbor cell to configure the CFRA resources for the CHO candidate configuration, if the neighbor cell is selected to be one of the CHO candidate cells. • a predicted beam index and / or beam identifier (e.g. SSB index) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). The beam index can be derived based on a time-domain index and / or a L3 filtered timedomain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam. The information can be used to assist the candidate network node to configure for the neighbor cell CFRA resources for the CHO candidate configuration.

[0394] • at least a confidence level(s) / indicator(s) for the derived measurement quantity difference or / and the derived cell identifier.

[0395] • at least a time duration under which the derived measurement quantity difference or / and the derived cell identifier is / are expected to be valid.

[0396] • Further details about the prediction information are provided in the ‘Further Details about the prediction information’ section below.

[0397] In a set of embodiments, the first prediction information for the at least one neighbor cell in relation to the at least a serving cell can be based on at least one time-domain prediction of a measurement value difference between a measurement of the at least one neighbor cell and a measurement of at least a serving cell. The First prediction information may correspond to:

[0398] • at least a predicted measurement quantity difference (e.g., a predicted RSRP difference) between the measurement quantity of the neighbor cell and the measurement quantity of the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0399] • at least a cell identifier derived based on a predicted measurement quantity difference between the neighbor cell and the serving cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted)

[0400] • at least a predicted cell identifier at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted).

[0401] • a predicted beam index and / or beam identifier (e.g. SSB index) of the neighbor cell at a future time instance “f” (e.g. in relation to the timing in which first message is transmitted). The beam index can be derived based on a time-domain index and / or a L3 filtered timedomain prediction of a measurement quantity (e.g. RSRP) of a beam and / or a time-domain prediction of a L3 filtered measurement quantity (e.g. RSRP) of a beam. The information can be used to assist the candidate network node to configure for the neighbor cell CFRA resources for the CHO candidate configuration.

[0402] • at least a confidence level(s) / indicator(s) for the predicted measurement quantity difference or / and the derived cell identifier. • at least a time duration under which the predicted measurement quantity difference or / and the derived cell identifier is / are expected to be valid.

[0403] • Further details about the prediction information are provided in the ‘Further Details about the prediction information’ section below.

[0404] In a set of embodiments, the first prediction information for the at least one neighbor cell can be based on the prediction of the duration of the event triggering fulfillment of the at least one neighbor cell. The first prediction information may correspond to:

[0405] • A flag set by the UE when the time domain predictions indicate that condition which triggered the event remain fulfilled (e.g. predicted RSRP value of the neighbor cell becomes an offset better than the predicted RSRP value of the PCell)

[0406] • A period of time T (in relation to the timing in which first message is transmitted), which indicates for how long time the condition which triggered the event is predicted to remain fulfilled, that is for how long time the predicted RSRP value of the neighbor cell remains an offset better than the predicted RSRP value of the PCell.

[0407] • At least a cell identifier (e.g. Cell ID, PCI + SSB frequency) of the neighbor cell which triggered the event

[0408] • Further details about the prediction information are provided in the “Further Details about the prediction information” section below.

[0409] In a set of embodiments, the UE can derive a first prediction information for the at least one neighbor cell. For example, based on at least one AI / ML model which receives as input one or more measurements of the at least one neighbor cell and provides one or more output(s) based on which the prediction information is derived.

[0410] In a set of embodiments, the UE can derive a second prediction information for the at least one serving cell. For example, based on at least one AI / ML model which receives as input one or more measurements of the at least one serving cell and provides one or more output(s) based on which the prediction information is derived.

[0411] Measurements

[0412] In a set of embodiments, the first message can also include one or more measurement(s) of the at least one neighbor cell and / or one or more measurements of the at least one serving cell. The one or more measurements may correspond to:

[0413] • measurement quantities for one or more SSB / CSI-RS beams / resources of the neighbor cell

[0414] • measurement quantities for one or more SSB / CSI-RS beams / resources of the serving cell

[0415] • measurement quantities for a single SSB / CSI-RS beam / resource of the neighbor cell • measurement quantities for a single SSB / CSI-RS beam / resource of the serving cell

[0416] • any combination of the above bullets

[0417] Reporting measurements in addition to the time-domain predictions enables the source network node to determine what is the current situation of the neighbor cell(s) and / or the PCell thanks to the measurements, and the future situation of the neighbor cell(s) and / or the PCell thanks to the time domain predictions. In addition, in case the source network node is also equipped with a network-based AI / ML model, the source network node may determine whether the predictions reported by the UE are similar to the predictions its own model is providing as output, which could increase the trust in the prediction, and consequently the actions taken based on the predictions. In one option, including one or more measurements in the first message may be configurable at the UE e.g. in a prediction reporting configuration there may be an indication indicating whether the UE shall include measurements and predictions, or only predictions.

[0418] Triggering of first message

[0419] In a set of embodiments, the first message may be transmitted in response to one or more measurements, such as upon fulfillment of an entry condition of an Event A3: neighbor cell measurement quantity (e.g. RSRP) an offset better than the measurement quantity of the PCell.

[0420] In a set of embodiments, the first message can be transmitted according to one or more parameters which the UE receives in a measurement configuration and / or a prediction configuration. The UE can receive the measurement configuration and / or the prediction configuration in a message the UE receives before it transmits the first message.

[0421] In a set of embodiments, the UE can derive a first prediction information for the at least one neighbor cell based on one or more parameters which the UE receives in a measurement configuration and / or a prediction configuration. The UE can receive the measurement configuration and / or the prediction configuration in a message the UE receives before it transmits the first message.

[0422] In a set of embodiments, the UE can derive a second prediction information for the at least one serving cell based on one or more parameters which the UE receives in a measurement configuration and / or a prediction configuration. The UE can receive the measurement configuration and / or the prediction configuration in a message the UE receives before it transmits the first message.

[0423] In one set of embodiments, the UE can transmit the first message in response to (or triggered by) one or more events. The one or more events and / or parameters for the one or more events may have been configured by the source network node. Below are some possible embodiments: • The UE transmits the first message periodically e.g. periodicity configured by the network, possibly as part of the measurement configuration and / or prediction configuration. In this example, the event is the end of a periodicity or period, so the UE transmits the message at the end of each period. The periodicity may also be controlled by a timer which starts when the period starts and has a timer value set to the periodicity value, so that when the UE transmits the first message when the timer expires.

[0424] • The UE transmits the first message in response to the fulfillment of a condition which takes as input one or more measurements of a neighbor cell and / or a serving cell. o ln one example, the UE transmits a MeasurementReport including prediction information for the neighbor cell and / or the serving cell when the entry condition of an Event A3 is fulfilled: measurements on neighbor cell (RSRP neighbor cell) becomes an offset better than measurements on the PCell (RSRP neighbor cell). o ln another example the UE transmits a MeasurementReport including prediction information on how long time (T) the entry condition (e.g. Event A3) remains fulfilled. o A time-to-trigger parameter may also be configured, so that the first message is transmitted when measurements fulfil the condition for a duration defined by the time to trigger parameter.

[0425] • The UE transmits first message in response to the fulfillment of a condition which takes as input prediction information of a neighbor cell and / or prediction information of a serving cell. o In one example, the UE transmits the first message in response to the first prediction information for at least one neighbor cell and / or the second prediction information for at least a serving cell, such as upon fulfillment of an entry condition related to an Event A3: time-domain prediction(s) of a neighbor cell measurement quantity (e.g. RSRP) on at least a time instance “f” is an offset better than time-domain prediction(s) of the PCell’s measurement quantity (e.g. RSRP) on at least the time instance “f”. o ln one example, the UE transmits a MeasurementReport including prediction information for the a neighbor cell and / or a serving cell when the entry condition of a prediction-based Event A3 is fulfilled: prediction information on neighbor cell (time-domain prediction of RSRP of the neighbor cell) becomes an offset better than prediction information on the PCell (time-domain prediction of RSRP of the PCell). o ln another example the UE transmits a MeasurementReport including prediction information on how long time (T) the prediction-based Event A3 condition remains fulfilled. o A time-to-trigger parameter may also be configured, so that the first message is transmitted when the predictions fulfil the condition for a duration defined by the time to trigger parameter. o A confidence level threshold parameter may also be configured, so that the first message is transmitted when the confidence level of the prediction information carried in the first message is above the configured threshold.

[0426] • The UE transmits first message in response to the fulfillment of a condition which takes as input prediction information of a neighbor cell and / or prediction information of a serving cell and / or one or more measurements of a neighbor cell and / or a serving cell.

[0427] • The UE transmits first message in response to the (re)configuration / activation of one or more time-domain prediction AI / ML model(s) used for generating the first message.

[0428] In one set of embodiments, the first prediction information for the at least one neighbor cell can be based on at least one time-domain prediction of a measurement of the at least one neighbor cell and / or the second prediction information for the at least a serving cell is based on at least one time-domain prediction of a measurement of the at least a serving cell and / or the first message also includes one or more measurement(s) of the at least one neighbor cell and / or one or more measurements of the at least one serving cell. In other words, the UE perform one or more measurements of a neighbor cell and / or of a serving cell.

[0429] In a set of embodiments, the UE can perform one or more measurements of a neighbor cell and / or of a serving cell based on a measurement configuration received in a message (e.g. RRC Reconfiguration, RRC Resume, RRC Setup) from the source network node.

[0430] - The measurement configuration may comprise one or more of: i. A measurement object (e.g. IE MeasObjectNR) indicating an SSB frequency (e.g. for a neighbor) and / or further cell quality derivation parameters ii. A reporting configuring (e.g. IE ReportConfig NR)

[0431] - The measurement configuration may be included in an RRCReconfiguration or an

[0432] RRCResume or an RRCSetup message the UE receives before it transmits the first message.

[0433] - The measurement configuration may include parameters indicating to the UE how to transmit the first message. - The measurement configuration may include parameters indicating to the UE what to be included in the first message.

[0434] - The measurement configuration may include parameters indicating to the UE what to measure, which needs to be included in the first message.

[0435] C / 70 execution steps

[0436] The method may further comprise the UE applying the stored CHO candidate configuration for the at least one neighbor cell and accessing the at least one neighbor cell when the CHO execution condition is fulfilled.

[0437] Accessing the at least one neighbor cell when the CHO execution condition is fulfilled may comprise the UE transmitting a random access preamble to the neighbor cell, receiving a Random Access Response from the neighbor cell and transmitting an RRC Reconfiguration Complete message to the neighbor cell.

[0438] The UE may transmit a complete message (e.g. RRC Reconfiguration Complete) to the source network node in response to receiving a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0439] The UE may receive the CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell which further comprises a Contention-Free Random Access (CFRA) resource configuration. The CFRA resource configuration may be associated to at least one beam of the neighbor cell (e.g. SSB index, CSI- RS identifier) mapped to the CFRA resource (SSB index=X, mapped to the CFRA resource with preamble index Y, Time / Frequency PRACH resource Z) which the UE has transmitted in the first message prediction information for the at least one beam of the neighbor cell e.g. predicted RSRP values of that beam indicating that close a CHO execution the beam would have a predicted RSRP value above a threshold (thus it would be a good beam for CFRA configuration). Upon applying that CHO candidate configuration, the UE may perform a contention-free random access by selecting an SSB and / or CSI-RS and transmitting a CFRA preamble in a time-frequency resource indicated int the CFRA resource configuration.

[0440] The CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell may further comprise an indication that the cell is configured for a fast recovery procedure (e.g. attemptCondReconfig set to ‘true’) in which upon a failure detection (e.g. Radio Link Failure, Handover Failure, CHO Failure) the UE initiates reestablishment, selects the neighbor cell and performs CHO execution (i.e. the UE applies the stored CHO candidate configuration of the at least one neighbor cell). Further Details about the prediction information

[0441] In one set of embodiments, the UE may transmit to a source network node, a first message including a first prediction information for at least one neighbor cell and / or a second prediction information for at least a serving cell (in general terms: prediction information for a cell). The first prediction information for the at least one neighbor cell and / or the second prediction information for at least a serving cell may correspond to one or more of:

[0442] • A Spatial-domain Downlink (DL) beam prediction for a Set A of beams o ln one option, the Spatial-domain Downlink (DL) beam prediction for a Set A of beams based on measurement results of Set B of beams o In one option, both the Set A of beams and the Set B of beams are of the same neighbor cell. For example, the Set A of beams are DL beams transmitting SSBs of the neighbor cell, i.e., each SSB of the Set A comprises a physical Cell identity (PCI) of the neighbor cell and is transmitted in the SSB frequency of the neighbor cell. Or, in other words, the UE assumes that different SSBs of the same cell are transmitted in different beams, meaning they are transmitted in different spatial direction. o ln one option, the Spatial-domain DL beam prediction comprises a prediction of a measurement quantity of a reference signal, such as an SSB or CSI-RS. For example, assuming beams transmitting SSBs, and assuming that Set A corresponds to [SSB(1), SSB(2), SSB (3), SSB (4)] and that Set B corresponds to [SSB(5), SSB(6), SSB (7), SSB (8)] the prediction information the UE derives may correspond to SS-RSRP for SSB (1), to SS-RSRP for SSB (2), to SS-RSRP for SSB (3), to SS-RSRP for SSB (4), based on the SS-RSRP for SSB (5), to SS- RSRP for SSB (6), to SS-RSRP for SSB (7), to SS-RSRP for SSB (8). o ln one option, the Spatial-domain DL beam prediction comprises a beam identifier (e.g. SSB index, CSI-RS resource identity, beam ID) derived based on a prediction of a measurement quantity of a reference signal in which the beam is transmitted. For example, the UE predicts an RSRP of a beam in Set A whose beam ID = X1 and includes the beam ID=X1 in the first message e.g. when the predicted RSRP of that beam is above a threshold. o In one option, Set A and Set B are different i.e. Set B is not a subset of Set A. For instance, Set B consists of SSB beams whereas Set A consists of CSI-RS beams. o In one option, Set B is a subset of Set A. o In one option, to derive one or more Spatial DL beam prediction(s) as an output of an AI / ML model, the AI / ML model receives as input one or more of: ■ At least a L1-RSRP measurement based on Set B;

[0443] ■ At least a L1-RSRP measurement based on Set B and assistance information e.g. beam pattern information and / or a configuration information related to one or more network transmission(s)

[0444] ■ At least a Cl R based on Set B;

[0445] ■ At least one L1-RSRP measurement based on Set B and the corresponding DL Tx and / or Rx beam ID. In one option, the one or more Spatial DL beam prediction(s) are one or more outputs of an AI / ML model In one option, a Spatial DL beam prediction corresponds to one or more of:

[0446] ■ Tx and / or Rx Beam ID(s) and / or

[0447] • For example, that may correspond to one or more Reference signal (RS) identifiers transmitted in a spatial direction or beam, such as an SSB Index (or SSB identifier) or a CSI-RS resource identity, and possibly derived based on prediction of measurements on the corresponding RS e.g. SSB ID=X corresponds to a predicted information when the predicted value of SS-RSRP of SSB ID=X is above a threshold.

[0448] ■ The predicted L1-RSRP of the N predicted DL Tx and / or Rx beam(s) e.g. top N predicted beams

[0449] • For example, that may correspond to N predicted RSRP values (Layer 1 RSRP) or other measurement quantities per beam and / or per RS transmitted on a spatial direction or beam, such as SS- RSRP, SS-RSRQ, SS-SINR, CSI-RSRP, CSI-RSRQ, CSI-SINR.

[0450] ■ Tx and / or Rx Beam angle(s) and / or the predicted L1-RSRP of the N predicted DL Tx and / or Rx beams

[0451] Fig. 9 is an example of the AI / ML model using the RSRP measurements from beams in Set B (beams denoted by gray circles) as input predicts the best beam in set A (beams denoted by white circles). The output of the AI / ML model could be predicted beam IDs with / without predicted RSRP values.

[0452] Fig. 10 is an example of the AI / ML model using the RSRP measurements from beams in Set B (beams denoted by gray circles) as input predicts the Top-K beams in set A (beams denoted by white circles). The output of the AI / ML model could be predicted beam IDs with / without predicted RSRP values.

[0453] • A Spatial-domain cell prediction for a cell X o In one option the spatial-domain cell prediction for a cell X corresponds to the value of a measurement quantity (e.g. an RSRP value, an RSRQ value, an SINR value) representing the measurement quantity of cell X (or a cell quality or cell measurement result). The spatial-domain cell prediction for cell X can be calculated based on one or more spatial-domain DL beam prediction(s) of a Set A of beams of cell X e.g. predicted RSRP values for each beam in the Set A of beams.

[0454] ■ In one sub-option, the beam prediction(s) for a Set A of beams of cell X is calculated based on measurements of a Set B of beams of cell X. For example, assuming beams transmitting SSBs, and assuming that Set A corresponds to [SSB(1), SSB(2), SSB (3), SSB (4)] and that Set B corresponds to [SSB(5), SSB(6), SSB (7), SSB (8)] the UE derives as prediction information the values of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), SS-RSRP for SSB (4), based on the SS- RSRP for SSB (5), SS-RSRP for SSB (6), SS-RSRP for SSB (7), SS-RSRP for SSB (8). Then, the UE uses the obtained predictions of SS-RSRP for SSB (1), SS-RSRP for SSB (2), to SS-RSRP for SSB (3), to SS-RSRP for SSB (4) to calculate the prediction of cell X e.g. highest SS-RSRP value out of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), to SS-RSRP for SSB (4).

[0455] ■ In one sub-option, the beam prediction(s) for a Set A of beams of cell X is calculated based on measurements of a Set B of beams of cell Y. For example, assuming beams transmitting SSBs, and assuming that Set A corresponds to [SSB(1), SSB(2), SSB (3), SSB (4)] of cell X and that Set B corresponds to [SSB(5), SSB(6), SSB (7), SSB (8)] of cell Y the UE derives as prediction information the values of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), SS-RSRP for SSB (4) of Cell X, based on the SS-RSRP for SSB (5), SS-RSRP for SSB (6), SS-RSRP for SSB (7), SS-RSRP for SSB (8). Then, the UE uses the obtained predictions of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), SS- RSRP for SSB (4) to calculate the prediction of cell X e.g. highest SS- RSRP value out of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), to SS-RSRP for SSB (4). o In one option the spatial-domain cell prediction for cell X corresponds to the value of a measurement quantity (e.g. an RSRP value, an RSRQ value, an SINR value) representing the measurement quantity of cell X (or a cell quality or cell measurement result). The spatial-domain cell prediction for neighbor cell X may be calculated based on one or more spatial-domain DL beam prediction(s) of a Set A of beams of cell X (e.g. predicted RSRP values for each beam in the Set A of beams) and / or measurements on a Set B of beams of cell X.

[0456] ■ In one sub-option, the beam prediction(s) for a Set A of beams of cell X is calculated based on measurements of a Set B of beams of cell X. For example, assuming beams transmitting SSBs, and assuming that Set A corresponds to [SSB(1), SSB(2), SSB (3), SSB (4)] and that Set B corresponds to [SSB(5), SSB(6), SSB (7), SSB (8)] the UE derives as prediction information the values of SS-RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), SS-RSRP for SSB (4), based on the SS- RSRP for SSB (5), SS-RSRP for SSB (6), SS-RSRP for SSB (7), SS- RSRP for SSB (8). Then, the UE uses the obtained predictions of SS- RSRP for SSB (1), SS-RSRP for SSB (2), SS-RSRP for SSB (3), SS-RSRP for SSB (4), AND the SS-RSRP for SSB (5), SS-RSRP for SSB (6), SS- RSRP for SSB (7), to SS-RSRP for SSB (8) to calculate the prediction of cell X e.g. highest SS-RSRP value out of the predicted SS-RSRP values (of Set A) and the actual SS-RSRP measurements for Set B.

[0457] • A Time-domain Downlink (DL) beam prediction for a Set A of beams of a cell X o In one option, the Time-domain Downlink (DL) beam prediction for a Set A of beams of a cell X is derived based on measurement results of Set B of beams of a cell X. The Set A and Set B may be the same, or Set B may be a subset of Set A, or Set A and Set B are non-overlapping. o In one option, the time-domain DL beam prediction for a Set A of beams corresponds to F predictions for F future time instances. Each prediction may be for each time instance and may be associated to each beam in the Set A for which the prediction is performed. o In one option, the time-domain DL beam prediction for a Set A of beams corresponds to one or more beam ID(s) of the Set A of beams, associated to a future time instance (out of multiple future time instances F, where F may be configured at the UE) and a respective time-domain prediction of a measurement quantity. A beam ID may correspond to a Reference Signal ID or index (such as an SSB index, denoted herein as SSB(k), for SSB with index number ‘k’) for an RS which is transmitted in that beam. For example, a predicted information may correspond to an SS-RSRP value for the corresponding SSB index SSB(k) of a cell (where a measurement quantity may also be configured). For example, assuming Set A of beams corresponds to SSB(1), SSB(2), SSB(3), SSB(4), the predicted information included in the first message may correspond to:

[0458] ■ For future time instance f=1 ;

[0459] • SS-RSRP=x1 , for SSB(1);

[0460] • SS-RSRP=x2, for SSB(2);

[0461] • SS-RSRP=x3, for SSB(3);

[0462] • SS-RSRP=x4, for SSB(4);

[0463] ■ For future time instance f=2;

[0464] • SS-RSRP=x1*, for SSB(1);

[0465] • SS-RSRP=x2*, for SSB(2);

[0466] • SS-RSRP=x3*, for SSB(3);

[0467] • SS-RSRP=x4*, for SSB(4);

[0468] ■ For future time instance f=3;

[0469] • SS-RSRP=x1**, for SSB(1);

[0470] • SS-RSRP=x2**, for SSB(2);

[0471] • SS-RSRP=x3**, for SSB(3);

[0472] • SS-RSRP=x4**, for SSB(4);

[0473] ■ For future time instance f=4;

[0474] • SS-RSRP=x1***, for SSB(1);

[0475] • SS-RSRP=x2***, for SSB(2);

[0476] • SS-RSRP=x3***, for SSB(3);

[0477] • SS-RSRP=x4***, for SSB(4); one option, the time-domain DL beam prediction for a Set A of beams corresponds to one or more beam ID(s) of the Set A of beams, associated to a future time instance ‘f, and a respective time-domain prediction of a measurement quantity, and a respective predicted time window within which the predicted beam ID(s) is / are valid. A beam ID may correspond to a Reference Signal ID or index (such as an SSB index, denoted herein as SSB(k), for SSB with index number ‘k’) for an RS which is transmitted in that beam. For example, a predicted information may correspond to an SS-RSRP value for the corresponding SSB index SSB(k) of a cell (where a measurement quantity may also be configured) and a time window during which the predicted SS-RSRP value is valid. For example, assuming Set A of beams corresponds to SSB(1), SSB(2), SSB(3), SSB(4), the predicted information included in the first message may correspond to:

[0478] ■ For future time instance f;

[0479] • SS-RSRP=x1 , for SSB(1); valid time window = t1

[0480] • SS-RSRP=x2, for SSB(2); valid time window = t2

[0481] • SS-RSRP=x3, for SSB(3); valid time window = t3

[0482] • SS-RSRP=x4, for SSB(4); valid time window = t4

[0483] ■ a common valid time window may be used to indicate the time duration where all predicted beams are valid, in that case, t1=t2=t3=t4=t. one option, the time-domain DL beam prediction for a Set A of beams corresponds to one or more beam ID(s) of the Set A of beams, associated to a given time instance ‘f’ (out of multiple future time instances F, where F may be configured at the UE). The one or more beam ID(s) may be selected based on respective timedomain prediction of a measurement quantity e.g. predicted value of an SS-RSRP for the corresponding SSB index of a neighbor cell. For example, assuming Set A of beams = Set B and correspond to SSB(1), SSB(2), SSB(3), SSB(4), the predicted information per time instance ‘f may correspond to the beam ID(s) of the beams whose measurement quantity (e.g. RSRP) is above a threshold (e.g. configured at the UE), or / and only top-K beams are reported. Assume that K=4 for the example case, as an example, the following predicted information is reported:

[0484] • For future time instance f=1 ; o SSB(1); o The UE includes SSB(1) for f=1 as a reported information because the predicted SS-RSRP for SSB(1) is above the threshold, while the predicted SS-RSRP values for f=1 for SSB(2), SSB(3), SSB(4) are not above threshold.

[0485] • For future time instance f=2; o SSB(1); o The UE includes SSB(1) for f=2 as a reported information because the predicted SS-RSRP for SSB(1) is above the threshold, while the predicted SS-RSRP values for f=2 for SSB(2), SSB(3), SSB(4) are not above threshold.

[0486] • For future time instance f=3; o SSB(1); o SSB(2); o The UE includes SSB(1) and SSB(2) for f=3 since reported information because the predicted SS-RSRP for SSB(1) and SSB(2) are both above the threshold, while the predicted SS-RSRP values for f=3 for SSB(3), SSB(4) are not above threshold.

[0487] • For future time instance f=4; o SSB(1); o SSB(2); o SSB(4); o The UE includes SSB(1), SSB(2), SSB(3), SSB(4) for f=4 since reported information because the predicted SS-RSRP for SSB(1), SSB(2), SSB(3), SSB(4) are above the threshold. one option, the time-domain DL beam prediction for a Set A of beams corresponds to one or more beam ID(s) ) of the Set A of beams at a future time instance f, and one or more predicted time window(s) within which the predicted beam ID(s) is / are valid. The one or more beam ID(s) are selected based on respective time-domain prediction of a measurement quantity. For example, assuming Set A of beams = Set B and correspond to SSB(1), SSB(2), SSB(3), SSB(4), the predicted information may correspond to the beam ID(s) of the beams whose measurement quantity (e.g. RSRP) is above a threshold (e.g. configured at the UE), and the predicted validation time for each beam.

[0488] Assume that the following prediction information can be reported

[0489] ■ For future time instance f;

[0490] • SSB(1); valid time window = t1

[0491] • SSB(2); valid time window =t2

[0492] • The UE includes SSB(1) and SSB(2) for f in reported information because the predicted SS-RSRP for SSB(1) and SSB(2) are both above the threshold, while the predicted SS-RSRP values for f=3 for SSB(3), SSB(4) are not above threshold. The SS-RSRP for SSB(1) and the SS-RSRP for SSB (2) are predicted to be above the threshold for time windows of t1 and t2, respectively.

[0493] • A Time-domain cell prediction for a cell X o In one option the time-domain cell prediction for a cell X corresponds to the value of a measurement quantity (e.g. an RSRP value, an RSRQ value, an SINR value), or rather a predicted value, representing the measurement quantity of cell X at a future time instance ‘f’ (or a predicted cell quality or predicted cell measurement result) for a future time instance ‘f’ o In one option, the time-domain cell prediction for cell X is calculated based on one or more time-domain DL beam prediction(s) of a Set A of beams of cell X e.g. predicted RSRP values for each beam in the Set A of beams. o In one option, both the prediction of the measurement quantity and the cell identifier associated to the cell X are included in the first message, for a given future time instance which may also be included in the first message. o For example, the UE obtains the following time-domain DL beam prediction of a Set A of beams of cell X (e.g., predicted best beam with predicted SS-RSRP value) for the future time instances as follows (e.g. as described above)

[0494] • Future time instance f=1 o SS-RSRP=x, for the predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4).

[0495] • For future time instance f=2; o SS-RSRP=x*, for the predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4).

[0496] • For future time instance f=3; o SS-RSRP=x**, for the predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4).

[0497] • For future time instance f=4; o SS-RSRP=x***, for the predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4).

[0498] ■ In one option, the UE considers as the predicted RSRP for cell X in time instance f=1 to be the predicted SS-RSRP value x of predicted best beam / Top-1 / strongest beam among SSB(1), SSB(2), SSB(3) and SSB(4); the predicted RSRP for cell X in time instance f=2 to be the predicted SS- RSRP value x* of predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4); the predicted RSRP for cell X in time instance f=3 to be the predicted SS-RSRP value x** of predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4); and the predicted RSRP for cell X in time instance f=4 to be the predicted SS-RSRP value x*** of predicted best beam / Top-1 beam among SSB(1), SSB(2), SSB(3) and SSB(4). Thus, what is included in the first message as predicted information may be following:

[0499] • Future time instance f=1 -> predicted RSRP for cell X= x;

[0500] • Future time instance f=2 -> predicted RSRP for cell X= x*;

[0501] • Future time instance f=3 -> predicted RSRP for cell X= x**;

[0502] • Future time instance f=4 -> predicted RSRP for cell X= x***.

[0503] Fig. 11 is an example of time domain cell prediction derivation based on predicted RSRP value of predicted best beam / Top-1 beam of set A beams of Cell X For example, the UE obtains the following time-domain DL beam prediction(s) of a Set A of beams of cell X for the future time instances as follows (e.g. as described above)

[0504] • Future time instance f=1 o SS-RSRP=x1 , for SSB(1); SS-RSRP=x2, for SSB(2); SS- RSRP=x3, for SSB(3); SS-RSRP=x4, for SSB(4).

[0505] • For future time instance f=2; o SS-RSRP=x1*, for SSB(1); SS-RSRP=x2*, for SSB(2); SS- RSRP=x3*, for SSB(3); SS-RSRP=x4*, for SSB(4);

[0506] • For future time instance f=3; o SS-RSRP=x1**, for SSB(1); SS-RSRP=x2**, for SSB(2); SS-RSRP=x3**, for SSB(3); SS-RSRP=x4**, for SSB(4);

[0507] • For future time instance f=4; o SS-RSRP=x1***, for SSB(1); SS-RSRP=x2***, for SSB(2); SS-RSRP=x3***, for SSB(3); SS-RSRP=x4***, for SSB(4);

[0508] ■ In one option, the UE considers as the predicted RSRP for cell X in time instance f=1 to be the highest predicted SS-RSRP value out of x1 , x2, x3, x4; the predicted RSRP for cell X in time instance f=2 to be the highest predicted SS-RSRP value out of x1*, x2*, x3*, x4*; the predicted RSRP for cell X in time instance f=3 to be the highest predicted SS-RSRP value out of x1**, x2**, x3**, x4**; and the predicted RSRP for cell X in time instance f=4 to be the highest predicted SS-RSRP value out of x1***, x2***, x3***, x4*. Thus, what is included in the first message as predicted information may be following:

[0509] Future time instance f=1 -> predicted RSRP for cell X= Max (x1 , x2, x3, x4)

[0510] Future time instance f=2 -> predicted RSRP for cell X= Max (x1*, x2*, x3*, x4*);

[0511] Future time instance f=3 -> predicted RSRP for cell X= Max (x1**, x2**, x3**, x4**); predicted RSRP for cell X= Max

[0512] ■ In one option, the UE considers as the predicted RSRP for cell X in time instance f=1 to be an average of the highest predicted SS-RSRP values e.g. highest SS-RSRP value averaged with the SS-RSRP values of the other SSBs whose SS-RSRP is above a threshold, up to a certain configurable value e.g. N. For simplicity this is simply denoted as an

[0513] AverageQ function, as follows:

[0514] Future time instance f=1 predicted RSRP for cell X= Average

[0515] (x1 , x2, x3, x4)

[0516] Future time instance f=2 predicted RSRP for cell X= Average

[0517] (x1*, x2*, x3*, x4*);

[0518] Future time instance f=3 predicted RSRP for cell X= Average

[0519] (x1**,x2**x3**x4**);

[0520] Future time instance f=4 predicted RSRP for cell X= Average

[0521] (x1*** x2*** x3*** x4***)'

[0522] Fig. 12 is an example of time domain cell prediction derivation based on Max().

[0523] Fig. 13 is an example of time domain cell prediction derivation based one Average(). In one option the time-domain cell prediction for neighbor cell X corresponds to a cell identifier such as a Cell ID and / or a PCI + SSB frequency, derived based on the predicted value of a measurement quantity (e.g. an RSRP value, an RSRQ value, an SI NR value) representing the measurement quantity of cell X at a future time instance ‘f (or a predicted cell quality or predicted cell measurement result) one option, for a future time instance ‘f the time-domain cell prediction for neighbor cell X is calculated based on one or more time-domain DL beam prediction(s) of a Set A of beams of cell X e.g. predicted RSRP values for each beam in the Set A of beams. one option, the UE obtains the following time-domain DL beam prediction(s) of a Set A of beams of cell X for the future time instances as follows

[0524] • Future time instance f=1 o SS-RSRP=x1, for SSB(1); SS-RSRP=x2, for SSB(2); SS- RSRP=x3, for SSB(3); SS-RSRP=x4, for SSB(4).

[0525] • For future time instance f=2; o SS-RSRP=x1*, for SSB(1); SS-RSRP=x2*, for SSB(2); SS- RSRP=x3*, for SSB(3); SS-RSRP=x4*, for SSB(4);

[0526] • For future time instance f=3; o SS-RSRP=x1**, for SSB(1); SS-RSRP=x2**, for SSB(2); SS-RSRP=x3**, for SSB(3); SS-RSRP=x4**, for SSB(4);

[0527] • For future time instance f=4; o SS-RSRP=x1***, for SSB(1); SS-RSRP=x2***, for SSB(2); SS-RSRP=x3***, for SSB(3); SS-RSRP=x4***, for SSB(4);

[0528] ■ In one option, the UE considers as the predicted RSRP for cell X in time instance f=1 to be the highest predicted SS-RSRP value out of x1 , x2, x3, x4; the predicted RSRP for cell X in time instance f=2 to be the highest predicted SS-RSRP value out of x1*, x2*, x3*, x4*; the predicted RSRP for cell X in time instance f=3 to be the highest predicted SS-RSRP value out of x1**, x2**, x3**, x4**; and the predicted RSRP for cell X in time instance f=4 to be the highest predicted SS-RSRP value out of x1***, x2***, x3***, x4*. Thus, the UE calculates the following and determines to include a Cell ID or not as the predicted information as follows:

[0529] • Future time instance f=1 - predicted RSRP for cell X= Max (x1 , x2, x3, x4) o When the predicted RSRP for cell X= Max (x1 , x2, x3, x4) > threshold, UE includes the Cell ID of cell X as predicted information for time instance f=1

[0530] • Future time instance f=2 -> predicted RSRP for cell X= Max (x1*, x2*, x3*, x4*); o When the predicted RSRP for cell X= Max (x1*, x2*, x3*, x4*) > threshold, UE includes the Cell ID of cell X as predicted information for time instance f=2

[0531] • Future time instance f=3 -> predicted RSRP for cell X= Max (x1**, x2**,x3**x4**);o When the predicted RSRP for cell X= Max (x1**, x2**, x3**, x4**) > threshold, UE includes the Cell ID of cell X as predicted information for time instance f=3

[0532] • Future time instance f=4 -> predicted RSRP for cell X= Max (x1***, x2***, x3***, x4***); o When the predicted RSRP for cell X= Max (x1***, x2***, x3***, x4***) > threshold, UE includes the Cell ID of cell X as predicted information for time instance f=4

[0533] • Following that logic, for each future time instance to be included in the first message e.g. f=1 , f=2, f=3, f=4 the UE may include one or more cell ID(s). The cell ID may be included for a future time instance when the predicted value of the measurement quantity of that cell for that time instance fulfills a criterion, e.g., being above a threshold in the examples above, or being an offset better than the predicted measurement quantity of the PCell (e.g. the entry condition of an Event A3 but based on time-domain prediction of a measurement quantity of a cell). An example of a prediction information may be the following: o Future time instance f=1 -> Cell ID=X, cell ID=Y o Future time instance f=2 -> Cell I D=X o Future time instance f=3 -> Cell ID=X o Future time instance f=4 -> Cell ID=X, cell ID=Z o That reported information would indicate that the cell whose cell ID=X has a predicted measurement quantity (RSRP) which fulfills the criteria (e.g. being above a threshold) in the future time instances f=1 , f=2, f=3, f=4, while the cell with Cell ID=Y only fulfills the criteria in f=1 , and the cell with cell ID= z in f=4. An AI / ML model can be designed to realize the beam-level measurement prediction in spatial domain or / and time-domain. Utilizing the predicted beam-level measurement quality(ies) or / and beam IDs generated from the AI / ML model output, a predicted cell-level measurement quality for a cell X can be derived using the approaches described above. An AI / ML model can also be designed to directly output the predicted cell-level measurement by taking L3 measurements of a set of beams as model input. Besides predicted beam-level or / and cell-level measurement quantities and beam / cell IDs, the model may also provide additional information such as confidence level of the model output, the validation time of the predicted measurements, etc.

[0534] The designed AI / ML model can be deployed at the UE and associated to a beam prediction feature or a RRM prediction feature. When connecting to a network node, a UE can report its support of the AI / ML model for the beam prediction feature or RRM prediction feature to the network node via UE capability reporting. Based on the received UE capability, together with other conditions, the network node can make decisions on whether to configure / active the AI / ML model at the UE or not.

[0535] Below are multiple examples on how to design an AI / ML model to achieve the beam / cell- level measurement quality prediction in spatial or / and time domain.

[0536] For the AI / ML model used for cell prediction, in an example, it is composed of multiple connected neurons. Optionally it contains one or a few of input layer, one or a few of hidden layer, and one output layer. For the input layer, it takes UE measurements results as the model input, where the measurement results are obtained based on measuring some reference signals, e.g., SSBs and / or CSI-RSs. Optionally, the measurement results would be normalized before input to the hidden layers. The normalization can change the value of the numeric variable in the dataset to a typical scale which improve model training. For the hidden layer(s), it is located between the input and output, in which the function applies weights to the inputs and directs them through an activation function to the output layer. Optionally, activation function can be one of Softmax function, Sigmoid function, ReLU function, Leaky ReLU, tanh function and Maxout. For the output layer, the output can be predicted RSRP values for each beam. Optionally, the output can be the probability values where each value means the probability of the beam to be the best beam.

[0537] In an example for the AI / ML model, the AI / ML model used for cell prediction is based on convolutional neural networks, optionally it contains one or a few of input layers, one of a few of convolution layer, one or a few of pooling layer and output layer. For the input layer, it takes UE measurements results as the model input, where the measurement results are obtained based on measuring some reference signals, e.g., SSBs and / or CSI-RSs. Optionally, the measurement results would be normalized before input to the convention layers. The normalization can change the value of the numeric variable in the dataset to a typical scale which improve model training. For the convention layer(s), it is used to extract the feature from the input. It applies a set of learnable filters(known as the kernels) to the input with smaller size than the whole input. These filters and kernels slide over the input data and computes the dot product between kernel weight and the corresponding input. The output of convention layer is referred as feature maps coming from the input measured RSRP values. For pooling layers, it involves sliding a two-dimensional filter over each channel of feature map and summarizing the features lying within the region covered by the filter. Before the output layer, there can be a fully connected layer to interpret / summarize the features obtained and directs them through activation function to the output layer. For the output layer, the output can be predicted RSRP values for each beam. Optionally, the output can be the probability values where each value means the probability of the beam to be the best beam.

[0538] In another set of examples, an AI / ML model is designed to realize the beam-level measurement prediction in the spatial domain. A predicted cell-level measurement quality for a cell X can be derived based on the predicted beam-level measurement quality(ies) or / and beam IDs generated from the AI / ML model output. Different design options for AI / ML based spatial domain beam prediction can be considered. Three example design options are listed below.

[0539] • Option 1) the AI / ML model predicts Top-1 / K beam ID(s), where the model takes the

[0540] (postprocessed) RSRP measurements of the beams in set B as model input and directly outputs the top-1 / K beam ID(s) of the beams in Set A.

[0541] • Option 2) the AI / ML model predicts Top-1 / K beam ID(s) and the associated predicted RSRP values, where the model takes the (postprocessed) RSRP measurements of the beams in set B as model input and directly outputs the top-1 / K beam ID(s) and the predicted RSRP values of these beams in set A.

[0542] • Option 3) the AI / ML model predicts top-1 / K beam ID(s) with / without the associated predicted RSRP values, where the model takes the (postprocessed) RSRP measurements of the beams in set B or / and the assistance information like UE position as model input.

[0543] As an example, the AI / ML model mentioned in the above three design options can be based on neural network architectures, e.g., convolutional neural network (CNN), fully connected neural network (NN), Residual Networks (ResNet). Fig. 14 shows two examples of model architectures, where Neural network B (NN B) is a model with higher complexity in comparison to NN A. The number of nodes in the dense layers equals the number of beams in Set A, NSetA. The model input takes RSRP of SSB and / or CSI RS of set B beams (one real value per measured beam, normalized based on min and max values per sample. Normalization is based on scaling the beam RSRP values in dB per sample to yield the range 0.0 to 1.0 for RSRP values for each sample. In case assistance information, such as UE location information, is also used as input to the neural network, that information is concatenated to the RSRP values after being separately scaled by a fixed scaling factor designed to yield values with maximum magnitudes in the order of 1 . A softmax cross-entropy function is used to generate the probability of a beam being the strongest beam, used to derive top-1 / K beams.

[0544] Fig. 14 shows examples of Neural Networks used for designing AI / ML models for spatial beam prediction. The number of nodes in the dense layers equals the number of beams N_SetA in Set A.

[0545] In another set of examples, an AI / ML model is designed to realize the beam-level measurement prediction in the time domain (which includes spatial and time domain prediction as a special case).

[0546] Fig. 15 illustrates an example of model input and model output selection when designing an AI / ML model for time domain beam prediction. The AI / ML model inputs are the L1-RSRPs measured from 5 consecutive time instances. So, the observation duration T1=5*40ms=200ms. Prediction is at the time instance immediately following the last observation window time instance, and a prediction at 160ms ahead for comparison. Hence the time duration for the best beam evaluation is T2= 40 ms or 160 ms. An example of the AI / ML model is described as the following.

[0547] As an example, the AI / ML model can be designed based on recurrent neural network (RNN), long short term memory network (LSTM), or transformer network architectures. An example model architecture can consist of two LSTM layers, a Dropout layer, Dense-Relu and a Dense-softmax, which are sequentially connected. The AI / ML model input size is (Nip, 5), where Nip is the number of L1-RSRPs measured at each of the five time instance. For model output, a categorical cross entropy loss function is used to generate a softmax output vector, whose size is equal to the number of beams contained in the set A, based on which the top-1 / K beams with the highest probability can be generated for each prediction time instance.

[0548] Further details about the CHO configuration(s)

[0549] In the method the UE can receive a CHO configuration including a CHO execution condition according to any of:

[0550] • The UE receives the CHO configuration in a first RRCReconfiguration and, in response to it, the UE transmits an RRCReconfigurationComplete. • The CHO configuration contains the configuration of CHO candidate cell(s) generated by the candidate network node(s) e.g. candidate gNB(s) and CHO execution condition(s) generated by the source network node e.g. source gNB.

[0551] • The CHO execution condition (or simply execution condition) may consist of one or two trigger condition(s) each configured as a Measurement ID associated to a reporting / trigger configuration (i.e. CHO events A3 / A5, as defined in 3GPP TS 38.331).

[0552] • When the UE executes CHO, i.e. the UE applies a stores RRCReconfiguration message and starts synchronization with a candidate cell which fulfills the CHO execution condition, and transmits an RRCReconfigurationComplete.

[0553] In a set of embodiments, the UE can receive a CHO configuration including a CHO execution condition and a CHO candidate configuration for the at least one neighbor cell.

[0554] The CHO configuration may correspond to the field conditionalReconfiguration-r16 and / or the Information Element ConditionalReconfiguration-r16, included in an RRC Reconfiguration message (e.g. RRCReconfiguration), and defined as follows:

[0555] The CHO configuration can comprise one or more of the following:

[0556] • An indication of a fast recovery e.g. parameter attemptCondReconfig. When that is present, the UE performs CHO if selected cell is a target candidate cell

[0557] • One of more CHO candidate configuration(s) e.g. in the IE CondReconfigToAddModList

[0558] • One of more indications for removing CHO candidate cell configuration(s) e.g. in the IE CondReconfigToRemoveList

[0559] The CHO candidate configuration may correspond to one or more of:

[0560] • An instance within the IE CondReconfigToAddModList e.g. the IE CondReconfigToAddMod and / or parameters within and / or The actual RRCReconfiguration message associated to the CHO candidate cell and to be applied when the CHO execution condition is stored e.g. field condRRCReconfig and / or the IE OCTET STRING (CONTAINING RRCReconfiguration)

[0561] The CHO execution condition may correspond to an indication of the execution condition that needs to be fulfilled in order to trigger the execution of a CHO. That may comprise one or more measurement identifiers and a measurement object (e.g. indicating the SSB frequency and other parameters for cell quality derivation). Each measurement identifier may be associated to a reporting configuration for CHO in which the actual execution condition parameters are included. For example, the CHO execution condition for a candidate cell may be indicated to the UE as a SEQUENCE of one or more IE(s) Measld(s).

[0562] Further details about CHO related actions at the source and / or candidate network node based on first and / or second predicted information

[0563] In a dependent step, the source network node can determine to trigger one or more actions based on the first prediction information and / or the second prediction information which has been received. The one or more actions may comprise:

[0564] • Configuring a neighbor cell as a CHO candidate based on the first and / or second prediction information of the serving and / or the neighbor cell(s), by transmitting to a network candidate node a CHO request when the first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell.

[0565] In one set of embodiments, the UE can be configured with an Event A3 upon reception of a reporting configuration (associated to a configured measurement object), including at least an A3 offset for a measurement quantity e.g. RSRP, RSRQ or SINR. The Event A3 may have as its entry condition the following: “neighbor cell measurement quantity offset better than PCell measurement quantity”.

[0566] When the Event A3 is fulfilled for at least one applicable cell X, which is a neighbor cell, (i.e. a neighbor cell with an A3 offset better than the PCell) for all measurements after layer 3 filtering taken during a Time To Trigger (e.g. configured timeToT rigger in the reporting configuration, denoted in Fig. 16 as a TTT) defined for this event, the UE transmits a Measurement Report message including one or more measurements, such as an RSRP value calculated based on SSB for the neighbor cell X. In other words, the measurements of cell X, in relation to measurements of the Pcell, triggers the UE to transmit the measurement report, as shown in Fig. 18.

[0567] Before transmitting the Measurement Report the UE can also include in the Measurement Report a first prediction information, comprising:

[0568] • One or more time-domain predictions of RSRP values of the neighbor cell X in one or more time instances f=1 , 2, ... , F, such as: pRSRP(f=1)=x1 , pRSRP(f=2)=x2, ... , pRSRP(f=F)=xF, denoted by the white stars in Figure 13. That could be considered as a first prediction information included in the first message.

[0569] • One or more time-domain predictions of RSRP values of the UE’s current Pcell in one or more time instances f=1 , 2, ... , F, such as: pRSRP(f=1)=y1 , pRSRP(f=2)=y2, ... , pRSRP(f=F)=yF, denoted by the white stars in Fig. 16. That could be considered as a second prediction information included in the first message.

[0570] The serving network node can receive the Measurement Report (e.g. MeasurementReport message) including the first prediction information, the second prediction and one or more measurements of the neighbor cell X and the PCell.

[0571] • (Source decision) In one option, based on the prediction information (and possibly the measurements), the serving network node is able to observe that the Event A3 condition will likely not remain fulfilled according to an A3 offset (e.g. configured as the UE as part of the CHO execution condition), which means that if the source network node would request that neighbor cell to a candidate network node, to be a CHO candidate cell, assuming the time-domain predictions are accurate, the UE would not execute CHO for that neighbor cell X. Hence, based on the prediction information, the source network node does not even send a CHO request to the candidate network node associated to the neighbor cell X (because the serving network node considers that cell X is not a good CHO candidate to configure the UE with). One example related to a source decision not to configure CHO for a neighbor cell reported in the first message is shown in Fig. 16: based on the predictions, the source network node observes that CHO execution would not be triggered.

[0572] • (Source decision) In another option (depicted in the signaling diagram of Fig. 18), based on the prediction information (and possibly the measurements), the serving network node is able to observe that the Event A3 condition will likely remain fulfilled according to an A3 offset (e.g. configured as the UE as part of the CHO execution condition), which means that if the source network node would request that neighbor cell to a candidate network node, to be a CHO candidate cell, assuming the timedomain predictions are accurate, the UE would likely execute CHO for that neighbor cell X. Hence, based on the prediction information, the source network sends a CHO request to the candidate network node associated to the neighbor cell X (because the serving network node considers that cell X is a good CHO candidate to configure the UE with. One example related to a source decision to configure CHO for a neighbor cell reported in the first message is shown in Fig. 17: based on the predictions, the source network node observes that CHO execution would be triggered.

[0573] • (Candidate decision) In another option (depicted in the signaling diagram of Fig. 19), the first prediction information (or part of the prediction information that is relevant to the neighbor cell for the CHO candidate configuration or, alternatively a postprocessed information based on the predicted information received from the UE) is used by the candidate network node to determine to accept or not a CHO request from the serving network node for configuring a UE with CHO having cell X as a CHO candidate cell. The serving network receives the Measurement Report including the PCell and cell X measurements and prediction information (e.g. predicted RSRP values in future time instances) and including at least part of the information in the Measurement Report (e.g. prediction information about cell X and / or the PCell) in the CHO request to the candidate network node, or include a post processed information based on the prediction information (e.g., top-K SSB index(es) of cell X with confidence level above a certain threshold during the prediction time duration between t+T and t+T+T2) in the CHO request to the candidate network node. For example, the CHO request may correspond to a HANDOVER REQUEST message including an indication that the request is for CHO (the IE Conditional Handover Information Request, including a CHO Trigger IE set to “CHO-initiation”), and a cell identifier of a candidate cell which is being requested, in this case, at least cell X. Based on the prediction information (e.g. first and second, about PCell and cell X), the candidate network node determines whether to accept or not the request for configuring CHO for cell X. Back to the example in Figs. 16 and 17, based on the prediction information (and possibly the measurements) of one of the neighbor cells, the candidate network node is able to observe that the Event A3 condition will likely not remain fulfilled according to an A3 offset (e.g. configured as the UE as part of the CHO execution condition), which means that if the candidate network node would accept the CHO request for cell X, assuming the time-domain predictions are accurate, CHO execution conditions would not be fulfilled forthat cell X, and the UE would not execute CHO forthat cell. Hence, based on the prediction information, the candidate network node does not even accept the request for configuring CHO for cell X neighbor.

[0574] • B) Triggering Early Data Forward (EDF) for a neighbor cell (of a candidate network node) which is configured (or it is to be configured at a UE as a CHO candidate cell). Triggering may comprise the source network node transmitting an EARLY STATUS TRANSFER message to the candidate network node of the neighbor cell and User Plane Data. o (neighbor cell is configured as CHO candidate and EDF triggered) In one option, EDF is triggered when the source network node receives a Measurement Reporting including first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell. o (neighbor cell is configured as CHO candidate, but EDF is not triggered) In one option, EDF is not triggered even when the source network node receives a Measurement Reporting including first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition is likely NOT going to be fulfilled after some time in the future for that neighbor cell. There might be other neighbor cells for which the likelihood for CHO execution is higher. o (EDF triggered when CHO is being configured) In one option, the first and / or second prediction information may be included in the Measurement Report which is received before the source network node transmits a CHO request for the candidate network node, so that based on the first and / or second prediction information the source network node determines to configure the neighbor cell as a CHO candidate cell and to trigger Early Data forwarding (EDF) for that cell I candidate network node when first and / or second prediction information of the serving and / or the neighbor cell(s) indicate that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell. o (EDF triggered after CHO has been configured) In one option, the source network node transmits a CHO request for the candidate network node, receives a CHO configuration including the CHO candidate cell configuration for a neighbor cell of the UE in response, and configures the UE with the CHO configuration including the CHO candidate cell configuration. At a later moment, the source network node receives from the UE a Measurement Report including first and / or second prediction information of the serving and / or the neighbor cell(s) which indicates that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell, so that in response to it, the source network node triggers EDF with the candidate network node of the neighbor cell which is configured as the CHO candidate cell. This option is illustrated in Fig. 20.

[0575] Notice that this can be used in combination with the other sets of embodiments in which the UE transmits the first message which is used as input for the source network node to determine to configure CHO, and after it has configured the UE with CHO, the UE transmits another first message including first and / or second prediction information for the PCell and / or the neighbor cell configured as a CHO candidate cell.

[0576] In one set of embodiments, the source network node can determine to trigger one or more actions based on the first prediction information and / or the second prediction information which has been received. The one or more actions may comprise the triggering of EDF for a subset of CHO candidate cell(s). The first prediction information and / or the second prediction information for the subset of CHO candidate cell(s) may indicate that that the CHO execution condition would likely be fulfilled after some time in the future for that neighbor cell.

[0577] • C) Configuring fast failure recovery. The source network node determines to configure a fast recovery (e.g. by including in a CHO configuration the ‘attemptCondReconfig’ field set to ‘true’) based on the first prediction information and / or the second prediction information which has been received. The first prediction information and / or the second prediction information for the subset of CHO candidate cell(s) indicate that that the CHO execution condition would likely not occur before a failure may occur e.g. Radio Link Failure, Handover Failure, CHO Failure. Upon a failure detection the would be able to UE initiate re-establishment, selects the neighbor cell and performs CHO execution (i.e. the UE applies the stored CHO candidate configuration of the at least one neighbor cell).

[0578] Fig. 21 shows an example of a communication system 2100 in accordance with some embodiments.

[0579] In the example, the communication system 2100 includes a telecommunication network 2102 that includes an access network 2104, such as a radio access network (RAN), and a core network 2106, which includes one or more core network nodes 2108. The access network 2104 includes one or more access network nodes, such as access network nodes 2110a and 2110b (which are interchangeably referred to as RAN network nodes 2110 herein), or any other similar 3rdGeneration Partnership Project (3GPP) access node or non-3GPP access point (AP). Moreover, as will be appreciated by those of skill in the art, a RAN network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network 2102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 2102 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network 2102, including one or more network nodes 2110 and / or core network nodes 2108.

[0580] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O- CU user plane (O-CU-UP), a RAN intelligent controller (RIC) (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1 , F1 , W1 , E1 , E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies.

[0581] The access network nodes 2110 facilitate direct or indirect connection of wireless devices (also referred to interchangeably herein as user equipment (UE)), such as by connecting UEs 2112a, 2112b, 2112c, and 2112d (one or more of which may be generally referred to as UEs 2112) to the core network 2106 over one or more wireless connections. The access network nodes 2110 may be, for example, access points (APs) (e.g. radio access points), base stations (BSs) (e.g. radio base stations, Node Bs, evolved Node Bs (eNBs) and New Radio (NR) NodeBs (gNBs)).

[0582] Unless otherwise indicated, the general term ‘network node’ as used herein refers to access network nodes 2110 and core network nodes 2108.

[0583] Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 2100 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system 2100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0584] The wireless devices / UEs 2112 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes 2110 and other communication devices. Similarly, the access network nodes 2110 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 2112 and / or with other network nodes or equipment in the telecommunication network 2102 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network 2102.

[0585] In the depicted example, the core network 2106 connects the access network nodes 2110 to one or more hosts, such as host 2116. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 2106 includes one more core network nodes (e.g. core network node 2108) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the wireless devices / UEs, access network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 2108. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (ALISF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0586] The host 2116 may be under the ownership or control of a service provider other than an operator or provider of the access network 2104 and / or the telecommunication network 2102, and may be operated by the service provider or on behalf of the service provider. The host 2116 may host a variety of applications to provide one or more services. Examples of such applications include the provision of live and / or pre-recorded audio / video content, data collection services, for example, retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0587] As a whole, the communication system 2100 of Fig. 21 enables connectivity between the wireless devices / UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2ndGeneration (2G), 3rdGeneration (3G), 4thGeneration (4G), 5thGeneration (5G) standards, or any applicable future generation standard (e.g. 6thGeneration (6G)); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox.

[0588] In some examples, the telecommunication network 2102 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 2102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 2102. For example, the telecommunications network 2102 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and / or Massive Machine Type Communication (mMTC) / Massive Internet of Things (loT) services to yet further UEs.

[0589] In some examples, the UEs 2112 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 2104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 2104. Additionally, a UE may be configured for operating in single- or multi-radio access technology (RAT) or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved- UTRA (UMTS Terrestrial Radio Access) Network) New Radio - Dual Connectivity (EN-DC).

[0590] In the example illustrated in Fig. 21 , the hub 2114 communicates with the access network 2104 to facilitate indirect communication between one or more UEs (e.g. UE 2112c and / or 2112d) and access network nodes (e.g. access network node 2110b). In some examples, the hub 2114 may be a controller, router, a content source and analytics node, or any of the other communication devices described herein regarding UEs. For example, the hub 2114 may be a broadband router enabling access to the core network 2106 for the UEs. As another example, the hub 2114 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 2110, or by executable code, script, process, or other instructions in the hub 2114. As another example, the hub 2114 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 2114 may be a content source. For example, for a UE that is a Virtual Reality VR headset, display, loudspeaker or other media delivery device, the hub 2114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 2114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 2114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy Internet of Things (loT) devices.

[0591] The hub 2114 may have a constant / persistent or intermittent connection to the network node 2110b. The hub 2114 may also allow for a different communication scheme and / or schedule between the hub 2114 and UEs (e.g. UE 2112c and / or 2112d), and between the hub 2114 and the core network 2106. In other examples, the hub 2114 is connected to the core network 2106 and / or one or more UEs via a wired connection. Moreover, the hub 2114 may be configured to connect to a Machine-to-Machine (M2M) service provider over the access network 2104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 2110 while still connected via the hub 2114 via a wired or wireless connection. In some embodiments, the hub 2114 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node 2110b. In other embodiments, the hub 2114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 2110b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0592] Fig. 22 shows a wireless device or UE 2200 in accordance with some embodiments.

[0593] As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a wireless device / UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless camera, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0594] A wireless device / UE may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to- everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g. a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g. a smart power meter).

[0595] The UE 2200 includes processing circuitry 2202 that is operatively coupled via a bus 2204 to an input / output interface 2206, a power source 2208, a memory 2210, a communication interface 2212, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Fig. 22. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc. The processing circuitry 2202 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 2210. The processing circuitry 2202 may be implemented as one or more hardware-implemented state machines (e.g. in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 2202 may include multiple central processing units (CPUs). The processing circuitry 2202 may be operable to provide, either alone or in conjunction with other UE 2200 components, such as the memory 2210, to provide UE 2200 functionality. For example, the processing circuitry 2202 may be configured to cause the UE 2202 to perform the methods as described with reference to Fig. W1.

[0596] In the example, the input / output interface 2206 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 2200. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g. a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0597] In some embodiments, the power source 2208 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g. an electricity outlet), photovoltaic device, or power cell, may be used. The power source 2208 may further include power circuitry for delivering power from the power source 2208 itself, and / or an external power source, to the various parts of the UE 2200 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 2208. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 2208 to make the power suitable for the respective components of the UE 2200 to which power is supplied.

[0598] The memory 2210 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 2210 includes one or more application programs 2214, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 2216. The memory 2210 may store, for use by the UE 2200, any of a variety of various operating systems or combinations of operating systems.

[0599] The memory 2210 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a Universal Subscriber Identity Module (USIM) and / or integrated SIM (ISIM), other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUlCC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 2210 may allow the UE 2200 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to offload data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 2210, which may be or comprise a device- readable storage medium.

[0600] The processing circuitry 2202 may be configured to communicate with an access network or other network using the communication interface 2212. The communication interface 2212 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 2222. The communication interface 2212 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g. another UE or a network node in an access network). Each transceiver may include a transmitter 2218 and / or a receiver 2220 appropriate to provide network communications (e.g. optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 2218 and receiver 2220 may be coupled to one or more antennas (e.g. antenna 2222) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0601] In some embodiments, communication functions of the communication interface 2212 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) or other Global Navigation Satellite System (GNSS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and / or standards, such as IEEE 802.11 , Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, NR, UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0602] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 2212, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g. once every 15 minutes if it reports the sensed temperature), random (e.g. to even out the load from reporting from several sensors), in response to a triggering event (e.g. when moisture is detected an alert is sent), in response to a request (e.g. a user initiated request), or a continuous stream (e.g. a live video feed of a patient).

[0603] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or controls a robotic arm performing a medical procedure according to the received input.

[0604] A UE, when in the form of an loT device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are devices which are or which are embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or VR, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence on the intended application of the loT device in addition to other components as described in relation to the UE 2200 shown in Fig. 22.

[0605] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-loT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0606] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0607] Fig. 23 shows an access network node 2300 or RAN network node 2300 in accordance with some embodiments.

[0608] As used herein, access network node or RAN network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other RAN network nodes or equipment or core network nodes, in a telecommunication network. Examples of access network nodes include, but are not limited to, access network nodes such as APs (e.g. radio access points), base stations (BSs) (e.g. radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), Open RAN (O-RAN) nodes or components of an O- RAN node (e.g., O-RU, O-DU, O-CU)..

[0609] Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A RAN network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node), and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0610] Other examples of access network nodes include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g. Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0611] The RAN network node 2300 includes processing circuitry 2302, a memory 2304, a communication interface 2306, and a power source 2308, and / or any other component, or any combination thereof. The RAN network node 2300 may be composed of multiple physically separate components (e.g. a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the RAN network node 2300 comprises multiple separate components (e.g. BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the RAN network node 2300 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g. separate memory 2304 for different RATs) and some components may be reused (e.g. a same antenna 2310 may be shared by different RATs). The RAN network node 2300 may also include multiple sets of the various illustrated components for different wireless technologies integrated into RAN network node 2300, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within RAN network node 2300.

[0612] The processing circuitry 2302 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other RAN network node 2300 components, such as the memory 2304, to provide network node 2300 functionality. For example, the processing circuitry 2302 may be configured to cause the RAN network node to perform the methods as described with reference to Figs. W2a and VV2b.

[0613] In some embodiments, the processing circuitry 2302 includes a system on a chip (SOC). In some embodiments, the processing circuitry 2302 includes one or more of radio frequency (RF) transceiver circuitry 2312 and baseband processing circuitry 2314. In some embodiments, the radio frequency (RF) transceiver circuitry 2312 and the baseband processing circuitry 2314 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry 2312 and baseband processing circuitry 2314 may be on the same chip or set of chips, boards, or units.

[0614] The memory 2304 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 2302. The memory 2304 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry 2302 and utilized by the RAN network node 2300. The memory 2304 may be used to store any calculations made by the processing circuitry 2302 and / or any data received via the communication interface 2306. In some embodiments, the processing circuitry 2302 and memory 2304 is integrated.

[0615] The communication interface 2306 is used in wired or wireless communication of signalling and / or data between network nodes, the access network, the core network, and / or a UE. As illustrated, the communication interface 2306 comprises port(s) / terminal(s) 2316 to send and receive data, for example to and from a network over a wired connection.

[0616] The communication interface 2306 also includes radio front-end circuitry 2318 that may be coupled to, or in certain embodiments a part of, the antenna 2310. Radio front-end circuitry 2318 comprises filters 2320 and amplifiers 2322. The radio front-end circuitry 2318 may be connected to an antenna 2310 and processing circuitry 2302. The radio front-end circuitry may be configured to condition signals communicated between antenna 2310 and processing circuitry 2302. The radio front-end circuitry 2318 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 2318 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 2320 and / or amplifiers 2322. The radio signal may then be transmitted via the antenna 2310. Similarly, when receiving data, the antenna 2310 may collect radio signals which are then converted into digital data by the radio front-end circuitry 2318. The digital data may be passed to the processing circuitry 2302. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0617] In certain alternative embodiments, the access network node 2300 does not include separate radio front-end circuitry 2318, instead, the processing circuitry 2302 includes radio frontend circuitry and is connected to the antenna 2310. Similarly, in some embodiments, all or some of the RF transceiver circuitry 2312 is part of the communication interface 2306. In still other embodiments, the communication interface 2306 includes one or more ports or terminals 2316, the radio front-end circuitry 2318, and the RF transceiver circuitry 2312, as part of a radio unit (not shown), and the communication interface 2306 communicates with the baseband processing circuitry 2314, which is part of a digital unit (not shown).

[0618] The antenna 2310 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 2310 may be coupled to the radio front-end circuitry 2318 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 2310 is separate from the network node 2300 and connectable to the RAN network node 2300 through an interface or port.

[0619] The antenna 2310, communication interface 2306, and / or the processing circuitry 2302 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 2310, the communication interface 2306, and / or the processing circuitry 2302 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0620] The power source 2308 provides power to the various components of RAN network node 2300 in a form suitable for the respective components (e.g. at a voltage and current level needed for each respective component). The power source 2308 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 2300 with power for performing the functionality described herein. For example, the RAN network node 2300 may be connectable to an external power source (e.g. the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 2308. As a further example, the power source 2308 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0621] Embodiments of the RAN network node 2300 may include additional components beyond those shown in Fig. 23 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the RAN network node 2300 may include user interface equipment to allow input of information into the RAN network node 2300 and to allow output of information from the RAN network node 2300. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the RAN network node 2300.

[0622] Fig. 24 is a block diagram illustrating a virtualization environment 2400 in which functions implemented by some embodiments may be virtualized.

[0623] In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 2400 hosted by one or more of hardware nodes, such as a hardware computing device that operates as an access network node, a wireless device / UE, a core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g. a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 2400 includes components defined by the Open-RAN (O-RAN) Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface.

[0624] Applications 2402 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 2400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0625] Hardware 2404 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 2406 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 2408a and 2408b (one or more of which may be generally referred to as VMs 2408), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 2406 may present a virtual operating platform that appears like networking hardware to the VMs 2408.

[0626] The VMs 2408 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 2406. Different embodiments of the instance of a virtual appliance 2402 may be implemented on one or more of VMs 2408, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0627] In the context of NFV, a VM 2408 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 2408, and that part of hardware 2404 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 2408 on top of the hardware 2404 and corresponds to the application 2402.

[0628] Hardware 2404 may be implemented in a standalone network node with generic or specific components. Hardware 2404 may implement some functions via virtualization. Alternatively, hardware 2404 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 2410, which, among others, oversees lifecycle management of applications 2402. In some embodiments, hardware 2404 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signalling can be provided with the use of a control system 2412 which may alternatively be used for communication between hardware nodes and radio units.

[0629] Although the computing devices described herein (e.g. UEs, RAN network nodes, core network node, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0630] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device- readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

[0631] The foregoing merely illustrates the principles of the disclosure. Various modifications and alterations to the described embodiments will be apparent to those skilled in the art in view of the teachings herein. It will thus be appreciated that those skilled in the art will be able to devise numerous systems, arrangements, and procedures that, although not explicitly shown or described herein, embody the principles of the disclosure and can be thus within the scope of the disclosure. Various exemplary embodiments can be used together with one another, as well as interchangeably therewith, as should be understood by those having ordinary skill in the art. The following numbered statements set out various optional embodiments for this disclosure:

[0632] Group A Embodiments (UE)

[0633] 1. A method performed by a user equipment, UE, being served by a first cell of a source network node, the method comprising: transmitting (W102), to the source network node, a first message comprising time-domain prediction information for a second cell.

[0634] 2. The method of embodiment 1 , wherein the time-domain prediction information is relevant to conditional handover of the UE to the second cell.

[0635] 3. The method of embodiment 1 or 2, wherein the time-domain prediction information for the second cell comprises an indication of a likelihood of a conditional handover of the UE to the second cell.

[0636] 4. The method of any previous embodiment, wherein the time-domain prediction information for the second cell is based on, or comprises, at least one prediction of a measurement of the second cell.

[0637] 5. The method of any previous embodiment, wherein the time-domain prediction information for the second cell comprises one or more of: a predicted signal strength or quality value for the second cell at a future time instance; a predicted cell identifier for the second cell at a future time instance; a cell identifier based on a predicted signal strength or quality value for the second cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the second cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the second cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the second cell at a future time instance; a predicted beam index and / or beam identifier of the second cell at a future time instance; a Synchronization Signal Block, SSB, index of the second cell at a future time instance; a corresponding confidence indicator of a predicted value for the second cell; a corresponding time duration for which a predicted value for the second cell is expected to be valid; and a corresponding time duration for which a predicted value for the second cell is expected to satisfy a condition.

[0638] 6. The method of any of embodiments 4-5, wherein the time-domain prediction information for the second cell is based on a prediction for fulfilment of an event trigger for the second cell.

[0639] 7. The method of embodiment 6, wherein the event trigger comprises an event or condition that triggers transmission by the UE of measurements of the second cell, and / or an event or condition that triggers conditional handover of the UE to the second cell.

[0640] 8. The method of embodiment 6 or 7, wherein the time-domain prediction information for the second cell comprises one or more of: a flag indicating that the event trigger is predicted to remain fulfilled; an indication of a period of time for which the event trigger is predicted to remain fulfilled; and a cell identifier of the second cell as the cell which triggered the event.

[0641] 9. The method of any preceding embodiment, wherein the time-domain prediction information for the second cell is further based on at least one prediction of a measurement of the first cell.

[0642] 10. The method of any preceding embodiment, wherein the time-domain prediction information for the second cell is based on a difference between a prediction of a measurement of the second cell and a prediction of a measurement of the first cell.

[0643] 11 . The method of any preceding embodiment, wherein the time-domain prediction information for the second cell comprises one or more of: a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a cell identifier based on a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a cell identifier based on a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a corresponding confidence indicator for the predicted difference; a corresponding confidence indicator for the cell identifier; a corresponding time duration for which the predicted difference is expected to be valid; a corresponding time duration for which the cell identifier is expected to be valid; and a corresponding time duration for which the predicted difference is expected to satisfy a condition.

[0644] 12. The method of any preceding embodiment, wherein the first message is a Radio Resource Control, RRC, measurement report message.

[0645] 13. The method of any preceding embodiment, wherein the method further comprises: receiving, from the source network node, a conditional handover candidate configuration for the second cell.

[0646] 14. The method of embodiment 13, wherein the conditional handover candidate configuration for the second cell is received after transmitting the first message.

[0647] 15. The method of embodiment 13, wherein the conditional handover candidate configuration for the second cell is received prior to transmitting the first message.

[0648] 16. The method of embodiment 15, wherein the method further comprises: evaluating a conditional handover execution condition associated with the second cell.

[0649] 17. The method of embodiment 16, wherein the method further comprises: responsive to determining that the conditional handover execution condition associated with the second cell is satisfied, executing conditional handover to the second cell.

[0650] 18. The method of any preceding embodiment, wherein the second cell is one of: the first cell, another cell of the source network node, and a cell of a second network node. 19. The method of any preceding embodiment, wherein the method further comprises: prior to transmitting the first message, receiving an indication of a property of the timedomain prediction information that the UE can transmit in the first message.

[0651] 20. The method of embodiment 19, wherein the indication is received from the source network node.

[0652] 21. The method of embodiment 19 or 20, wherein the property of the time-domain prediction information is a quantity of the time-domain prediction information that the UE can transmit in the first message.

[0653] 22. The method of embodiment 21, wherein the quantity of the time-domain prediction information comprises one or more of: a number of cells, a number of predicted Synchronization Signal Blocks, and a number of Channel State Information Reference Signals.

[0654] 23. The method of any preceding embodiment, wherein the first message further comprises time-domain prediction information for a third cell, wherein the third cell is one of: the first cell, another cell of the source network node, and a cell of a third network node.

[0655] 24. The method of embodiment 23, wherein the time-domain prediction information for the third cell comprises one or more of: a predicted signal strength or quality value for the third cell at a future time instance; a predicted cell identifier for the third cell at a future time instance; a cell identifier for the third cell based on a predicted signal strength or quality value for the third cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the third cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the third cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the third cell at a future time instance; a predicted beam index and / or beam identifier of the third cell at a future time instance; a Synchronization Signal Block, SSB, index of the third cell at a future time instance; a corresponding confidence indicator of a predicted value for the third cell; a corresponding time duration for which a predicted value for the third cell is expected to be valid; and a corresponding time duration for which a predicted value for the third cell is expected to satisfy a condition.

[0656] 25. The method of any preceding embodiment, wherein the first message is transmitted responsive to one or more measurements.

[0657] 26. The method of embodiment 25, wherein the one or more measurements indicate that an event trigger is fulfilled for the second cell, wherein the event trigger comprises an event or condition.

[0658] 27. The method of embodiment 27, wherein the event trigger is an Event A3 for the second cell and / or an Event A4 for the second cell.

[0659] 28. The method of any preceding embodiment, wherein the first message is transmitted according to one or more parameters which the UE received, prior to transmitting the first message, in a measurement configuration and / or a prediction configuration.

[0660] Group B Embodiments (source network node)

[0661] 29. A method performed by a source network node, wherein a user equipment, UE, is being served by a first cell of the source network node, the method comprising: receiving (VV202), from the UE, a first message comprising time-domain prediction information for a second cell.

[0662] 30. The method of embodiment 29, wherein the time-domain prediction information is relevant to conditional handover of the UE to the second cell.

[0663] 31. The method of embodiment 29 or 30, wherein the time-domain prediction information for the second cell comprises an indication of a likelihood of a conditional handover of the UE to the second cell.

[0664] 32. The method of any of embodiments 29-31 , wherein the time-domain prediction information for the second cell is based on, or comprises, at least one time-domain prediction of a measurement of the second cell. 33. The method of any of embodiments 29-32, wherein the time-domain prediction information for the second cell comprises one or more of: a predicted signal strength or quality value for the second cell at a future time instance; a predicted cell identifier for the second cell at a future time instance; a cell identifier based on a predicted signal strength or quality value for the second cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the second cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the second cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the second cell at a future time instance; a predicted beam index and / or beam identifier of the second cell at a future time instance; a Synchronization Signal Block, SSB, index of the second cell at a future time instance; a corresponding confidence indicator of a predicted value for the second cell; a corresponding time duration for which a predicted value for the second cell is expected to be valid; and a corresponding time duration for which a predicted value for the second cell is expected to satisfy a condition.

[0665] 34. The method of any of embodiments 29-33, wherein the time-domain prediction information for the second cell is based on a prediction for fulfilment of an event trigger for the second cell.

[0666] 35. The method of embodiment 34, wherein the event trigger comprises an event or condition that triggers transmission by the UE of measurements of the second cell, and / or an event or condition that triggers conditional handover of the UE to the second cell.

[0667] 36. The method of embodiment 34 or 35 wherein the time-domain prediction information for the second cell comprises one or more of: a flag indicating that the event trigger is predicted to remain fulfilled; an indication of a period of time for which the event trigger is predicted to remain fulfilled; and a cell identifier of the second cell as the cell which triggered the event. 37. The method of any of embodiments 29-36, wherein the time-domain prediction information for the second cell is further based on at least one time-domain prediction of a measurement of the first cell.

[0668] 38. The method of any of embodiments 29-37, wherein the time-domain prediction information for the second cell is based on a difference between a prediction of a measurement of the second cell and a prediction of a measurement of the first cell.

[0669] 39. The method of any of embodiments 29-38, wherein the time-domain prediction information for the second cell comprises one or more of: a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a cell identifier based on a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a cell identifier based on a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a corresponding confidence indicator for the predicted difference; a corresponding confidence indicator for the cell identifier; a corresponding time duration for which the predicted difference is expected to be valid; a corresponding time duration for which the cell identifier is expected to be valid; and a corresponding time duration for which the predicted difference is expected to satisfy a condition.

[0670] 40. The method of any of embodiments 29-39, wherein the first message is a Radio Resource Control, RRC, measurement report message.

[0671] 41 . The method of any of embodiments 29-40, wherein the method further comprises: based on the time-domain prediction information for the second cell, configuring the UE with the second cell as a conditional handover candidate cell. 42. The method of embodiment 41 , wherein configuring the UE comprises: determining, based on the time-domain prediction information for the second cell, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE; and responsive to the determined likelihood indication satisfying a criterion, configuring the UE with the second cell as a conditional handover candidate cell.

[0672] 43. The method of embodiment 41 or 42, wherein configuring the UE with the second cell as a conditional handover candidate cell comprises: transmitting, to the UE, a conditional handover candidate configuration for the second cell and a conditional handover execution condition for the second cell.

[0673] 44. The method of any of embodiments 29-43, wherein the method further comprises: based on the time-domain prediction information for the second cell, triggering Early Data Forwarding, EDF, for the second cell.

[0674] 45. The method of any of embodiments 29-44, wherein the method further comprises: based on the time-domain prediction information for the second cell, configuring fast failure recovery.

[0675] 46. The method of embodiment 45, wherein configuring fast failure recovery comprises determining to include in a conditional handover configuration for the second cell a ‘attemptCondReconfig’ field set to ‘true’.

[0676] 47. The method of any of embodiments 29-46, wherein the second cell is a cell of a second network node, and wherein the method further comprises: after receiving the first message, transmitting, to the second network node, a conditional handover request for configuring a conditional handover for the second cell.

[0677] 48. The method of embodiment 47, wherein the conditional handover request further comprises the time-domain prediction information for the second cell or information derived therefrom.

[0678] 49. The method of embodiment 48, wherein the derived information is one of: part of the timedomain prediction information for the second cell received from the UE; and post-processed information based on the time-domain prediction information for the second cell received from the UE.

[0679] 50. The method of any of embodiments 47-49, wherein the method further comprises: after transmitting the conditional handover request, receiving, from the second network node, a conditional handover candidate configuration for the second cell.

[0680] 51 . The method of any of embodiments 29-50, wherein the second cell is one of: the first cell, another cell of the source network node, and a cell of a second network node.

[0681] 52. The method of any of embodiments 29-51 , wherein the method further comprises: prior to receiving the first message, transmitting, to the UE, an indication of a property of the time-domain prediction information that the UE can transmit in the first message.

[0682] 53. The method of embodiment 52, wherein the property of the prediction information is a quantity of the time-domain prediction information that the UE can transmit in the first message.

[0683] 54. The method of embodiment 53, wherein the quantity of the time-domain prediction information comprises one or more of: a number of cells, a number of predicted Synchronization Signal Blocks, and a number of Channel State Information Reference Signals.

[0684] 55. The method of any of embodiments 29-54, wherein the first message further comprises time-domain prediction information for a third cell, wherein the third cell is one of: the first cell, another cell of the source network node, and a cell of a third network node.

[0685] 56. The method of embodiment 55, wherein the time-domain prediction information for the third cell comprises one or more of: a predicted signal strength or quality value for the third cell at a future time instance; a predicted cell identifier for the third cell at a future time instance; a cell identifier for the third cell based on a predicted signal strength or quality value for the third cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the third cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the third cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the third cell at a future time instance; a predicted beam index and / or beam identifier of the third cell at a future time instance; a Synchronization Signal Block, SSB, index of the third cell at a future time instance; a corresponding confidence indicator of a predicted value for the third cell; a corresponding time duration for which a predicted value for the third cell is expected to be valid; and a corresponding time duration for which a predicted value for the third cell is expected to satisfy a condition.

[0686] Group B Embodiments continued (second network node = candidate)

[0687] 57. A method performed by a second network node, wherein a user equipment, UE, is being served by a first cell of a source network node, the method comprising: receiving (VV204), from the source network node, a conditional handover request for configuring a conditional handover for a second cell, wherein the second cell is a cell of a second network node, and the conditional handover request comprises time-domain prediction information for the second cell or information derived therefrom.

[0688] 58. The method of embodiment 57, wherein the derived information is one of: part of the timedomain prediction information for the second cell; and post-processed information based on the time-domain prediction information for the second cell.

[0689] 59. The method of embodiment 57 or 58, wherein the time-domain prediction information is relevant to conditional handover of the UE to the second cell.

[0690] 60. The method of any of embodiments 57-59, wherein the time-domain prediction information for the second cell comprises an indication of a likelihood of a conditional handover of the UE to the second cell.

[0691] 61 . The method of any of embodiments 57-60, wherein the time-domain prediction information for the second cell is based on, or comprises, at least one prediction of a measurement of the second cell.

[0692] 62. The method of any of embodiments 57-61 , wherein the time-domain prediction information for the second cell comprises one or more of: a predicted signal strength or quality value for the second cell at a future time instance; a predicted cell identifier for the second cell at a future time instance; a cell identifier based on a predicted signal strength or quality value for the second cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the second cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the second cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the second cell at a future time instance; a predicted beam index and / or beam identifier of the second cell at a future time instance; a Synchronization Signal Block, SSB, index of the second cell at a future time instance; a corresponding confidence indicator of a predicted value for the second cell; a corresponding time duration for which a predicted value for the second cell is expected to be valid; and a corresponding time duration for which a predicted value for the second cell is expected to satisfy a condition.

[0693] 63. The method of any of embodiments 57-62, wherein the time-domain prediction information for the second cell is based on a prediction for fulfilment of an event trigger for the second cell.

[0694] 64. The method of embodiment 63, wherein the event trigger comprises an event or condition that triggers transmission by the UE of measurements of the second cell, and / or an event or condition that triggers conditional handover of the UE to the second cell.

[0695] 65. The method of embodiment 63 or 64 wherein the time-domain prediction information for the second cell comprises one or more of: a flag indicating that the event trigger is predicted to remain fulfilled; an indication of a period of time for which the event trigger is predicted to remain fulfilled; and a cell identifier of the second cell as the cell which triggered the event.

[0696] 66. The method of any of embodiments 57-65, wherein the time-domain prediction information for the second cell is further based on at least one time-domain prediction of a measurement of the first cell. 67. The method of any of embodiments 57-66, wherein the time-domain prediction information for the second cell is based on a difference between a prediction of a measurement of the second cell and a prediction of a measurement of the first cell.

[0697] 68. The method of any of embodiments 57-67, wherein the time-domain prediction information for the second cell comprises one or more of: a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a cell identifier based on a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a cell identifier based on a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a corresponding confidence indicator for the predicted difference; a corresponding confidence indicator for the cell identifier; a corresponding time duration for which the predicted difference is expected to be valid; a corresponding time duration for which the cell identifier is expected to be valid; and a corresponding time duration for which the predicted difference is expected to satisfy a condition.

[0698] 69. The method of any of embodiments 57-68, wherein the time-domain prediction information for the second cell or information derived therefrom that is comprised in the conditional handover request further comprises time-domain prediction information for a third cell or information derived therefrom, wherein the third cell is one of: the first cell, and another cell of the source network node.

[0699] 70. The method of embodiment 69, wherein the time-domain prediction information for the third cell comprises one or more of: a predicted signal strength or quality value for the third cell at a future time instance; a predicted cell identifier for the third cell at a future time instance; a cell identifier for the third cell based on a predicted signal strength or quality value for the third cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the third cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the third cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the third cell at a future time instance; a predicted beam index and / or beam identifier of the third cell at a future time instance; a Synchronization Signal Block, SSB, index of the third cell at a future time instance; a corresponding confidence indicator of a predicted value for the third cell; a corresponding time duration for which a predicted value for the third cell is expected to be valid; and a corresponding time duration for which a predicted value for the third cell is expected to satisfy a condition.

[0700] 71 . The method of any of embodiments 57-70, wherein the method further comprises: based on the prediction information, determining whether to accept or reject the conditional handover request for configuring the conditional handover for the second cell.

[0701] 72. The method of embodiment 71 , wherein determining whether to accept or reject the conditional handover request comprises: determining, based on the time-domain prediction information for the second cell or information derived therefrom, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE; and responsive to the determined likelihood indication satisfying a criterion, accepting the conditional handover request for configuring the conditional handover for the second cell; and responsive to the determined likelihood indication failing to satisfy the criterion, rejecting the conditional handover request for configuring the conditional handover for the second cell.

[0702] 73. The method of embodiment 71 or 72, wherein accepting the conditional handover request comprises: transmitting, to the source network node, a handover request acknowledge message.

[0703] 74. The method of any of embodiments 57-73, wherein the method further comprises: based on the time-domain prediction information for the second cell or information derived therefrom, configuring Contention-Free Random-Access resources per beam for the second cell, wherein the second cell is a conditional handover candidate for the UE.

[0704] Group C Embodiments

[0705] 75. A computer program product comprising a computer readable medium having computer readable code embodied therein, the computer readable code being configured such that, on execution by a suitable computer or processor, the computer or processor is caused to perform the method of any of the Group A embodiments or the Group B embodiments.

[0706] 76. A user equipment, UE, configured to perform the method of any of the Group A embodiments.

[0707] 77. A user equipment, UE, comprising a processor and a memory, said memory containing instructions executable by said processor whereby said UE is operative to perform the method of any of the Group A embodiments.

[0708] 78. A first radio access network, RAN, node, configured to perform the method of any of the Group B embodiments.

[0709] 79. A first radio access network, RAN, node comprising a processor and a memory, said memory containing instructions executable by said processor whereby said first RAN node is operative to perform the method of any of the Group B embodiments.

[0710] 80. A user equipment, UE, comprising: processing circuitry configured to cause the user equipment to perform any of the steps of any of the Group A embodiments; and power supply circuitry configured to supply power to the processing circuitry.

[0711] 81. A network node, the network node comprising: processing circuitry configured to cause the network node to perform any of the steps of any of the Group B embodiments; power supply circuitry configured to supply power to the processing circuitry.

[0712] 82. A user equipment, UE, the UE comprising: an antenna configured to send and receive wireless signals; radio front-end circuitry connected to the antenna and to processing circuitry, and configured to condition signals communicated between the antenna and the processing circuitry; the processing circuitry being configured to perform any of the steps of any of the Group A embodiments; an input interface connected to the processing circuitry and configured to allow input of information into the UE to be processed by the processing circuitry; an output interface connected to the processing circuitry and configured to output information from the UE that has been processed by the processing circuitry; and a battery connected to the processing circuitry and configured to supply power to the UE.

Claims

Claims1. A method performed by a user equipment, UE, being served by a first cell of a source network node, the method comprising: transmitting (602), to the source network node, a first message comprising time-domain prediction information for a second cell; receiving, from the source network node, a conditional handover, CHO, configuration comprising a CHO execution condition and a CHO candidate configuration for the second cell; and evaluating the CHO execution condition associated with the second cell.

2. The method of claim 1 , wherein the time-domain prediction information for the second cell comprises an indication of a likelihood of a conditional handover of the UE to the second cell.

3. The method of any of claim 1 or 2, wherein the time-domain prediction information for the second cell is based on, or comprises, at least one prediction of a measurement of the first cell and / or at least one prediction of a measurement of the second cell.

4. The method of any of claims 1-3, wherein the time-domain prediction information for the second cell comprises one or more of: a predicted signal strength or quality value for the second cell at a future time instance; a predicted cell identifier for the second cell at a future time instance; a cell identifier based on a predicted signal strength or quality value for the second cell at a future time instance; a predicted Reference Signal Received Power, RSRP, of the second cell at a future time instance; a predicted Reference Signal Received Quality, RSRQ, of the second cell at a future time instance; a predicted Signal to Interference plus Noise Ratio, SINR, of the second cell at a future time instance; a predicted beam index and / or beam identifier of the second cell at a future time instance; a Synchronization Signal Block, SSB, index of the second cell at a future time instance; a corresponding confidence indicator of a predicted value for the second cell; a corresponding time duration for which a predicted value for the second cell is expected to be valid; anda corresponding time duration for which a predicted value for the second cell is expected to satisfy a condition.

5. The method of any of claims 3 or 4 wherein the time-domain prediction information for the second cell is based on a prediction for fulfilment of an event trigger for the second cell.

6. The method of claim 5, wherein the event trigger comprises an event or condition that triggers transmission by the UE of measurements of the second cell, and / or an event or condition that triggers conditional handover of the UE to the second cell.

7. The method of claim 5 or 6, wherein the time-domain prediction information for the second cell comprises one or more of: a flag indicating that the event trigger is predicted to remain fulfilled; an indication of a period of time for which the event trigger is predicted to remain fulfilled; and a cell identifier of the second cell as the cell which triggered the event.

8. The method of any of claims 1-7, wherein the time-domain prediction information for the second cell is based on a difference between a prediction of a measurement of the second cell and a prediction of a measurement of the first cell.

9. The method of any of claims 1-8, wherein the time-domain prediction information for the second cell comprises one or more of: a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a cell identifier based on a difference between a predicted signal strength or quality value for the second cell at a future time instance and a predicted signal strength or quality value for the first cell at the future time instance; a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a cell identifier based on a predicted measurement quantity difference between the measurement quantity of the second cell and the measurement quantity of the first cell at a future time instance; a corresponding confidence indicator for the predicted difference;a corresponding confidence indicator for the cell identifier; a corresponding time duration for which the predicted difference is expected to be valid; a corresponding time duration for which the cell identifier is expected to be valid; and a corresponding time duration for which the predicted difference is expected to satisfy a condition.

10. The method of any of claims 1-9, wherein the first message is a Radio Resource Control, RRC, measurement report message.11 . The method of any of claims 1-10, wherein the CHO candidate configuration for the second cell is received after transmitting the first message.

12. The method of any of claims 1-11 , wherein the CHO candidate configuration for the second cell is received, and the CHO execution condition evaluated, prior to transmitting the first message.

13. The method of any of claims 1-12, wherein the method further comprises: responsive to determining that the conditional handover execution condition associated with the second cell is satisfied, executing conditional handover to the second cell.

14. The method as claimed in claim 13, wherein the method is for assisting the triggering of Early Data Forwarding, EDF, and data continuity at the UE upon CHO execution.

15. The method of any of claims 1-14, wherein the second cell is one of: the first cell, another cell of the source network node, and a cell of a second network node.

16. The method of any of claims 1-15, wherein the method further comprises: prior to transmitting the first message, receiving an indication of a property of the timedomain prediction information that the UE can transmit in the first message.

17. The method of claim 16, wherein the indication is received from the source network node.

18. The method of claim 16 or 17, wherein the property of the time-domain prediction information is a quantity of the time-domain prediction information that the UE can transmit in the first message.

19. The method of claim 18, wherein the quantity of the time-domain prediction information comprises one or more of: a number of cells, a number of predicted Synchronization Signal Blocks, and a number of Channel State Information Reference Signals.

20. The method of any of claims 1-19, wherein the first message further comprises time-domain prediction information for a third cell, wherein the third cell is one of: the first cell, another cell of the source network node, and a cell of a third network node.

21. The method of any of claims 1-20, wherein the first message is transmitted according to one or more parameters which the UE received, prior to transmitting the first message, in a measurement configuration and / or a prediction configuration.

22. A method performed by a source network node, wherein a user equipment, UE, is being served by a first cell of the source network node, the method comprising: receiving (702), from the UE, a first message comprising time-domain prediction information for a second cell; and transmitting, to the UE, a conditional handover, CHO, configuration comprising a CHO candidate configuration for the second cell and a CHO execution condition for the second cell.

23. The method of claim 22, wherein the CHO configuration is based on the time-domain prediction information for the second cell.

24. The method of claim 23, wherein the method further comprises: determining, based on the time-domain prediction information for the second cell, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE; and wherein transmitting the CHO configuration to the UE is responsive to the determined likelihood indication satisfying a criterion.

25. The method of any of claims 22-24, wherein the method further comprises: based on the time-domain prediction information for the second cell, triggering Early Data Forwarding, EDF, for the second cell.

26. The method of any of claims 22-25, wherein the method further comprises:based on the time-domain prediction information for the second cell, configuring fast failure recovery.

27. The method of claim 26, wherein configuring fast failure recovery comprises determining to include in a conditional handover configuration for the second cell a ‘attemptCondReconfig’ field set to ‘true’.

28. The method of any of claims 22-27, wherein the second cell is a cell of a second network node, and wherein the method further comprises: after receiving the first message, transmitting, to the second network node, a conditional handover request for configuring a conditional handover for the second cell.

29. The method of claim 28, wherein the conditional handover request further comprises the time-domain prediction information for the second cell or information derived therefrom.

30. The method of claim 29, wherein the derived information is one of: part of the time-domain prediction information for the second cell received from the UE; and post-processed information based on the time-domain prediction information for the second cell received from the UE.31 . The method of any of claims 28-30, wherein the method further comprises: after transmitting the conditional handover request, receiving, from the second network node, a conditional handover candidate configuration for the second cell.

32. The method of any of claims 22-31 , wherein the second cell is one of: the first cell, another cell of the source network node, and a cell of a second network node.

33. The method of any of claims 22-32, wherein the method further comprises: prior to receiving the first message, transmitting, to the UE, an indication of a property of the time-domain prediction information that the UE can transmit in the first message.

34. A method performed by a second network node, wherein a user equipment, UE, is being served by a first cell of a source network node, the method comprising: receiving (804), from the source network node, a conditional handover request for configuring a conditional handover for a second cell, wherein the second cell is a cell of a secondnetwork node, and the conditional handover request comprises time-domain prediction information for the second cell or information derived therefrom.

35. The method of claim 34, wherein the derived information is one of: part of the time-domain prediction information for the second cell; and post-processed information based on the timedomain prediction information for the second cell.

36. The method of claim 34 or 35, wherein the time-domain prediction information for the second cell or information derived therefrom that is comprised in the conditional handover request further comprises time-domain prediction information for a third cell or information derived therefrom, wherein the third cell is one of: the first cell, and another cell of the source network node.

37. The method of any of claims 34-36, wherein the method further comprises: based on the prediction information, determining whether to accept or reject the conditional handover request for configuring the conditional handover for the second cell.

38. The method of claim 37, wherein determining whether to accept or reject the conditional handover request comprises: determining, based on the time-domain prediction information for the second cell or information derived therefrom, a likelihood indication indicating a likelihood of the second cell being a target cell for conditional handover of the UE; and responsive to the determined likelihood indication satisfying a criterion, accepting the conditional handover request for configuring the conditional handover for the second cell; and responsive to the determined likelihood indication failing to satisfy the criterion, rejecting the conditional handover request for configuring the conditional handover for the second cell.

39. The method of claim 36 or 37, wherein accepting the conditional handover request comprises: transmitting, to the source network node, a handover request acknowledge message.

40. The method of any of claims 34-39, wherein the method further comprises: based on the time-domain prediction information for the second cell or information derived therefrom, configuring Contention-Free Random-Access resources per beam for the second cell, wherein the second cell is a conditional handover candidate for the UE.

41. A computer program product comprising a computer readable medium having computer readable code embodied therein, the computer readable code being configured such that, on execution by a suitable computer or processor, the computer or processor is caused to perform the method of any of claims 1-40.

42. A user equipment, UE, configured to perform the method of any of claims 1-21.

43. A user equipment, UE, comprising a processor and a memory, said memory containing instructions executable by said processor whereby said UE is operative to perform the method of any of claims 1-21.

44. A first radio access network, RAN, node, configured to perform the method of any of claims 22-40.

45. A first radio access network, RAN, node comprising a processor and a memory, said memory containing instructions executable by said processor whereby said first RAN node is operative to perform the method of any of claims 22-40.

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