Generating measurement reports based on time-domain predictions of beam measurement information

Abstract

A communication device in a communications network that includes a network node can generate (1020) a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report. The report can include information associated with a subset of the plurality of beams. Generating the report can include selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the report can further include sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. The communication device can further transmit (1030) the report to the network node.

Description

GENERATING MEASUREMENT REPORTS BASED ON TIME-DOMAIN PREDICTIONS OF BEAM MEASUREMENT INFORMATIONTECHNICAL FIELD

[0001] The present disclosure is related to wireless communication systems and more particularly to generating measurement reports based on time-domain predictions of beam measurement information. For example, selecting and sorting beams to include in measurement reports which include time-domain predictions of beam measurement information.BACKGROUND

[0002] FIG. 1 illustrates an example of a new radio (NR) network (e.g., a 5th Generation (5G) network) including a 5G core (5GC) network 130, network nodes 120a-b (e.g., 5G base station (gNB)), multiple communication devices 110 (also referred to as user equipment (UE)).

[0003] A UE in NR may be configured by the network to perform measurements (e.g., reference signal received power (RSRP), reference signal received quality (RSRQ), signal-to- interference-plus-noise ratio (SINR)) on one or more neighbor cells associated to a measurement object (e.g., associated to a synchronization signal block (SSB) frequency) and report information in a radio resource control (RRC) measurement report. In some examples, the information includes the measurements on the one or more neighbor cells. In additional or alternative examples, the information includes beam measurement information including beam identifier (e.g., SSB index) or beam measurements (e.g., synchronization signal (SS)-RSRP, SS- RSRQ, and SS-SINR).SUMMARY

[0004] According to some embodiments, a method of operating a communication device in a communications network that includes a network node is provided. The method includes generating a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report. The report includes information associated with a subset of a plurality of beams. Generating the report includes selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the report further includes generating the report comprises sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. The method further includes transmitting the report to the network node.

[0005] According to additional or alternative embodiments, generating the report includes generating the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0006] According to additional or alternative embodiments, generating the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams includes generating the report to include only the mobility related timedomain prediction of beam measurement information associated with the plurality of beams.

[0007] According to additional or alternative embodiments, generating the report includes sorting the subset of the plurality of beams based on at least one of: a trigger quantity; a beambased measurement reporting quantity; a beam-based prediction reporting quantity; and a prediction-based trigger quantity.

[0008] According to additional or alternative embodiments, the report includes a radio resource control, RRC, measurement report.

[0009] According to additional or alternative embodiments, the method further includes receiving configuration information from the network node, the configuration information indicating how to generate the report based on the mobility related time-domain prediction of beam measurement information. Generating the report includes generating the report based on the configuration information.

[0010] According to additional or alternative embodiments, the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0011] According to additional or alternative embodiments, transmitting the report includes at least one of: periodically transmitting the report; transmitting the report in response to an event trigger; semi-persistently transmitting the report; and aperiodically transmitting the report.

[0012] According to additional or alternative embodiments, the mobility related timedomain prediction of beam measurement information includes a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurement of the beam that includes at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

[0013] According to additional or alternative embodiments, the mobility related timedomain prediction of beam measurement information includes a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning, ML, model for mobility or RRM related prediction.

[0014] According to other embodiments, an apparatus for generating measurement reports based on time-domain predictions of beam measurement information is provided. The apparatus includes a processor and a memory. The memory contains instructions executable by the processor whereby the apparatus is operative to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams. The apparatus is further operative to transmit the report to the network node. Generating the report includes selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the report includes sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0015] According to additional or alternative embodiments, the apparatus is further operative to perform any of the above methods.

[0016] According to other embodiments, a communication device is provided. The communication device is adapted to perform operations including generating a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams. The operations further including transmitting the report to the network node. Generating the report includes selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the report includes sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0017] According to additional or alternative embodiments, the communication device is further adapted to perform any of the above methods.

[0018] According to other embodiments, a computer program is provided. The computer program includes program code to be executed by processing circuitry of a communication device, whereby execution of the program code causes the communication device to perform operations. The operations include generating a report based on a mobility related time -domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams. The operations further include transmitting the report to the network node. Generating the report includes selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality ofbeams. Generating the report includes sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0019] According to additional or alternative embodiments, execution of the program code causes the communication device to perform operations further comprising any of the operations of the above methods.

[0020] According to additional or alternative embodiments, a computer program product is provided. The computer program product includes a non-transitory storage medium including program code to be executed by processing circuitry of a communication device, whereby execution of the program code causes the communication device to perform operations including generating a report based on a time-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams. The operations further include transmitting (1030) the report to the network node. Generating the report includes selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the report includes sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0021] According to additional or alternative embodiments, execution of the program codes causes the communication device to perform any of the above methods.

[0022] According to other embodiments, a method of operating a network node in a communications network that includes a communication device is provided. The method includes generating configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. Generating the configuration information includes generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the configuration information further includes generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. The method further includes transmitting the configuration information to the communication device. The method further includes receiving the report from the communication device.

[0023] According to additional or alternative embodiments, generating the configuration information includes generating the instructions to cause the communication device to generate the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Receiving the report includes receiving the report including the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0024] According to additional or alternative embodiments, generating the configuration information includes generating the instructions to cause the communication device to generate the report to include only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Receiving the report includes receiving the report including only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0025] According to additional or alternative embodiments, generating the configuration information includes generating instructions to cause the communication device to generate the report with a subset of the plurality of beams sorted based on at least one of: a trigger quantity; a beam-based measurement reporting quantity; a beam-based prediction reporting quantity; and a prediction-based trigger quantity.

[0026] According to additional or alternative embodiments, the report includes a radio resource control, RRC, measurement report.

[0027] According to additional or alternative embodiments, the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0028] According to additional or alternative embodiments, receiving the report includes at least one of: periodically receiving the report; receiving the report in response to an event trigger; semi-persistently receiving the report; and aperiodically receiving the report.

[0029] According to additional or alternative embodiments, the mobility related timedomain prediction of beam measurement information includes a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurement of the beam that includes at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

[0030] According to additional or alternative embodiments, the mobility related timedomain prediction of beam measurement information includes a beam identifier of a beam of theplurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

[0031] According to other embodiments, an apparatus for enabling generation of measurement reports based on time-domain predictions of beam measurement information is provided. The apparatus includes a processor and a memory, the memory containing instructions executable by the processor whereby the apparatus is operative to generate configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. The apparatus further operative to transmit the configuration information to the communication device. The apparatus further operative to receive the report from the communication device. Generating the configuration information includes generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time -domain prediction of beam measurement information associated with the plurality of beams. Generating the configuration information includes generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0032] According to additional or alternative embodiments, the apparatus is further operative to perform any of the above network node operations.

[0033] According to other embodiments, a network node is provided. The network node is adapted to perform operations including generating configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. The operations further include transmitting the configuration information to the communication device. The operations further include receiving the report from the communication device. Generating the configuration information includes generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the configuration information includes generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0034] According to additional or alternative embodiments, the operations further include any of the operations of the above network node methods.

[0035] According to other embodiments, a computer program is provided. The computer program includes program code to be executed by processing circuitry of a network node, whereby execution of the program code causes the network node to perform operations including generating configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. The operations further including transmitting the configuration information to the communication device. The operations further including receiving the report from the communication device. Generating the configuration information includes generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Generating the configuration information includes generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0036] According to additional or alternative embodiments, the operations further include any of the operation of the above network node methods.

[0037] According to other embodiments, a computer program product is provided. The computer program product includes a non-transitory storage medium including program code to be executed by processing circuitry of a network node, whereby execution of the program code causes the network node to perform operations including generating configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. The operations further include transmitting the configuration information to the communication device. The operations further include receiving the report from the communication device. Generating the configuration information includes generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time -domain prediction of beam measurement information associated with the plurality of beams. Generating the configuration information includes generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0038] According to additional or alternative embodiments, the operations further include any of the operations of the above network node methods.

[0039] According to other embodiments, a non-transitory computer readable medium, host, or system is provided to perform one of the above methods.

[0040] Certain embodiments may provide one or more of the following technical advantages. In some embodiments, the inclusion of time-domain prediction(s) of beam measurement information in a Measurement Report may benefit the right allocation of random access resources by a target network node and / or prevent ping-pong handovers.

[0041] In some examples, a benefit in having a sorting function for including time-domain prediction(s) of beam measurement information (or for including the list of ordered / sorted beam indexes based on the sorting quantity which can be a time domain based prediction quantity e.g., pRSRP, pRSRQ, PSINR (without including the time domain prediction(s) of the beam measurement information)) is that the UE includes the time-domain prediction(s) of beam measurement information for the beams (or only a list of ordered / sorted beam indexes based on the sorting quantity) the network most likely will choose to allocate random access resources for a handover, reconfiguration with sync, a dual connectivity setup, an SCG addition, a carrier aggregation setup, activation or deactivation, a conditional handover configuration, a LTM configuration, etc. And, having the sorting makes sure that the most relevant beams (either based on the measurements or based on the predictions) will be included.

[0042] In additional or alternative examples, when a beam-based predicted reporting quantity is used as sorting quantity for determining the beams per cell for which to include timedomain prediction(s) of beam measurement information, one of the advantages of such option is that the predicted values are not only included but influence the sorting of the beams per cell i.e. which beams to include in the RRC Measurement Report per cell, and enables the possibility to include in the RRC Measurement Report beams which shows excellent predicted values in the future (e.g. very high pRSRP for future time instances), despite note being the strongest for the actual measurements.

[0043] In additional or alternative examples, when the prediction-based trigger quantity (pRSRP, pRSRQ, pSINR) is used as sorting quantity and determining the cells to be included in the reports, the UE includes beams with the best time domain predictions and may include the beam level measurements along with the predictions, this enables the network to reply more on the quality of the beams in future time instances (deduced form the reported perditions) for the mobility purpose than the quality at the time being deduced from the measurements. In particular if the best beam at the current time is predicted to be a very bad beam in the future time instances, the UE does not include such beam in the triggered report and instead reports the cells with higher quality in the future time instances to be selected at target for mobility purpose e.g., allocating RACH resources for the handover execution toward such beams.BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate certain non-limiting embodiments of inventive concepts. In the drawings:

[0045] FIG. 1 is a schematic diagram illustrating an example of a 5thgeneration (“5G”) network;

[0046] FIG. 2 is a block diagram illustrating an example of a measurement model in which time-domain prediction of beam measurement information are included in an RRC measurement report in accordance with some embodiments;

[0047] FIG. 3 is a graph illustrating an example of using mobility related time-domain predictions in accordance with some embodiments;

[0048] FIG. 4 is a schematic diagram illustrating an example of an AI / ML model input and output for time domain beam prediction in accordance with some embodiments;

[0049] FIG. 5 is a block diagram illustrating an example of an AI / ML LSTM model used to predict the best beam index for the predicting time instance in accordance with some embodiments;

[0050] FIG .6 is a flow chart illustrating an example of operations of a transformer encoder based neural network in accordance with some embodiments;

[0051] FIG. 7 is a flow chart illustrating an example of operations of a transformer encoder in accordance with some embodiments;

[0052] FIG. 8 is a flow chart illustrating an example of operations of multi head self attention in accordance with some embodiments;

[0053] FIG. 9 is a flow chart illustrating an example of operations of scaled dot-production attention in accordance with some embodiments;

[0054] FIG. 10 is a flow chart illustrating an example of operations performed by a communication device in accordance with some embodiments;

[0055] FIG. 11 is a flow chart illustrating an example of operations performed by a network node in accordance with some embodiments.

[0056] FIG. 12 is a block diagram of a communication system in accordance with some embodiments;

[0057] FIG. 13 is a block diagram of a user equipment in accordance with some embodiments;

[0058] FIG. 14 is a block diagram of a network node in accordance with some embodiments; and

[0059] FIG. 15 is a block diagram of a virtualization environment in accordance with some embodiments.DETAILED DESCRIPTION

[0060] 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, in which examples of embodiments of inventive concepts are shown. Inventive concepts may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of present inventive concepts to those skilled in the art. It should also be noted that these embodiments are not mutually exclusive. Components from one embodiment may be tacitly assumed to be present / used in another embodiment.

[0061] A UE can include in an RRC Measurement Report the performed measurements on one or more cells up to a maximum number of cells. In case event triggered Measurement Report is configured (e.g., when the fulfillment of an event triggers the transmission of the RRC Measurement Report) the neighbor cells to be included are the so-called triggered cells, for example, the UE includes up to a maximum number of triggered cells in an RRC Measurement Report.

[0062] The “maximum number” of cells can be defined by the parameter “maxReportCells”, defined as an INTEGER (L.maxCellReport), and configured at the UE in the IE ReportConfigNR. In case there are more triggered cells than such a maximum number, the UE needs to determine which cells are to be included, so that the associated information is included. This can be performed via a so-called sorting function for cell measurement information.

[0063] In generating an event-triggered RRC measurement report, sorting is performed by the UE based on the trigger quantity (e.g., RSRP, RSRQ, or SINR). When an event is configured (e.g., event A3 in ReportConfigNR), the UE is also configured with a trigger quantity, to indicate based on which quantity the event shall be considered fulfilled.

[0064] The trigger quantity is configured by the field “aN-ThresholdM”, which is a threshold value associated to the selected trigger quantity (e.g., RSRP, RSRQ, SINR) per RS Type (e.g. SS / PBCH block, CSI-RS) to be used in NR measurement report triggering condition for event number aN (e.g., a3). And if multiple thresholds are defined for event number aN, the thresholds are differentiated by M. In the same eventA5, the network configures the samequantity for the MeasTriggerQuantity of the a5 -Threshold 1 and for the MeasTriggerQuantity of the a5-Threshold2.

[0065] In periodic RRC Measurement Report, sorting is performed by the UE based on RSRP, if RSRP is configured as a reporting quantity. Otherwise, RSRQ is used if RSRP is not configured. Otherwise, SINR is used.

[0066] A similar reasoning is applicable for beam(s) i.e. for SSB indexes and / or CSI-RS resource identifiers to be included, per included triggered cell. Once cells are included by the UE in the RRC Measurement Report, based on the sorting quantity, the UE needs to determine which beams to include for each included cells. That is also determined based on the same sorting quantity.

[0067] The UE can include in an RRC Measurement Report beam measurement information up to a maximum number of beams, for a given cell determined to be included in the RRC Measurement Report. The maximum number of beams may also be denoted as a maximum number of Reference Signal (RS) Indexes, such as SSB indexes and / or CSI-RS resource identifiers, considering that these RS(s) are transmitted in beams (e.g. spatial directions) for a given neighbor cell.

[0068] The “maximum number of beams” is defined by the parameter “maxNrofRS- IndexesToReport”, defined as an INTEGER, and configured at the UE in the IE ReportConfigNR. In case there are more measured / detected beam(s) than such a maximum number, the UE needs to determine which beams (i.e. which RS indexes) are to be included for a given included cell, so that the associated information is included. That is done via a so-called sorting function for beam measurement information.

[0069] There currently exist certain challenges. A concept is being considered for AI / ML aided mobility for network triggered L3-based handover: a UE equipped with a AI / ML model for Mobility (or RRM measurements) including time-domain predictions of beam measurement information, per cell, in an RRC Measurement Report.

[0070] The basic idea is that a UE is equipped with a UE sided AI / ML model for performing time-domain predictions of beam measurement information, such as time-domain predictions of beam measurements e.g. predicted RSRP (pRSRP), predicted RSRQ (pRSRQ) or predicted SINR (pSINR) for one or more beams of a cell i.e. for SSB(s) and / or CSI-RS resource(s) transmitted by the network in beams / spatial directions. In other words, these pRSRP, pRSRQ and / or pSINR values per beam for one or more serving and / or neighbour cells would be produced during an inference phase (i.e., running the AI / ML model with the current state (input) information), which are output of the AI / ML model for an RRM measurements / mobility related functionality.

[0071] When an RRC Measurement Report is triggered (based on actual L3 filtered cell level measurements, as defined in TS 38.331), the UE includes one or more time-domain predictions of beam measurement information for serving cells, ‘best’ neighbors in a serving frequency and / or neighbouring cells. In that case, a problem exists when the UE performs timedomain prediction(s) of beam measurement information for more beams than the maximum number of beams per cell for which the UE is allowed to include time-domain predictions in the RRC Measurement Report. Thus, the UE needs to include the time-domain prediction(s) of beam measurement information for a subset of ‘N’ beams of a cell determined to be included in the RRC Measurement Report.

[0072] Moreover, the UE may report time-domain beam predictions (output of the AI / ML models), denoted here time-domain prediction(s) of beam measurement information, to the network wherein the network will use both the measurements and the predictions to decide about the mobility (or CA / DC) procedures. However, co-existence of beam level measurements (i.e., legacy beam level measurements such as RSRP, RSRQ and SINR) and the beam level predictions of the measurements (such as pRSRP, pRSRQ, pSINR) lends itself careful considerations when a limited set of measurements and predictions can be reported to the network. In particular the problem of how the UE populates and includes the measurements and time-domain predictions in the measurement report while the total number of measurements and predictions for the detected cells is more than the allowed number of cells in the report is not yet addressed.

[0073] For that reason, a sorting function for time-domain prediction(s) of beam measurement information is required.

[0074] Various embodiments herein address some of these challenges by a procedure in which a UE determines a subset of ‘N’ beams of a cell for which the UE includes time-domain prediction(s) of beam measurement information in a measurement report (e.g. RRC Measurement Report). That is necessary when there are more beams in a cell for which the UE has available time-domain prediction(s) of beam measurement information than the maximum number of beams in a cell for which the UE is allowed to include time-domain prediction(s) of beam measurement information, in an RRC Measurement Report (i.e. number of beams for which the UE has available time-domain prediction(s) of beam measurement information > ‘N’).

[0075] The UE determines that the subset of ‘N’ beams of a cell are the top ‘N’ beams of a cell sorted according to a sorting quantity which is based on one or more of the following: 1) A trigger quantity the UE is configured with (e.g. RSRP, RSRQ, SINR); 2) A beam -based measurement reporting quantity the UE is configured with (e.g. RSRP, RSRQ, SINR); 3) A beam -based prediction (or predicted) reporting quantity the UE is configured with (e.g.predicted RSRP, predicted RSRQ, predicted SINR); and 4) A prediction-based trigger quantity, e.g., a pRSRP, pRSRQ, pSINR e.g., in case report is triggered by fulfillment of entry condition of an event evaluated based on mobility related time-domain prediction(s) , e.g., a pRSRP, pRSRQ, pSINR.

[0076] In some examples, the UE sends a report to the network, including the sorted beam information in the report associated to the included cell(s). In an embodiment the report is a RRC Measurement Report which includes measurements and / or prediction(s). In another embodiment the report is a new (dedicated) report which may only include the prediction information i.e., without including the measurements.

[0077] In additional or alternative examples, the UE is configured with the value ‘N’, within the reporting configuration instance (e.g. IE ReportConfigNR) associated to the RRC Measurement Report which is to be transmitted. In one option, ‘N’ is also the maximum number of beams for which the UE includes beam measurement information; in that case, the UE may include time-domain prediction(s) (or information derived from it) for the same beams for which the UE includes beam measurement information. In another option, ‘N’ is the maximum number of beams for which the UE includes time-domain prediction(s) of beam measurement information and ‘M’ (possibly different than ‘N’) is the number of beams for which the UE includes beam measurement information; in that case, the UE may include time-domain prediction(s) (or information derived from it) for different beams than the beams for which the UE includes beam measurement information.

[0078] In additional or alternative examples, the UE is configured with the RRC Measurement Report which is one or more or: event-triggered; periodical; aperiodic; semi- persistent.

[0079] FIG. 2 illustrates an example of a measurement model in which the time-domain predictions of beam measurement information are included in an RRC measurement report.

[0080] In some embodiments, only beams with ‘good enough’ time-domain prediction(s) of measurements are sorted i.e. beams whose time domain prediction(s) of beam measurements for the sorting quantity are above a threshold. Such threshold may be set to a different value than the consolidation threshold for including beam measurement information (or set to the same value).

[0081] In additional or alternative embodiments, the time-domain prediction(s) of beam measurement information comprises at least the following information: Beam identifiers or reference signal ID (e.g. SSB index); and Associated time-domain prediction(s) of beam measurements (e.g. predicted RSRP, predicted RSRQ, predicted SINR) for the beam whose beam identifier is included.

[0082] In additional or alternative embodiments, when the network configures the UE to NOT include the time-domain prediction(s) of beam measurements, the above described method is applied to include the best beams’ identifiers without including the time domain predictions associated to the beams, potentially sorted in a decreasing order of the sorting quantity which can be time domain prediction(s) of the beam measurement information. In order words, upon receiving such a configuration the beam sorting function receives time domain prediction(s) of the beam measurement information and / or the beam measurements information as input and sorts the beam identifiers based on the sorting quantity. Then UE includes an ordered / sorted list of beam identifiers in the measurement report.

[0083] In additional or alternative embodiments, including a subset of beams in decreasing order of a sorting quantity, will be done by including the best beam identity (with strongest value for the sorting quantity) and the rest of the beams whose sorting quantity is above a configured beam suitability / consolidation threshold.

[0084] In additional or alternative embodiments, the UE may also include the associated beam measurements if requested by the network in the received configuration.

[0085] In additional or alternative embodiments, the UE may also include the associated time domain prediction(s) of the beam measurements in the report if requested by the network in the received configuration.

[0086] Various embodiments herein describe a procedure at a UE for determining a subset of ‘N’ beams of a cells are the top ‘N’ beams of a cell for which to include time-domain prediction(s) of beam measurement information in a measurement report (e.g. an RRC Measurement Report). Such a function is necessary when the UE has available time-domain prediction(s) of beam measurement information for more beams in a cell compared to the maximum number of beams per cell (for including time-domain prediction(s) of beam measurement information) that are allowed to be included in an RRC Measurement Report (denoted ‘N’ e.g., maxNrofRS-IndexesToReport according to TS 38.331 version 18.1.0).

[0087] A “beam” in this context may correspond to a Reference Signal (RS) and / or Synchronization Signal (SS) e.g. received by the UE and associated to a spatial direction.

[0088] For example, a beam of a cell may correspond to a Synchronization Signal Block (SSB) of a cell, including an SSB index. Thus, a cell with multiple SSBs, each SSB including a different SSB index and the same Physical Cell Identifier of the cell, may correspond to a cell with multiple beams i.e. sorting beams of a cell may correspond to sorting SSB(s) of a cell.

[0089] For example, a beam of a cell may correspond to a Channel State Information Reference Signal (CSI-RS) resource of a cell, including a CSI-RS resource identifier. Thus, a cell with multiple CSI-RS resources, each CSI-RS including a different CSI-RS resourceidentifier, may correspond to a cell with multiple beams i.e. sorting beams of a cell may correspond to sorting CSI-RS identifier(s) of a cell.

[0090] For example, a beam of a cell may correspond to a Mobility Reference signal(s) of a cell, including a MRS identifier. Thus, a cell with multiple MRSs, each MRS including a different MRS identifier, may correspond to a cell with multiple beams i.e. sorting beams of a cell may correspond to sorting MRS identifier(s) of a cell.

[0091] According to the method, the UE determines that the subset of ‘N’ beams of a cell are the top ‘N’ beams of a cell sorted according to a sorting quantity which is based on one or more of the following: 1) A trigger quantity the UE is configured with (e.g. RSRP, RSRQ, SINR); 2) A beam -based measurement reporting quantity the UE is configured with (e.g. RSRP, RSRQ, SINR); 3) A beam-based prediction reporting quantity the UE is configured with (e.g. predicted RSRP, predicted RSRQ, predicted SINR); and 4) A prediction-based trigger quantity, e.g., a pRSRP, pRSRQ, pSINR, in case report is triggered by fulfillment of entry condition of an event evaluated based on mobility related time-domain prediction(s) e.g., a pRSRP, pRSRQ, pSINR.

[0092] A measurement quantity in this context may also be called a quantity derived based on a measurement of a reference signal associated to a network entity such as a cell and / or a beam. Measurement quantities may reflect some property at a given point in time of the radio link the UE is detecting e.g. a cell power in the downlink (DL), cell coverage, cell signal to noise + interference ratio, etc.

[0093] Thus, the term “beam-based measurement reporting quantity” refers to a reporting quantity for which the UE needs to report beam measurement information. For example, when a “beam-based measurement reporting quantity” is set to be RSRP, the UE needs to derive L3 filter measurements per beam of a cell (e.g. serving cell) and, based on that, derive beam measurement information e.g. beam identifier(s) of beams whose RSRP is above a threshold.

[0094] The term “beam-based prediction reporting quantity” refers to a prediction reporting quantity for which the UE needs to report time-domain prediction(s) of beam measurement information. For example, when a “beam-based prediction reporting quantity” is set to be pRSRP, the UE needs to report pRSRP value(s) and / or values derived from pRSRP values.

[0095] Examples of measurement quantities are: i) Reference Signal Received Power (RSRP); ii) Reference Signal Received Quality (RSRQ); iii) Signal to Interference Noise Ratio (SINR). A measurement quantity may be associated to a reference signal type (e.g. SSB, CSI- RS, Mobility Reference Signal), in case that reference signal type is used for measuring and deriving the measurement quantity. For example, an SS-RSRP is an RSRP measured on an SSB, a CSI-RSRP is an RSRP value measured on a CSI-RS.

[0096] The UE includes for at least one cell the time-domain prediction(s) of beam measurement information. The at least one cell for which the UE includes the time-domain prediction(s) of beam measurement information may corresponds to one or more of: a serving cell; a neighbor cell in a neighbor frequency or non-serving celll; a candidate cell for conditional handover; a candidate cell for Layer 1 / Layer 2 triggered mobility (“LTM”); and a neighbor cell in a serving frequency.

[0097] In some embodiments, the at least one cell for which the UE includes the timedomain prediction(s) of beam measurement information corresponds to a serving cell can include a Primary Cell, a Special Cell (SpCell), a SpCell of a Master Cell Group (MCG), a SpCell of a Secondary Cell Group (SCG), PScell, a Secondary Cell (Scell) of the MCG; an SCell of the SCG, etc.). In some examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, beam measurement information. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, time-domain prediction(s) of beam measurement information. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured with an event-triggered report or periodical report. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured with an event-triggered report and the event is associated to a serving cell e.g. A3 event in which the UE triggers the report when a neighbour is an offset better than a serving cell.

[0098] In additional or alternative embodiments, the at least one cell for which the UE includes the time-domain prediction(s) of beam measurement information corresponds to the neighbour cell in a neighbour frequency or non-serving cell. In some examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, beam measurement information. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, time-domain prediction(s) of beam measurement information. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured with an event-triggered report or periodical report which is associated to a neighbour cell e.g. A3 event in which the UE triggers the report when a neighbour is an offset better than a serving cell.

[0099] In additional or alternative embodiments, the at least one cell for which the UE includes the time-domain prediction(s) of beam measurement information corresponds to acandidate cell for Conditional Handover (or other form of conditional reconfiguration). In some examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, beam measurement information for a candidate cell for CHO. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, time-domain prediction(s) of beam measurement information.

[0100] In additional or alternative embodiments, the at least one cell for which the UE includes the time-domain prediction(s) of beam measurement information corresponds to a candidate cell for Layer 1 / Layer 2 Triggered Mobility (LTM). In some examples, the UE includes the time-domain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, beam measurement information for a candidate cell for LTM. In additional or alternative examples, the UE includes the timedomain prediction(s) of beam measurement information when the UE is configured to include, in the associated reporting configuration, time-domain prediction(s) of beam measurement information.

[0101] In additional or alternative embodiments, the at least one cell for which the UE includes the time-domain prediction(s) of beam measurement information corresponds to a neighbour cell in a serving frequency. In some examples, the UE includes the time-domain prediction(s) of beam measurement information for a neighbour cell in a serving frequency, when the UE is configured to include, in the associated reporting configuration, beam measurement information for neighbour cell in a serving frequency e.g. ‘best’ neighbors in a serving frequency. In additional or alternative examples, the UE includes the time-domain prediction(s) of beam measurement information for a neighbour cell in a serving frequency when the UE is configured to include, in the associated reporting configuration, time-domain prediction(s) of beam measurement information for a neighbour cell in a serving frequency. In additional or alternative examples,, the UE includes the time-domain prediction(s) of beam measurement information for a neighbour cell in a serving frequency when the UE is configured with an event-triggered report or periodical report.

[0102] In additional or alternative embodiments, the UE includes in the measurement report (e.g. RRC Measurement Report) one or more time-domain prediction(s) of beam measurement information of at least one cell, up to a number of ‘N’ beams (configured at the UE by a network node). The UE includes the one or more beams up to ‘N’, per cell, in decreasing order of the sorting quantity determined by the UE, which depending on the solution may either be an actual measurement quantity (e.g. RSRP, RSRQ, SINR) or a prediction of a measurement quantity in afuture time instance (e.g. predicted RSRP, predicted RSRQ, predicted SINR). The one or more beams corresponds to a subset of ‘N’ beams of the cell. In other words, the UE has available time-domain prediction(s) of beam measurement information for beam(s) of a cell in an SSB frequency configured in a measurement object (e.g. IE MeasObjectNR) associated with the reporting configuration instance (e.g. IE ReportConfigNR) associated to an RRC Measurement Report which is to be transmitted (e.g. event-triggered, periodic).

[0103] In additional or alternative embodiments, the time-domain prediction(s) of beam measurement information may also be called RRM (Radio Resource Management) measurement related time-domain prediction(s) of beams, and includes, for example, predicted value(s) or inferences of a measurement quantity (RSRP) for a beam of a cell in at least one future time instance (in relation to the time in which the RRC Measurement Report is being transmitted).

[0104] In additional or alternative embodiments, a measurement report may correspond to an RRC Measurement Report, as defined in TS 38.331, which may include beam measurement information derived from L3 filtered beam measurement(s). However, the measurement report is not limited to that example, so the method is applicable to any sort of measurement report the UE is configured to report, wherien the report is configured to include time-domain prediction(s) of beam measurement information in which the size is limited and, in particular, when there are more beams in a cell with time-domain prediction(s) of beam measurement information than the configured value ‘N’. In that sense, a measurement report may correspond to e.g.: i) a Layer 1 (LI) or Medium Access Control layer (MAC) measurement report (e.g. a CSI report or similar for Lower-Layer triggered Mobility (LTM) measurement reporting); ii) a LI measurement report transmitted on Physical Uplink Control Channel, PUCCH; iii) a LI measurement report transmitted on Physical Uplink Shared Channel PUSCH.

[0105] In additional or alternative embodiments, the UE performs the sorting of beams per cell, for which to include time-domain prediction(s) of beam measurement information. Thus, for one or more cells the UE has determined to include in a measurement report, the UE performs the sorting of the beams based on the sorting quantity determined according to the method.

[0106] In additional or alternative embodiments, the UE performs the sorting of beams per cell, for which to include time-domain prediction(s) of beam measurement information, but the UE may also include for these beams one or more beam measurement information (i.e. not only prediction(s)).

[0107] In additional or alternative embodiments, the UE performs the sorting of beams per cell, for which to include time-domain prediction(s) of beam measurement information, when there are available time -domain prediction(s) of beam measurement information for a cell whichthe UE has determined to include in the measurement report. In some examples, it may be the case that the UE is configured to report the time-domain prediction(s) of beam measurement information for a cell which becomes a triggered cell for an event-triggered report, however, for that triggered cell the UE does not have available time-domain prediction(s) of beam measurement information. In additional or alternative examples, it may be the case that the UE is configured to report the time-domain prediction(s) of beam measurement information for a cell which becomes a triggered cell for an event-triggered report, however, the AI / ML model and / or functionality is not applicable i.e. the UE is not able to infer the time-domain prediction(s) of beam measurement information.

[0108] In additional or alternative embodiments, the UE may also be configured with one or more measurement reporting quantities for which the UE is to report cell-based measurements. For example, the UE may be configured with a measurement reporting quantity = RSRP, meaning the UE is to include cell-based RSRP per cell in a measurement report; while, the UE may be configured with a beam-based reporting quantity = RSRQ, meaning the UE is to include beam-based RSRQ per cell in a measurement report.

[0109] In additional or alternative embodiments, determining the beams per cell to include time-domain prediction(s) of beam measurement information, depends on various aspects, such as the trigger for the report e.g. if it is event triggered, periodic, aperiodic, semi-persistent. Also, there may be different manners to define for each of these alternatives 1, 2, 3 what exact quantity is determined by the UE.

[0110] In additional or alternative embodiments, sorting quantity is equivalent to trigger quantity. In some examples, the UE determines that the subset of ‘N’ beams of a cell for which to include time-domain prediction(s) of beam measurement information are the top ‘N’ beams of a cell sorted according to a sorting quantity which is 1) a trigger quantity the UE is configured with (e.g. RSRP, RSRQ, SINR). When the RRC Measurement Report in which the UE is configured to include mobility related time-domain prediction(s) is an event-triggered RRC Measurement Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to eventTriggered), the UE determines that the sorting quantity (e.g. for including a list of beams for a cell in the measurement report) is the measurement quantity configured as the trigger quantity.

[0111] An event-triggered measurement report is referred as the main example, however, the option is applicable whenever there is a form of trigger quantity the UE is configured with, based one which a measurement report is triggered to be transmitted.

[0112] In the case of event-triggered measurement reports, the UE may be configured to include time-domain prediction(s) of beam measurement information for beams of a neighbourcell, in case an event is associated to measurements of a neighbour cell, like in event A3 (neighbour becomes offset better than SpCell). In that case, the subset of ‘N’ beams of a cell for which to include time-domain prediction(s) of beam measurement information corresponds to a subset of ‘N’ beams of a so-called triggered cell i.e. beams of a cell for which a condition triggering the transmission of the measurement report is fulfilled. These may also be considered applicable cells.

[0113] In the case of event-triggered measurement reports, the UE may be configured to include time-domain prediction(s) of beam measurement information for beams of serving cells the UE is configured with for a cell group e.g. for the PCell and Master Cell Group (MCG) Secondary Cell(s), in case the reporting configuration for which the time-domain prediction(s) of beam measurement information is configured is configured within the MeasConfig for the MCG; or / and for the PScell and Secondary Cell Group (SCG) Secondary Cell(s), in case the reporting configuration for which the time-domain prediction(s) of beam measurement information is configured is configured within the MeasConfig for the SCG. In that case, the subset of ‘N’ beams of a serving cell for which to include time-domain prediction(s) of beam measurement information corresponds to a subset of ‘N’ beams of a serving cell.

[0114] In some embodiments, when the reportType is set to eventTriggered, for an NR cell, the UE considers the quantity used in the aN-Threshold (for eventAl, eventA2, eventA4, eventA4Hl and eventA4H2) or in the a5-Threshold2 (for eventA5, eventA5Hl and eventA5H2) or in the aN-Offset (for eventA3, eventA3Hl, eventA3H2 and eventA6) or in the xl-Threshold2 (for eventXl) as the sorting quantity.

[0115] In additional or alternative embodiments, when the trigger quantity is set to RSRP, the UE determines RSRP as the sorting quantity. Or, when the trigger quantity is set to RSRQ, the UE determines RSRQ as the sorting quantity. Or, when the trigger quantity is set to SINR, the UE determines SINR as the sorting quantity.

[0116] In additional or alternative embodiments, the UE considers the sorting quantity to be the trigger quantity when the trigger quantity (e.g. RSRP) is also configured as a prediction reporting quantity for beam measurement information. For example, if the UE is configured with RSRP as trigger quantity, and predicted RSRP per beam is also configured as a quantity to be reported by the UE and / or to be inferred by the UE.

[0117] In additional or alternative embodiments, the sorting quantity is determined according to the method is used by the UE to determine the beam(s) for which to include timedomain prediction(s) of beam measurement information. However, the exact beams per cell which are included may differ for the different cell(s), despite the sorting quantity being the same for the different cells determined to be included.

[0118] In some examples, the UE is configured to include in an RRC Measurement Report time-domain prediction(s) of beam measurement information, such as predicted RSRP per beam and / or predicted RSRQ per beam and / or predicted SINR values per beam, for the cell(s) which are to be included in the RRC Measurement Report. When that is an event-triggered report i.e. reportType in IE ReportConfigNR set to eventTriggered, for an event A3 (entering / entry condition: neighbour cell becomes an offset better than SpCell e.g. PCell), with trigger quantity set to RSRQ (e.g. a3-Offset, of IE MeasTriggerQuantityOffset, set to ‘rsrq’), the entering / entry condition is considered fulfilled when neighbour cell’s RSRQ becomes offset better than the SpCell’s RSRQ for a period of time so-called tiem to Trigger (TTT).

[0119] Assuming that the UE is configured to report a maximum number of beams per cell = 2 but, for a given cell (e.g. serving cell or a neighbor cell), there are 3 beams for which the UE has available time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein RSRQ(B) > RSRQ(A) > RSRQ(C). Note that pRSRP(A,k) denotes the predicted RSRP value of beam A in a future time instance indicated by the value k e.g. k-th future time instance.

[0120] Since trigger quantity is determined to be RSRQ, sorting the beams in decreasing RSRQ order leads to the following order:1) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);2) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);3) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);And, since the maximum number of beams per cell = 2, only beams in position 1 and 2 are included in the RRC Measurement Report for that cell and, these are the beams for which the UE includes the time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values.

[0121] In order words, the UE determines the trigger quantity to be the sorting quantity for determining the beams per cell for which the UE includes the time-domain prediction(s) of beam measurement information. This does not take into account the values of the time-domain prediction(s) of beam measurement information.

[0122] One of the advantages of these embodiments is that the time-domain prediction(s) of beam measurement information are included opportunistically for the beams per cell for which the UE would anyways report in a legacy RRC Measurement Report i.e. the expected beams per cell, included in the report, do not change, but the report is enriched for these particular beams.

[0123] In some embodiments, when the UE includes the subset of ‘N’ beams of the at least one cell the UE includes the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold. In some examples, the UE includes the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements, when it is explicitly configured by the network in the received configuration (otherwise only beam identifiers for the predicted beams are included). In additional or alternative examples, the UE the UE includes the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration.

[0124] In additional or alternative embodiments, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’. In some examples, the UE is configured with a predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) which is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold (associated to beam measurement information) can be absThreshSS-BlocksConsolidation in accordance with the 3 GPP TS 38.331 version 18.1.0. In another example network may configure a dedicated / different beam suitability / consolidation threshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0125] In some embodiments, a sorting quantity is equivalent to a predicted version of the triggering quantity. The UE determines that the subset of beams of a cell for which to include time-domain prediction(s) of beam measurement information are the top ‘X’ beams of a cell sorted according to a sorting quantity which is a predicted version of the trigger quantity the UE is configured with (e.g. predicted RSRP or predicted RSRQ, predicted SINR will be counted as a sorting quantity depending on the triggering quantity which can be one or RSRP, RSRQ, or SINR). When the RRC Measurement Report in which the UE is configured to include timedomain prediction(s) of beam measurement information is an event-triggered RRC Measurement Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to eventTriggered), the UE determines that the sorting quantity for including one or more beams in the measurement report is the predicted version of measurement quantity configured as the trigger quantity. In an embodiment the UE selects the predictedversion of the trigger quantity only if being configured / instructed by the network, otherwise the triggering quantity will be a default sorting quantity.

[0126] In some examples, if RSRP is configured as a3-Offset for an A3 event, upon fulfilment of the entering / entry condition of the A3 event for a period of time (e.g., TTT), the UE includes a list of best beams in a decreasing order of a time domain RSRP prediction since the sorting quantity is RSRP prediction (pRSRP). With the same logic, when the trigger quantity for the measurement report is set to RSRQ, the UE determines time domain beam prediction(s) of RSRQ quantity as the sorting quantity.

[0127] In additional or alternative embodiments, when the trigger quantity is set to SINR, the UE determines time domain beam prediction(s) of SINR as the sorting quantity.

[0128] An event-triggered measurement report is referred as the main example, however, the option is applicable whenever there is a form of a trigger quantity the UE is configured with, based one which a measurement report is triggered to be transmitted.

[0129] In the case of event-triggered measurement reports, the UE may be configured to include time-domain prediction(s) of beam measurement information for beams of a neighbour cell, in case an event is associated to measurements of a neighbour cell, like in event A3 (neighbour becomes offset better than SpCell). In that case, the subset of beams of a cell for which to include time-domain prediction(s) of beam measurement information corresponds to a subset of beams of a so-called triggered cell i.e. beams of a cell for which a condition triggering the transmission of the measurement report is fulfilled. These may also be considered applicable cells.

[0130] In some examples, when the reportType is set to eventTriggered, for an NR cell, the UE considers the predicted version of quantity used in the aN-Threshold (for eventAl, eventA2, eventA4, eventA4Hl and eventA4H2) or predicted version of quantity used in the a5- Threshold2 (for eventA5, eventA5Hl and eventA5H2) or predicted version of quantity used in the aN-Offset (for eventA3, eventA3Hl, eventA3H2 and eventA6) or predicted version of quantity used in the xl-Threshold2 (for eventXl) as the sorting quantity.

[0131] In additional or alternative examples, the UE is configured to include in an RRC Measurement Report time -domain prediction(s) of beam measurement information, such as predicted RSRP per beam and / or predicted RSRQ per beam and / or predicted SINR values per beam, for the cell(s) which are to be included in the RRC Measurement Report. When that is an event-triggered report i.e. reportType in IE ReportConfigNR set to eventTriggered, for an event A3 (entering / entry condition: neighbour cell becomes an offset better than SpCell e.g. PCell), with trigger quantity set to RSRQ (e.g. a3 -Offset, of IE MeasTriggerQuantityOffset, set to‘rsrq’), the entering / entry condition is considered fulfilled when neighbour cell’s RSRQ becomes offset better than the SpCell’s RSRQ for a period of time, so-called TTT).

[0132] Assuming that the UE is configured to report a maximum number of beams per cell = 2 but, for a given cell (e.g. serving cell or a neighbour cell), there are 3 beams for which the UE has available time -domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); whereinRSRQ(B) > RSRQ(A) > RSRQ(C); and pRSRQ(A, 1) > pRSRQ(B, 1) > pRSRQ(C, 1).

[0133] Here, pRSRP(A,k) denotes the predicted RSRP value of beam A in a future time instance indicated by the value k e.g. k-th future time instance.

[0134] Since trigger quantity is determined to be RSRQ, sorting the beams in decreasing pRSRQ order leads to the following order:1) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);2) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);3) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);And, since the maximum number of beams per cell = 2, only beams in position 1 and 2 are included in the RRC Measurement Report for that cell and, these are the beams for which the UE includes the time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values.

[0135] In some embodiments, if the network configures the UE to NOT include the time domain prediction(s) of beam measurements, the UE includes a sorted / ranked list of the beam identities / indexes wherein the sorting the beams is performed based on the time domain prediction(s) of the beam measurements.

[0136] In additional or alternative embodiments, the UE may include the legacy beam measurements such as RSRP, RSRQ, SINR associated to the beams sorted based on the time domain predictions of the beam measurements. In some examples, the UE may include the beam measurements such as RSRP, RSRQ, SINR associated to the beams sorted based on the time domain predictions of the beam measurements, if requested by the network as part of received configuration.

[0137] In additional or alternative embodiments, including a subset of beams of the at least one cell comprises including the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold. In some examples, the UE may include the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements if requested by the network in the received configuration. In additional or alternative examples, the UE may include the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration

[0138] In additional or alternative embodiments, the configured predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold can be absThreshSS-BlocksConsolidation in accordance with the 3GPP TS 38.331 version 18.1.0. In another example, network may configure a dedicated / different beam suitability / consolidation threshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0139] In some examples, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’.

[0140] Embodiments associated with a sorting quantity being equivalent to a beam-based prediction reporting quantity (rule-based) are described below. In some embodiments, the UE determines that the subset of ‘N’ beams of a cell for which to include time-domain prediction(s) of beam measurement information are the top ‘N’ beams of a cell sorted according to a sorting quantity which is based on 3) a beam-based prediction reporting quantity the UE is configured with (e.g. predicted RSRP), based on a rule which prioritizes a prediction reporting quantity.

[0141] When the RRC Measurement Report in which the UE is configured to include timedomain prediction(s) of beam measurement information is an event-triggered RRC Measurement Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to eventTriggered), the UE determines that the sorting quantity is a beam-based prediction reporting quantity.

[0142] In some examples, for a given RRC Measurement Report for which the UE needs to include time-domain prediction(s) of beam measurement information (such as pRSRQ), the UEis configured with one or more beam-based prediction reporting quantities. That indicates to the UE what beam-based predicted quantities (e.g. pRSRP per SSB and / or pRSRQ per SSB, and / or pSINR per SSB) are to be included in an RRC Measurement Report for a number of beams of a cell to be included in the RRC Measurement Report. That also indicates to the UE which prediction quantities per beam (e.g. per SSB, per CSI-RS resource) are to be inferred by an AI / ML model i.e. which inferences to produce by the AI / ML model, per cell, since there are the ones to be included in the RRC Measurement Report. The beam-based reporting prediction quantities may be configured in the IE ReportConfigNR, in which an event-triggered RRC Measurement Report is also configured (i.e. reportType set to eventTriggered), to indicate which beam-based reporting prediction quantities are to be included in the report, when triggered.

[0143] In additional or alternative examples, the sorting quantity is one of the configured beam -based reporting prediction quantities. In additional or alternative examples, when a single beam-based reporting prediction quantity is configured, the UE uses that single beam-based reporting prediction quantity as the sorting quantity e.g. pSINR. In additional or alternative examples, when multiple beam-based reporting prediction quantities are configured, and pRSRP is one of them, the UE uses pRSRP as the sorting quantity e.g. pSINR. In additional or alternative examples, when multiple beam-based reporting prediction quantities are configured, and pRSRP is not one of them, the UE uses pRSRQ as the sorting quantity e.g. pSINR. In additional or alternative examples, when multiple beam-based reporting prediction quantities are configured, one of them is explicitly indicated to be the sorting quantity.

[0144] In additional or alternative embodiments, the UE is configured to include in an RRC Measurement Report time-domain prediction(s) of beam measurement information, such as the following reporting prediction quantities predicted RSRP and / or predicted RSRQ, for the beams which are to be included in the RRC Measurement Report per cell. When that is an event- triggered report i.e. reportType in IE ReportConfigNR set to eventTriggered, for an event A3 (entering / entry condition: neighbour cell becomes an offset better than SpCell e.g. PCell), with trigger quantity set to RSRQ (e.g. aN-Offset, of IE MeasTriggerQuantityOffset, set to ‘rsrq’), the entering / entry condition is considered fulfilled when neighbour cell’s RSRQ becomes offset better than the SpCell ’s RSRQ).

[0145] In additional or alternative embodiments, the UE is configured to report a maximum number of beams per cell = 2, but there 3 beams with available time-domain prediction(s) of beam measurement information. And, for each of these beams the UE has available predicted RSRP (denoted pRSRP) and predicted RSRQ, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam Cell C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein pRSR(B) > pRSRP(A) > pRSRP(C). Note that pRSRP(A,k) denotes the predicted RSRP value of beam A in a future time instance indicated by the value k e.g. k-th future time instance.

[0146] In additional or alternative embodiments, the sorting quantity is one of the configured beam-based reporting prediction quantities (not necessarily related to the trigger quantity) in this example: pRSRP and pRSRQ. Considering the sub-option in which when multiple beam-based reporting prediction quantities are configured, and pRSRP is one of them, the UE uses pRSRP as the sorting quantity, the UE considers pRSRP and the sorting quantity for the second example. In other words, since pRSRP is configured as one of the beam-based reporting prediction quantities, the UE determines pRSRP to be the sorting quantity, and sorting the beams per cell in decreasing pRSRP order leads to the following order:1) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);2) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);3) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);And, since the maximum number of cells = 2, only beams in position 1 and 2 for that cell are included in the RRC Measurement Report and these are the beams for which the UE includes time-domain prediction(s) of beam measurement information such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ, for cells B and A.

[0147] In some examples, the UE determines one of the beam-based reporting prediction quantities to be the sorting quantity for determining the beams per cell for which the UE includes the time-domain prediction(s) of beam measurement information.

[0148] One of the advantages of these embodiments is that the predicted values are not only included but influence the sorting of the beams per cell i.e. which beams to include in the RRC Measurement Report per cell, and enables the possibility to include in the RRC Measurement Report beams which shows excellent predicted values in the future (e.g. very high pRSRP for future time instances), despite note being the strongest for the actual measurements.

[0149] Embodiments associated with a sorting quantity being equivalent to a beam-based prediction reporting quantity (associated with a trigger quantity) are described below.

[0150] In some embodiments, the UE determines that the subset of ‘N’ beams of a cell for which to include time -domain prediction(s) of beam measurement information are the top ‘N’ beams of a cell sorted according to a sorting quantity which is based on 3) a beam-based prediction reporting quantity the UE is configured with (e.g. predicted RSRP), associated to a trigger quantity the UE is configured with (e.g. trigger quantity RSRP). In other words, this is asif the UE would determine the sorting quantity to be the trigger quantity, but the sorting would be performed based on the associated predicted quantity.

[0151] In some examples, when the RRC Measurement Report in which the UE is configured to include time-domain prediction(s) of beam measurement information is an event- triggered RRC Measurement Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to eventTriggered), the UE determines that the sorting quantity is a beam-based reporting prediction quantity associated to a trigger quantity.

[0152] In additional or alternative examples, for a given RRC Measurement Report for which the UE needs to include time-domain prediction(s) of beam measurement information (such as pRSRQ), the UE is configured with one or more beam-based reporting prediction quantities. That indicates to the UE what predicted quantities (e.g. pRSRP and / or pRSRQ, and / or pSINR) per beam are to be included in an RRC Measurement Report per cell. That also indicates to the UE which prediction quantities are to be inferred by an AI / ML model for beams of a cell i.e. which inferences to produce by the AI / ML model, since there are the ones to be included in the RRC Measurement Report. The beam-based reporting prediction quantities may be configured in the IE ReportConfigNR, in which an event-triggered RRC Measurement Report is also configured (i.e. reportType set to eventTriggered), to indicate which beam-based reporting prediction quantities are to be included in the report, when triggered.

[0153] In additional or alternative examples, the sorting quantity is a beam-based reporting prediction quantity associated to a trigger quantity. The association may be that they are of the same type e.g. if RSRP is a measurement quantity, its associated predicted quantity is predicted RSRP. In some examples, when RSRP is set as the trigger quantity, the UE uses pRSRP as the sorting quantity. In additional or alternative examples, when RSRQ is set as the trigger quantity, the UE uses pRSRQ as the sorting quantity. In additional or alternative examples, when SINR is set as the trigger quantity, the UE uses pSINR as the sorting quantity.

[0154] In additional or alternative examples, the UE is configured to include in an RRC Measurement Report time-domain prediction(s) of beam measurement information, such as the following beam- based reporting prediction quantities predicted RSRP and / or predicted RSRQ, for the beams per cell which are to be included in the RRC Measurement Report. When that is an event-triggered report i.e. reportType in IE ReportConfigNR set to eventTriggered, for an event A3 (entering / entry condition: neighbour cell becomes an offset better than SpCell e.g. PCell), with trigger quantity set to RSRQ (e.g. aN-Offset, of IE MeasTriggerQuantityOffset, set to ‘rsrq’), the entering / entry condition is considered fulfilled when neighbour cell’s RSRQ becomes offset better than the SpCell ’s RSRQ).

[0155] In some embodiments, the UE is configured to report a maximum number of beams per cell = 2, but there 3 beams for a given cell. And, for each of these beams the UE has available predicted RSRP (denoted pRSRP) and predicted RSRQ, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein:RSRQ(B) > RSRQ(A) > RSRQ(C) pRSRP(C, 1) > pRSRP(B, 1) > pRSRP(A, 1) pRSRQ(C, 1) > pRSRQ(A, 1) > pRSRQ(B, 1)

[0156] Herein, pRSRQ(A,k) denotes the predicted RSRQ value of beam A in a future time instance indicated by the value k e.g. k-th future time instance.

[0157] In some embodiments, the sorting quantity is the beam-based reporting prediction quantity associated with the trigger quantity, in this example: pRSRQ (associated with RSRQ, which is the trigger quantity). In other words, since RSRQ is configured as trigger quantity and one of the beam-based reporting prediction quantities is pRSRQ, the UE determines pRSRQ to be the sorting quantity, and sorting the beams per cell in decreasing pRSRQ order leads to the following order:1) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);2) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);3) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);And, since the maximum number of beams per cell to report time-domain prediction(s) = 2, only beams in position 1 and 2 are included in the RRC Measurement Report for that particular cell, for including time-domain prediction(s) of beam measurement information.

[0158] In some examples, the UE determines one of the beam-based reporting prediction quantities to be the sorting quantity for determining the beams per cell for which the UE includes the time-domain prediction(s) of beam measurement information. The sorting takes into account the values of the time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values.

[0159] One of the advantages of these embodiments is that the predicted values are not only included but influence the sorting i.e. which beams per cell to include in the RRC Measurement Report, and enables the possibility to include in the RRC Measurement Report beams per cell which shows excellent predicted values in the future (e.g. very high pRSRP for future time instances), despite note being the strongest for the actual measurements. At the same time, it considers the trigger quantity configured for a given event.

[0160] In some examples, when the UE is configured to NOT include the time domain prediction(s) of beam measurements, the UE includes a sorted / ranked list of the beam identities / indexes sorted based on the time domain prediction(s) of the beam measurements.

[0161] In additional or alternative examples, the UE includes beam measurements such as RSRP, RSRQ, SINR associated to the included beams sorted based on the time domain predictions of the beam measurements.

[0162] In additional or alternative examples, the UE includes the beam measurements such as RSRP, RSRQ, SINR associated to the included beams sorted based on the time domain predictions of the beam measurements, when it is configured by the network as part of received configuration.

[0163] In additional or alternative embodiments, including a subset of beams of at least one cell comprises including the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold received as part of configuration. In some examples, the UE may include the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements if requested by the network in the received configuration. In additional or alternative examples, the UE the UE may include the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration

[0164] In some embodiments, the configured predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold can be absThreshSS-BlocksConsolidation in accordance with the 3GPP TS 38.331 version 18.1.0. In another example, network may configure a dedicated / different beam suitability / consolidation threshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0165] In the above example, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’

[0166] Embodiments associated with a sorting quantity including a prediction-based trigger quantity (e.g., pRSRP, pRSRQ, pSINR) of the report is described below.

[0167] In some embodiments, the UE determines that the subset of ‘N’ beams of a cell for which to include time -domain prediction(s) of beam measurement information are the top ‘N’ beams of a cell sorted according to a sorting quantity which is based on 4) a prediction-based trigger quantity the UE is configured with (e.g. predicted RSRP). In other words, this is as if the UE would determine the sorting quantity to be the trigger quantity, which is a prediction-based triggering quantity, and the sorting would be performed based on that prediction-based triggering quantity that triggred the report being sent by the UE to the network.

[0168] In additional or alternative embodiments, the sorting quantity can be the predictionbased trigger quantity, if the prediction of the triggering cells is / are enough accurate e.g., the prediction confidence of the predictions that triggered the report is above a configured confidence score. Otherwise, if the prediction is not enough accurate, the event based report will not be triggered or if the report is triggred the sorting will be done based on the actual measurement(s) of the same quantity e.g., if pRSRP triggered an event-based report but pRSRP confidence / accuracy is not above the confidence / accuracy threshold, the RSRP quantity (i.e., measurement based quantity) will be chosen as a sorting quantity for the beams to be included for a cell in the report.

[0169] When the RRC Measurement Report in which the UE is configured to include mobility related time-domain prediction(s) is an event-triggered Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to predicted- eventTriggered), the UE determines that the sorting quantity is the trigger quantity which is one of the prediction quantity e.g., pRSRP, pRSRQ, pSINR.

[0170] In some examples, for a given Report for which the UE needs to include mobility related time-domain prediction(s) (such as pRSRP, and / or pRSRQ and / or pSINR), the UE is configured with one or more triggering quantities (e.g., the prediction quantity used in the prediction form of aN-Threshold (for eventAl, eventA2, eventA4, eventA4Hl and eventA4H2) or in the a5-Threshold2 (for eventA5, eventA5Hl and eventA5H2) or in the prediction form of. aN-Offset (for eventA3, eventA3Hl, eventA3H2 and eventA6) or in the prediction form of xl- Threshold2 (for eventXl)).

[0171] In additional or alternative examples, the sorting quantity is the prediction-based triggering quantity that eventually triggered the measurement report. In some examples, when the pRSRP value triggered the measurement report, the UE uses pRSRP as the sorting quantity to include the beam predictions associated to the cell(s) included in the report. In additional or alternative examples, when the pRSRQ value triggered the measurement report, the UE uses pRSRQ as the sorting quantity to include the beam predictions associated to the cell(s) included in the report. In additional or alternative examples, when the pSINR value triggered themeasurement report, the UE uses pSINR as the sorting quantity to include the beam predictions associated to the cell(s) included in the report.

[0172] In additional or alternative embodiments, when the pRSRP value triggered the measurement report and the prediction confidence / accuracy is above a certain threshold, the UE uses pRSRP as the sorting quantity otherwise RSRP will be chosen as sorting quantity to include the beam predictions associated to the cell(s) included in the report. In additional or alternative embodiments, when the pRSRQ value triggered the measurement report and the prediction confidence / accuracy is above a certain threshold, the UE uses pRSRQ as the sorting quantity otherwise RSRQ will be chosen as sorting quantity to include the beam predictions associated to the cell(s) included in the report. In additional or alternative embodiments, when the pSINR value triggered the measurement report and the prediction confidence / accuracy is above a certain threshold, the UE uses pSINR as the sorting quantity otherwise SINR will be chosen as sorting quantity to include the beam predictions associated to the cell(s) included in the report.

[0173] In additional or alternative embodiments, the UE is configured to trigger and include in a Report mobility related time-domain prediction(s) and or measurements, for the cells which are to be included in the Report upon being triggered upon fulfilment of a prediction-based event. When that is an event-triggered report i.e. reportType in IE ReportConfigNR set to prediction-eventTriggered, for an predicted event A3 (entering / entry condition: the prediction of a quantity (pRSRP, pRSRQ, pSINR) of a neighbour cell becomes an offset better than SpCell e.g. PCell), with trigger quantity set to predicted RSRQ (e.g. a3 -Offset, of IE MeasTriggerQuantityOffset, set to predicted ‘rsrq’), the entering / entry condition is considered fulfilled when neighbour cell’s predicted RSRQ becomes offset better than the SpCell ’s predicted RSRQ).

[0174] In some embodiments, the UE is configured to report a maximum number of beams = 2, but there are 3 beams with available predictions. And, for each of the beams the UE has available predicted RSRP (denoted pRSRP) and predicted RSRQ, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein:RSRQ(B) > RSRQ(A) > RSRQ(C), as in the first example pRSRP(C, 1) > pRSRP(B, 1) > pRSRP(A, 1) pRSRQ(C, 1) > pRSRQ(A, 1) > pRSRQ(B, 1)

[0175] As before, pRSRP(A,k) denotes the predicted RSRP value of cell A in a future time instance indicated by the value k e.g. k-th future time instance.

[0176] In additional or alternative embodiments, the sorting quantity is the prediction-based trigger quantity, in this example: pRSRQ that fulfilled the triggering condition of an event and hence triggred a report. Therefore the UE sorts the beams for the included cells in the report in decreasing pRSRQ order which leads to the following order:1) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);2) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);3) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);And, since the maximum number of beams to be included in the report is 2, only beams in position 1 and 2 associated to the cell are included in the RRC Measurement Report and these are the beams (i.e., beam C and beam A) for which the UE includes the mobility related timedomain prediction(s), such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ.

[0177] In some examples, pRSRQ values may not be included in the report if they are not among the reporting quantity. In other words, the UE sorts the reporting quantities using the prediction-based trigger quantity while the prediction-based trigger quantity is not included in the report.

[0178] In additional or alternative embodiments, the UE only takes into account the prediction quantities of the cells in which the accuracy / confidence of the predictions is above a minimum configured threshold and discard the rest of the cells with predictions of the triggered quantities with lower than threshold accuracy / confidence.

[0179] In additional or alternative embodiments, the UE performs the sorting based on the measurement equivalent quantity of the prediction-based quantity. For example, if the measurement report triggering quantity is pRSRP the UE performs sorting of the beam(s) included in the report based on the measurement quantity of RSRP, or if the measurement report triggering quantity is pRSRQ, the UE performs sorting of the beam(s) included in the report based on the measurement quantity of RSRQ. In another example if the measurement report triggering quantity is pSINRthe UE performs sorting of the beam(s) included in the report based on the measurement quantity of SINR. This is to avoid missing inclusion of the beams for which the time domain prediction does not exist while the legacy measurements indicate a very high quality. Such beams would be missing in the measurement report, if the UE sorts the beam(s) of a cell included in the measurement report based on the prediction-based triggering quantities.

[0180] In some examples, when the UE is configured to NOT include the time domain prediction(s) of beam measurements, the UE includes a sorted / ranked list of the beam identities / indexes sorted based on the time domain prediction(s) of the beam measurements.

[0181] In additional or alternative examples, the UE includes beam measurements such as RSRP, RSRQ, SINR associated to the included beams sorted based on the time domain predictions of the beam measurements.

[0182] In additional or alternative examples, the UE includes the beam measurements such as RSRP, RSRQ, SINR associated to the included beams sorted based on the time domain predictions of the beam measurements, when it is configured by the network as part of received configuration.

[0183] In additional or alternative examples, including a subset of beams of at least one cell comprises including the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold received as part of configuration.

[0184] In additional or alternative examples, the UE may include the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements if requested by the network in the received configuration

[0185] In additional or alternative examples, the UE the UE may include the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration

[0186] In additional or alternative examples, the configured predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold can be absThreshSS-BlocksConsolidation in accordance with the 3GPP TS 38.331 version 18.1.0. In another example, network may configure a dedicated / different beam suitability / consolidation threshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0187] In additional or alternative examples, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’.

[0188] Embodiments herein may focus on the A3 event, but the same innovations are applicable to Al, A2 and A6 events.

[0189] Event A3 is defined in the RRC TS 38.331 (version 18.1.0) according to the following, wherein the event is fulfilled if all the measurements in the (TTT) period fulfil the entry condition (Inequality A3-1) of the A3 event.

[0190] Prediction of the A3 event can be seen as applying A3 entry condition(s) on the predicted quantities e.g., predicted RSRP (pRSRP) value associated with a future instance instead of the actual measurements (i.e., using mobility related time-domain prediction(s)), as shown below

[0191] Once the UE mobility related time-domain prediction(s) and evaluation of the condition(s) based on the prediction-based trigger quantity indicate fulfilment of the A3 event for a period of time so called Time-To-Trigger (TTT), the UE sends a report to the network including the available measurements and / or predictions. This is schematically shown in FIG. 3.

[0192] Using mobility related time-domain prediction(s) in A3 event prediction (i.e., monitoring fulfilment of the entering condition(s) in the predicted A3 event based on predictionbased trigger quantity which is part of mobility related time-domain prediction(s)).

[0193] Note that the report sent by the UE upon fulfilment of the entry condition(s) associated to the prediction-based event, the UE sends a report. In an embodiment the report is RRC measurement report but it can be a new report by which the UE sends the prediction(s) to the network. In another embodiment the report can be an enriched / enhanced version of the measurement report including the measurement and predictions (time domain mobility related prediction and / or the spatial or frequency related predictions).

[0194] Embodiments associated with a sorting quantity including beam -based measurement reporting quantity (rule-based) are described below.

[0195] In some embodiments, the UE determines that the subset of ‘N’ beams of a cell for which to include time -domain prediction(s) of beam measurement information are the top ‘N’ beams of a cell sorted according to a sorting quantity which is is based on 2) A beam-based measurement reporting quantity the UE is configured with (e.g. RSRP, RSRQ, SINR).

[0196] When the RRC Measurement Report in which the UE is configured to include timedomain prediction(s) of beam measurement information is a periodical RRC Measurement Report, the UE determines that the sorting quantity is a beam-based reporting quantity.

[0197] In the case of periodical measurement reports, the subset of ‘N’ beams of a cell corresponds to a subset of the beams allowed to be included in the measurement report per cell determined to be included e.g. explicitly configured in a list of beams per cell, associated to a particular SSB frequency and / or measurement object.

[0198] When the RRC Measurement Report in which the UE is configured to include timedomain prediction(s) of beam measurement information is a periodical RRC MeasurementReport (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to PeriodicalReportConfig), the UE determines that the sorting quantity is one of the beam-based reporting quantities, according to the following rule: if a single beam-based reporting quantity is configured, that is the sorting quantity; else if RSRP is configured, RSRP is the sorting quantity; else (RSRP is not configured), RSRQ is the sorting quantity. According to this rule, SINR is determined to be the sorting quantity when it is configured as the single beambased reporting quantity.

[0199] In some embodiments,, the UE is configured to include in an RRC Measurement Report time -domain prediction(s) of beam measurement information, such as the following beam -based reporting prediction quantities predicted RSRP and / or predicted RSRQ, for the beams per cell which are to be included in the RRC Measurement Report. In the example, that is a periodical report so the UE is also configured with one or more beam-based reporting quantities i.e. measurement quantities for which the UE is to include beam measurement information, e.g., RSRP and RSRQ. The UE is configured to report a maximum number of beams per cell = 2, but there are 3 beams for which the UE has available time-domain prediction(s) of beam measurement information.

[0200] For each of these beams the UE has available predicted RSRP (denoted pRSRP) and predicted RSRQ, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein:RSRP(C) > RSRP(A) > RSRP(B)RSRQ(B) > RSRQ(A) > RSRQ(C) pRSRP(C, 1) > pRSRP(B, 1) > pRSRP(A, 1) pRSRQ(C, 1) > pRSRQ(A, 1) > pRSRQ(B, 1)

[0201] As before, pRSRP(A,k) denotes the predicted RSRP value of a beam A of a cell in a future time instance indicated by the value k e.g. k-th future time instance.

[0202] In some embodiments, the sorting quantity is one of the configured beam-based reporting quantities, in this example: RSRP and RSRQ. And, since multiple beam -based reporting quantities are configured, and RSRP is configured as one of them, the UE determines RSRP to be the sorting quantity. The UE sorts the beams per cell in decreasing RSRP order which leads to the following order:1) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);2) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);3) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);And, since the maximum number of beams per cell for including time-domain predictions of beam measurement information = 2, only beams in position 1 and 2 for that cell are included in the RRC Measurement Report and these are the beams for which the UE includes the timedomain predictions of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ: beams C and A.

[0203] In some examples, the UE determines one of the beam-based reporting quantities to be the sorting quantity for determining the beams per cell for which the UE includes the timedomain predictions of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values.

[0204] One of the advantages of these examples is that the predicted values are included opportunistically for the beams for which the UE would anyways report beam measurement information in a legacy RRC Measurement Report.

[0205] In some examples, when the UE includes the subset of ‘N’ beams of the at least one cell the UE includes the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0206] In additional or alternative examples, the UE includes the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements, when it is explicitly configured by the network in the received configuration (otherwise only beam identifiers for the predicted beams are included).

[0207] In additional or alternative examples, the UE the UE includes the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration.

[0208] In additional or alternative examples, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’.

[0209] In additional or alternative examples, the UE is configured with a predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) which is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold (associated to beam measurement information) can be absThreshSS-BlocksConsolidation in accordance with the 3GPP TS 38.331 version 18.1.0. In another example network may configure a dedicated / different beam suitability / consolidationthreshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0210] Embodiments associated with a Sorting quantity including a beam-based prediction reporting quantity (rule-based) are described below.

[0211] In some embodiments, the UE determines that the subset of ‘N’ beams of a cell are the top ‘X’ beams per cell sorted according to a sorting quantity which is based on 3) a beambased prediction reporting quantity the UE is configured with (e.g. beam -based predicted RSRP), based on a rule which prioritizes a beam-based prediction reporting quantity.

[0212] When the RRC Measurement Report in which the UE is configured to include timedomain prediction(s) of beam measurement information is a periodical RRC Measurement Report (e.g. when the measld has an associated IE ReportConfigNR which includes a reportType set to PeriodicalReportConfig), the UE determines that the sorting quantity is a beam-based reporting prediction quantity.

[0213] In some examples, for a given RRC Measurement Report for which the UE needs to include time-domain prediction(s) of beam measurement information (such as pRSRQ), the UE is configured with one or more beam-based reporting prediction quantities. That indicates to the UE what beam-based predicted quantities (e.g. pRSRP and / or pRSRQ, and / or pSINR) are to be included in an RRC Measurement Report per cell to be included in the RRC Measurement Report. That also indicates to the UE which beam-based prediction quantities are to be inferred by an AI / ML model i.e. which inferences to produce by the AI / ML model, since there are the ones to be included in the RRC Measurement Report. The beam-based reporting prediction quantities may be configured in the IE ReportConfigNR, in which a periodical RRC Measurement Report is also configured (i.e. reportType set to periodical), to indicate which beam-based reporting prediction quantities are to be included in the report, when triggered.

[0214] In additional or alternative examples, the sorting quantity is one of the configured beam -based reporting prediction quantities.

[0215] In additional or alternative examples, when a single beam -based reporting prediction quantity is configured, the UE uses that single beam-based reporting prediction quantity as the sorting quantity e.g. pSINR.

[0216] In additional or alternative examples, when multiple beam -based reporting prediction quantities are configured, and pRSRP is one of them, the UE uses pRSRP as the sorting quantity e.g. pSINR.

[0217] In additional or alternative examples, when multiple beam -based reporting prediction quantities are configured, and pRSRP is not one of them, the UE uses pRSRQ as the sorting quantity e.g. pSINR.

[0218] In additional or alternative examples, when multiple beam -based reporting prediction quantities are configured, one of them is explicitly indicated to be the sorting quantity.

[0219] In additional or alternative embodiments, the UE is configured to include in an RRC Measurement Report time-domain prediction(s) of beam measurement information, such as the following beam-based reporting prediction quantities predicted RSRP and / or predicted RSRQ, for the cells which are to be included in the RRC Measurement Report. When that is periodical report the UE transmits an RRC Measurement Report according to a configured periodicity, in which the reporting period is configured at the UE e.g. in the IE ReportConfigNR.

[0220] In some embodiments, the UE is configured to report a maximum number of beam per cell for including the time-domain prediction(s) of beam measurement information, = 2, but there 3 beams with available time-domain prediction(s) of beam measurement information. And, for each of these 3 beams, for a given cell, the UE has available predicted RSRP (denoted pRSRP) and predicted RSRQ, as follows:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); wherein:RSRQ(B) > RSRQ(A) > RSRQ(C), as in the first example pRSRP(C, 1) > pRSRP(B, 1) > pRSRP(A, 1) pRSRQ(C, 1) > pRSRQ(A, 1) > pRSRQ(B, 1)

[0221] As before, pRSRP(A,k) denotes the predicted RSRP value of beam A of a cell in a future time instance indicated by the value k e.g. k-th future time instance.

[0222] In some examples, the sorting quantity is one of the configured beam-based reporting prediction quantities, in this example: pRSRP and pRSRQ. Considering the sub-option in which when multiple beam-based reporting prediction quantities are configured, and pRSRP is one of them, the UE uses pRSRP as the sorting quantity, the UE considers pRSRP and the sorting quantity for the second example. In other words, since pRSRP is configured as one of the beam-based reporting prediction quantities, the UE determines pRSRP to be the sorting quantity, and sorting the beams per cell in decreasing pRSRP order leads to the following order:1) Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1);2) Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1);3) Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);And, since the maximum number of beams to include time-domain predictions of beam measurement information = 2, only beams in positions 1 and 2 per cell are included in the RRC Measurement Report and these are the beams for which the UE includes the time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ, Beams C and B.

[0223] In some examples, the UE determines one of the beam-based reporting prediction quantities to be the sorting quantity for determining the beams per cell for which the UE includes the time-domain prediction(s) of beam measurement information, such as predicted RSRP (denoted pRSRP) and / or predicted RSRQ and / or predicted SINR values. The sorting takes into account the values of the time-domain prediction(s) of beam measurement information, per cell to be included in the measurement report.

[0224] One of the advantages of these embodiments is that the predicted values per beam are not only included but influence the sorting i.e. which beams per cell to include in the RRC Measurement Report, and enables the possibility to include in the RRC Measurement Report beams per cell which shows excellent predicted values in the future (e.g. very high pRSRP for future time instances), despite note being the strongest for the actual measurements.

[0225] In some examples, when the UE includes the subset of ‘N’ beams of the at least one cell the UE includes the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0226] In additional or alternative examples, the UE includes the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements, when it is explicitly configured by the network in the received configuration (otherwise only beam identifiers for the predicted beams are included).

[0227] In additional or alternative examples, the UE the UE includes the beam identifiers of the sorted beams AND associated beam measurements in the report if requested by the network in the received configuration.

[0228] In additional or alternative examples, the total number of included beams (subset of the available beams which are sorted based on the sorting quantity) can be less than maximum number of allowed beams denoted as ‘N’.

[0229] In additional or alternative examples, the UE is configured with a predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) which is set to the same value as a beam suitability / consolidation threshold(associated to beam measurement information). In this example, the predicted beam suitability / consolidation threshold (associated to beam measurement information) can be absThreshSS-BlocksConsolidation in accordance with the 3GPP TS 38.331 version 18.1.0. In another example network may configure a dedicated / different beam suitability / consolidation threshold for the prediction quantities i.e., the beam is included in the list of beams in the measurement report if its sorting quantity that is a prediction quantity is above the dedicated predicted beam suitability / consolidation threshold configured by the network.

[0230] In aperiodic reporting or semi-persistent reporting, the UE receives a request from the network (e.g. in an RRC message) and, in response to the request, the UE reports one or more measurement results e.g. in an RRC Measurement Report, including beam measurement information. In the case of aperiodic, a single RRC Measurement Report is transmitted. In the case of semi-persistent the UE transmits multiple RRC Measurement reports after the request e.g. periodically.

[0231] In the case of aperiodic or semi-persistent measurement reports, that the subset of ‘N’ beams of a cell (for which to report time-domain prediction(s) of beam measurement information) corresponds to beams of a cell which may be indicated in the request, or beams of a cell associated to a configuration indication included in the request e.g. a reporting configuration identifier and / or a measurement configuration identifier. In one sub-option, the received request include beam identifiers (e.g. SSB indexes and / Or CSI-RS resource identifiers) for which the UE needs to include beam measurement information.

[0232] In aperiodic or semi-persistent measurement reporting, any of the embodiments / options in which the UE determines the sorting quantity to be i) a beam-based measurement reporting quantity (rule-based) or ii) a beam-based prediction reporting quantity (rule-based) may be applied for such a case.

[0233] In some examples, the UE determines the sorting quantity to be a quantity indicated in the request message e.g. RSRP, RSRQ, SINR.

[0234] In additional or alternative examples, the UE receives the request message which indicates to the UE that the UE is to use as sorting quantity a beam-based measurement reporting quantity e.g. RSRP, RSRQ, SINR.

[0235] In additional or alternative examples, the UE receives the request message which indicates to the UE that the UE is to use as sorting quantity a beam-based prediction reporting quantity e.g. predicted RSRP, predicted RSRQ, predicted SINR.

[0236] In additional or alternative examples, when the UE includes the subset of ‘N’ beams of the at least one cell the UE includes the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sortingquantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0237] In additional or alternative examples, the time-domain prediction(s) of beam measurement information are not associated to a beam-measurement quantity, such as when the prediction(s) comprise predicted location related information and / or predicted trajectory information and / or predicted beam target information (beam identifier the UE is likely to move in a future time instance).

[0238] In additional or alternative examples, the UE may determine the sorting quantity to be associated to one of these metrics, and the UE sorts the beams per cell in decreasing order to likelihood of the beam being a beam the UE would select in the cell e.g. during random access in a handover. In other words, the top ‘N’ beams to include in the measurement report per cell are the beams for which predictions indicate that the UE is most likely to move to in a future time instance for a target cell.

[0239] In additional or alternative examples, when the UE includes the subset of ‘N’ beams of the at least one cell the UE includes the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0240] In the following it is disclosed different alternatives to include the subset of ‘N’ beams per cell in the measurement report, for which the UE includes the time-domain predictions of beam measurement information.

[0241] (same subset of beams for a cell) In one option, the subset of ‘N’ beams per cell for which the UE includes the time-domain predictions of beam measurement information (e.g. pRSRP), are the ‘N’ beams per cell for which the UE includes the beam -based measurement information (e.g. as configured as a reporting quantity and / or as trigger quantity). Thus, when the sorting function is performed and the ‘N’ beams for a cell are selected to be included according to a sorting quantity (top N, in decreasing order according to the sorting quantity), the UE includes the beam measurement information (e.g. beam identifiers and / or associated L3 filtered measurements) for these beams and one or more available time-domain predictions of beam measurement information (e.g. pRSRP).

[0242] (separate subsets of beams per cell) In another option, the subset of ‘N’ beams per cell for which the UE includes the time-domain predictions of beam measurement information (e.g. pRSRP) are not necessarily the same ‘M’ beams for which the UE includes beam measurement information. In other words, for a given cell determined by the UE to be included in the measurement report, the UE performs a first sorting function (defined according to themethod (e.g. based on a beam-based prediction measurement quantity associated to the trigger quantity, such as pRSRQ) for sorting the beams per cell for which to include the time-domain predictions for beam measurement information (e.g. pRSRP) and a second sorting function for sorting the beams for which to include the beam measurement information (e.g. based on trigger quantity, in the case of an event triggered RRC Measurement Report).

[0243] In additional or alternative examples, the additional sorting function is the same as the first sorting function.

[0244] In additional or alternative examples, the additional sorting function is different than the first sorting function.

[0245] The fact that the subsets of beams per cell are separated (e.g. included in two different ‘lists’ or ‘sets’ in the RRC Measurement Report per reported cell and, possibly per RS type) does not preclude that the same beams are included e.g. in case the first and the second sorting function(s) are the same, or in case the results of the sorting leads to the same output even in case the sorting fimction(s) are different.

[0246] In additional or alternative examples, for this case of two sorting functions and two separated subsets of beams per cell, the UE is configured with two values of maximum number of beams per cell to report: a first value ‘N’ associated to the number of beams for which to include the time -domain prediction(s) of beam measurement information and a second value ‘M’ associated to the number of beams per cell for which to include the beam measurement information.

[0247] Thus, when the first sorting function is performed and the ‘N’ beams per cell are selected to be included according to a sorting quantity (top N, in decreasing order according to the sorting quantity), the UE includes the for these cells the one or more mobility related timedomain predictions.

[0248] And, when the second sorting function is performed and the ‘M’ beams per cell are selected to be included according to a sorting quantity (top M, in decreasing order according to the sorting quantity), the UE includes the for these beams per cell the beam measurement information.

[0249] In another sub-option, for this case of two sorting functions and two separated subsets of beams per cell to be reported, the UE is configured with a single value for the maximum number of beams per cell i.e. the value ‘N’ associated to the number of beams for which to include the time-domain prediction(s) of beam measurement information is the same value associated to the number of beams per cell for which to include the beam measurement information.

[0250] Thus, when the sorting function is performed and the ‘N’ beams per cell are selected to be included according to a sorting quantity (top N, in decreasing order according to the sorting quantity), the UE includes the beam measurement information per cell for these beams and one or more available time-domain prediction(s) of beam measurement information.

[0251] In some embodiments, the UE determines a subset of ‘N’ beams per cell for which to include time-domain prediction(s) beam measurement information in a measurement report (e.g. RRC Measurement Report).

[0252] In some examples, the time-domain prediction(s) of beam measurement information may be one or more time-domain predictions related to UE beam-based mobility. For example, when the input to a Al / ML model is one or more values of a certain type, and the output of the ML model are time-domain predictions such as one or more indications, such as values of a certain type at a future time instance (such as predicted measurement values) or within a time window in a future time instance. The values of a certain type may be for example measurement values (e.g. RSRP, RSRQ or SINR, of a cell and / or beam and / or reference signal), UE location(s) such as beams or positions, and those values may be obtained (e.g. measured) by the UE or given.

[0253] In additional or alternative examples, the time-domain prediction(s) of beam measurement information may be one of more indications of predicted values of radio measurements per beam )also called time-domain prediction of a beam measurement), in future time instances, such as predicted RSRP, predicted RSRQ, predicted SINR per beam. These may be associated to beam-level radio measurements, such as RSRP, RSRQ or SINR associated with a beam such as an SSB or CSI-RS beam identity related to a cell.

[0254] In additional or alternative examples, the time-domain prediction(s) of beam measurement information may be one or more indications of one or more predicted beams of a target cell for mobility, each cell identified with a cell global identity (CGI), PCI and ARFCN, or other form of cell identifier (e.g. candidate cell identifier). In this case, one option is that the UE determines the sorting quantity to be the likelihood of the beam of the target cell becoming a selected beam in a random access procedure during a handover. In other words, suppose that there are 3 beams of a target cell and the UE can only include 2 beams in a measurement report, the UE includes the 2 with highest chances to be selected during random access in case such a cell is selected for handover.

[0255] In additional or alternative examples, the time-domain prediction(s) of beam measurement information may be one or more indications of one or more predicted UE locations, where a UE location may be, for example, a UE position coordinate.

[0256] In this case, one option is that the UE determines the sorting quantity to be the likelihood of the beam becoming a beam of a target cell in a handover.

[0257] A confidence value associated with any of the above indications, indicating the confidence of predicted values.

[0258] A confidence value associated with any of the above indications, indicating the confidence of the AI / ML model in predicted values.

[0259] A validity time information associated with any of the above indications, indicating a time interval in which the predicted values are valid

[0260] A time-domain prediction(s) of beam measurement information may also be a value derived from one or more time-domain prediction(s) of beam measurements e.g. an average, a maximum of multiple values, values above a threshold, etc.

[0261] A beam identifier such as an SSB index, Mobility Reference Signal identifier, RS identifier and / or CSI-RS resource identifier which identifies a beam associated to a future time instance.

[0262] In this case, the time-domain prediction(s) of beam measurement information comprises a beam identifier of the beam of the cell such as an SSB index

[0263] In one option, the beam identifier of the beam of the cell is derived from at least one time-domain prediction of a beam measurement of that beam, wherein the at least one timedomain prediction of a beam measurement comprises one or more of: predicted RSRP, predicted RSRQ, predicted SINR.

[0264] In one option, the beam identifier of the beam of the cell is provided as an output of an inference function and / or AI / ML model for mobility and / or RRM related prediction.

[0265] In one option, the time-domain prediction(s) of beam measurement information comprises a beam identifier of the beam of the cell AND one or more time-domain prediction of beam measurements, wherein that comprises one or more of: predicted RSRP, predicted RSRQ, predicted SINR. In other words, the UE includes in a measurement report, for a cell, and for a beam, its beam identifier (associated to future time instance(s)) and associated time-domain prediction of beam measurement.

[0266] When the time-domain prediction(s) of beam measurement information comprises one of more indications of predicted values of radio measurements for one or more beams, in future time instances, such as predicted RSRP, predicted RSRQ, predicted SINR, one may denote that to be a time-domain beam prediction e.g. for a cell X, also denoted a time-domain prediction of a beam measurement.

[0267] In one option the time-domain beam prediction of a beam (e.g. SSB) of a cell X corresponds to or is associated to the value of a measurement quantity (e.g. an RSRP value, anRSRQ value, an SINR value), or rather a predicted value, representing the measurement quantity of a beam 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 .

[0268] In one option, the time-domain beam prediction of a beam of cell X is calculated (inferred) 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.

[0269] An AI / ML model can be designed to realize the beam-level measurement prediction in time-domain i.e. to produce one or more time-domain prediction(s) of beam measurement information. An AI / ML model can 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 measurement quantities and beam IDs (e.g. SSB indexes and / or CSI-RS resource identifiers), the AI / ML model may also provide additional information like confidence level of the model output, the validation time of the predicted measurements, etc.

[0270] The designed AI / ML model can be deployed at the UE and associated to a beam prediction feature / functionality, or a RRM prediction feature / functionality or a Mobility prediction feature / functionality. 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.

[0271] Multiple examples are described below regarding how to design an AI / ML model to achieve the time-domain prediction of beam measurement information.

[0272] For the AI / ML model used for time-domain prediction of beam measurement information, 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 (e.g. per beam and / or SSB and / or CSI-RS resource, per cell) as the model input, where the beam measurement results are obtained based on measuring some reference signals per beam (per cell), 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.

[0273] 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 bepredicted 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.

[0274] In an example for the AI / ML model, the AI / ML model used for time-domain predictions of beam measurement information 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 beam measurements results as the model input, where the measurement results are obtained based on measuring one or more reference signals per beam (per cell), 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 fdters 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 per beam of a cell. For pooling layers, it involves sliding a two-dimensional fdter over each channel of feature map and summarizing the features lying within the region covered by the filter. Before the ouput 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 of a cell. Optionally, the output can be the probability values where each value means the probability of the beam to be the best beam of a cell. 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).

[0275] FIG. 4 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 LI -RSRP values per beam measured from 5 consecutive time instances. So, the observation duration Tl=5*40ms=200ms. The time-domain prediction of beam measurement information is at the time instance 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.

[0276] As an example, illustrated in FIG. 5, the AI / ML model is 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 / MLmodel input size is (Nip, 5), where Nip is the number of Ll-RSRPs measured at each of the five time instances. 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-l / K beams with the highest probability can be generated for each prediction time instance.

[0277] As another example, the AI / ML model mentioned in the above design options can be based on transformer encoder architecture. The encoder is composed of a stack of identical layers where each layer has some sub-layers. FIG. 6 illustrates an example of a transformer encoder based NN 600 that receives normalized RSRPs as input. The transformer encoder based NN can include Dense layers 620, 660, a positional embedding layer 630, a transformer encoder layer 700, dropout layer 650, and a loss function 670. FIG. 7 illustrates an example of architecture for the transformer encoder 700. Within the transformer encoder 700, there is a sublayer called multi-head self-attention 800 where normalized RSRPs would be inputted to several (e.g., h) linear layers 740, 760, layer norms 730, 780, a rectified linear unit (ReLU) 750 and concatenate layers 720, 770 to extend the dimension with more information explored, and association between these extended samples can be learned by scaled dot-product attention followed by concatenation and linear fully connected neural network.

[0278] FIGS. 8-9 illustrate the example of multi-head self-attention 800 and scaled dotproduct attention 900.

[0279] In the following it is disclosed the UE actions when there are multiple time-domain predicted measurement values for multiple ’k’ time instances in the future for a beam of a cell e.g. when the AI / ML model at the UE derives as inference and / or outputs the values for a given beam of a cell: pRSRP(A,l), pRSRP(A,2), pRSRP(A,3), ... ., pRSRP(A,k), wherein pRSRP(A,k) denotes the predicted RSRP value of beam A of a cell in a future time instance indicated by the value k e.g. k-th future time instance.

[0280] In the case in which the UE determines the sorting quantity to be e.g. 3) a beambased prediction reporting quantity the UE is configured with, the UE determines a value (e.g. representative value) derived from at least one of the multiple available time-domain prediction(s) of beam measurement information to sort the beams.

[0281] For example, let us assume the following beams for a given cell, determined to be included in the measurement report:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1); pRSRP(A, 2), pRSRQ(A, 2); pRSRP(A, 3), pRSRQ(A, 3);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1); pRSRP(B, 2), pRSRQ(B, 2); pRSRP(B, 3), pRSRQ(B, 3);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); pRSRP(B, 2), pRSRQ(B, 2); pRSRP(B, 3), pRSRQ(B, 3).

[0282] As before, pRSRP(A,k) denotes the predicted RSRP value of a beam A of a cell in a future time instance indicated by the value k e.g. k-th future time instance.

[0283] The UE determines a value per beam of that cell (representative value), of the sorting quantity, to sort the beams for that cell, wherein the value is associated to at least one of the multiple values of a beam-based prediction reporting quantity (e.g. predicted RSRQ values) in the multiple future time instances. The value of the sorting quantity per beam is determine to be one of the following: i) determining the latest time-domain prediction per beam to be the value used by the UE in the sorting; ii) determining the first time-domain prediction per beam to be the value used by the UE in the sorting; iii) determining the maximum value among the time-domain prediction(s) of beam measurement information per beam to be the value used by the UE in the sorting; iv) determining the minimum value among the time-domain prediction(s) of beam measurement information per beam of a cell to be the value used by the UE in the sorting; v) determining an average value of the time-domain prediction(s) per beam to be the value used by the UE in the sorting; vi) determining the maximum with highest accuracy and / or lowest prediction error among the time-domain prediction(s) per beam to be the value used by the UE in the sorting; vii) determining the value associated to a time instance k indicated by the network among the time-domain prediction(s) per beam to be the value used by the UE in the sorting.

[0284] For example, let us assume the UE determines predicted RSRQ as sorting quantity and option i) is used to determine the value to be used for sorting beams i.e. i) UE determines the latest time-domain prediction per beam to be the value used by the UE in the sorting. Thus, this is the input to the sorting function:Beam A: pRSRQ(A, 3);Beam B: pRSRQ(B, 3);Beam C: pRSRQ(C, 3); wherein pRSRQ(C, 3) > pRSRQ(B, 3) > pRSRQ(A, 3).

[0285] In that case, when the maximum number of beams for which to report time-domain predictions of beam measurement information is N=2, the UE includes in the measurementreport forthat cell the beams C and B, and corresponding time-domain beam measurement information for beams C and B (e.g. pRSRP and / or pRSRQ and / or pSINR and associated beam identifiers e.g. SSB indexes).

[0286] In one option, the UE includes in the measurement report, for the included beam of the included cell, only the latest time-domain prediction per cell. In another option, the UE also includes the other values available for other time instances for that beam.

[0287] For example, let us assume the UE determines predicted RSRQ as sorting quantity and option ii) is used to determine the value to be used for sorting i.e. ii) UE determines the first time-domain prediction per beam of a cell to be the value used by the UE in the sorting. Thus, this is the input to the sorting function:Beam A: pRSRQ(A, 1);Beam B: pRSRQ(B, 1);Beam C: pRSRQ(C, 1); wherein pRSRQ(B, 1) > pRSRQ(A, 1) > pRSRQ(C, 1).

[0288] In that case, when the maximum number of beams of a cell to report time-domain predictions of beam measurement information is N=2, the UE would include in the measurement report the beams B and A forthat cell. In one option, the UE includes in the measurement report, for the included cell(s), only the first time-domain prediction of the beams B and A for the cell. In another option, the UE also includes the other values available for other time instances for beams B and A of that cell.

[0289] For example, let us assume the UE determines predicted RSRQ as sorting quantity and option iv) is used to determine the value to be used for sorting i.e. iv) the UE determines an average value of the time-domain prediction(s) per beam to be the value used by the UE in the sorting; Thus, this is the input to the sorting function:Beam A: average (pRSRQ(A, 1); pRSRQ(A, 2); pRSRQ(A, 3))Beam B: average (pRSRQ(B, 1); pRSRQ(B, 2); pRSRQ(B, 3))Beam C: average (pRSRQ(C, 1); pRSRQ(C, 2); pRSRQ(C, 3)) wherein average (pRSRQ(A, 1); pRSRQ(A, 2); pRSRQ(A, 3)) > average (pRSRQ(B, 1); pRSRQ(B, 2); pRSRQ(B, 3)) > average (pRSRQ(C, 1); pRSRQ(C, 2); pRSRQ(C, 3)).

[0290] In that case, when max number of beams per cell to report time-domain predictions of beam measurement information is N=2, the UE would include in the measurement report beams A and B for that cell.

[0291] The benefit here is that this works for the case in which the AI / ML model produces a different number of values for future time instances for the different beams of a cell. This is also an advantage of options iii) and v).

[0292] In one option, the UE derives the same number of values for future time instances per beams of a cell which are considering in the sorting, to be included in the measurement report.

[0293] In one option, the UE includes in the measurement report, for the included beams of an included cell, only the representative values according to one or more of the options above (e.g. i), ii), iii), . . . , vii)) per cell. In another option, the UE also includes the other values available for other time instances.

[0294] In another option, the UE derives different number of values for future time instances for the beams to be included of an included cell.

[0295] For example, let us assume the following scenario for beams A, B, C of a cell:Beam A: RSRP(A), RSRQ(A); pRSRP(A, 1), pRSRQ(A, 1);Beam B: RSRP(B), RSRQ(B); pRSRP(B, 1), pRSRQ(B, 1); pRSRP(B, 2), pRSRQ(B, 2); pRSRP(B, 3), pRSRQ(B, 3);Beam C: RSRP(C), RSRQ(C); pRSRP(C, 1), pRSRQ(C, 1); pRSRP(C, 2), pRSRQ(C, 2);

[0296] As before, pRSRP(A,k) denotes the predicted RSRP value of beam A of a cell in a future time instance indicated by the value k e.g. k-th future time instance. As one can see, there is 1 predicted value for beam A, for pRSRP and pRSRQ; 3 for beam B for pRSRP and pRSRQ; and 2 for beam C.

[0297] In some embodiments, the UE determines predicted RSRQ as sorting quantity and option i) is used to determine the value to be used for sorting. In other words, the UE determines the latest time-domain prediction per beam of a cell to be the value used by the UE in the sorting.

[0298] In one variant, the latest value is the latest per beam of a cell i.e. for beam A: pRSRQ (A,l), for beam B: pRSRQ (B,3) and for beam C: pRSRQ(C,2). Thus, when pRSRQ (A,l) > pRSRQ(C,2) > pRSRQ (B,3) the sorting is as follows:1) Beam A2) Beam C3) Beam B

[0299] In another variant, the latest value is the latest which is common for all beams of a cell i.e. for beam A: pRSRQ (A,l), for beam B: pRSRQ (B, 1) and for beam C: pRSRQ(C,l), since all the beams of that cell (which were listed here) have the first prediction (k= 1 ) as the latest prediction. Thus, when pRSRQ (A,l) > pRSRQ(B,l) > pRSRQ (C, 1) the sorting is as follows:1) Beam A2) Beam B3) Beam C.

[0300] Operations of a communication device 1300 (implemented using the structure of FIG. 13) will now be discussed with reference to the flow chart of FIG. 10 according to some embodiments of inventive concepts. For example, modules may be stored in memory 1310 of FIG. 13, and these modules may provide instructions so that when the instructions of a module are executed by respective communication device processing circuitry 1302, communication device 1300 performs respective operations of the flow chart.

[0301] FIG. 10 illustrates an example of operations performed by a communication device in a communications network that includes a network node.

[0302] At block 1010, processing circuitry 1302 receives, via communication interface 1312, configuration information.

[0303] At block 1020, processing circuitry 1302 generates a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams. In some embodiments, generating the report includes generating the report based on the configuration information.

[0304] In additional or alternative embodiments, generating the report includes selecting (1022) the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0305] In additional or alternative embodiments, generating the report includes sorting (1024) the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0306] In additional or alternative embodiments, generating the report includes generating the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. In some examples, generating the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams includes generating the report to include only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0307] In additional or alternative embodiments, generating the report includes sorting the subset of the plurality of beams based on at least one of: a trigger quantity; a beam -based measurement reporting quantity; a beam-based prediction reporting quantity; and a predictionbased trigger quantity.

[0308] At block 1030, processing circuitry 1302 transmits, via communication interface 1312, the report. In some embodiments, transmitting the report includes at least one of:periodically transmitting the report; transmitting the report in response to an event trigger; semi- persistently transmitting the report; and aperiodically transmitting the report.

[0309] In some embodiments, the report includes a radio resource control, RRC, measurement report.

[0310] In additional or alternative embodiments, the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0311] In additional or alternative embodiments, the mobility related time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurement of the beam that includes at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

[0312] In additional or alternative embodiments, the mobility related time-domain prediction of beam measurement information includes a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

[0313] Various operations from the flow chart of FIG. 4 may be optional with respect to some embodiments of communication devices and related methods.

[0314] Operations of a network node 1300 (implemented using the structure of FIG. 14) will now be discussed with reference to the flow chart of FIG. 11 according to some embodiments of inventive concepts. For example, modules may be stored in memory 1404 of FIG. 14, and these modules may provide instructions so that when the instructions of a module are executed by respective network node processing circuitry 1402, network node 1400 performs respective operations of the flow chart.

[0315] FIG. 11 illustrates an example of operations performed by a network node in a communications network that includes a communication device.

[0316] At block 1110, processing circuitry 1402 generates configuration information to cause a communication device to generate a report based on at mobility related time-domain prediction of beam measurement information. In some embodiments, generating the configuration information includes generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0317] In additional or alternative embodiments, generating the configuration information includes generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0318] In additional or alternative embodiments, generating the configuration information includes generating instructions to cause the communication device to generate the report with a subset of the plurality of beams sorted based on at least one of: a trigger quantity; a beam -based measurement reporting quantity; a beam-based prediction reporting quantity; and a predictionbased trigger quantity.

[0319] At block 1120, processing circuitry 1402 transmit, via communication interface 1406, the configuration information not the communication device.

[0320] At block 1130, processing circuitry 1402 receive, via communication interface 1406, the report. In some embodiments, generating the configuration information includes generating the instructions to cause the communication device to generate the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Receiving the report includes receiving the report including the mobility related timedomain prediction of beam measurement information associated with the plurality of beams.

[0321] In additional or alternative embodiments, generating the configuration information includes generating the instructions to cause the communication device to generate the report to include only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams. Receiving the report comprises receiving the report including only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

[0322] In additional or alternative embodiments, the report includes a radio resource control, RRC, measurement report.

[0323] In additional or alternative embodiments, the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0324] In additional or alternative embodiments, receiving the report includes at least one of: periodically receiving the report; receiving the report in response to an event trigger; semi- persistently receiving the report; and aperiodically receiving the report.

[0325] In additional or alternative embodiments, the mobility related time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurementof the beam that includes at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

[0326] In additional or alternative embodiments, the mobility related time-domain prediction of beam measurement information includes a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

[0327] Various operations from the flow chart of FIG. 5 may be optional with respect to some embodiments of communication devices and related methods.

[0328] Example Embodiments are provided below.

[0329] Embodiment 1. A method at a User Equipment (UE) for determining a subset of ‘N’ beams of at least one cell for which to include time-domain prediction(s) of beam measurement information in a measurement report, the method comprising: receiving a message from a network node including a configuration indicating to the UE to include in the measurement report the one or more time -domain prediction(s) of beam measurement information of the subset of ‘N‘ beams of the at least one cell; including in the measurement report, before transmitting the measurement report, the one or more time-domain prediction(s) of beam measurement information for the subset of ‘N‘ beams of the at least one cell in decreasing order of a sorting quantity, the sorting quantity is determined to be one or more of the following: a trigger quantity the UE is configured with; a beam-based measurement reporting quantity the UE is configured with; a beam-based prediction reporting quantity the UE is configured with; and a prediction-based trigger quantity e.g., pRSRP, pRSRQ, pSINR the UE is configured with; and transmitting a report. In an embodiment the report is a RRC Measurement Report which includes measurements and / or prediction(s). In another embodiment the report is a new (dedicated) report which may only include the prediction information i.e., without including the measurements.

[0330] Embodiment 2. The method of Embodiment 1, wherein the at least one cell for which to include time-domain prediction(s) of beam measurement information may correspond to one or more of: a serving cell, such as a Primary Cell, a Special Cell (SpCell), a SpCell of a Master Cell Group (MCG), a SpCell of a Secondary Cell Group (SCG), PScell, a Secondary Cell (Scell) of the MCG; an SCell of the SCG, etc.);a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for Conditional Handover; a candidate cell for Layer 1 / Layer 2 Triggered Mobility (LTM); a neighbor cell in a serving frequency.

[0331] Embodiment 3. The method of any of Embodiments 1-2, wherein the measurement report is triggered to be transmitted based on one or more of the following criteria: periodically; event-triggered; semi-persistent; aperiodic (e.g. based on a request from the network).

[0332] Embodiment 4. The method of any of Embodiments 1-2, wherein the sorting quantity is determined to be the trigger quantity the UE is configured with when the measurement report is triggered by the fulfillment of an event (i.e. in the case of event-triggered measurement report) with entering conditions based on one or more measurements according to a measurement quantity (e.g. RSRP, RSRQ, SINR).

[0333] Embodiment 5. The method of any of Embodiments 1-2, wherein the sorting quantity is determined to be the beam-based measurement reporting quantity the UE is configured with when the measurement report is triggered to be transmitted periodically (i.e. in the case of periodic measurement report) as follows: when a single reporting quantity is configured, that beam-based reporting quantity is the sorting quantity; when a first measurement quantity (e.g. RSRP) is configured as a beam-based measurement reporting quantity, that first measurement reporting quantity is the sorting quantity; and when a first measurement quantity (e.g. RSRP) is NOT configured as a beam-based measurement reporting quantity, a second measurement reporting quantity (e.g. RSRQ) is the sorting quantity.

[0334] Embodiment 6. The method of any of Embodiments 1-5, wherein the sorting quantity is determined to be the beam-based prediction reporting quantity the UE is configured with which is associated to a trigger quantity the UE is configured with.

[0335] Embodiment 7. The method of Embodiment 6, wherein: when the UE is configured with RSRP a trigger quantity for an event-based measurement report, determining beam-based predicted RSRP to be the sorting quantity.when the UE is configured with RSRQ a trigger quantity for an event-based measurement report, determining beam-based predicted RSRQ to be the sorting quantity. when the UE is configured with SINR a trigger quantity for an event-based measurement report, determining beam-based predicted SINR to be the sorting quantity.

[0336] Embodiment 8. The method of any of Embodiments 1-7, wherein the sorting quantity is determined to be the beam-based prediction reporting quantity the UE is configured with when the measurement report is triggered to be transmitted periodically (i.e. in the case of periodic measurement report) as follows: when a single beam-based prediction reporting quantity is configured, that beam-based reporting quantity is the sorting quantity; when a first beam -based prediction quantity (e.g. predicted RSRP) is configured as a beam-based prediction reporting quantity, that first beam-based prediction quantity is the sorting quantity; when a first beam-based prediction quantity (e.g. predicted RSRP) is NOT configured as a beam-based prediction reporting quantity, a second beam-based prediction reporting quantity (e.g. predicted RSRQ) is the sorting quantity.

[0337] Embodiment 9. The method of Embodiment 1, wherein including the one or more time-domain prediction(s) of beam measurement information for the subset of ‘N‘ beams of the at least one cell in decreasing order of a sorting quantity, is performed for one or more cells the UE has determined to include in the measurement report.

[0338] Embodiment 10. The method of any of Embodiments l-9„ wherein the time-domain prediction(s) of beam measurement information comprises a beam identifier of the beam of the cell e.g. an SSB index and / or an RS identifier and / or a CSI-RS resource identifier and / or a Mobility Reference Signal identifier.

[0339] Embodiment 11. The method of Embodiment 10, wherein a beam identifier of the beam of the cell (e.g. an SSB index and / or an RS identifier and / or a CSI-RS resource identifier and / or a Mobility Reference Signal identifier) is derived from at least one time-domain prediction of a beam measurement of that beam, wherein the at least one time-domain prediction of a beam measurement comprises one or more of: predicted RSRP, predicted RSRQ, predicted SINR.

[0340] Embodiment 12. The method of Embodiment 10, wherein the beam identifier of the beam of the cell (e.g. an SSB index and / or an RS identifier and / or a CSI-RS resource identifier and / or a Mobility Reference Signal identifier) is provided as an output of an inference function and / or AI / ML model for mobility and / or RRM related prediction.

[0341] Embodiment 13. The method of any of Embodiments 1-12, wherein the timedomain prediction(s) of beam measurement information comprises a beam identifier of the beam of the cell AND one or more time-domain prediction of beam measurements (e.g. predicted RSRP, predicted RSRQ, predicted SINR).

[0342] Embodiment 14. The method of any of Embodiments 1-13, wherein the message from a network node indicates (e.g. absence of a parameter within the message) to the UE to include for a cell in the measurement report, one or more beam identifier(s) for the beam(s) which were sorted according to the sorting quantity (i.e., not including the time domain prediction of beam measurements).

[0343] Embodiment 15. The method of any of Embodiments 1-14, wherein the message from a network node indicates to the UE to include in the measurement report for a cell which is to be included, one or more beam identifier(s) for the beam(s) which were sorted according to the sorting quantity, AND one or more time-domain prediction of beam measurements (e.g. predicted RSRP, and / or predicted RSRQ, and / or predicted SINR) for the beam identifiers.

[0344] Embodiment 16. The method of any of Embodiments 1-15, wherein the message from a network node indicates to the UE to include in the measurement report one or more beam measurement information (e.g. beam identifier and / or associated beam measurement(s)) of the subset of ‘N‘ beams of the at least one cell, when the sorting quantity is determined to be a prediction quantity (e.g. sorting quantity is predicted RSRP, or predicted RSRQ, or predicted SINR).

[0345] Embodiment 17. The method of any of Embodiments 1-16, wherein including a subset of ‘N‘ beams of the at least one cell comprises including the beam identifiers of the sorted beams in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0346] Embodiment 18. The method of Embodiment 17, wherein the configured predicted beam suitability / consolidation threshold (associated to time-domain predictions of beam measurement information) is set to the same value as a beam suitability / consolidation threshold (associated to beam measurement information).

[0347] Embodiment 19. The method of any of Embodiments 1 -18„ wherein including a subset of ‘N‘ beams of the at least one cell comprises including the beam identifiers of the sorted beams AND associated time-domain prediction(s) of beam measurements (e.g. predicted RSRP, predicted RSRQ and / or predicted SINR), in decreasing order of a sorting quantity, including the best beam (with strongest value for the sorting quantity) and the remaining beams whose sorting quantity is above a configured predicted beam suitability / consolidation threshold.

[0348] Embodiment 20. The method of any of Embodiments 1-19, wherein when the associated time-domain prediction(s) of beam measurements (e.g. predicted RSRP, predicted RSRQ and / or predicted SINR) are L3 fdtered before being used as sorting quantity.

[0349] Embodiment 21. The method of any of Embodiments 1-20, wherein when the associated time-domain prediction(s) of beam measurements (e.g. predicted RSRP, predicted RSRQ and / or predicted SINR) are L3 fdtered before being included in a measurement report.

[0350] Embodiment 22. The method of any of Embodiments 1-21, wherein the sorting quantity is determined to be the prediction-based trigger quantity such as pRSRP, pRSRQ, pSINRthe UE is configured with.

[0351] Additional Example Embodiments are described below.

[0352] Embodiment Al. A method of operating a communication device in a communications network that includes a network node, the method comprising: generating (1020) a report based on atime-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams; and transmitting (1030) the report to the network node.

[0353] Embodiment A2. The method of Embodiment Al, wherein generating the report comprises selecting the subset of the plurality of beams based on the time-domain prediction of beam measurement information associated with the plurality of beams.

[0354] Embodiment A3. The method of any of Embodiments Al-2, wherein generating the report comprises sorting the subset of the plurality of beams based on the time-domain prediction of beam measurement information associated with the plurality of beams.

[0355] Embodiment A4. The method of any of Embodiments Al-3, wherein generating the report comprises generating the report to include the time-domain prediction of beam measurement information associated with the plurality of beams.

[0356] Embodiment A5. The method of Embodiment A4, wherein generating the report to include the time-domain prediction of beam measurement information associated with the plurality of beams comprises generating the report to include only the time-domain prediction of beam measurement information associated with the plurality of beams.

[0357] Embodiment A6. The method of any of Embodiments Al-5, wherein generating the report comprises sorting the subset of the plurality of beams based on at least one of: a trigger quantity; a beam-based measurement reporting quantity a beam-based prediction reporting quantity; an a prediction-based trigger quantity

[0358] Embodiment A7. The method of any of Embodiments Al-6, wherein the report comprises a radio resource control, RRC, measurement report.

[0359] Embodiment A8. The method of any of Embodiments A 1-7, further comprising receiving (1010) configuration information from the network node, the configuration information indicating how to generate the report based on the time-domain prediction of beam measurement information wherein generating the report comprises generating the report based on the configuration information.

[0360] Embodiment A9. The method of any of Embodiments Al-8, wherein the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0361] Embodiment A 10. The method of any of Embodiments A 1 -9, wherein transmitting the report comprises at least one of: periodically transmitting the report; transmitting the report in response to an event trigger; semi-persistently transmitting the report; and aperiodically transmitting the report.

[0362] Embodiment Al l. The method of any of Embodiments A 1 - 10, wherein the time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a time-domain prediction of a beam measurement of the beam that comprises at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; an a predicted signal interference-to-noise ratio, pSINR

[0363] Embodiment A 12. The method of any of Embodiments A 1-10, wherein the time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

[0364] Embodiment A13. A method of operating a network node in a communications network that includes a communication device, the method comprising:generating (1110) configuration information including instructions to cause the communication device to generate a report based on a time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device.

[0365] Embodiment A14. The method of Embodiment A13, wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the time-domain prediction of beam measurement information associated with the plurality of beams.

[0366] Embodiment A15. The method of any of Embodiments A 13- 14, wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the time-domain prediction of beam measurement information associated with the plurality of beams.

[0367] Embodiment A16. The method of any of Embodiments A 13- 15, wherein generating the configuration information comprises generating the instructions to cause the communication device to generate the report to include the time-domain prediction of beam measurement information associated with the plurality of beams, and wherein receiving the report comprises receiving the report including the time-domain prediction of beam measurement information associated with the plurality of beams.

[0368] Embodiment A17. The method of Embodiment A16, wherein generating the configuration information comprises generating the instructions to cause the communication device to generate the report to include only the time-domain prediction of beam measurement information associated with the plurality of beams, and wherein receiving the report comprises receiving the report including only the timedomain prediction of beam measurement information associated with the plurality of beams.

[0369] Embodiment Al 8. The method of any of Embodiments A 13- 17, wherein generating the configuration information comprises generating instructions to cause the communication device to generate the report with a subset of the plurality of beams sorted based on at least one of: a trigger quantity; a beam-based measurement reporting quantity; a beam-based prediction reporting quantity; and a prediction-based trigger quantity.

[0370] Embodiment A19. The method of any of Embodiments A13-18, wherein the report comprises a radio resource control, RRC, measurement report.

[0371] Embodiment A20. The method of any of Embodiments A13-19, wherein the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

[0372] Embodiment A21. The method of any of Embodiments A 13-20, wherein receiving the report comprises at least one of: periodically receiving the report; receiving the report in response to an event trigger; semi-persistently receiving the report; and aperiodically receiving the report.

[0373] Embodiment A22. The method of any of Embodiments A13-21, wherein the time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a time-domain prediction of a beam measurement of the beam that comprises at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

[0374] Embodiment A23. The method of any of Embodiments A13-21, wherein the time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

[0375] Embodiment A24. A communication device (1300) adapted to perform operations comprising: generating (1020) a report based on atime-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams; and transmitting (1030) the report to the network node.

[0376] Embodiment A25. The communication device of Embodiment A24, the operations further comprising any of the operations of Embodiments A2-12.

[0377] Embodiment A26. A computer program comprising program code to be executed by processing circuitry (1302) of a communication device (1300), whereby execution of the program code causes the communication device to perform operations comprising: generating (1020) a report based on atime-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams; and transmitting (1030) the report to the network node.

[0378] Embodiment A27. The computer program of Embodiment A26, the operations further comprising any of the operations of Embodiments A2-12.

[0379] Embodiment A28. A computer program product comprising a non-transitory storage medium (1310) including program code to be executed by processing circuitry (1302) of a communication device (1300), whereby execution of the program code causes the communication device to perform operations comprising: generating (1020) a report based on atime-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams; and transmitting (1030) the report to the network node.

[0380] Embodiment A29. The computer program product of Embodiment A28, further comprising any of the operations of Embodiments A2-12.

[0381] Embodiment A30. A network node (1400) adapted to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device.

[0382] Embodiment A31. The network node of Embodiment A30, the operations further comprising any of the operations of Embodiments A 14-23.

[0383] Embodiment A32. A computer program comprising program code to be executed by processing circuitry (1402) of a network node (1400), whereby execution of the program code causes the network node to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; andreceiving (1130) the report from the communication device.

[0384] Embodiment A33. The computer program of Embodiment A32, the operations further comprising any of the operations of Embodiments A 14-23.

[0385] Embodiment A34. A computer program product comprising a non-transitory storage medium (1404) including program code to be executed by processing circuitry (1402) of a network node (1400), whereby execution of the program code causes the network node to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device.

[0386] Embodiment A35. The computer program product of Embodiment A34, further comprising any of the operations of Embodiments A 14-23.

[0387] FIG. 12 shows an example of a communication system 1200 in accordance with some embodiments.

[0388] In the example, the communication system 1200 includes a telecommunication network 1202 that includes an access network 1204, such as a radio access network (RAN), and a core network 1206, which includes one or more core network nodes 1208. The access network 1204 includes one or more access network nodes, such as network nodes 1210a and 1210b (one or more of which may be generally referred to as network nodes 1210), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a 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 1202 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 1202 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 1202, including one or more network nodes 1210 and / or core network nodes 1208.

[0389] 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 (near-real time or non-realtime) 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 Al, Fl, Wl, El, 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 0-RAN Alliance or comparable technologies. The network nodes 1210 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 1212a, 1212b, 1212c, and 1212d (one or more of which may be generally referred to as UEs 1212) to the core network 1206 over one or more wireless connections.

[0390] 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 1200 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 1200 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0391] The UEs 1212 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 1210 and other communication devices. Similarly, the network nodes 1210 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 1212 and / or with other network nodes or equipment in the telecommunication network 1202 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 1202.

[0392] In the depicted example, the core network 1206 connects the network nodes 1210 to one or more host computing systems, such as host 1216. 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 1206 includes one more core network nodes (e.g., core network node 1208) that are structured with hardware and software components. Features ofthese components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 1208. 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 (AUSF), 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).

[0393] The host 1216 may be under the ownership or control of a service provider other than an operator or provider of the access network 1204 and / or the telecommunication network 1202. The host 1216 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as 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.

[0394] As a whole, the communication system 1200 of FIG. 12 enables connectivity between the 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 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 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.

[0395] In some examples, the telecommunication network 1202 is a cellular network that implements 3 GPP standardized features. Accordingly, the telecommunications network 1202 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 1202. For example, the telecommunications network 1202 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)ZMassive loT services to yet further UEs.

[0396] In some examples, the UEs 1212 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 1204 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 1204. Additionally, a UE may be configured for operating in single- or multi-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-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).

[0397] In the example, the hub 1214 communicates with the access network 1204 to facilitate indirect communication between one or more UEs (e.g., UE 1212c and / or 1212d) and network nodes (e.g., network node 1210b). In some examples, the hub 1214 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 1214 may be a broadband router enabling access to the core network 1206 for the UEs. As another example, the hub 1214 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 1210, or by executable code, script, process, or other instructions in the hub 1214. As another example, the hub 1214 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 1214 may be a content source. For example, for a UE that is a VR device, display, loudspeaker, or other media delivery device, the hub 1214 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 1214 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 1214 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0398] The hub 1214 may have a constant / persistent or intermittent connection to the network node 1210b. The hub 1214 may also allow for a different communication scheme and / or schedule between the hub 1214 and UEs (e.g., UE 1212c and / or 1212d), and between the hub 1214 and the core network 1206. In other examples, the hub 1214 is connected to the core network 1206 and / or one or more UEs via a wired connection. Moreover, the hub 1214 may be configured to connect to an M2M service provider over the access network 1204 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 1210 while still connected via the hub 1214 via a wired or wireless connection. In some embodiments, the hub 1214 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 1210b. In other embodiments,the hub 1214 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 1210b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0399] FIG. 13 shows a UE 1300 in accordance with some embodiments. The UE 1300 presents additional details of some embodiments of the UE 1212 of Figure 1. 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 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 cameras, gaming console or device, music storage / playback device, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), an Augmented Reality (AR) or Virtual Reality (VR) 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-IoT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0400] A UE may support device-to-device (D2D) communication, for example by implementing a 3 GPP 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).

[0401] The UE 1300 includes processing circuitry 1302 that is operatively coupled via a bus 1304 to an input / output interface 1306, a power source 1308, a memory 1310, a communication interface 1312, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in FIG. 13. 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.

[0402] The processing circuitry 1302 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions storedas machine-readable computer programs in the memory 1310. The processing circuitry 1302 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 1302 may include multiple central processing units (CPUs).

[0403] In the example, the input / output interface 1306 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 1300. 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.

[0404] In some embodiments, the power source 1308 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 1308 may further include power circuitry for delivering power from the power source 1308 itself, and / or an external power source, to the various parts of the UE 1300 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 1308. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 1308 to make the power suitable for the respective components of the UE 1300 to which power is supplied.

[0405] The memory 1310 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 1310 includes one or more application programs 1314, such as an operating system, web browser application, a widget, gadget engine, or otherapplication, and corresponding data 1316. The memory 1310 may store, for use by the UE 1300, any of a variety of various operating systems or combinations of operating systems.

[0406] The memory 1310 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 USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 1310 may allow the UE 1300 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load 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 1310, which may be or comprise a device-readable storage medium.

[0407] The processing circuitry 1302 may be configured to communicate with an access network or other network using the communication interface 1312. The communication interface 1312 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 1322. The communication interface 1312 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 1318 and / or a receiver 1320 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 1318 and receiver 1320 may be coupled to one or more antennas (e.g., antenna 1322) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0408] In the illustrated embodiment, communication functions of the communication interface 1312 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) 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 MultipleAccess (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / intemet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0409] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 1312, 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).

[0410] 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 to a robotic arm performing a medical procedure according to the received input.

[0411] A UE, when in the form of an Internet of Things (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 a device which is or which is 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 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 of the intended application of the loT device in addition to other components as described in relation to the UE 1300 shown in FIG. 13.

[0412] 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 oneparticular example, the UE may implement the 3GPP NB-IoT 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.

[0413] 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.

[0414] FIG. 14 shows a network node 1400 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU).

[0415] 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 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).

[0416] Other examples of 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).

[0417] The network node 1400 includes a processing circuitry 1402, a memory 1404, a communication interface 1406, and a power source 1408. The network node 1400 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 network node 1400 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 network node 1400 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 1404 for different RATs) and some components may be reused (e.g., a same antenna 1410 may be shared by different RATs). The network node 1400 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 1400, 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 network node 1400.

[0418] The processing circuitry 1402 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 network node 1400 components, such as the memory 1404, to provide network node 1400 functionality.

[0419] In some embodiments, the processing circuitry 1402 includes a system on a chip (SOC). In some embodiments, the processing circuitry 1402 includes one or more of radio frequency (RF) transceiver circuitry 1412 and baseband processing circuitry 1414. In some embodiments, the radio frequency (RF) transceiver circuitry 1412 and the baseband processing circuitry 1414 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 1412 and baseband processing circuitry 1414 may be on the same chip or set of chips, boards, or units.

[0420] The memory 1404 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 othervolatile 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 1402. The memory 1404 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 1402 and utilized by the network node 1400. The memory 1404 may be used to store any calculations made by the processing circuitry 1402 and / or any data received via the communication interface 1406. In some embodiments, the processing circuitry 1402 and memory 1404 is integrated.

[0421] The communication interface 1406 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface 1406 comprises port(s) / terminal(s) 1416 to send and receive data, for example to and from a network over a wired connection. The communication interface 1406 also includes radio front-end circuitry 1418 that may be coupled to, or in certain embodiments a part of, the antenna 1410. Radio front-end circuitry 1418 comprises filters 1420 and amplifiers 1422. The radio front-end circuitry 1418 may be connected to an antenna 1410 and processing circuitry 1402. The radio front-end circuitry may be configured to condition signals communicated between antenna 1410 and processing circuitry 1402. The radio front-end circuitry 1418 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio frontend circuitry 1418 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 1420 and / or amplifiers 1422. The radio signal may then be transmitted via the antenna 1410. Similarly, when receiving data, the antenna 1410 may collect radio signals which are then converted into digital data by the radio front-end circuitry 1418. The digital data may be passed to the processing circuitry 1402. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0422] In certain alternative embodiments, the network node 1400 does not include separate radio front-end circuitry 1418, instead, the processing circuitry 1402 includes radio front-end circuitry and is connected to the antenna 1410. Similarly, in some embodiments, all or some of the RF transceiver circuitry 1412 is part of the communication interface 1406. In still other embodiments, the communication interface 1406 includes one or more ports or terminals 1416, the radio front-end circuitry 1418, and the RF transceiver circuitry 1412, as part of a radio unit (not shown), and the communication interface 1406 communicates with the baseband processing circuitry 1414, which is part of a digital unit (not shown).

[0423] The antenna 1410 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 1410 may be coupled to the radio front-endcircuitry 1418 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 1410 is separate from the network node 1400 and connectable to the network node 1400 through an interface or port.

[0424] The antenna 1410, communication interface 1406, and / or the processing circuitry 1402 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 1410, the communication interface 1406, and / or the processing circuitry 1402 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.

[0425] The power source 1408 provides power to the various components of network node 1400 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 1408 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 1400 with power for performing the functionality described herein. For example, the network node 1400 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 1408. As a further example, the power source 1408 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.

[0426] Embodiments of the network node 1400 may include additional components beyond those shown in FIG. 14 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 network node 1400 may include user interface equipment to allow input of information into the network node 1400 and to allow output of information from the network node 1400. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 1400. In some embodiments providing a core network node, such as core network node 108 of FIG. 12, some components, such as the radio front-end circuitry 1418 and the RF transceiver circuitry 1412 may be omitted.

[0427] FIG. 15 is a block diagram illustrating a virtualization environment 1500 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may includevirtualizing 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 1500 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, 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 1500 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface. Virtualization may facilitate distributed implementations of a network node, UE, core network node, or host.

[0428] Applications 1502 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0429] Hardware 1504 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 1506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 1508a and 1508b (one or more of which may be generally referred to as VMs 1508), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 1506 may present a virtual operating platform that appears like networking hardware to the VMs 1508.

[0430] The VMs 1508 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 1506. Different embodiments of the instance of a virtual appliance 1502 may be implemented on one or more of VMs 1508, 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.

[0431] In the context of NFV, a VM 1508 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 1508, and that part of hardware 1504 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 1508 on top of the hardware 1504 and corresponds to the application 1502.

[0432] Hardware 1504 may be implemented in a standalone network node with generic or specific components. Hardware 1504 may implement some functions via virtualization. Alternatively, hardware 1504 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 1510, which, among others, oversees lifecycle management of applications 1502. In some embodiments, hardware 1504 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 signaling can be provided with the use of a control system 1512 which may alternatively be used for communication between hardware nodes and radio units.

[0433] Although the computing devices described herein (e.g., UEs, network nodes) 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 anotherexample, 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.

[0434] 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.

Claims

CLAIMSWhat is claimed is:

1. A method of operating a communication device in a communications network that includes a network node, the method comprising: generating (1020) a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams; and transmitting (1030) the report to the network node, wherein generating the report comprises selecting (1022) the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the report comprises sorting (1024) the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

2. The method of Claim 1, wherein generating the report comprises generating the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

3. The method of Claim 2, wherein generating the report to include the mobility related timedomain prediction of beam measurement information associated with the plurality of beams comprises generating the report to include only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

4. The method of any of Claims 1-3, wherein generating the report comprises sorting the subset of the plurality of beams based on at least one of: a trigger quantity; a beam-based measurement reporting quantity; a beam-based prediction reporting quantity; and a prediction-based trigger quantity.

5. The method of any of Claims 1-4, wherein the report comprises a radio resource control, RRC, measurement report.

6. The method of any of Claims 1-5, further comprising: receiving (1010) configuration information from the network node, the configuration information indicating how to generate the report based on the mobility related time-domain prediction of beam measurement information, wherein generating the report comprises generating the report based on the configuration information.

7. The method of any of Claims 1-6, wherein the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

8. The method of any of Claims 1-7, wherein transmitting the report comprises at least one of: periodically transmitting the report; transmitting the report in response to an event trigger; semi-persistently transmitting the report; and aperiodically transmitting the report.

9. The method of any of Claims 1-8, wherein the mobility related time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurement of the beam that comprises at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

10. The method of any of Claims 1-9, wherein the mobility related time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning, ML, model for mobility orRRM related prediction.

11. A method of operating a network node in a communications network that includes a communication device, the method comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device, wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

12. The method of Claims 11, wherein generating the configuration information comprises generating the instructions to cause the communication device to generate the report to include the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein receiving the report comprises receiving the report including the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

13. The method of Claim 12, wherein generating the configuration information comprises generating the instructions to cause the communication device to generate the report to include only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein receiving the report comprises receiving the report including only the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

14. The method of any of Claims 11-13, wherein generating the configuration informationcomprises generating instructions to cause the communication device to generate the report with a subset of the plurality of beams sorted based on at least one of: a trigger quantity; a beam-based measurement reporting quantity; a beam-based prediction reporting quantity; and a prediction-based trigger quantity.

15. The method of any of Claims 11-14, wherein the report comprises a radio resource control, RRC, measurement report.

16. The method of any of Claims 11-15, wherein the plurality of beams are associated with one or more cells that include at least one of: a serving cell; a neighbor cell in a neighbor frequency; a non-serving cell; a candidate cell for conditional handover; a candidate cell for layer 1 / layer 2 triggered mobility, LTM; and a neighbor cell in a serving frequency.

17. The method of any of Claims 11-16, wherein receiving the report comprises at least one of: periodically receiving the report; receiving the report in response to an event trigger; semi-persistently receiving the report; and aperiodically receiving the report.

18. The method of any of Claims 11-17, wherein the mobility related time-domain prediction of beam measurement information comprises a beam identifier of a beam of the plurality of beams based on a mobility related time-domain prediction of a beam measurement of the beam that comprises at least one of: a predicted reference signal received power, pRSRP; a predicted reference signal received quality, pRSRQ; and a predicted signal interference-to-noise ratio, pSINR.

19. The method of any of Claims 11-18, wherein the mobility related time-domain predictionof beam measurement information comprises a beam identifier of a beam of the plurality of beams based on an output of an interference function or machine learning model, ML, for mobility or RRM related prediction.

20. An apparatus (1300) for generating measurement reports based on time-domain predictions of beam measurement information comprising a processor and a memory, the memory containing instructions executable by the processor whereby the apparatus is operative to: generate (1020) a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams; and transmit (1030) the report to the network node, wherein generating the report comprises selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the report comprises sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

21. The apparatus of Claim 20, further operative to perform any of the operations of Claims 2- 10.

22. A communication device (1300) adapted to perform operations comprising: generating (1020) a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams; and transmitting (1030) the report to the network node, wherein generating the report comprises selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the report comprises sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

23. The communication device of Claim 22, the operations further comprising any of theoperations of Claims 2-10.

24. A computer program comprising program code to be executed by processing circuitry (1302) of a communication device (1300), whereby execution of the program code causes the communication device to perform operations comprising: generating (1020) a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams of cells included in the report, the report including information associated with a subset of the plurality of beams; and transmitting (1030) the report to the network node, wherein generating the report comprises selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the report comprises sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

25. The computer program of Claim 24, the operations further comprising any of the operations of Claims 2-10.

26. A computer program product comprising a non-transitory storage medium (1310) including program code to be executed by processing circuitry (1302) of a communication device (1300), whereby execution of the program code causes the communication device to perform operations comprising: generating (1020) a report based on atime-domain prediction of beam measurement information associated with a plurality of beams, the report including information associated with a subset of a plurality of beams; and transmitting (1030) the report to the network node, wherein generating the report comprises selecting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the report comprises sorting the subset of the plurality of beams based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

27. The computer program product of Claim 26, further comprising any of the operations ofClaims 2-10.

28. An apparatus (1400) for enabling generation of measurement reports based on timedomain predictions of beam measurement information comprising a processor and a memory, the memory containing instructions executable by the processor whereby the apparatus is operative to: generate (1110) configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams; transmit (1120) the configuration information to the communication device; and receive (1130) the report from the communication device, wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

29. The apparatus of Claim 28, further operative to perform any of the operations of Claims 12-19.

30. A network node (1400) adapted to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device, wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the reportbased on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

31. The network node of Claim 30, the operations further comprising any of the operations of Claims 12-19.

32. A computer program comprising program code to be executed by processing circuitry (1402) of a network node (1400), whereby execution of the program code causes the network node to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device, wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

33. The computer program of Claim 32, the operations further comprising any of the operations of Claims 12-19.

34. A computer program product comprising a non-transitory storage medium (1404) including program code to be executed by processing circuitry (1402) of a network node (1400), whereby execution of the program code causes the network node to perform operations comprising: generating (1110) configuration information including instructions to cause the communication device to generate a report based on a mobility related time-domain prediction of beam measurement information associated with a plurality of beams; transmitting (1120) the configuration information to the communication device; and receiving (1130) the report from the communication device,wherein generating the configuration information comprises generating the instructions to cause the communication device to a subset of the plurality of beams to include in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams, and wherein generating the configuration information comprises generating the instructions to cause the communication device to sort a subset of the plurality of beams included in the report based on the mobility related time-domain prediction of beam measurement information associated with the plurality of beams.

35. The computer program product of Claim 34, further comprising any of the operations ofClaims 12-19.

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