Logging ai / ML based predictions in son reports upon certain events

Abstract

Systems and methods are disclosed for logging and reporting predicted measurements and / or predicted information in a wireless communications system. In one embodiment, a method performed by a User Equipment (UE) comprises logging (e.g., storing) one or more predicted measurements and / or predicted information upon detecting a mobility- related event (e.g., radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation), and reporting information in a Self-Optimizing Network (SON) report (e.g., a Radio Link Failure (RLF) report or a Successful Hanover Report (SHR)), the information comprising the one or more predicted measurements and / or the predicted information to a network node.

Description

[0001] LOGGING AI / ML BASED PREDICTIONS IN SON REPORTS UPON CERTAIN EVENTS RELATED APPLICATIONS This application claims the benefit of provisional patent application serial number 63 / 625,549, filed January 26, 2024, the disclosure of which is hereby incorporated herein by reference in its entirety. TECHNICAL FIELD The present disclosure relates to a cellular communications network and, more specifically, Self-Optimizing Network (SON) reporting in a cellular communications network. BACKGROUND The Artificial Intelligence (AI) / Machine Learning (ML) for the physical layer (PHY) workin 3rd Generation Partnership Project (3GPP) Release (Rel-) 18 has been limited to lower layerfeatures, such as beam Management, which is sometimes referred to as intra-cell mobility. Otherfeatures, such as layer 3 (L3) handovers, Radio Resource Control (RRC) measurementsconfiguration, and reporting of predictions have not been part of the Rel-18. Hence, a Rel-19Study Item to study the usage of AI / ML for L3 Mobility and / or Radio Resource Management(RRM) measurements is considered. As stated in RP-232624, “Moderator’s summary of 8.5.2.10SON / MDT, Moderator (CMCC)”, the objective of the study item includes: ^Study and evaluate potential benefits and gains of AI / ML aided mobility for networktriggered L3-based handover, considering the following aspects: oAI / ML based RRM measurement and event prediction^ Cell-level measurement prediction including intra and inter-frequency(User Equipment (UE) sided and network (NW) sided model)^ Inter-cell Beam-level measurement prediction for L3 Mobility (UEsided and NW sided model) oHandover (HO) failure / Radio Link Failure (RLF) prediction (UE sided model)o Measurement events prediction (UE sided model)^ Study the need / benefits of any other UE assistance information for the network sidemodel. ^The evaluation of the AI / ML aided mobility benefits should consider HO performanceKey Performance Indicators (KPIs) and complexity tradeoffs. SUMMARY Systems and methods are disclosed for logging and reporting predicted measurements and / or predicted information in a wireless communications system. In one embodiment, a method performed by a User Equipment (UE) comprises logging (e.g., storing) one or more predicted measurements and / or predicted information upon detecting a mobility-related event (e.g., radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation), and reporting information in a Self-Optimizing Network (SON) report (e.g., a Radio Link Failure (RLF) report or a Successful Hanover Report (SHR)), the information comprising the one or more predicted measurements and / or the predicted information to a network node. In this manner, the network (e.g., a serving / source network node) is able to become aware of the future state / condition of the radio measurements for the UE (e.g., with respect to the neighboring cells) prior to a mobility operation. Hence, the network can make decisions not only based on the UE’s current state / condition e.g., radio measurements at the time of failure, but also the predicted measurements and / or predicted information. The insight provided by this information enables the network to perform mobility robustness optimization related decisions with a higher accuracy and performance. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates one or more predicted values of one or more cell-level (e.g., layer-3) filtered radio measurements (e.g., one or more predicted RSRP values, one or more predicted RSRQ values, and / or one or more predicted SINR values) associated with a cell identity (e.g., CGI or PCI and ARFCN) of a respective cell. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates one or more predicted values of one or more cell-level layer- 1 radio measurements (so called CSI-report) (e.g., one or more predicted RSRP values, one or more RSRQ values, and / or one or more SINR values) associated with a cell identity (e.g., CGI or PCI and ARFCN) and / or associated with a CSI-RS resource ID. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates one or more predicted values of one or more beam-level radio measurements (e.g., one or more RSRP values, one or more RSRQ values, and / or one or more SINR values) associated with a specific beam (e.g., associated with a specific SSB or CSI- RS beam identity) related to a cell (e.g., a cell identified by a CGI or PCI and ARFCN). In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates one or more predicted target cells for the mobility procedure. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates a predicted UE location and / or a predicted UE trajectory. In one embodiment, the one or more predicted measurements are associated with a confidence value (e.g., a confidence value that indicates a confidence (e.g., a confidence of a prediction mechanism or model (e.g., an AI / ML prediction mechanism or model) in the one or more predicted measurements). In one embodiment, the one or more predicted measurements are associated with a validity time information indication, indicating a time interval in which the predicted value(s) of the measurements are valid. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates a predicted failure available at the moment the event is triggered, but predicted earlier than the moment the UE logs the report. In one embodiment, the report is an RLF report, and the UE indicates in the RLF report logged at time t0 that it had predicted an RLF in source in time instances t0-T e.g. with a certain likelihood. In another embodiment, the report is an HOF report logged at time t0, and the predicted information comprises information that indicates that the UE had predicted a HOF in time instances t0-T e.g. with a certain likelihood. In another embodiment, the report is an RLF report logged at time t0, the and predicted information comprises information that indicates that the UE had predicted a HOF in time instances t0-T e.g. with a certain likelihood. In one embodiment, the one or more predicted measurements and / or predicted information comprise information that indicates one or more spatial domain predictions of one or more measurements. In one embodiment, the UE logs available measurement information of a cell and / or a beam without the UE having performed the measurement of that cell. In another embodiment, the predicted measurements and / or predicted information predicted for a first set of cell(s) and / or beam(s) predicted based on a set of measurement information for a second set of cell(s) and / or beam(s). In one embodiment, the report is a radio link failure report triggered upon a failure of a mobility procedure. In one embodiment, the report is a radio link failure report triggered upon a radio link failure after a successful mobility procedure. In one embodiment, the report is a radio link failure report triggered upon a radio link failure in a source cell, e.g. before any mobility procedure while being configured to perform predictions on the radio measurements. In one embodiment, the report is a successful handover report, SHR, triggered upon a successful execution of mobility procedure. In one embodiment, the mobility procedure is a L3 (RRC) based reconfiguration with synch procedure such as normal handover (reconfigurationWithSynch) or a conditional handover (reconfigurationWithSynch) performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell). In one embodiment, the mobility procedure is a Layer 1 or Layer 2 based mobility procedure so called LTM cell switch procedure performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell). In one embodiment, the report is a new, AI / ML related report. In one embodiment, the report is triggered upon a mobility event (e.g., a mobility procedure being successfully or non- successfully executed). Corresponding embodiments of a UE are also disclosed. Embodiments of a network node are also disclosed. In one embodiment, a method performed by a network node comprises receiving a SON report from a UE, the report comprising one or more predicted measurements and / or predicted information in a Self- Optimizing Network, SON, report (e.g., a Radio Link Failure, RLF, report or a Successful Hanover Report, SHR), the SON report related being related to a mobility-related event (e.g., radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation). In one embodiment, the method further comprises performing one or more actions based on the SON report. In one embodiment, the method further comprises sending the SON report to another network node (e.g., a serving network node of the UE). BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the disclosure, and together with the description serve to explain the principles of the disclosure. Figure 1 illustrates a procedure in accordance with an embodiment of the presentdisclosure in which a User Equipment (UE) logs and reports predicted measurements and / orpredicted information in a Self-Optimizing Network (SON) report; Figure 2 illustrates a procedure in which a UE logs and reports predicted measurements and / or predicted information in RLF report upon detecting a mobility procedure failure e.g., LTM cell switch failure or L3 based mobility e.g., reconfiguration with synch failure; Figure 3 illustrates a procedure in accordance with an embodiment of the present disclosure in which a UE logs and reports predicted measurements and / or predicted information in an SHR upon determining to log a successful handover report after successful completion of a mobility procedure e.g., successful completion of LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure; Figure 4 illustrates a procedure in which a UE logs and reports predicted measurements and / or predicted information in RLF report upon detecting a RLF after successful completion / execution of a mobility procedure e.g., LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure; Figure 5 illustrates a procedure in accordance with an embodiment of the present disclosure in which a UE logs and reports predicted measurements and / or predicted information in an AI / ML report upon detecting a mobility event or radio link failure upon execution of a mobility procedure e.g., LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure; Figure 6 shows an example of a communication system in accordance with someembodiments of the present disclosure; Figure 7 shows a User Equipment device (UE) in accordance with some embodiments ofthe present disclosure; Figure 8 shows a network node in accordance with some embodiments of the presentdisclosure; Figure 9 is a block diagram of a host, which may be an embodiment of the host of Figure6, in accordance with various aspects of the present disclosure described herein; Figure 10 is a block diagram illustrating a virtualization environment in which functionsimplemented by some embodiments of the present disclosure may be virtualized; and Figure 11 shows a communication diagram of a host communicating via a network nodewith a UE over a partially wireless connection in accordance with some embodiments of the present disclosure. DETAILED DESCRIPTION The embodiments set forth below represent information to enable those skilled in the art to practice the embodiments and illustrate the best mode of practicing the embodiments. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the disclosure and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure. 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. There currently exist certain challenge(s). Self-Optimizing Network (SON) features, e.g.,Mobility Robustness Optimization (MRO), leverage on the User Equipment (UE) reports such asRadio Link Failure (RLF) report or Successful Handover Report (SHR) or successful PrimarySecondary Cell (PSCell) change / addition report (SPR) to troubleshoot failures and optimize thenetwork functionalities e.g., various types of handover procedures such as normalreconfiguration with synch or conditional reconfiguration with synch or Dual Active Protocol Stack (DAPS) handover or Layer-1 / Layer-2 based mobility (so called Lower-layer TriggeredMobility (LTM) cell switch procedures). Based on the current SON reports e.g., RLF report orSHR, among other information, the wireless terminal (i.e., the so called UE) logs only theavailable radio measurements of the neighboring cells or frequencies in the report i.e., the actual radio measurements such as Reference Signal Received Power (RSRP), Reference SignalReceived Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR) per cell or beam levelin the reports. Based on such measurements, the network tries to take counter actions against thedetected sub-optimal behavior or the failures. However, network action is limited to the state ofthe UE and the radio environment at the time of the detected failure, and lack of post-event(failure or handover) knowledge might lead to sub-optimal network behavior and waste ofnetwork resources. For example, based on the radio measurements provided in the RLF report, the network may decide to change the Cell Individual Offset (CIO) to trigger handover later or earlier toprevent failures. However, changing the CIO value would lead to delay in handover (HO) (satfrom T1 to T2), while the network is not aware of the radio condition at the time T2, so the decision might worsen the situation. In another example, based on the radio measurements provided in the RLF report, the network may decide to change the target cell (from target cell A to the target cell B) for the next handovers. Although performing handover at the time of T1 to the target cell B might look optimal, the network may not be aware that the new target cell B might be a worse choice than the cell A or other cells after a short period of time. Thus, the MRO feature is currently limited to mobility optimization based on the actualradio measurements performed and collected at the time of failure and hence it does nothave any insight about the radio condition after the new decisions and the consequences of optimization decisions, and therefore the network is unable to incorporate such information in the optimization process. Certain aspects of the disclosure and their embodiments may provide solutions to these orother challenges. Embodiments of a method performed by a wireless terminal (i.e., a so calledUE) are disclosed herein. In one embodiment, as illustrated in Figure 1, a method performed bya UE comprises any one or more of the following: ^Step 100: The UE receives (e.g., from a network node) a configuration to include / logpredicted value(s) of radio measurements in a SON report.^ Step 102: The UE generates predicted measurements and / or predicted information(e.g., predicted radio measurements e.g., time domain and / or spatial domain predictions e.g., radio link measurements such as RSRP and / or RSRQ in the future in time, or the spatial radio measurements predictions e.g., predicting the RSRP / RSRQ measurements ofa neighboring cell based on the existing / available measurements) or predicts one or moretarget cell for mobility purpose e.g., HO). oIn one embodiment, the UE determines whether to generate the predictedmeasurements and / or predicted information based on a network configuration i.e., the network prior to detecting a mobility related event (e.g., in step 104) provides a configuration to the UE instructing the UE whether to log predicted values in related SON report or not (see, e.g., step 100). Furthermore, the network mayprovide the configuration on which predicted measurements and / or information are to be logged in the report. In this case, the UE performs step 102 if (e.g., only if) the UE is configured to log such predicted measurements / information. ^Steps 104 and 106: The UE detects a mobility related event and logs a report based onthe detected event. oIn one embodiment, the detected mobility related event is detecting a failure inexecuting a mobility procedure, and the SON report is a Radio Link Failure(RLF) report (so called RLF-report). In one embodiment, the UE includes, in theRLF-report, information and measurements according to 3GPP TechnicalSpecification (TS) 38.331 (see, e.g., version 17.6.0).o In another embodiment, the detected mobility related event is a detected failure ina serving cell (without executing any mobility procedure), and the SON report is aRLF report (so called RLF-report). In one embodiment, the UE includes in theRLF-report information and measurements according to 3GPP TS 38.331 (e.g., version 17.6.0). oIn another embodiment, the detected mobility related event is detecting a failureafter a successful mobility operation, and the SON report is an RLF report (socalled RLF-report). In one embodiment, the UE includes in the RLF-report information and measurements according to the 3GPP TS 38.331 (e.g., version 17.6.0). oIn another embodiment, the detected mobility related event is detecting asuccessful mobility operation, and the SON report is a Successful HandoverReport (SHR). In one embodiment, the UE includes in the SHR information and measurements according to 3GPP TS 38.331 (e.g., version 17.6.0). oIn another embodiment, the detected mobility related event is triggering a newSON report for Artificial Intelligence (AI) / Machine Learning (ML) purposes, e.g.an AIML. The UE includes AI / ML related information (such as time domain prediction(s) and / or spatial domain prediction(s), e.g. produced as output of anAI / ML model) and measurements in the new SON report.^ Step 108: The UE logs / includes the predicted measurements and / or predictedinformation (e.g., predicted radio measurements e.g., time domain and / or spatial domainpredictions e.g., radio link measurements such as RSRP and / or RSRQ in the future intime, or the spatial radio measurements predictions e.g., predicting the RSRP / RSRQmeasurements of a neighboring cell based on the existing / available measurements) or thepredicted one or more target cell for mobility purpose e.g., HO) in the SON report. oIn one embodiment, the UE determines whether to log the predictedmeasurements and / or predicted information in the SON report based on a networkconfiguration i.e., the network prior to the detected mobility related event provides a configuration to the UE instructing the UE whether to log the predicted values in the report or not. Furthermore, the network may provide the configuration on which predicted measurements and / or information are to be logged in the report.^ Step 110: The UE reports (i.e., sends) the SON report including the predictedmeasurements to the network, e.g., upon network request. As also shown in Figure 1, the network node to which the UE sends the SON report may, for example, forward the SON report to another network node (e.g., a serving network node ofthe UE) at which an optimization(s) based on the SON report is performed (step 112).Exemplary embodiments of the present disclosure may include any one of A1) A method at a User Equipment (UE), the method comprising:- Logging and reporting one or more predicted measurement(s) and / or predictedinformation in a SON report (RLF report or SHR) upon detecting an event such as radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation, wherein the one or more predicted measurements and / or predicted information comprises, e.g., any one or more of the following:o An indication indicating one or more predicted values of the cell-level layer-3filtered radio measurements such as RSRP, RSRQ, SINR associated with the cell identity such as cell global identity (CGI) or PCI and ARFCN. The predicted values can be used for the normal Layer 3 based mobility procedures (e.g., reconfiguration with synch or conditional handover) and related MRO purposes. ^The predicted measurement and / or information may be associated with aconfidence value indicating the confidence of the AI / ML model in predicted value of the measurements. ^The measurement may be associated with a confidence value indicatingthe confidence of predicted value of the measurements. ^The predicted measurement and / or information may be associated with avalidity time information indication, indicating a time interval in which the predicted value(s) of the measurements are valid. oAn indication indicating one or more predicted values of the cell-level layer-1radio measurements (so called CSI-report) such as RSRP, RSRQ, SINR associated with the cell identity such as cell global identity (CGI) or PCI and ARFCN, and / or may associated with CSI-RS resource ID. The predicted values can be used for the LTM cell switch operations and related MRO purposes. ^The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. ^The prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements.^ The prediction may be associated with a validity time informationindication indicating a time interval in which the predicted value(s) of the measurements are valid.An indication indicating one or more predicted values of the beam-level radiomeasurements such as RSRP, RSRQ, SINR associated with specific beam such asSSB or CSI-RS beam identity related to a cell identified by a cell global identity(CGI) or PCI and ARFCN. ^The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. ^The prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements in AI / ML. ^The prediction may be associated with a validity time informationindication indicating a time interval in which the predicted value(s) of the measurements are valid.An indication indicating the prediction of one or more target cell(s) for themobility procedure.^ The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. ^The prediction may be associated with a confidence value indicating theconfidence of predicted values. ^The prediction may be associated with a validity time informationindication indicating a time interval in which the predicted values are valid.An indication related to the predicted UE location or predicted UE trajectory.^ The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. ^The prediction may be associated with a confidence value indicating theconfidence of predicted values. ^The prediction may be associated with a validity time informationindication indicating a time interval in which the predicted values are valid.An indication indicating a predicted failure available at the moment the event istriggered, but predicted earlier than the moment the UE logs the SON report.^ In one option, the UE indicates in the RLF report logged at time t0 that ithad predicted an RLF in source in time instances t0-T, e.g., with a certainlikelihood. ^In one option, the UE indicates in the HOF report logged at time t0 that ithad predicted a HOF in time instances t0-T, e.g., with a certain likelihood.^ In one option, the UE indicates in the RLF report logged at time t0 that ithad predicted a HOF in time instances t0-T, e.g., with a certain likelihood.o An indication indicating spatial domain prediction(s) of measurements.^ In one option, the UE logs available measurement information of a celland / or a beam without the UE having to perform the measurement of that cell. In other words, the UE uses a set of measurement information of a setof cell(s) and / or beam(s) to predict measurement information of anotherset of cell(s) and / or beam(s). ^This increases the amount of information available at the networkside at the moment of the failure. A2) A method according to A1, wherein the information in A1 is logged by the UE in aradio link failure report so-called RLF report triggered upon a failure of a mobility procedure.A3) A method according to A1, wherein the information in A1 is logged by the UE in aradio link failure report so-called RLF report triggered upon a failure after a successful mobilityprocedure. A5) A method according to A1, wherein the information in A1 is logged by the UE in aradio link failure report so-called RLF report triggered upon a failure in a source cell, e.g. beforeany mobility procedure while being configured to perform predictions on the radio measurements. A6) A method according to A1, wherein the information in A1 is logged by the UE in asuccessful handover report so-called SHR triggered upon a successful execution of mobilityprocedure. A7) A method according to A2-A6, wherein the mobility procedure is a L3 (RRC) based reconfiguration with synch procedure such as normal handover (reconfigurationWithSynch) or a conditional handover (reconfigurationWithSynch) performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell) A8) A method according to A2-A6, wherein the mobility procedure is a Layer 1 or Layer 2 based mobility procedure so called LTM cell switch procedure performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell). A9) A method according to A2-A6, wherein the information in A1 is logged in a new, AI / ML related report. The report may be triggered upon mobility events such as a mobility procedure being successfully or non-successfully executed. Certain embodiments may provide one or more of the following technical advantage(s).Embodiments of the proposed solution enable the serving / source network node to become awareof the future state / condition of the radio measurements for the UE with respect to theneighboring cells prior to a mobility operation. Hence, the serving / source network node canmake decisions not only based on the UE’s current state / condition e.g., radio measurements atthe time of failure, but also the predicted values of the measurements. The insight provided bythe predicted values e.g., predicted radio measurements enables the network to perform the mobility robustness optimization related decisions with a higher accuracy and performance. In another example, predictions might indicate whether predictions would have been useful or not to prevent that failure which has occurred. For example, by knowing that time domainprediction(s) of neighbors at the moment of the failure indicate good neighbors, the networkmay, later in the future, activate the time domain prediction feature for UEs, so that it may takeas input for later decisions. Now, the description will provide further details regarding embodiments of the present disclosure. According to embodiments of the present disclosure, a UE logs and reports to a networknode (e.g. a cell served by a network node) information about a prediction of measurementsperformed or available at the time of detecting a mobility related event such as, e.g., a radio linkfailure or mobility procedure failure or a successful execution of a mobility procedure. According to embodiments of the present disclosure, the UE may be (optionally in some embodiments) configured with one or more configurations associated with prediction of themeasurements (e.g., received as part of an Radio Resource Control (RRC) Reconfigurationmessage e.g., as part of OtherConfig or as part of a new Information Element (IE)), and furthermore the UE (optionally in some embodiments) receives an indication to include predicted measurements in a SON report (e.g., RLF report) upon detecting an event related to the mobility procedure. The method is described based on different scenarios in the following subsections. Logging Prediction Information and Measurements in Case of Mobility Procedure Failure Figure 2 illustrates a procedure in which a UE logs and reports predicted measurementsand / or predicted information in RLF report upon detecting a mobility procedure failure e.g.,LTM cell switch failure or L3 based mobility e.g., reconfiguration with synch failure. As illustrated in Figure 2, the procedure includes the following: Steps 200A and 200B (Optional): Optionally, a serving network node (e.g., servingRadio Access Network (RAN) node such as, e.g., a serving gNodeB (gNB) of the UE in the caseof New Radio (NR)) of the UE sends, and the UE receives, one or more configuration(s) toinclude / log measurements and information available based on some prediction mechanism(s)(e.g., an AI / ML based mechanism or model) in an RLF report. ^In one embodiment, the one or more configuration(s) are received as part of an RRCReconfiguration message e.g., as part of OtherConfig or a new IE of the received RRC Reconfiguration message. ^In another embodiment, the one or more configuration(s) are additionally or alternativelyreceived as part of a system information message(s) e.g., System Information Block(SIB) 1, i.e., SIB1. Step 202: The UE generates predicted measurements(s) and / or predicted information, using a prediction scheme or model (e.g., an AI / ML prediction scheme or model). The predictedmeasurement(s) and / or predicted information may include any of those detailed herein such as,e.g., any one or more of those described below in regard to steps 206 and 208. Step 204: The UE detects a radio link failure event upon execution of a mobilityprocedure, either based on a configuration received from the network (L3 handover command orLTM cell switch command) or based on the fulfillment of some execution conditions associated to a conditional mobility (reconfiguration with synch) configuration. Step 206 and 208: The UE logs an RLF report and includes in the RLF report predictedmeasurement(s) and / or predicted information, upon detecting the RLF in step 204. The predictedmeasurements and information can comprise any one or more of the following: -An indication indicating one or more predicted values (e.g., time-domain predictedvalue(s)) of the cell-level layer-3 filtered radio measurements such as RSRP, RSRQ, SINR associated with the cell identity such as Cell Global Identity (CGI) or Physical Cell Identity (PCI) and Absolute Radio Frequency Channel Number (ARFCN). The predictedvalues can be used for the normal Layer-3 based mobility procedures (e.g., reconfiguration with synch or conditional handover) and related MRO purposes.o The measurement may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe measurement may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe measurement may be associated with a validity time information indicationindicating a time interval in which the predicted value(s) of the measurements are valid.- An indication indicating one or more predicted values of the cell-level layer-1 radiomeasurements (so called CSI measurements) such as RSRP, RSRQ, SINR associated with the cell identity such as cell CGI or PCI and ARFCN and may associated with Channel State Information (CSI) Reference Signal (CSI-RS) resource Identifier (ID). Thepredicted values can be used for the LTM cell switch operations and related MRO purposes. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted value(s) of the measurements are valid.- An indication indicating one or more predicted values of the beam level radiomeasurements such as RSRP, RSRQ, SINR associated with specific beam such as Synchronization Signal Block (SSB) or CSI-RS beam identity related to a cell identifiedby a cell CGI or PCI and ARFCN. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted value(s) of the measurements are valid.- An indication indicating the prediction of one or more target cells for the mobilityprocedure.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.- An indication related to the predicted UE location or predicted UE trajectory.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted value(s) are valid. oSuch information could be used by the network to optimize the target cell of themobility procedures based on the UE reported location / trajectory prediction.- An indication related to the prediction of transition to the RRC_IDLE state. In a non-limiting example, the UE logs in the RLF report that with certain likelihood it shouldhave transit to the RRC_IDLE state after the failure. Such information can be used by the network to send the UE to the RRC_IDLE state prior to the radio link failure.- An indication related to the prediction of the data arrival. In a non-limiting example, theUE logs in the RLF report that with certain likelihood it should have (not) received / senddata on the established bearer. Such information can be used by the network to send the UE to the RRC_IDLE state prior to the radio link failure e.g., when the UE predicts there will be no upcoming data to be received / sent by the UE.- An indication of a predicted event fulfillment, e.g. the fulfillment of a measurementreporting event. A measurement reporting event may be an event that different channels / cells that the UE measuring is fulfilling certain conditions, one such example is the A3 event which is fulfilled if the cell that the UE is associated with has a signal strength which is a threshold worse than another cell. The UE may hence with this indication indicate that an event is predicted to become fulfilled. The UE may further indicate the expected time (or time window) when the event is expected to become fulfilled.- An indication indicating one or more predicted values of the RAN visible applicationlayer measurements (so called RVQoE measurements) such as application-level bufferlevel or playout delay for media startup. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements in AI / ML. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted value of the measurements is valid. oThe information could be used by the network to optimize the target cell of themobility procedures based on the UE reported end user experience.- An indication indicating RLF prediction(s) e.g. output(s) of an AI / ML model, generatedT time units earlier than the triggering of the failure event which led the UE to log the report. Thanks to that the network figures out whether the AI / ML model for the RLF prediction has been successful or not. In other words, the UE logs information about a predicted failure available at the moment the event is triggered, but predicted earlier than the moment the UE logs the SON report. oIn one option, the UE indicates in the RLF report logged at time t0 that it hadpredicted an RLF in source in time instances t0-T, e.g., with a certain likelihood.o In one option, the UE indicates in the HOF report logged at time t0 that it hadpredicted a HOF in time instances t0-T, e.g., with a certain likelihood.o In one option, the UE indicates in the RLF report logged at time t0 that it hadpredicted a HOF in time instances t0-T, e.g., with a certain likelihood.o The network may use the information to determine whether the report of thepredictions, e.g. in prediction of RLFs, would have prevented the failure or not.That may be used by the network as input for that next time the UE can configurethe UE to send prediction failure reports, for capable UEs, e.g. withinmeasurement reports.- An indication indicating Handover Failure prediction(s), e.g. output(s) of an AI / MLmodel, generated T time units earlier than the triggering of the failure event which led the UE to log the report. Thanks to that the network figures out whether the AI / ML model for the RLF prediction has been successful or not. oAn indication indicating spatial domain prediction(s) of measurements.^ In one option, the UE logs available measurement information of a celland / or a beam without the UE having to perform the measurement of thatcell. In other words, the UE uses a set of measurement information of a setof cell(s) and / or beam(s) to predict measurement information of anotherset of cell(s) and / or beam(s). ^This increases the amount of information available at the networkside at the moment of the failure. ^The network may use the information to determine whether the report ofthe predictions, e.g. in prediction of RLFs, would have prevented thefailure or not. That may be used by the network as input for that next timethe UE can configure the UE to send prediction failure reports, for capable UEs, e.g. within measurement reports.Step 210: The UE reports the RLF report including the predicted measurements to thenetwork (e.g., to a network node), e.g., upon network request.Step 212 (Optional): The network node may optionally forward the RLF report including the predicted measurements and / or information to the serving network node, where the serving network node may then use this information for one or more optimizations. Logging Prediction Information and Measurements in Case of Logging Successful Handover Report After a Successful Completion / Execution of a Mobility Procedure Figure 3 illustrates a procedure in accordance with an embodiment of the presentdisclosure in which a UE logs and reports predicted measurements and / or predicted informationin an SHR upon determining to log a successful handover report after successful completion of a mobility procedure e.g., successful completion of LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure. As illustrate in Figure 3, the steps of the procedure are as follows: Steps 300A and 300B (Optional): Optionally, a serving network node (e.g., serving RANnode such as, e.g., a serving gNB of the UE in the case of NR) sends, and the UE receives, oneor more configuration(s) to include / log measurements and information available based on someprediction mechanism (e.g., an AI / ML based mechanism or model) in a SHR. ^In one embodiment, the one or more configuration(s) are received as part of an RRCReconfiguration message e.g., as part of OtherConfig or a new IE or successful handoverreport configuration of the received RRC Reconfiguration message.^ In another embodiment, the one or more configuration(s) are additionally or alternativelyreceived as part system information message e.g., SIB1. Step 302: The UE generates predicted measurements(s) and / or predicted information, using a predication scheme or model (e.g., an AI / ML prediction scheme or model). The predicted measurement(s) and / or predicted information may include any of those detailed herein such as, e.g., any one or more of those described below in regard to steps 306 and 308. Step 304: The UE determines (e.g., based on the successful handover report configuration) to log a successful handover report upon successful completion / execution of a mobility procedure executed either based on a configuration received from the network (L3 handover command or LTM cell switch command) or based on the fulfillment of some execution conditions associated to a conditional mobility (reconfiguration with synch) configuration, and logging the SHR. Steps 306 and 308: The UE logs an SHR and includes in the SHR predictedmeasurement(s) and / or predicted information. The predicted measurements and information cancomprise any one or more of the following: -An indication indicating one or more predicted values of the cell level layer-3 filteredradio measurements such as RSRP, RSRQ, SINR associated with the cell identity such as cell CGI or PCI and ARFCN. The predicted values can be used for the normal Layer-3 based mobility procedures (e.g., reconfiguration with synch or conditional handover) and related MRO purposes. oThe measurement may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe measurement may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe measurement may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid. -An indication indicating one or more predicted values of the cell level layer-1 radiomeasurements (so called CSI measurements) such as RSRP, RSRQ, SINR associated with the cell identity such as CGI or PCI and ARFCN. The predicted values can be used for the LTM cell switch operations and related MRO purposes. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements.o The prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more predicted values of the beam level radiomeasurements such as RSRP, RSRQ, SINR associated with specific beam such as SSB or CSI-RS beam identity related to a cell identified by a cell global identity (CGI) or PCIand ARFCN. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating the prediction of one or more target cell for the mobilityprocedure. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.- An indication related to the predicted UE location or predicted UE trajectory.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.o Such information could be used by the network to optimize the target cell of themobility procedures based on the UE reported location / trajectory prediction.- An indication related to the prediction of transition to the RRC_IDLE / RRC_Inactivestate. In a non-limiting example, the UE logs in the SHR that with certain likelihood itshould have transit to the RRC_IDLE state after the handover. Such information can be used by the network to send the UE to the RRC_IDLE / RRC_Inactive state prior to execution of the mobility procedure. -An indication related to the prediction of the data arrival. In a non-limiting example, theUE logs in the SHR that with certain likelihood it should have (not) received / send data onthe established bearer. Such information can be used by the network to send the UE to the RRC_IDEL / RRC_Inactive state prior to the radio link failure e.g., when the UE predicts there will be no upcoming data to be received / sent by the UE. -An indication of a predicted event fulfillment, e.g. the fulfillment of a measurementreporting event. A measurement reporting event may be an event that different channels / cells that the UE measuring is fulfilling certain conditions, one such example is the A3 event which is fulfilled if the cell that the UE is associated with has a signal strength which is a threshold worse than another cell. The UE may hence with this indication indicate that an event is predicted to become fulfilled. The UE may further indicate the expected time (or time window) when the event is expected to become fulfilled. -An indication indicating one or more predicted values of the RAN visible applicationlayer measurements (so called RVQoE measurements) such as application-level bufferlevel or playout delay for media startup. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid. oThe information could be used by the network to optimize the target cell of themobility procedures based on the UE reported end user experience. Step 310: The UE reports the SON report including the predicted measurements to thenetwork (e.g., to a network node), e.g., upon network request. Step 312 (Optional): The network node may optionally forward the SHR including the predicted measurements and / or information to the serving network node, where the serving network node may then use this information for one or more optimizations. Logging Prediction Information and Measurements in Case of Detecting a Radio LinkFailure After a Successful Mobility ProcedureFigure 4 illustrates a procedure in which a UE logs and reports predicted measurementsand / or predicted information in RLF report upon detecting a RLF after successfulcompletion / execution of a mobility procedure e.g., LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure. As illustrated in Figure 3, the procedure includes the following: Steps 400A and 400B (Optional): Optionally, a serving network node (e.g., servingRAN node such as, e.g., a serving gNB of the UE in the case of NR) sends, and the UE receives,one or more configuration(s) to include / log measurements and information available based onsome prediction scheme (e.g., an AI / ML based scheme or model) in an RLF report. ^In one embodiment, the one or more configuration(s) are received as part of an RRCReconfiguration message e.g., as part of otherConfig or a new IE of the received RRC Reconfiguration message. ^In another embodiment, the one or more configuration(s) are additionally or alternativelyreceived as part system information message e.g., SIB1. Step 402: The UE generates predicted measurements(s) and / or predicted information, using a predication scheme or model (e.g., an AI / ML prediction scheme or model). The predicted measurement(s) and / or predicted information may include any of those detailed herein such as, e.g., any one or more of those described below in regard to step 408. Step 404: The UE successfully executes a mobility procedure. Step 406: The UE detects a radio link failure event after successfully executing themobility procedure, either based on a configuration received from the network (L3 handovercommand or LTM cell switch command) or based on the fulfillment of some execution conditions associated to a conditional mobility (reconfiguration with synch) configuration, and the UE logs an RLF report for the detected radio link failure. Step 408: The UE logs predicted measurements and information in the RLF report upondetecting radio link failure after successfully completing a mobility procedure. The predicted measurements and information can comprise any one or more of the following:- An indication indicating one or more predicted values of the cell level layer-3 filteredradio measurements such as RSRP, RSRQ, SINR associated with the cell identity such as CGI or PCI and ARFCN. The predicted values can be used for the normal Layer-3 based mobility procedures (e.g., reconfiguration with synch or conditional handover) and related MRO purposes. oThe measurement may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe measurement may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe measurement may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more predicted values of the cell level layer-1 radiomeasurements (so called CSI measurements) such as RSRP, RSRQ, SINR associated with the cell identity such as CGI or PCI and ARFCN. The predicted values can be used for the LTM cell switch operations and related MRO purposes. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more predicted values of the beam level radiomeasurements such as RSRP, RSRQ, SINR associated with specific beam such as SSB or CSI-RS beam identity related to a cell identified by a CGI or PCI and ARFCN.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more target cell for the mobility procedure.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.- An indication related to the predicted UE location or predicted UE trajectory.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.o Such information could be used by the network to optimize the target cell of themobility procedures based on the UE reported location / trajectory prediction.- An indication related to the prediction of transition to the RRC_IDLE state. In a non-limiting example, the UE logs in the RLF report that with certain likelihood it shouldhave transit to the RRC_IDLE state after the failure. Such information can be used by the network to send the UE to the RRC_IDLE state prior to the radio link failure.- An indication related to the prediction of the data arrival. In a non-limiting example, theUE logs in the RLF report that with certain likelihood it should have (not) received / senddata on the established bearer. Such information can be used by the network to send the UE to the RRC_IDLE state prior to the radio link failure e.g., when the UE predicts there will be no upcoming data to be received / sent by the UE.- An indication of a predicted event fulfillment, e.g. the fulfillment of a measurementreporting event. A measurement reporting event may be an event that different channels / cells that the UE measuring is fulfilling certain conditions, one such example is the A3 event which is fulfilled if the cell that the UE is associated with has a signal strength which is a threshold worse than another cell. The UE may hence with this indication indicate that an event is predicted to become fulfilled. The UE may further indicate the expected time (or time window) when the event is expected to become fulfilled.- An indication indicating one or more predicted values of the RAN visible applicationlayer measurements (so called RVQoE measurements) such as application-level bufferlevel or playout delay for media startup. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid. oThe information could be used by the network to optimize the target cell of themobility procedures based on the UE reported end user experience. -The predicted measurements and information can be the predicted values at the time ofsuccessful execution of the mobility procedure, or the predicted measurements and information can be the predicted values at the time of failure or both of them (i.e., predicted measurements at the time of successful mobility and the predictedmeasurements at the time of failure) with an indication indicating the time at which the prediction was performed. Step 410: The UE reports the RLF report including the predicted measurements and / or thepredicted information to the network (e.g., a network node), e.g., upon network request.Step 412 (Optional): The network node may optionally forward the RLF report including the predicted measurements and / or information to the serving network node, where the serving network node may then use this information for one or more optimizations. Logging Prediction Information and Measurements in Case of a Successful or a Non- Successful Mobility Event Figure 5 illustrates a procedure in accordance with an embodiment of the present disclosure in which a UE logs and reports predicted measurements and / or predicted information in an AI / ML report upon detecting a mobility event or radio link failure upon execution of a mobility procedure e.g., LTM cell switch procedure or L3 based mobility e.g., reconfiguration with synch procedure. As illustrated in Figure 5, the procedure includes the following: Steps 500A and 500B (Optional): Optionally, a serving network node (e.g., serving RANnode such as, e.g., a serving gNB of the UE in the case of NR) sends, and the UE receives, oneor more configuration(s) to include / log measurements and information available based on someprediction mechanism (e.g., an AI / ML based mechanism or model) in an AI / ML report. ^In one embodiment, the one or more configuration(s) are received as part of an RRCReconfiguration message e.g., as part of a OtherConfig or a new IE of the received RRC Reconfiguration message. ^In another embodiment, the one or more configuration(s) are additionally or alternativelyreceived as part system information message e.g., SIB1. Step 502: The UE generates predicted measurements(s) and / or predicted information, using a predication scheme or model (e.g., an AI / ML prediction scheme or model). The predicted measurement(s) and / or predicted information may include any of those detailed herein such as, e.g., any one or more of those described below in regard to step 508. Step 504: The UE successfully executes a mobility procedure towards a target cell or aradio link failure occurs upon execution of a mobility procedure.Step 506: The UE detects the successful mobility event (of step 504) either based on aconfiguration received from the network (L3 handover command or LTM cell switch command) or based on the fulfillment of some execution conditions associated to a conditional mobility (reconfiguration with synch) configuration. Alternatively, the UE detects a radio link failure event (of step 504) upon executing a mobility procedure. In other words, in step 506, the UE determines to log the detected event, e.g., based on one or more triggering conditions (e.g., one or more triggering conditions received, e.g., from the serving network node). Step 508: The UE logs predicted measurements and / or predicted information in an AI / MLreport upon detecting the mobility event in step 506. The predicted measurements andinformation can comprise any one or more of the following: -An indication indicating one or more predicted values of the cell level layer-3 filteredradio measurements such as RSRP, RSRQ, SINR associated with the cell identity such as cell global identity (CGI) or PCI and ARFCN. The predicted values can be used for the normal Layer-3 based mobility procedures (e.g., reconfiguration with synch or conditional handover) and related MRO purposes. oThe measurement may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe measurement may be associated with a confidence value indicating theconfidence of predicted value of the measurements.o The measurement may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more predicted values of the cell level layer-1 radiomeasurements (so called CSI measurements) such as RSRP, RSRQ, SINR associated with the cell identity such as cell global identity (CGI) or PCI and ARFCN. The predicted values can be used for the LTM cell switch operations and related MRO purposes. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more predicted values of the beam level radiomeasurements such as RSRP, RSRQ, SINR associated with specific beam such as SSB or CSI-RS beam identity related to a cell identified by a cell global identity (CGI) or PCIand ARFCN. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid.- An indication indicating one or more target cell for the mobility procedure.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.- An indication related to the predicted UE location or predicted UE trajectory.o The prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted values. oThe prediction may be associated with a confidence value indicating theconfidence of predicted values. oThe prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values are valid.o Such information could be used by the network to optimize the target cell of themobility procedures based on the UE reported location / trajectory prediction.- An indication related to the prediction of transition to the RRC_IDLE state. In a non-limiting example, the UE logs in the AI / ML report that with certain likelihood it shouldhave transit to the RRC_IDLE state after the failure. Such information can be used by the network to send the UE to the RRC_IDLE state prior to a radio link failure.- An indication related to the prediction of the data arrival. In a non-limiting example, theUE logs in the AI / ML report that with certain likelihood it should have (not)received / send data on the established bearer. Such information can be used by the network to send the UE to the RRC_IDLE state prior to a radio link failure e.g., when the UE predicts there will be no upcoming data to be received / sent by the UE.- An indication of a predicted event fulfillment, e.g. the fulfillment of a measurementreporting event. A measurement reporting event may be an event that different channels / cells that the UE measuring is fulfilling certain conditions, one such example is the A3 event which is fulfilled if the cell that the UE is associated with has a signal strength which is a threshold worse than another cell. The UE may hence with this indication indicate that an event is predicted to become fulfilled. The UE may further indicate the expected time (or time window) when the event is expected to become fulfilled.- An indication indicating one or more predicted values of the RAN visible applicationlayer measurements (so called RVQoE measurements) such as application-level bufferlevel or playout delay for media startup. oThe prediction may be associated with a confidence value indicating theconfidence of the AI / ML model in predicted value of the measurements. oThe prediction may be associated with a confidence value indicating theconfidence of predicted value of the measurements.o The prediction may be associated with a validity time information indicationindicating a time interval in which the predicted values of the measurements arevalid. oThe information could be used by the network to optimize the target cell of themobility procedures based on the UE reported end user experience. -The predicted measurements and information can be the predicted values at the time ofsuccessful execution of the mobility procedure, or the predicted measurements and information can be the predicted values at the time of failure with an indication indicating the time at which the prediction was performed. Step 510: The UE reports the AI / ML report including the predicted measurements to thenetwork (e.g., to a network node), e.g., upon network request.Step 512 (Optional): The network node may optionally forward the AI / ML report including the predicted measurements and / or information to the serving network node, where the serving network node may then use this information for one or more optimizations. Example Implementation of the Pre-Synch Status Information in the RLF Report Example 1: A non-limiting example of logging the predicted measurements andinformation in the RLF report is implemented (and highlighted via bold, underlined text) in thefollowing based on 3GPP TS 38.331 version 17.6.0. RLF report content determinationThe UE shall determine the content in the VarRLF-Report as follows:1> clear the information included in VarRLF-Report, if any;1>set the plmn-IdentityList to include the list of EPLMNs stored by the UE (i.e. includes the RPLMN); 1> set the measResultLastServCell to include the cell level RSRP, RSRQ and the availableSINR, of the source PCell (in case HO failure) or PCell (in case RLF) based on the available SSB and CSI-RS measurements collected up to the moment the UE detected failure;1> if the SS / PBCH block-based measurement quantities are available:2> set the rsIndexResults in measResultLastServCell to include all the available measurementquantities of the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the highest SS / PBCH block RSRP is listed first if SS / PBCH block RSRP measurement results are available, otherwise the highest SS / PBCH block RSRQ is listed first if SS / PBCH block RSRQ measurement results are available, otherwise the highest SS / PBCH block SINR is listed first, based on the available SS / PBCH block based measurements collected up to the moment the UE detected failure; 1> if the CSI-RS based measurement quantities are available:2> set the rsIndexResults in measResultLastServCell to include all the available measurementquantities of the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the highest CSI-RS RSRP is listed first if CSI-RS RSRP measurement results are available, otherwise the highest CSI-RS RSRQ is listed first if CSI-RS RSRQ measurement results are available, otherwise the highest CSI-RS SINR is listed first, based on the available CSI-RS based measurements collected up to the moment the UE detected failure;1> set the ssbRLMConfigBitmap and / or csi-rsRLMConfigBitmap in measResultLastServCell toinclude the radio link monitoring configuration of the source PCell (in case HO failure) orPCell (in case RLF), if available;1> for each of the configured measObjectNR in which measurements are available:2> if the SS / PBCH block-based measurement quantities are available:3> set the measResultListNR in measResultNeighCells to include all the available measurementquantities of the best measured cells, other than the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the cell with highest SS / PBCH block RSRP is listed first if SS / PBCH block RSRP measurement results are available, otherwise the cell with highest SS / PBCH block RSRQ is listed first if SS / PBCH block RSRQ measurement results are available, otherwise the cell with highest SS / PBCH block SINR is listed first, based on the available SS / PBCH block based measurements collected up to the moment the UE detected failure; 4> for each neighbour cell included, include the optional fields that are available;NOTE 0a:For the neighboring cells included in measResultListNR in measResultNeighCells orderedbased on the SS / PBCH block measurement quantities, UE also includes the CSI-RS basedmeasurement quantities, if available. 2> if the CSI-RS based measurement quantities are available:3> set the measResultListNR in measResultNeighCells to include all the available measurementquantities of the best measured cells, other than the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the cell with highest CSI-RS RSRP is listed first if CSI-RS RSRP measurement results are available, otherwise the cell with highest CSI-RS RSRQ is listed first if CSI-RS RSRQ measurement results are available, otherwise the cell with highest CSI-RS SINR is listed first, based on the available CSI-RS based measurements collected up to the moment the UE detected radio link failure; 4> for each neighbour cell included, include the optional fields that are available;NOTE 0b:For ordering the neighboring cells based on the CSI-RS measurement quantities, UE includes measurements only for the cells not yet included in measResultListNR inmeasResultNeighCells to avoid overriding SS / PBCH block-based ordered measurements. 2> for each neighbour cell, if any, included in measResultListNR in measResultNeighCells:3> if the UE supports RLF-Report for conditional handover and if the neighbour cell is one of thecandidate cells for which the reconfigurationWithSync is included in the masterCellGroup inthe MCG VarConditionalReconfig at the moment of the detected failure:4> set choConfig in MeasResult2NR to the execution condition for each measId withincondTriggerConfig associated to the neighbour cell within the MCGVarConditionalReconfig; 4> if the first entry of choConfig corresponds to a fulfilled execution condition at the momentof handover failure, or radio link failure; or4> if the second entry of choConfig, if available, corresponds to a fulfilled execution conditionat the moment of handover failure, or radio link failure:5> set firstTriggeredEvent to the execution condition condFirstEvent corresponding to thefirst entry of choConfig or to the execution condition condSecondEvent correspondingto the second entry of choConfig, whichever execution condition was fulfilled first intime; 5> set timeBetweenEvents to the elapsed time between the point in time of fullfilling thecondition in choConfig that was fulfilled first in time, and the point in time of fullfillingthe condition in choConfig that was fulfilled second in time, if both the first executioncondition corresponding to the first entry and the second execution condition corresponding to the second entry in the choConfig were fullfilled;1> for each of the configured measurement Objects in which predicted measurements areavailable: 2> if the SS / PBCH block-based predicted measurement quantities are available:3> set the measResultListNR in measResultNeighCells to include all the available predictedmeasurement quantities of the best measured cells, other than the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the cell with highest SS / PBCH block RSRP prediction is listed first if SS / PBCH block RSRP measurement prediction are available, otherwise the cell with highest SS / PBCH block RSRQ is listed first if SS / PBCH block RSRQ measurement prediction are available, otherwise the cell with highest SS / PBCH block SINR is listed first, based on the available SS / PBCH block based measurement prediction collected up to the moment the UE detected failure;NOTE 0a: For the neighboring cells included in measResultListNR in measResultNeighCellsordered based on the SS / PBCH block measurement prediction, UE also includes the CSI-RS based measurement prediction values, if available. 2> if the CSI-RS based measurement predictions are available:3> set the measResultListNR in measResultNeighCells to include all the availablemeasurement predictions of the best measured cells, other than the source PCell (in case HO failure) or PCell (in case RLF), ordered such that the cell with highest CSI-RS RSRP prediction value is listed first if CSI-RS RSRP measurement prediction values are available, otherwise the cell with highest CSI-RS RSRQ predicition is listed first if CSI- RS RSRQ measurement prediction values are available, otherwise the cell with highest CSI-RS SINR prediction is listed first, based on the available CSI-RS based measurements prediction value collected up to the moment the UE detected radio link failure;NOTE 0b: For ordering the neighboring cells based on the CSI-RS measurement predicitons,UE includes measurement prediction values only for the cells not yet included in measResultListNR in measResultNeighCells to avoid overriding SS / PBCH block-basedordered cells and predicitons.1> for each of the configured EUTRA frequencies in which measurements are available;2> set the measResultListEUTRA in measResultNeighCells to include the best measured cells orderedsuch that the cell with highest RSRP is listed first if RSRP measurement results are available, otherwise the cell with highest RSRQ is listed first, and based on measurements collected up to the moment the UE detected failure; 3> for each neighbour cell included, include the optional fields that are available;NOTE 1: The measured quantities are filtered by the L3 filter as configured in the mobility measurementconfiguration. The measurements are based on the time domain measurement resource restriction, if configured. Exclude-listed cells are not required to be reported.1> set the c-RNTI to the C-RNTI used in the source PCell (in case HO failure) or PCell (in caseRLF);1> if the failure is detected due to reconfiguration with sync failure as described in 5.3.5.8.3, setthe fields in VarRLF-report as follows:2> set the connectionFailureType to hof;2> if the UE supports RLF-Report for DAPS handover and if any DAPS bearer was configured whileT304 was running: 3> set lastHO-Type to daps;3> if radio link failure was detected in the source PCell, according to clause 5.3.10.3:4> set timeConnSourceDAPS-Failure to the time between the initiation of the DAPS handoverexecution and the radio link failure detected in the source PCell while T304 was running; 4> set the rlf-Cause to the trigger for detecting the source radio link failure in accordance withclause 5.3.10.4; 2> if the UE supports RLF-Report for conditional handover and if configuration of the conditionalhandover is available in the MCG VarConditionalReconfig at the moment of the handover failure:3> if the UE executed a conditional handover toward target PCell according to thecondRRCReconfig of the target PCell:4> set timeSinceCHO-Reconfig to the time elapsed between the execution of the lastRRCReconfiguration message including reconfigurationWithSync for the target PCell of thefailed conditional handover, and the reception in the source PCell of the last conditionalReconfiguration including the condRRCReconfig of the target PCell of the failedconditional handover; 3> else:4> set timeSinceCHO-Reconfig to the time elapsed between the execution of the lastRRCReconfiguration message including reconfigurationWithSync for the target PCell of thefailed handover, and the reception in the source PCell of the last conditionalReconfiguration including the condRRCReconfig;3> set choCandidateCellList to include the global cell identity, if available, and otherwise to thephysical cell identity and carrier frequency of each of the candidate target cells for conditional handover included in condRRCReconfig within the MCG VarConditionalReconfig at the timeof the failed handover, excluding the candidate target cells included in measResulNeighCells; 2> if the UE supports RLF-Report for conditional handover and if the last executedRRCReconfiguration message including reconfigurationWithSync was concerning a conditionalhandover: 3> set lastHO-Type to cho;2> set the nrFailedPCellId in failedPCellId to the global cell identity and tracking area code, ifavailable, and otherwise to the physical cell identity and carrier frequency of the target PCell of the failed handover; 2> include nrPreviousCell in previousPCellId and set it to the global cell identity and tracking areacode of the PCell where the last RRCReconfiguration message including reconfigurationWithSyncwas received; 2> set the timeConnFailure to the elapsed time since the execution of the last RRCReconfigurationmessage including the reconfigurationWithSync;> else if the failure is detected due to Mobility from NR failure as described in 5.4.3.5, set thefields in VarRLF-report as follows:2> set the connectionFailureType to hof;2> if last MobilityFromNRCommand concerned a failed inter-RAT handover from NR to E-UTRAand if the UE supports Radio Link Failure Report for Inter-RAT MRO EUTRA (NR to EUTRA): 3> set the eutraFailedPCellId in failedPCellId to the global cell identity and tracking area code, ifavailable, and otherwise to the physical cell identity and carrier frequency of the target PCell of the failed handover;2> include nrPreviousCell in previousPCellId and set it to the global cell identity and tracking areacode of the PCell where the last MobilityFromNRCommand message was received;2> set the timeConnFailure to the elapsed time since the initialization of the handover associated tothe last MobilityFromNRCommand message;1> else if the failure is detected due to radio link failure as described in 5.3.10.3, set the fields inVarRLF-report as follows:2> set the connectionFailureType to rlf;2> set the rlf-Cause to the trigger for detecting radio link failure in accordance with clause5.3.10.4; 2> set the nrFailedPCellId in failedPCellId to the global cell identity and the tracking areacode, if available, and otherwise to the physical cell identity and carrier frequency of the PCell where radio link failure is detected; 2> if an RRCReconfiguration message including the reconfigurationWithSync was receivedbefore the connection failure: 3> if the last successfully executed RRCReconfiguration message including thereconfigurationWithSync concerned an intra NR handover and it was received whileconnected to the previous PCell to which the UE was connected before connecting to the PCell where radio link failure is detected; and 3> if T311 was not running before entering the PCell in which the radio link failure wasdetected: 4> include the nrPreviousCell in previousPCellId and set it to the global cell identityand the tracking area code of the PCell where the last executed RRCReconfiguration message including reconfigurationWithSync was received;4> if the last executed RRCReconfiguration message includingreconfigurationWithSync was concerning a DAPS handover:5> set lastHO-Type to daps;4> else if the last executed RRCReconfiguration message includingreconfigurationWithSync was concerning a conditional handover:5> set lastHO-Type to cho;4> set the timeConnFailure to the elapsed time since the execution of the lastRRCReconfiguration message including the reconfigurationWithSync;3> else if the last RRCReconfiguration message including the reconfigurationWithSyncconcerned a handover to NR from E-UTRA and if the UE supports Radio Link Failure Report for Inter-RAT MRO EUTRA: 4> include the eutraPreviousCell in previousPCellId and set it to the global cellidentity and the tracking area code of the E-UTRA PCell where the last RRCReconfiguration message including reconfigurationWithSync was receivedembedded in E-UTRA RRC message MobilityFromEUTRACommand message asspecified in TS 36.331

[0010] clause 5.4.3.3;4> set the timeConnFailure to the elapsed time since reception of the lastRRCReconfiguration message including the reconfigurationWithSync embedded inE-UTRA RRC message MobilityFromEUTRACommand message as specified inTS 36.331

[0010] clause 5.4.3.3; 2> if configuration of the conditional handover is available in the MCGVarConditionalReconfig at the moment of declaring the radio link failure: 3> set timeSinceCHO-Reconfig to the time elapsed between the detection of the radio linkfailure, and the reception, in the source PCell, of the last conditionalReconfiguration including the condRRCReconfig message;3> set choCandidateCellList to include the global cell identity if available, and otherwiseto the physical cell identity and carrier frequency of each of all the candidate target cells for conditional handover included in condRRCReconfig within the MCGVarConditionalReconfig at the time of radio link failure, excluding the candidatetarget cells included in measResulNeighCells; 1> if connectionFailureType is rlf and the rlf-Cause is set to randomAccessProblem orbeamFailureRecoveryFailure; or 1> if connectionFailureType is hof and if the failed handover is an intra-RAT handover:2> set the ra-InformationCommon to include the random-access related information asdescribed in clause 5.7.10.5; 1> if available, set the locationInfo as in 5.3.3.7.The UE may discard the radio link failure information or handover failure information, i.e. releasethe UE variable VarRLF-Report, 48 hours after the radio link failure / handover failure is detected.NOTE 2: In this clause, the term 'handover failure' has been used to refer to 'reconfiguration with syncfailure'. MeasResults The IE MeasResults covers measured results for intra-frequency, inter-frequency, inter-RAT mobility and measured results for NR sidelink communication / discovery. MeasResults information element-- ASN1START-- TAG-MEASRESULTS-STARTMeasResults ::= SEQUENCE { measId MeasId, measResultServingMOList MeasResultServMOList, measResultNeighCells CHOICE { measResultListNR MeasResultListNR, ..., measResultListEUTRA MeasResultListEUTRA, measResultListUTRA-FDD-r16 MeasResultListUTRA-FDD-r16, sl-MeasResultsCandRelay-r17 OCTET STRING -- Contains PC5 SL-MeasResultListRelay-r17 measResultListNR-Predicted MeasResultListNR-Predicted OPTIONAL}OPTIONAL, ..., [[ measResultServFreqListEUTRA-SCG MeasResultServFreqListEUTRA-SCG OPTIONAL, measResultServFreqListNR-SCG MeasResultServFreqListNR-SCG OPTIONAL, measResultSFTD-EUTRA MeasResultSFTD-EUTRA OPTIONAL, measResultSFTD-NR MeasResultCellSFTD-NR OPTIONAL ]], [[ measResultCellListSFTD-NR MeasResultCellListSFTD-NR OPTIONAL ]], [[ measResultForRSSI-r16 MeasResultForRSSI-r16OPTIONAL, locationInfo-r16 LocationInfo-r16 OPTIONAL, ul-PDCP-DelayValueResultList-r16 UL-PDCP-DelayValueResultList-r16OPTIONAL,measResultsSL-r16 MeasResultsSL-r16 OPTIONAL, measResultCLI-r16 MeasResultCLI-r16 OPTIONAL ]], [[ measResultRxTxTimeDiff-r17 MeasResultRxTxTimeDiff-r17 OPTIONAL, sl-MeasResultServingRelay-r17 OCTET STRING OPTIONAL, -- Contains PC5 SL-MeasResultRelay-r17ul-PDCP-ExcessDelayResultList-r17 UL-PDCP-ExcessDelayResultList-r17 OPTIONAL, coarseLocationInfo-r17 OCTET STRINGOPTIONAL ]] } MeasResultServMOList ::= SEQUENCE (SIZE (1..maxNrofServingCells)) OF MeasResultServMO MeasResultServMO ::= SEQUENCE { servCellId ServCellIndex, measResultServingCell MeasResultNR, measResultBestNeighCell MeasResultNR OPTIONAL, ... } MeasResultListNR ::= SEQUENCE (SIZE (1..maxCellReport)) OF MeasResultNR MeasResultListNR-Predicted ::= SEQUENCE (SIZE (1..maxCellReport)) OF PredictedmeasResultNR MeasResultNR ::= SEQUENCE { physCellId PhysCellId OPTIONAL, measResult SEQUENCE { cellResults SEQUENCE{ resultsSSB-Cell MeasQuantityResults OPTIONAL, resultsCSI-RS-Cell MeasQuantityResults OPTIONAL }, rsIndexResults SEQUENCE{resultsSSB-Indexes ResultsPerSSB-IndexList OPTIONAL, resultsCSI-RS-Indexes ResultsPerCSI-RS-IndexList OPTIONAL } OPTIONAL }, ..., [[ cgi-Info CGI-InfoNR OPTIONAL ]] , [[ choCandidate-r17 ENUMERATED {true} OPTIONAL, choConfig-r17 SEQUENCE (SIZE (1..2)) OF CondTriggerConfig-r16 OPTIONAL, triggeredEvent-r17 SEQUENCE { timeBetweenEvents-r17 TimeBetweenEvent-r17 OPTIONAL, firstTriggeredEvent ENUMERATED {condFirstEvent, condSecondEvent} OPTIONAL } OPTIONAL ]] } predicted_MeasResultNR ::= SEQUENCE { physCellId PhysCellId OPTIONAL,cgi-Info CGI-InfoNR MeasResultListEUTRA ::= SEQUENCE (SIZE (1..maxCellReport)) OF MeasResultEUTRA MeasResultEUTRA ::= SEQUENCE { eutra-PhysCellId PhysCellId, measResult MeasQuantityResultsEUTRA, cgi-Info CGI-InfoEUTRA OPTIONAL, ...} MultiBandInfoListEUTRA ::= SEQUENCE (SIZE (1..maxMultiBands)) OF FreqBandIndicatorEUTRA MeasQuantityResults ::= SEQUENCE { rsrp RSRP-Range OPTIONAL, rsrq RSRQ-Range OPTIONAL, sinr SINR-Range OPTIONAL }MeasQuantityResultsEUTRA ::= SEQUENCE {rsrp RSRP-RangeEUTRA OPTIONAL, rsrq RSRQ-RangeEUTRA OPTIONAL, sinr SINR-RangeEUTRA OPTIONAL } ResultsPerSSB-IndexList::= SEQUENCE (SIZE (1..maxNrofIndexesToReport2)) OF ResultsPerSSB-Index ResultsPerSSB-Index ::= SEQUENCE { ssb-Index SSB-Index, ssb-Results MeasQuantityResults OPTIONAL } ResultsPerCSI-RS-IndexList::= SEQUENCE (SIZE (1..maxNrofIndexesToReport2)) OF ResultsPerCSI-RS-Index ResultsPerCSI-RS-Index ::= SEQUENCE { csi-RS-Index CSI-RS-Index, csi-RS-Results MeasQuantityResults OPTIONAL } MeasResultServFreqListEUTRA-SCG ::= SEQUENCE (SIZE (1..maxNrofServingCellsEUTRA)) OF MeasResult2EUTRA MeasResultServFreqListNR-SCG ::= SEQUENCE (SIZE (1..maxNrofServingCells)) OF MeasResult2NR MeasResultListUTRA-FDD-r16 ::= SEQUENCE (SIZE (1..maxCellReport)) OF MeasResultUTRA-FDD-r16 MeasResultUTRA-FDD-r16 ::= SEQUENCE { physCellId-r16 PhysCellIdUTRA-FDD-r16, measResult-r16 SEQUENCE { utra-FDD-RSCP-r16 INTEGER (-5..91) OPTIONAL, utra-FDD-EcN0-r16 INTEGER (0..49) OPTIONAL } } MeasResultForRSSI-r16 ::= SEQUENCE { rssi-Result-r16 RSSI-Range-r16, channelOccupancy-r16 INTEGER (0..100) } MeasResultCLI-r16 ::= SEQUENCE { measResultListSRS-RSRP-r16 MeasResultListSRS-RSRP-r16OPTIONAL, measResultListCLI-RSSI-r16 MeasResultListCLI-RSSI-r16 OPTIONAL } MeasResultListSRS-RSRP-r16 ::= SEQUENCE (SIZE (1.. maxCLI-Report-r16)) OF MeasResultSRS- RSRP-r16 MeasResultSRS-RSRP-r16 ::= SEQUENCE { srs-ResourceId-r16 SRS-ResourceId, srs-RSRP-Result-r16 SRS-RSRP-Range-r16 } MeasResultListCLI-RSSI-r16 ::= SEQUENCE (SIZE (1.. maxCLI-Report-r16)) OF MeasResultCLI-RSSI-r16MeasResultCLI-RSSI-r16 ::= SEQUENCE { rssi-ResourceId-r16 RSSI-ResourceId-r16, cli-RSSI-Result-r16 CLI-RSSI-Range-r16 } UL-PDCP-DelayValueResultList-r16 ::= SEQUENCE (SIZE (1..maxDRB)) OF UL-PDCP- DelayValueResult-r16 UL-PDCP-DelayValueResult-r16 ::= SEQUENCE { drb-Id-r16 DRB-Identity, averageDelay-r16 INTEGER (0..10000), ... } UL-PDCP-ExcessDelayResultList-r17 ::= SEQUENCE (SIZE (1..maxDRB)) OF UL-PDCP- ExcessDelayResult-r17 UL-PDCP-ExcessDelayResult-r17 ::= SEQUENCE { drb-Id-r17 DRB-Identity, excessDelay-r17 INTEGER (0..31), ... } TimeBetweenEvent-r17 ::= INTEGER (0..1023)-- TAG-MEASRESULTS-STOP-- ASN1STOP MeasResultEUTRA field descriptions eutra-PhysCellId Identifies the physical cell identity of the E-UTRA cell for which the reporting is being performed. The UE reports a value in the range 0..503, other values are reserved. MeasResultNR field descriptions averageDelay Indicates average delay for the packets during the reporting period, as specified in TS 38.314

[0053] . Value 0 corresponds to 0 millisecond, value 1 corresponds to 0.1 millisecond, value 2 corresponds to 0.2 millisecond, and so on. cellResults Cell level measurement results. choCandidate This field indicates whether the associated cell is a candidate target cell for conditional handover or conditional PSCell change or addition. This field may be included only in the SuccessHO-Report orSuccessPSCell-Report within UEInformationResponse message.choConfig If the associated cell is a candidate target cell for conditional handover, this field indicates the conditional handover execution condition for each measId within condTriggerConfig associated to the cell. This fieldmay be included only in the rlf-report within UEInformationResponse message.drb-Id Indicates DRB value for which uplink PDCP delay ratio or value is provided, according to TS 38.314

[0053] . firstTriggeredEvent This field is set to condFirstEvent if the execution condition associated to the first entry of choConfig wasfulfilled first in time. This field is set to condSecondEvent if the execution condition associated to the secondentry of choConfig was fulfilled first in time. This field may be included in rlf-report withinUEInformationResponse message or in SCGFailureInformation message.locationInfo Positioning related information and measurements. physCellId The physical cell identity of the NR cell for which the reporting is being performed. predicted_MeasResultNR This field includes the prediction of the measurements. The predicitons are logged in the radio link failure report and the successful handover report. resultsSSB-Cell Cell level measurement results based on SS / PBCH related measurements. resultsSSB-Indexes Beam level measurement results based on SS / PBCH related measurements. resultsCSI-RS-Cell Cell level measurement results based on CSI-RS related measurements. resultsCSI-RS-Indexes Beam level measurement results based on CSI-RS related measurements. rsIndexResults Beam level measurement results. timeBetweenEvents Indicates the time elapsed between fulfilling the conditional execution conditions included in choConfig. Value in milliseconds. The maximum value 1023 means 1023ms or longer. This field may be included in the reports associated to UEInformationResponse message, e.g., rlf-Report or in the SCGFailureInformationmessage. Example 2: A non-limiting example of the TCI state of the target cells or (so called pre-synchronization information of the target cell) in the RLF report is shown in the following basedon the TS 38.331 version 17.6.0. measResultListNR-r16 MeasResultList2NR-r16 OPTIONAL, measResultListEUTRA-r16 MeasResultList2EUTRA-r16 OPTIONAL } OPTIONAL, c-RNTI-r16 RNTI-Value, previousPCellId-r16 CHOICE { nrPreviousCell-r16 CGI-Info-Logging-r16, eutraPreviousCell-r16 CGI-InfoEUTRALogging } OPTIONAL, failedPCellId-r16 CHOICE { nrFailedPCellId-r16 CHOICE { cellGlobalId-r16 CGI-Info-Logging-r16, pci-arfcn-r16 PCI-ARFCN-NR-r16 }, eutraFailedPCellId-r16 CHOICE { cellGlobalId-r16 CGI-InfoEUTRALogging,pci-arfcn-r16 PCI-ARFCN-EUTRA-r16 } }, reconnectCellId-r16 CHOICE { nrReconnectCellId-r16 CGI-Info-Logging-r16,eutraReconnectCellId-r16 CGI-InfoEUTRALogging } OPTIONAL, timeUntilReconnection-r16 TimeUntilReconnection-r16 OPTIONAL, reestablishmentCellId-r16 CGI-Info-Logging-r16 OPTIONAL, timeConnFailure-r16 INTEGER (0..1023) OPTIONAL, timeSinceFailure-r16 TimeSinceFailure-r16, connectionFailureType-r16 ENUMERATED {rlf, hof}, rlf-Cause-r16 ENUMERATED {t310- rlc-MaxNumRetx, beamFailureRecoveryFailure,lbtFailure-r16,bh-rlfRecoveryFailure, t312- expiry-r17, spare1}, locationInfo-r16 LocationInfo-r16 OPTIONAL, noSuitableCellFound-r16 ENUMERATED {true} OPTIONAL, ra-InformationCommon-r16 RA-InformationCommon-r16 OPTIONAL, ..., [[ csi-rsRLMConfigBitmap-v1650 BIT STRING (SIZE (96)) OPTIONAL ]], [[ lastHO-Type-r17 ENUMERATED {cho, daps, spare2, spare1}OPTIONAL, timeConnSourceDAPS-Failure-r17 TimeConnSourceDAPS-Failure-r17 OPTIONAL, timeSinceCHO-Reconfig-r17 TimeSinceCHO-Reconfig-r17 OPTIONAL, choCellId-r17 CHOICE { cellGlobalId-r17 CGI-Info-Logging-r16, pci-arfcn-r17 PCI-ARFCN-NR-r16 } OPTIONAL, choCandidateCellList-r17 ChoCandidateCellList-r17 OPTIONAL ]], }, eutra-RLF-Report-r16 SEQUENCE { failedPCellId-EUTRA CGI-InfoEUTRALogging, measResult-RLF-Report-EUTRA-r16 OCTET STRING,..., [[ measResult-RLF-Report-EUTRA-v1690 OCTET STRING OPTIONAL ]], [[ preSynch-targetCell-r19 ENUMERATED {synch-DL, synch-UL, synch-DL&UP} OPTIONAL, ]] Or in another example implementation notSynch-targetCell-r19 ENUMERATED {true} OPTIONAL, RLF-Report field descriptionschoCandidateCellList This field is used to indicate the list of candidate target cells for conditional handover included incondRRCReconfig at the time of connection failure. The field does not include the candidate target cellsincluded in measResultNeighCells. choCellId This field is used to indicate the candidate target cell for conditional handover included incondRRCReconfig that the UE selected for CHO based recovery while T311 is running.connectionFailureType This field is used to indicate whether the connection failure is due to radio link failure or handover failure. csi-rsRLMConfigBitmap,csi-rsRLMConfigBitmap-v1650 These fields are used to indicate the CSI-RS indexes configured in the RLM configurations for the active BWP when the UE declares RLF or HOF. The UE first fills in the csi-rsRLMConfigBitmap-r16 to indicate thefirst 96 CSI-RS indexes and then csi-rsRLMConfigBitmap-v1650 to indicate the latter 96 CSI-RS indexes.The first / leftmost bit in csi-rsRLMConfigBitmap-r16 corresponds to CSI-RS index 0, the second bit corresponds to CSI-RS index 1. The first / leftmost bit in csi-rsRLMConfigBitmap-v1650 corresponds to CSI- RS index 96, the second bit corresponds to CSI-RS index 97. These fields are included only if the RadioLinkMonitoringConfig for the respective BWP is configured.c-RNTI This field indicates the C-RNTI used in the PCell upon detecting radio link failure or the C-RNTI used in the source PCell upon handover failure. failedPCellId This field is used to indicate the PCell in which RLF is detected or the target PCell of the failed handover. For intra-NR handover nrFailedPCellId is included and for the handover from NR to EUTRAeutraFailedPCellId is included. The UE sets the ARFCN according to the frequency band used fortransmission / reception when the failure occurred. failedPCellId-EUTRA This field is used to indicate the PCell in which RLF is detected or the source PCell of the failed handover in an E-UTRA RLF report. lastHO-Type This field is used to indicate the type of the last executed handover before the last detected connection failure. The field is set to cho if the last executed handover was initiated by a conditional reconfigurationexecution. The field is set to daps if the last executed handover was a DAPS handover.measResultListEUTRA This field refers to the last measurement results taken in the neighboring EUTRA Cells, when the radio link failure or handover failure happened. measResultListNR This field refers to the last measurement results taken in the neighboring NR Cells, when the radio link failure or handover failure happened. measResultLastServCell This field refers to the log measurement results taken in the PCell upon detecting radio link failure or the source PCell upon handover failure. measResult-RLF-Report-EUTRA Includes the E-UTRA RLF-Report-r9 IE as specified in TS 36.331

[0010] .measResult-RLF-Report-EUTRA-v1690 Includes the E-UTRA RLF-Report-v9e0 IE as specified in TS 36.331

[0010] .noSuitableCellFound This field is set by the UE when the T311 expires. preSynch-targetCell This field indicates whether the UE was in synch with the target prior to the execution of the mobility procedure. synch-DL is used if the UE was only in downlink synch with the target cell. synch-UL is used if the UE was only in uplink synch with the target cell. synch-DL&UP is used if the UE was in uplink and downlink synch with the target cell prior the mobility procedure execution. notSynch-targetCell This field is set when the target cell was not a cell that UE was in synch prior to the mobility procedure execution i.e., the target cell was not a cell the UE received a candidate cell TCI activation command previousPCellId This field is used to indicate the source PCell of the last handover (source PCell when the last executed RRCReconfiguration message including reconfigurationWithSync was received). For intra-NR handovernrPreviousCell is included and for the handover from EUTRA to NR eutraPreviousCell is included. ra-InformationCommon This field is optionally included when connectionFailureType is set to 'hof' or when connectionFailureType isset to 'rlf' and the rlf-Cause equals to 'randomAccessProblem' or 'beamRecoveryFailure'; otherwise thisfield is absent. reconnectCellId This field is used to indicate the cell in which the UE comes back to connected after connection failure and after failing to perform reestablishment. If the UE comes back to RRC CONNECTED in an NR cell then nrReconnectCellID is included and if the UE comes back to RRC CONNECTED in an LTE cell theneutraReconnectCellID is includedreestablishmentCellId If the UE was not configured with conditionalReconfiguration at the time of re-establishment attempt, or ifthe cell selected for the re-establishment attempt is not a candidate target cell for conditional reconfiguration, this field is used to indicate the cell in which the re-establishment attempt was made after connection failure. rlf-Cause This field is used to indicate the cause of the last radio link failure that was detected. In case of handover failure information reporting (i.e., the connectionFailureType is set to 'hof'), the UE is allowed to set this fieldto any value, except for the case in which a radio link failure was detected in the source PCell while performing a DAPS handover. ssbRLMConfigBitmap This field is used to indicate the SS / PBCH block indexes configured in the RLM configurations for the active BWP when the UE declares RLF or HOF.The first / leftmost bit corresponds to SSB index 0, the second bit corresponds to SSB index 1. This field is included only if the RadioLinkMonitoringConfig for the respectiveBWP is configured. timeConnFailure This field is used to indicate the time elapsed since the last HO execution until connection failure. Actualvalue = field value * 100ms. The maximum value 1023 means 102.3s or longer. timeConnSourceDAPS-Failure This field is used to indicate the time that elapsed between the last DAPS handover execution and the radio link failure detected in the source cell while T304 is running. Value in milliseconds. The maximum value1023 means 1023ms or longer. timeSinceFailure This field is used to indicate the time that elapsed since the connection (radio link or handover) failure. Value in seconds. The maximum value 172800 means 172800s or longer. In the case of failure(s) (either at source or at target or at both) associated to DAPS handover, this field indicates the time elapsed since the latest connection (radio link or handover) failure. timeSinceCHO-Reconfig In case of handover failure, this field is used to indicate the time elapsed between the initiation of the last handover execution towards the target cell and the reception of the latest conditional reconfiguration. Incase of radio link failure, this field is used to indicate the time elapsed between the radio link failure and the reception of the latest conditional reconfiguration while connected to the source PCell. Actual value = field value * 100ms. The maximum value 1023 means 102.3s or longer. timeUntilReconnection This field is used to indicate the time that elapsed between the connection (radio link or handover) failure and the next time the UE comes to RRC CONNECTED in an NR or EUTRA cell, after failing to perform reestablishment. Value in seconds. The maximum value 172800 means 172800s or longer.Further Description Figure 6 shows an example of a communication system 600 in which the embodimentsdescribed above may be implemented. In the example, the communication system 600 includes a telecommunication network 602 that includes an access network 604, such as a Radio Access Network (RAN), and a core network 606, which includes one or more core network nodes 608. The access network 604 includes one or more access network nodes, such as network nodes 610A and 610B (one or more of which may be generally referred to as network nodes 610), or any other similar Third Generation Partnership Project (3GPP) access nodes or non-3GPP Access Points (APs). The network nodes 610 may perform the operations of the serving network node or network node described above, e.g., with respect to Figures 1 to 5. 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 602 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 602 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 602, including one or more network nodes 610 and / or core network nodes 608. 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- real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node maysupport a specification by, for example, supporting an interface defined by the ORANspecification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access nodemay be a logical node in a physical node. Furthermore, an ORAN network node may beimplemented 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 OrchestrationFramework via an O-2 interface defined by the O-RAN Alliance or comparable technologies.The network nodes 610 facilitate direct or indirect connection of User Equipment (UE), such as by connecting UEs 612A, 612B, 612C, and 612D (one or more of which may be generally referred to as UEs 612) to the core network 606 over one or more wireless connections. Note that that UEs 612 perform the operations of the UE described above, e.g., with respect to Figures 1 to 5. 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 600 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 600 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system. The UEs 612 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 610 and other communication devices. Similarly, the network nodes 610 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 612 and / or with other network nodes or equipment in the telecommunication network 602 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 602. In the depicted example, the core network 606 connects the network nodes 610 to one or more hosts, such as host 616. 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 606 includes one more core network nodes (e.g., core network node 608) that are structured with hardware and software components. Features of these 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 608. 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). The host 616 may be under the ownership or control of a service provider other than an operator or provider of the access network 604 and / or the telecommunication network 602, and may be operated by the service provider or on behalf of the service provider. The host 616 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.As a whole, the communication system 600 of Figure 6 enables connectivity between theUEs, network nodes, and hosts. In that sense, the communication system 600 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 Second, Third, Fourth, or Fifth Generation (2G, 3G, 4G, or 5G) standards, or any applicable future generation standard (e.g., Sixth Generation (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. In some examples, the telecommunication network 602 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunication network 602 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 602. For example, the telecommunication network 602 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing enhanced Mobile Broadband (eMBB) services to other UEs, and / or massive Machine Type Communication (mMTC) / massive Internet of Things (IoT) services to yet further UEs. In some examples, the UEs 612 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 604 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 604. Additionally, a UE may beconfigured for operating in single- or multi-Radio Access Technology (RAT) or multi-standardmode. For example, a UE may operate with any one or combination of WiFi, New Radio (NR), and LTE, i.e. being configured for Multi-Radio Dual Connectivity (MR-DC), such as EvolvedUMTS Terrestrial RAN (E-UTRAN) NR - Dual Connectivity (EN-DC).In the example, a hub 614 communicates with the access network 604 to facilitate indirect communication between one or more UEs (e.g., UE 612C and / or 612D) and network nodes (e.g., network node 610B). In some examples, the hub 614 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 614 may be a broadband router enabling access to the core network 606 for the UEs. As another example, the hub 614 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 610, or by executable code, script, process, or other instructions in the hub 614. As another example, the hub 614 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 614 may be a content source. For example, for a UE that is a Virtual Reality (VR) headset, display, loudspeaker or other media delivery device, the hub 614 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 614 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 614 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy IoT devices. The hub 614 may have a constant / persistent or intermittent connection to the network node 610B. The hub 614 may also allow for a different communication scheme and / or schedule between the hub 614 and UEs (e.g., UE 612C and / or 612D), and between the hub 614 and the core network 606. In other examples, the hub 614 is connected to the core network 606 and / or one or more UEs via a wired connection. Moreover, the hub 614 may be configured to connect to a Machine-to-Machine (M2M) service provider over the access network 604 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 610 while still connected via the hub 614 via a wired or wireless connection.In some embodiments, the hub 614 may be a dedicated hub – that is, a hub whose primaryfunction is to route communications to / from the UEs from / to the network node 610B. In otherembodiments, the hub 614 may be a non-dedicated hub – that is, a device which is capable ofoperating to route communications between the UEs and the network node 610B, but which is additionally capable of operating as a communication start and / or end point for certain data channels. Figure 7 shows a UE 700 in accordance with some embodiments. As used herein, a UErefers 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 smartphone, mobile phone, cell phone, Voice over Internet Protocol (VoIP) phone, wireless local loopphone, desktop computer, Personal Digital Assistant (PDA), wireless camera, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, Laptop Embedded Equipment (LEE), Laptop Mounted Equipment (LME), smart device, wireless Customer Premise Equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3GPP, including a Narrowband Internet of Things (NB-IoT) UE, a Machine Type Communication (MTC) UE, and / or an enhanced MTC (eMTC) UE. A UE may support Device-to-Device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), or Vehicle-to-Everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter). The UE 700 includes processing circuitry 702 that is operatively coupled via a bus 704 to an input / output interface 706, a power source 708, memory 710, a communication interface 712, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Figure 7. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc. The processing circuitry 702 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 710. The processing circuitry 702 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 702 may include multiple Central Processing Units (CPUs). In the example, the input / output interface 706 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 700. 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. In some embodiments, the power source 708 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 708 may further include power circuitry for delivering power from the power source 708 itself, and / or an external power source, to the various parts of the UE 700 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 708. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 708 to make the power suitable for the respective components of the UE 700 to which power is supplied. The memory 710 may be or be configured to include memory such as Random Access Memory (RAM), Read Only Memory (ROM), Programmable ROM (PROM), Erasable PROM (EPROM), Electrically EPROM (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 710 includes one or more application programs 714, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 716. The memory 710 may store, for use by the UE 700, any of a variety of various operating systems or combinations of operating systems. The memory 710 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 RAM (SDRAM), external micro-DIMM SDRAM, smartcard memory such as a tamper resistant module in the form of a Universal Integrated Circuit Card (UICC) including one or more Subscriber Identity Modules (SIMs), such as a Universal SIM (USIM) and / or Internet Protocol Multimedia Services Identity Module (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 a ‘SIM card.’ The memory 710 may allow the UE 700 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 memory710, which may be or comprise a device-readable storage medium. The processing circuitry 702 may be configured to communicate with an access network or other network using the communication interface 712. The communication interface 712 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 722. The communication interface 712 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 718 and / or a receiver 720 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 718 and receiver 720 may be coupled to one or more antennas (e.g., the antenna 722) and may share circuit components, software, or firmware, or alternatively be implemented separately. In the illustrated embodiment, communication functions of the communication interface 712 may include cellular communication, WiFi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communicationssuch as Bluetooth, NFC, location-based communication such as the use of the Global PositioningSystem (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband CDMA (WCDMA), GSM, LTE, NR, UMTS, WiMax, Ethernet, Transmission Control Protocol / Internet Protocol (TCP / IP), Synchronous Optical Networking (SONET), Asynchronous Transfer Mode (ATM), Quick User Datagram Protocol Internet Connection (QUIC), Hypertext Transfer Protocol (HTTP), and so forth. Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 712, 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). 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. A UE, when in the form of an IoT 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 IoT device are a device which is or which is embedded in: a connected refrigerator or freezer, a television, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) orVR, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- oritem-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 IoT device comprises circuitry and / or software in dependence of the intended application of the IoT device in addition to other components as described in relation to the UE 700 shown in Figure 7. As yet another specific example, in an IoT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements and transmits the results of suchmonitoring and / or measurements to another UE and / or a network node. The UE may in this casebe an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-IoT standard. In other scenarios, a UEmay represent a vehicle, such as a car, a bus, a truck, a ship, an airplane, or other equipment thatis capable of monitoring and / or reporting on its operational status or other functions associated with its operation. 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 speedinformation (obtained through a speed sensor) to a second UE that is a remote controlleroperating 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. Figure 8 shows a network node 800 in accordance with some embodiments. As usedherein, 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 atelecommunication network. Examples of network nodes include, but are not limited to, APs(e.g., radio APs), Base Stations (BSs) (e.g., radio BSs, Node Bs, evolved Node Bs (eNBs), NR Node Bs (gNBs)), and O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O- CU). 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 RemoteRadio Units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such RRUs mayor 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). 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 BS 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). The network node 800 includes processing circuitry 802, memory 804, a communication interface 806, and a power source 808. The network node 800 may be composed of multiple physically separate components (e.g., a NodeB component and an 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 800 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 800 may be configured to support multiple RATs. In such embodiments, some components may be duplicated (e.g., separate memory 804 for different RATs) and some components may be reused (e.g., a same antenna 810 may be shared by different RATs). The network node 800 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 800, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, Long Range Wide Area Network (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 the network node 800. The processing circuitry 802 may comprise a combination of one or more of a microprocessor, controller, microcontroller, CPU, DSP, ASIC, FPGA, 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 800 components, such as the memory 804, to provide network node 800 functionality. In some embodiments, the processing circuitry 802 includes a System on a Chip (SOC). In some embodiments, the processing circuitry 802 includes one or more of Radio Frequency (RF) transceiver circuitry 812 and baseband processing circuitry 814. In some embodiments, the RF transceiver circuitry 812 and the baseband processing circuitry 814 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 the RF transceiver circuitry 812 and the baseband processing circuitry 814 may be on the same chip or set of chips, boards, or units. The memory 804 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, RAM, ROM, mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD), or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable, and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 802. The memory 804 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 802 and utilized by the network node 800. The memory 804 may be used to store any calculations made by the processing circuitry 802 and / or any data received via the communication interface 806. In some embodiments, the processing circuitry 802 and the memory 804 are integrated. The communication interface 806 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 806 comprises port(s) / terminal(s) 816 to send and receive data, for example to and from a network over a wired connection. The communication interface 806 also includes radio front-end circuitry 818 that may be coupled to, or in certain embodiments a part of, the antenna 810. The radio front-end circuitry 818 comprises filters 820 and amplifiers 822. The radio front-end circuitry 818 may be connected to the antenna 810 and the processing circuitry 802. The radio front-end circuitry 818 may be configured to condition signals communicated between the antenna 810 and the processing circuitry 802. The radio front-end circuitry 818 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 818 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of the filters 820 and / or the amplifiers 822. The radio signal may then be transmitted via the antenna 810. Similarly, when receiving data, the antenna 810 may collect radio signals which are then converted into digital data by the radio front-end circuitry 818. The digital data may be passed to the processing circuitry 802. In other embodiments, the communication interface 806 may comprise different components and / or different combinations of components. In certain alternative embodiments, the network node 800 does not include separate radio front-end circuitry 818; instead, the processing circuitry 802 includes radio front-end circuitry and is connected to the antenna 810. Similarly, in some embodiments, all or some of the RF transceiver circuitry 812 is part of the communication interface 806. In still other embodiments, the communication interface 806 includes the one or more ports or terminals 816, the radio front- end circuitry 818, and the RF transceiver circuitry 812 as part of a radio unit (not shown), and the communication interface 806 communicates with the baseband processing circuitry 814, which is part of a digital unit (not shown). The antenna 810 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 810 may be coupled to the radio front-end circuitry 818 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 810 is separate from the network node 800 and connectable to the network node 800 through an interface or port. The antenna 810, the communication interface 806, and / or the processing circuitry 802 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node 800. Any information, data, and / or signals may be received from a UE, another network node, and / or any other network equipment. Similarly, the antenna 810, the communication interface 806, and / or the processing circuitry 802 may be configured to perform any transmitting operations described herein as being performed by the network node 800. Any information, data, and / or signals may be transmitted to a UE, another network node, and / or any other network equipment. The power source 808 provides power to the various components of the network node 800 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 808 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 800 with power for performing the functionality described herein. For example, the network node 800 may be connectable to an external power source (e.g., the power grid or an electricity outlet) via input circuitry or an interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 808. As a further example, the power source 808 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. Embodiments of the network node 800 may include additional components beyond thoseshown in Figure 8 for providing certain aspects of the network node’s functionality, includingany of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node 800 may include user interface equipment to allow input of information into the network node 800 and to allow output of information from the network node 800. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 800. Figure 9 is a block diagram of a host 900, which may be an embodiment of the host 616 ofFigure 6, in accordance with various aspects described herein. As used herein, the host 900 may be or comprise various combinations of hardware and / or software including a standalone server, a blade server, a cloud-implemented server, a distributed server, a virtual machine, container, or processing resources in a server farm. The host 900 may provide one or more services to one or more UEs. The host 900 includes processing circuitry 902 that is operatively coupled via a bus 904 to an input / output interface 906, a network interface 908, a power source 910, and memory 912. Other components may be included in other embodiments. Features of these components may be substantially similar to those described with respect to the devices of previous figures, such asFigures 7 and 8, such that the descriptions thereof are generally applicable to the correspondingcomponents of the host 900. The memory 912 may include one or more computer programs including one or more host application programs 914 and data 916, which may include user data, e.g. data generated by a UE for the host 900 or data generated by the host 900 for a UE. Embodiments of the host 900 may utilize only a subset or all of the components shown. The host application programs 914 may be implemented in a container-based architecture and may provide support for video codecs (e.g., Versatile Video Coding (VVC), High Efficiency Video Coding (HEVC), Advanced Video Coding (AVC), Moving Picture Experts Group (MPEG), VP9) and audio codecs (e.g., Free Lossless Audio Codec (FLAC), Advanced Audio Coding (AAC), MPEG, G.711), including transcoding for multiple different classes, types, or implementations of UEs (e.g., handsets, desktop computers, wearable display systems, and heads-up display systems). The host application programs 914 may also provide for user authentication and licensing checks and may periodically report health, routes, and content availability to a central node, such as a device in or on the edge of a core network. Accordingly, the host 900 may select and / or indicate a different host for Over-The-Top (OTT) services for a UE. The host application programs 914 may support various protocols, such as the HTTP Live Streaming (HLS) protocol, Real-Time Messaging Protocol (RTMP), Real-Time Streaming Protocol (RTSP), Dynamic Adaptive Streaming over HTTP (DASH or MPEG-DASH), etc. Figure 10 is a block diagram illustrating a virtualization environment 1000 in whichfunctions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices, and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more Virtual Machines (VMs) implemented in one or more virtual environments 1000 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 1000 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface. Applications 1002 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 1000 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein. Hardware 1004 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 maybe executed by the processing circuitry to instantiate one or more virtualization layers 1006 (alsoreferred to as hypervisors or VM Monitors (VMMs)), provide VMs 1008A and 1008B (one or more of which may be generally referred to as VMs 1008), and / or perform any of the functions, features, and / or benefits described in relation with some embodiments described herein. The virtualization layer 1006 may present a virtual operating platform that appears like networking hardware to the VMs 1008. The VMs 1008 comprise virtual processing, virtual memory, virtual networking, or interface and virtual storage, and may be run by a corresponding virtualization layer 1006. Different embodiments of the instance of a virtual appliance 1002 may be implemented on one or more of the VMs 1008, 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. In the context of NFV, a VM 1008 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 1008, and that part of the hardware 1004 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs 1008, 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 1008 on top of the hardware 1004 and corresponds to the application 1002. The hardware 1004 may be implemented in a standalone network node with generic or specific components. The hardware 1004 may implement some functions via virtualization. Alternatively, the hardware 1004 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 1010, which, among others, oversees lifecycle management of the applications 1002. In some embodiments, the hardware 1004 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 RAN or a base station. In some embodiments, some signaling can be provided with the use of a control system 1012 which may alternatively be used for communication between hardware nodes and radio units. Figure 11 shows a communication diagram of a host 1102 communicating via a networknode 1104 with a UE 1106 over a partially wireless connection in accordance with some embodiments. Example implementations, in accordance with various embodiments, of the UE(such as the UE 612A of Figure 6 and / or the UE 700 of Figure 7), the network node (such as thenetwork node 610A of Figure 6 and / or the network node 800 of Figure 8), and the host (such asthe host 616 of Figure 6 and / or the host 900 of Figure 9) discussed in the preceding paragraphswill now be described with reference to Figure 11. Like the host 900, embodiments of the host 1102 include hardware, such as a communication interface, processing circuitry, and memory. The host 1102 also includes software, which is stored in or is accessible by the host 1102 and executable by the processing circuitry. The software includes a host application that may be operable to provide a service to a remote user, such as the UE 1106 connecting via an OTT connection 1150 extending between the UE 1106 and the host 1102. In providing the service to the remote user, a host application may provide user data which is transmitted using the OTT connection 1150. The network node 1104 includes hardware enabling it to communicate with the host 1102 and the UE 1106. The connection 1160 may be direct or pass through a core network (like the core network 606 of Figure 6) and / or one or more other intermediate networks, such as one or more public, private, or hosted networks. For example, an intermediate network may be a backbone network or the Internet. The UE 1106 includes hardware and software, which is stored in or accessible by the UE 1106 and executable by the UE’s processing circuitry. The software includes a client application, such as a web browser or operator-specific “app” that may be operable to provide a service to a human or non-human user via the UE 1106 with the support of the host 1102. In the host 1102, an executing host application may communicate with the executing client application via the OTT connection 1150 terminating at the UE 1106 and the host 1102. In providing the service to the user, the UE's client application may receive request data from the host's host application and provide user data in response to the request data. The OTT connection 1150 may transfer both the request data and the user data. The UE's client application may interact with the user to generate the user data that it provides to the host application through the OTT connection 1150. The OTT connection 1150 may extend via the connection 1160 between the host 1102 and the network node 1104 and via a wireless connection 1170 between the network node 1104 and the UE 1106 to provide the connection between the host 1102 and the UE 1106. The connection 1160 and the wireless connection 1170, over which the OTT connection 1150 may be provided, have been drawn abstractly to illustrate the communication between the host 1102 and the UE 1106 via the network node 1104, without explicit reference to any intermediary devices and the precise routing of messages via these devices. As an example of transmitting data via the OTT connection 1150, in step 1108, the host 1102 provides user data, which may be performed by executing a host application. In some embodiments, the user data is associated with a particular human user interacting with the UE 1106. In other embodiments, the user data is associated with a UE 1106 that shares data with the host 1102 without explicit human interaction. In step 1110, the host 1102 initiates a transmission carrying the user data towards the UE 1106. The host 1102 may initiate the transmission responsive to a request transmitted by the UE 1106. The request may be caused by human interaction with the UE 1106 or by operation of the client application executing on the UE 1106. The transmission may pass via the network node 1104 in accordance with the teachings of the embodiments described throughout this disclosure. Accordingly, in step 1112, the network node 1104 transmits to the UE 1106 the user data that was carried in the transmission that the host 1102 initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In step 1114, the UE 1106 receives the user data carried in the transmission, which may be performed by a client application executed on the UE 1106 associated with the host application executed by the host 1102. In some examples, the UE 1106 executes a client application which provides user data to the host 1102. The user data may be provided in reaction or response to the data received from the host 1102. Accordingly, in step 1116, the UE 1106 may provide user data, which may be performed by executing the client application. In providing the user data, the client application may further consider user input received from the user via an input / output interface of the UE 1106. Regardless of the specific manner in which the user data was provided, the UE 1106 initiates, in step 1118, transmission of the user data towards the host 1102 via the network node 1104. In step 1120, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 1104 receives user data from the UE 1106 and initiates transmission of the received user data towards the host 1102. In step 1122, the host 1102 receives the user data carried in the transmission initiated by the UE 1106. One or more of the various embodiments improve the performance of OTT services provided to the UE 1106 using the OTT connection 1150, in which the wireless connection 1170 forms the last segment. In an example scenario, factory status information may be collected and analyzed by the host 1102. As another example, the host 1102 may process audio and video data which may have been retrieved from a UE for use in creating maps. As another example, the host 1102 may collect and analyze real-time data to assist in controlling vehicle congestion (e.g., controlling traffic lights). As another example, the host 1102 may store surveillance video uploaded by a UE. As another example, the host 1102 may store or control access to media content such as video, audio, VR, or AR which it can broadcast, multicast, or unicast to UEs. As other examples, the host 1102 may be used for energy pricing, remote control of non-time critical electrical load to balance power generation needs, location services, presentation services (such as compiling diagrams etc. from data collected from remote devices), or any other function of collecting, retrieving, storing, analyzing, and / or transmitting data. In some examples, a measurement procedure may be provided for the purpose of monitoring data rate, latency, and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 1150 between the host 1102 and the UE 1106 in response to variations in the measurement results. The measurement procedure and / or the network functionality for reconfiguring the OTT connection 1150 may be implemented in software and hardware of the host 1102 and / or the UE 1106. In some embodiments, sensors (not shown) may be deployed in or in association with other devices through which the OTT connection 1150 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or by supplying values of other physical quantities from which software may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 1150 may include message format, retransmission settings, preferred routing, etc.; the reconfiguring need not directly alter the operation of the network node 1104. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signaling that facilitates measurements of throughput, propagation times, latency, and the like by the host 1102. The measurements may be implemented in that software causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 1150 while monitoring propagation times, errors, etc. Although the computing devices described herein (e.g., UEs, network nodes, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions, and methods disclosed herein. Determining, calculating, obtaining, or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box or nested within multiple boxes, in practice computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware. In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored 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 hardwired 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. Those skilled in the art will recognize improvements and modifications to the embodiments of the present disclosure. All such improvements and modifications are considered within the scope of the concepts disclosed herein. Some example embodiments of the present disclosure are as follows: Group A Embodiments Embodiment 1: A method performed by a User Equipment, UE, the method comprising:logging (e.g., storing) (108; 208; 308; 408; 508) one or more predicted measurements and / orpredicted information upon detecting a mobility-related event (e.g., radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation);and reporting (110; 210; 310; 410; 510) information in a Self-Optimizing Network, SON, report(e.g., a Radio Link Failure, RLF, report or a Successful Hanover Report, SHR), the information comprising the one or more predicted measurements and / or the predicted information to a network node. Embodiment 2: The method of embodiment 1, wherein the one or more predictedmeasurements and / or predicted information comprise information that indicates one or morepredicted values of one or more cell-level (e.g., layer-3) filtered radio measurements (e.g., one ormore predicted RSRP values, one or more predicted RSRQ values, and / or one or more predictedSINR values) associated with a cell identity (e.g., CGI or PCI and ARFCN) of a respective cell.Embodiment 3: The method of embodiment 1 or 2, wherein the one or more predictedmeasurements and / or predicted information comprise information that indicates one or morepredicted values of one or more cell-level layer-1 radio measurements (so called CSI-report)(e.g., one or more predicted RSRP values, one or more RSRQ values, and / or one or more SINRvalues) associated with a cell identity (e.g., CGI or PCI and ARFCN) and / or associated with aCSI-RS resource ID. Embodiment 4: The method of any of embodiments 1 to 3, wherein the one or more predicted measurements and / or predicted information comprise information that indicates one or more predicted values of one or more beam-level radio measurements (e.g., one or more RSRPvalues, one or more RSRQ values, and / or one or more SINR values) associated with a specificbeam (e.g., associated with a specific SSB or CSI-RS beam identity) related to a cell (e.g., a cellidentified by a CGI or PCI and ARFCN). Embodiment 5: The method of any of embodiments 1 to 4, wherein the one or more predicted measurements and / or predicted information comprise information that indicates one ormore predicted target cells for the mobility procedure.Embodiment 6: The method of any of embodiments 1 to 5, wherein the one or more predicted measurements and / or predicted information comprise information that indicates a predicted UE location and / or a predicted UE trajectory.Embodiment 7: The method of any of embodiments 1 to 6, wherein the one or morepredicted measurements are associated with a confidence value (e.g., a confidence value that indicates a confidence (e.g., a confidence of a prediction mechanism or model (e.g., an AI / ML prediction mechanism or model) in the one or more predicted measurements). Embodiment 8: The method of any of embodiments 1 to 7, wherein the one or morepredicted measurements are associated with a validity time information indication, indicating a time interval in which the predicted value(s) of the measurements are valid. Embodiment 9: The method of any of embodiments 1 to 8, wherein the one or more predicted measurements and / or predicted information comprise information that indicates a predicted failure available at the moment the event is triggered, but predicted earlier than the moment the UE logs the report. Embodiment 10: The method of embodiment 9, wherein the report is an RLF report, and the UE indicates in the RLF report logged at time t0 that it had predicted an RLF in source in time instances t0-T e.g. with a certain likelihood. Embodiment 11: The method of embodiment 9, wherein the report is an HOF report logged at time t0, and the predicted information comprises information that indicates that the UE had predicted a HOF in time instances t0-T e.g. with a certain likelihood. Embodiment 12: The method of embodiment 9, wherein the report is an RLF report logged at time t0, the and predicted information comprises information that indicates that the UE had predicted a HOF in time instances t0-T e.g. with a certain likelihood. Embodiment 13: The method of any of embodiments 1 to 12, wherein the one or more predicted measurements and / or predicted information comprise information that indicates one or more spatial domain predictions of one or more measurements. Embodiment 14: The method of embodiment 13, wherein the UE logs availablemeasurement information of a cell and / or a beam without the UE having performed themeasurement of that cell. Embodiment 15: The method of embodiment 13, wherein the predicted measurements and / or predicted information predicted for a first set of cell(s) and / or beam(s) predicted based on a set of measurement information for a second set of cell(s) and / or beam(s). Embodiment 16: The method of any of embodiments 1 to 15, wherein the report is a radio link failure report triggered upon a failure of a mobility procedure. Embodiment 17: The method of any of embodiments 1 to 15, wherein the report is a radiolink failure report triggered upon a radio link failure after a successful mobility procedure. Embodiment 18: The method of any of embodiments 1 to 15, wherein the report is a radiolink failure report triggered upon a radio link failure in a source cell, e.g. before any mobilityprocedure while being configured to perform predictions on the radio measurements. Embodiment 19: The method of any of embodiments 1 to 15, wherein the report is a successful handover report, SHR, triggered upon a successful execution of mobility procedure. Embodiment 20: The method of any of embodiments 16-19, wherein the mobility procedure is a L3 (RRC) based reconfiguration with synch procedure such as normal handover (reconfigurationWithSynch) or a conditional handover (reconfigurationWithSynch) performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell). Embodiment 21: The method of any of embodiments 16-19, wherein the mobility procedure is a Layer 1 or Layer 2 based mobility procedure so called LTM cell switch procedure performed between source and target primary cell (so called PCell) or between source and target primary secondary cell (PSCell). Embodiment 22: The method of any of embodiments 16-19, wherein the report is a new,AI / ML related report. Embodiment 23: The method of embodiment 22, wherein the report is triggered upon amobility event (e.g., a mobility procedure being successfully or non-successfully executed).Embodiment 24: The method of any of the previous embodiments, further comprising:providing user data; and forwarding the user data to a host via the transmission to the networknode. Group B Embodiments Embodiment 25: A method performed by a network node, the method comprising: receiving (110; 210; 310; 410; 510) a Self-Optimizing Network, SON, report from a UE, the report comprising one or more predicted measurements and / or predicted information in a Self- Optimizing Network, SON, report (e.g., a Radio Link Failure, RLF, report or a SuccessfulHanover Report, SHR), the SON report related being related to a mobility-related event (e.g.,radio link failure or a mobility procedure failure or a successful execution and / or completion of a mobility operation). Embodiment 26: The method embodiment 25, further comprising performing (112; 212; 312; 412; 512) one or more actions based on the SON report. Embodiment 27: The method of embodiment 25, further comprising sending (112; 212; 312; 412; 512) the SON report to another network node (e.g., a serving network node of the UE). e Embodiment 29: The method of any of embodiments 25 to 27, wherein the SON report is as described in any one of embodiments 2 to 23. Embodiment 30: The method of any of the previous embodiments, further comprising:obtaining user data; and forwarding the user data to a host or a user equipment.Group C Embodiments Embodiment 31: A user equipment comprising: processing circuitry configured to performany of the steps of any of the Group A embodiments; and power supply circuitry configured tosupply power to the processing circuitry. Embodiment 32: A network node comprising: processing circuitry configured to performany of the steps of any of the Group B embodiments; and power supply circuitry configured tosupply power to the processing circuitry. Embodiment 33: A user equipment (UE) comprising: an antenna configured to send andreceive wireless signals; radio front-end circuitry connected to the antenna and to processingcircuitry, and configured to condition signals communicated between the antenna and theprocessing circuitry; the processing circuitry being configured to perform any of the steps of anyof the Group A embodiments; an input interface connected to the processing circuitry andconfigured to allow input of information into the UE to be processed by the processing circuitry; an output interface connected to the processing circuitry and configured to output informationfrom the UE that has been processed by the processing circuitry; and a battery connected to theprocessing circuitry and configured to supply power to the UE. Embodiment 34: A host configured to operate in a communication system to provide anover-the-top (OTT) service, the host comprising: processing circuitry configured to provide userdata; and a network interface configured to initiate transmission of the user data to a networknode in a cellular network for transmission to a user equipment (UE), the network node having a communication interface and processing circuitry, the processing circuitry of the network nodeconfigured to perform any of the operations of any of the Group B embodiments to transmit theuser data from the host to the UE. Embodiment 35: The host of the previous embodiment, wherein: the processing circuitryof the host is configured to execute a host application that provides the user data; and the UEcomprises processing circuitry configured to execute a client application associated with the host application to receive the transmission of user data from the host. Embodiment 36: A method implemented in a host configured to operate in a communication system that further includes a network node and a user equipment (UE), themethod comprising: providing user data for the UE; and initiating a transmission carrying theuser data to the UE via a cellular network comprising the network node, wherein the network node performs any of the operations of any of the Group B embodiments to transmit the user data from the host to the UE. Embodiment 37: The method of the previous embodiment, further comprising, at the network node, transmitting the user data provided by the host for the UE. Embodiment 38: The method of any of the previous 2 embodiments, wherein the user data is provided at the host by executing a host application that interacts with a client application executing on the UE, the client application being associated with the host application. Embodiment 39: A communication system configured to provide an over-the-top (OTT)service, the communication system comprising a host comprising: processing circuitryconfigured to provide user data for a user equipment (UE), the user data being associated withthe over-the-top service; and a network interface configured to initiate transmission of the userdata toward a cellular network node for transmission to the UE, the network node having a communication interface and processing circuitry, the processing circuitry of the network node configured to perform any of the operations of any of the Group B embodiments to transmit the user data from the host to the UE. Embodiment 40: The communication system of the previous embodiment, furthercomprising: the network node; and / or the UE.Embodiment 41: A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to initiatereceipt of user data; and a network interface configured to receive the user data from a networknode in a cellular network, the network node having a communication interface and processing circuitry, the processing circuitry of the network node configured to perform any of the operations of any of the Group B embodiments to receive the user data from a user equipment (UE) for the host. Embodiment 42: The host of the previous 2 embodiments, wherein: the processingcircuitry of the host is configured to execute a host application that receives the user data; and the host application is configured to interact with a client application executing on the UE, the client application being associated with the host application. Embodiment 43: The host of the any of the previous 2 embodiments, wherein the initiating receipt of the user data comprises requesting the user data. Embodiment 44: A method implemented by a host configured to operate in a communication system that further includes a network node and a user equipment (UE), themethod comprising: at the host, initiating receipt of user data from the UE, the user dataoriginating from a transmission which the network node has received from the UE, wherein the network node performs any of the steps of any of the Group B embodiments to receive the user data from the UE for the host. Embodiment 45: The method of the previous embodiment, further comprising at the network node, transmitting the received user data to the host. Embodiment 46: A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to provide userdata; and a network interface configured to initiate transmission of the user data to a cellularnetwork for transmission to a user equipment (UE), wherein the UE comprises a communication interface and processing circuitry, the communication interface and processing circuitry of the UE being configured to perform any of the operations of any of the Group A embodiments to receive the user data from the host. Embodiment 47: The host of the previous embodiment, wherein the cellular network further includes a network node configured to communicate with the UE to transmit the user data to the UE from the host. Embodiment 48: The host of the previous 2 embodiments, wherein: the processingcircuitry of the host is configured to execute a host application, thereby providing the user data;and the host application is configured to interact with a client application executing on the UE,the client application being associated with the host application. Embodiment 49: A method implemented by a host operating in a communication system that further includes a network node and a user equipment (UE), the method comprising:providing user data for the UE; and initiating a transmission carrying the user data to the UE viaa cellular network comprising the network node, wherein the UE performs any of the operations of any of the Group A embodiments to receive the user data from the host. Embodiment 50: The method of the previous embodiment, further comprising: at the host,executing a host application associated with a client application executing on the UE to receive the user data from the host application. Embodiment 51: The method of the previous embodiment, further comprising: at the host,transmitting input data to the client application executing on the UE, the input data beingprovided by executing the host application, wherein the user data is provided by the clientapplication in response to the input data from the host application. Embodiment 52: A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to provide userdata; and a network interface configured to initiate transmission of the user data to a cellularnetwork for transmission to a user equipment (UE), wherein the UE comprises a communication interface and processing circuitry, the communication interface and processing circuitry of the UE being configured to perform any of the steps of any of the Group A embodiments to transmit the user data to the host. Embodiment 53: The host of the previous embodiment, wherein the cellular network further includes a network node configured to communicate with the UE to transmit the user data from the UE to the host. Embodiment 54: The host of the previous 2 embodiments, wherein: the processingcircuitry of the host is configured to execute a host application, thereby providing the user data;and the host application is configured to interact with a client application executing on the UE,the client application being associated with the host application. Embodiment 55: A method implemented by a host configured to operate in a communication system that further includes a network node and a user equipment (UE), themethod comprising: at the host, receiving user data transmitted to the host via the network nodeby the UE, wherein the UE performs any of the steps of any of the Group A embodiments to transmit the user data to the host. Embodiment 56: The method of the previous embodiment, further comprising: at the host,executing a host application associated with a client application executing on the UE to receive the user data from the UE. Embodiment 57: The method of the previous 2 embodiments, further comprising: at thehost, transmitting input data to the client application executing on the UE, the input data beingprovided by executing the host application, wherein the user data is provided by the clientapplication in response to the input data from the host application.

Claims

CLAIMS1. A method performed by a User Equipment, UE, the method comprising:storing (108; 208; 308; 408; 508) one or more predicted measurements and / or predicted information upon detecting a mobility-related event; and reporting (110; 210; 310; 410; 510) information in a Self-Optimizing Network, SON, report to a network node, the information comprising the one or more predicted measurements and / or the predicted information.

2. The method of claim 1, wherein the one or more predicted measurements and / orpredicted information comprise information that indicates one or more predicted time-domain radio measurements, one or more predicted spatial-domain radio measurements, or both one or more predicted time-domain radio measurements and one or more predicted spatial-domain radio measurements.

3. The method of claim 1 or 2, wherein the one or more predicted measurements and / orpredicted information comprise information that indicates one or more predicted values of one or more cell-level filtered radio measurements associated with a cell identity of a respective cell.

4. The method of claim 3, wherein the one or more predicted values of the one or more cell-level filtered radio measurements comprise one or more predicted Reference Signal Received Power, RSRP, values, one or more predicted Reference Signal Received Quality, RSRQ, values, and / or one or more predicted Signal to Interference plus Noise Ratio, SINR, values.

5. The method of any of claims 1 to 4, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates one or more predicted values of one or more cell-level layer-1 radio measurements associated with a cell identity and / or associated with a Channel State Information, CSI, Reference Signal, RS, resource identifier.

6. The method of any of claims 1 to 5, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates one or more predicted values of one or more beam-level radio measurements associated with a specific beam related to a cell.

7. The method of any of claims 1 to 6, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates one or more predicted targetcells for a mobility procedure.

8. The method of any of claims 1 to 7, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates a predicted location of the UEand / or a predicted trajectory of the UE.

9. The method of any of claims 1 to 8, wherein the one or more predicted measurements areassociated with a confidence value for the one or more predicted measurements.

10. The method of any of claims 1 to 9, wherein the one or more predicted measurements areassociated with a validity time information indication that indicates a time interval in which thepredicted measurements are valid.

11. The method of any of claims 1 to 10, wherein the SON report is either a Radio LinkFailure, RLF, report or a Successful Handover Report, SHR.

12. The method of any of claims 1 to 10, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates a predicted failure available at a moment the mobility-related event is triggered, but predicted earlier than a moment the UE stores the one or more predicted measurements and / or predicted information for the SON report.

13. The method of claim 12, wherein the SON report is a Radio Link Failure, RLF report,and the UE indicates in the RLF report logged at a first time that the UE had, at a second timethat is prior to the first time, predicted an RLF in a source cell of the UE .

14. The method of claim 12, wherein the SON report is an Handover Failure, HOF, reportlogged at a first time, and the predicted information comprises information that indicates that theUE had, at a second time that is prior to the first time, predicted a HOF.

15. The method of claim 12, wherein the SON report is an Radio Link Failure, RLF, reportlogged at a first time, and the predicted information comprises information that indicates that theUE had, at a second time that is prior to the first time, predicted a Handover Failure, HOF.

16. The method of any of claims 1 to 15, wherein the one or more predicted measurementsand / or predicted information comprise information that indicates one or more spatial domain predictions of one or more radio measurements.

17. The method of claims 1 to 16, wherein the UE uses a set of measurement information ofa first set of cells and / or beams to provide the one or more predicted measurements for a secondset of cells and / or beams without the UE having performed measurements on the second set ofcells and / or beams.

18. The method of any of claims 1 to 17, wherein the detected mobility-related event is afailure of a mobility procedure, and the report is a radio link failure report triggered upondetecting the failure of the mobility procedure.

19. The method of any of claims 1 to 17, wherein the detected mobility-related event is aradio link failure after a successful mobility procedure, and the report is a radio link failurereport triggered upon detecting the radio link failure after the successful mobility procedure.

20. The method of any of claims 1 to 17, wherein the detected mobility-related event is aradio link failure in a source cell of the UE, and the report is a radio link failure report triggeredupon detecting the radio link failure in the source cell of the UE.

21. The method of any of claims 1 to 17, wherein the detected mobility-related event is aradio link failure in a source cell of the UE before any mobility procedure while beingconfigured to perform predictions on radio measurements, and the report is a radio link failurereport triggered upon detecting the radio link failure in the source cell of the UE.

22. The method of any of claims 1 to 17, wherein the detected mobility-related event is asuccessful execution of a mobility procedure, and the report is a successful handover report,SHR, triggered upon detecting the successful execution of the mobility procedure.

23. The method of any of claims 18 to 22, wherein the mobility procedure is a Layer 3 (L3),or Radio Resource Control (RRC), based reconfiguration with synch procedure such as normalhandover (reconfigurationWithSynch) or a conditional handover (reconfigurationWithSynch)performed between source and target primary cells or between source and target primarysecondary cells.

24. The method of any of claims 18 to 22, wherein the mobility procedure is a Layer 1 orLayer 2 based mobility procedure performed between source and target primary cells or betweensource and target primary secondary cells.

25. The method of any of claims 18 to 22, wherein the report is an Artificial Intelligence, AI, / Machine Learning, ML, related report.

26. The method of claim 25, wherein the reporting is triggered upon a mobility event.

27. A User Equipment, UE, adapted to:store (108; 208; 308; 408; 508) one or more predicted measurements and / or predicted information upon detecting a mobility-related event; and report (110; 210; 310; 410; 510) information in a Self-Optimizing Network, SON, report to a network node, the information comprising the one or more predicted measurements and / or the predicted information.

28. The UE of claim 27, further adapted to perform the method of any of claims 2 to 26.

29. A User Equipment, UE, (700) comprising:a communication interface (712) comprising a transmitter (718) and a receiver (720); and processing circuitry (702) associated with the communication interface (712), the processing circuitry (702) configured to cause the UE (700) to: store (108; 208; 308; 408; 508) one or more predicted measurements and / or predicted information upon detecting a mobility-related event; and report (110; 210; 310; 410; 510) information in a Self-Optimizing Network, SON, report to a network node, the information comprising the one or more predicted measurements and / or the predicted information.

30. The UE (700) of claim 29, wherein the processing circuitry (702) is further configured tocause the UE (700) to operate in accordance with any of claims 2 to 26.

31. A method performed by a network node, the method comprising:receiving (110; 210; 310; 410; 510) a Self-Optimizing Network, SON, report from a UserEquipment, UE, wherein the SON report comprises one or more predicted measurements and / orpredicted information, and the SON report is related to a mobility-related event.

32. The method claim 31, further comprising performing (112; 212; 312; 412; 512) one ormore actions based on the SON report.

33. The method of claim 31, further comprising sending (112; 212; 312; 412; 512) the SONreport to another network node.

34. A network node adapted to:receive (110; 210; 310; 410; 510) a Self-Optimizing Network, SON, report from a UserEquipment, UE, wherein the SON report comprises one or more predicted measurements and / orpredicted information, and the SON report is related to a mobility-related event.

35. The network node of claim 34, further adapted to perform the method of any of claims 32to 33.

36. A network node (800) comprising processing circuitry (802) configured to cause thenetwork node (800) to: receive (110; 210; 310; 410; 510) a Self-Optimizing Network, SON, report from a UserEquipment, UE, wherein the SON report comprises one or more predicted measurements and / orpredicted information, and the SON report is related to a mobility-related event.

37. The network node (800) of claim 36, wherein the processing circuitry (802) is furtherconfigured to cause the network node (800) to perform the method of any of claims 32 to 33.

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