Activating or releasing an inference configuration

Abstract

According to an example, a method performed by a wireless communication device for activating or releasing an inference configuration is provided The method comprises obtaining an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node, and determining applicability of the inference configuration at the wireless communication device. The method also comprises, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration, and / or if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration.

Description

[0001] ACTIVATING OR RELEASING AN INFERENCE CONFIGURATION

[0002] Background

[0003] Beam prediction: Beam management use case for AI / ML for PHY

[0004] The use case of beam prediction which is being standardized as in 3GPP Release 19 (Rel-19) work item consists of spatial beam prediction, and temporal beam prediction. 3GPP aims for specify predictions of the “best” beam (or beams) from a Set A of beams using measurement results from another Set B of beams.

[0005] According to 3GPP Technical Report (TR) 38.843, the spatial-domain beam prediction for Set A of beams is based on measurement results of Set B of beams, whereas the temporal beam prediction for Set A of beams is based on the historic measurement results of Set B of beams.

[0006] Set A and Set B of beams have not been specified yet, however, the following two scenarios may be considered as examples:

[0007] • Set B is a subset of a Set A. For example, Figure 1 illustrates an example of Synchronization Signal Block (SSB)ZChannel State Information Reference Signal (CSI-RS) beams where Set B is a subset of Set A. Set A is a set of 8 SSB / CSI-RS beams (both light and dark circles). The User Equipment (UE) measures Set B (the 4 beams indicated by dark circles). Artificial Intelligence / Machine Learning (The AI / ML) model should predict the best beam (or beams) in Set A using only measurements from Set B. Figure 1 illustrates a grid-of-beam type radiation pattern: each row (resp. column) depicts a certain zenith (resp. azimuth) angle from the antenna array. Set A has 8 beams and Set B has 4 beams (indicated by dark circles).

[0008] • Set A and Set B correspond to two different sets of beams. For example, Figure 2 illustrates an example where Set A is a set of narrow beams and Set B is a set of wide beams. Set A is a set of 30 narrow CSI-RS beams, and Set B is a set of 8 wide SSB beams. The UE measures beams in Set B and the AI / ML model should predict the best beam(s) from Set A.

[0009] The beam prediction can be performed (e.g. by an AI / ML model) in the gNodeB (gNB) and / or in the UE, and the gain is twofold. From the UE point of view, the UE would be able to generate good radio measurement estimations without really measuring certain resources (e.g. actual SSBs, CSI-RS or other RS(s)), thereby saving energy, whereasfrom the gNB point of view, the gNB can get good radio measurements estimation from the UE without providing the measuring resources, thereby limiting the overhead over the airinterface.

[0010] Whether the UE can perform the beam prediction on a certain set of resources with a certain accuracy, depends on so called applicability conditions of an AI / ML model / function. In particular, an AI / ML model / function may be trained to perform the beam prediction under certain applicability conditions e.g. speed, location, beam configuration(s), deployment, etc. Such applicability conditions need to be fulfilled in order for the AI / ML model / function to generate the expected output, i.e. beam prediction for this use case, with enough accuracy. The applicability conditions may include a set of parameters / variables under which the AI / ML model / function was trained e.g. a given Set B for the inference of a Set A. Such set may include for example UE-specific conditions under which the model was trained, as the UE speed, the UE antenna shape, UE sensors information such as UE orientation, motion sensors etc; whereas some other parameters / variables may depend on the specific network configuration under which the model was trained, e.g. the deployment scenario (e.g. indoor / outdoor), the carrier frequency, the gNB transmit (TX) port number, the gNB TX power, etc.

[0011] In order to determine whether an AI / ML model / function is applicable or not, the UE needs to assess the applicability conditions of such AI / ML model / function with respect to the output (beam prediction) that needs the generated and received input (e.g. radio measurement resources configured by the gNB).

[0012] Applicability reporting

[0013] Related to the discussion above, applicability reporting has been discussed during the Rel-18 study item. Applicability reporting allows the UE to inform the gNB about the applicability of an AI / ML functionality (or model) while the UE is connected to this gNB. An AI / ML functionality may be applicable or not depending on a number of factors, so called applicability conditions, that are only partly under the control of the gNB. For example, whether the UE has an AI / ML functionality (or model) that is applicable given the current location of the UE, or given the current speed of the UE, is not something that the network can control or it can know, because typically it is assumed that the UE-side model is not trained and generated by the gNB (rather, it is typically assumed that the UE-side model is trained and generated by a node outside the Radio Access Network (RAN), such as an Over The Top (OTT) server or Core Network (CN) function controlled by the UE-vendor or by the Mobile Network Operator (MNO).Two types of applicability reporting were identified during the Rel-18 study item, i.e. proactive reporting and reactive reporting. The reactive reporting implies the gNB inquiring the UE about the applicability of AI / ML model / functionality, and the UE responding with the AI / ML models / functionalities that are applicable, whereas with the proactive reporting UE signals to the network autonomously, i.e. without any inquiry, about the AI / ML model / functionalities that are applicable. ”

[0014] The former, i.e. reactive reporting can be used for example in response to a network configuration e.g. inference related configuration, including for example beam resource configuration of Set A and / or Set B. The UE will then respond indicating if the AI / ML model / functionality is applicable based on this inference configuration. The latter, i.e. the proactive reporting can be configured to the UE to allow the UE to report at any point in time a change in the applicability of an AI / ML model / functionality, i.e. an AI / ML model / functionality that was not applicable becomes applicable or vice versa.

[0015] More details of the reactive and proactive reporting are currently discussed in Intel Corporation, “Report of [POST126]

[0032] [AI / ML PHY] LCM (lntel / Samsung)_Phase 2,” 3GPP TSG RAN WG2 Meeting #126, Fukuoka, Japan, May 20th-24th, 2024.

[0016] Figure 3 is a signaling diagram of signaling in an applicability report procedure. The procedure includes the following steps:

[0017] • Step 1 : Network sends UECapabilityEnquiry message to initiate the procedure to a UE reporting its AI / ML supported functionalities.

[0018] • Step 2: UE sends UECapablitylnformation message to network, containing supported functionalities at the UE side.

[0019] • Step 3: Network provides network configurations and initiates UE to report its applicable functionalities.

[0020] • Step 4: UE sends applicable functionalities to network.

[0021] • Step 5: Network sends updated inference configuration for applicable functionalities reported in Step 4 to the UE. (see Q2-6)

[0022] • Step 6: Start inference / monitoring based on network / UE activation / deactivation.

[0023] As shown in step 6, a “supported functionality” (e.g. beam management, or reporting of spatial domain and / or time domain prediction(s) or inference(s)) is activated, to refer to functionalities which are activated and for which a UE is performing inference, in response to a network configuration in Step 3.Figure 4 is a signaling diagram of signaling in an example of a proactive reporting procedure. The procedure includes the following steps:

[0024] • Step 1 : Network sends UECapabilityEnqiry message to initiate the procedure to a UE reporting its AI / ML supported functionalities

[0025] • Step 2: UE sends UECapablitylnformation message to network, containing supported functionalities at the UE side

[0026] • Step 3: Network configures UE that it is allowed to provide its applicable functionalities

[0027] • Step 4: UE sends applicable functionalities to network upon change of applicable functionality / condition

[0028] • Step 5: Network sends inference configuration for the applicable functionalities to the UE

[0029] • Step 6: Start inference / monitoring based on network / UE activation / deactivation

[0030] Periodic inference reporting

[0031] The UE can be configured to periodically report beam prediction(s), also called inference(s) or prediction(s), e.g., L1-RSRP prediction(s), according to an inference configuration (which may also be called a prediction configuration). These may be time-domain prediction(s), and / or spatial domain prediction(s) / inferences.

[0032] 6G and AI / ML for PHY Life Cycle Management (LCM)

[0033] AI / ML for physical layer (PHY) use cases should also become part of 6G, possibly in the first release, in particular beam management. One reason is that 6G should continue to address the high bands as in New Radio (NR), including other bands which may also rely on beamforming and, require beam management procedures. In addition, AI / ML for PHY could be one of the new features or group of features in 6G.

[0034] Thus, even if some of the terminology proposed in this disclosure follows the 5G NR principles, examples of this disclosure are also applicable for 6G.

[0035] There currently exist certain challenge(s). For example, when the UE receives an inference configuration for periodic reporting, e.g. reporting of time-domain and / or spatial-domain prediction(s) of beam measurements (SSB or CSI measurements), in an RRC Reconfiguration (e.g. within an instance of the IE CSI-ReportConfig), the UE determines whether such inference configuration is applicable or not. And, in case such inference configuration is determined by the UE to be applicable, the UE considers the inferenceconfiguration up and running (i.e. activated) and as fast as the UE is able to perform the inferences the UE reports (according to the configured periodicity). In other words, according to the 3GPP agreements the periodic inference configuration does not need to be explicitly activated (if it is applicable).

[0036] This was captured in the following RAN1#119 agreements, in the text underlined:

[0037]

[0038] When the UE determines that the periodic inference configuration is non-applicable, the UE would not be able transmit these periodic inferences and the UE indicates to the network (in an applicability report) that the inference configuration is not applicable e.g. in RRC Reconfiguration Complete or in a UE Assistance information message. However, it is not clear what happens to such periodic inference configuration.

[0039] If later that periodic inference configuration becomes applicable, the UE indicates that change to the network, and it is once again not clear what happens to the periodic inference configuration.

[0040] Summary

[0041] Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, examples of this disclosure provide a method at a UE tohandle a periodic inference configuration the UE has received which is determined by the UE to be non-applicable, and / or is determined to change from applicable to non-applicable, and / or is determined to change from non-applicable to applicable.

[0042] An example aspect of this disclosure provides a method performed by a wireless communication device for activating or releasing an inference configuration. The method comprises obtaining an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node, and determining applicability of the inference configuration at the wireless communication device. The method alco comprises, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration, and / or if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration.

[0043] Another example aspect of this disclosure provides a method performed by a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information. The method comprises receiving, from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device, and releasing the inference configuration.

[0044] A further example aspect of this disclosure provides a tangible, non-transient computer-readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations in a wireless communication device for activating or releasing an inference configuration. The operations comprise obtaining an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node, and determining applicability of the inference configuration at the wireless communication device. The operations also comprise, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration, and / or if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration.

[0045] A still further example aspect of this disclosure provides a tangible, non-transient computer-readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations in a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inferenceconfiguration for periodically performing inference and / or periodically reporting inference information. The operations comprise receiving, from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device, and releasing the inference configuration.

[0046] An additional aspect of this disclosure provides apparatus in a wireless communication device for activating or releasing an inference configuration. The apparatus comprises processing circuitry and a memory. The apparatus is configured to obtain an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node, and determine applicability of the inference configuration at the wireless communication device. The apparatus is also configured to, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activate the inference configuration, and / or if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, release the inference configuration.

[0047] Another example aspect of this disclosure provides apparatus in a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information. The apparatus comprises processing circuitry and a memory. The apparatus is configured to receive, from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device, and release the inference configuration.

[0048] Brief Description of the Drawings

[0049] For a better understanding of the embodiments of the present disclosure, and to show how it may be put into effect, reference will now be made, by way of example only, to the accompanying drawings, in which:

[0050] Figure 1 illustrates an example of SSB / CSI-RS beams;

[0051] Figure 2 illustrates an example of SSB and CSI-RS beams;

[0052] Figure 3 is a signaling diagram of signaling in an example of an applicability report procedure;

[0053] Figure 4 is a signaling diagram of signaling in an example of a proactive reporting procedure;

[0054] Figure 5 is a flow chart illustrating a method in accordance with some embodiments; Figure 6 is a flow chart illustrating a method in accordance with some embodiments;Figure 7 illustrates a signaling diagram of an example of autonomous release of periodic inference configuration during initial inference configuration;

[0055] Figure 8 illustrates a signaling diagram of an example of autonomous release of periodic inference configuration when that is changed from applicable to non-applicable;

[0056] Figure 9 illustrates a signaling diagram of autonomous activation of a periodic inference configuration when that is changed from non-applicable to applicable;

[0057] Figure 10 illustrates a signaling diagram of an example of activation of a periodic inference configuration when that is changed from non-applicable to applicable, based on reception of a new MAC CE for periodic inference configuration;

[0058] Figure 11 illustrates a signaling diagram of an example of activation of a periodic inference configuration when that is changed from non-applicable to applicable, based on reception of a MAC CE for Semi-Persistent CSI reporting;

[0059] Figure 12 shows an example of a communication system in accordance with some embodiments;

[0060] Figure 13 shows an example of another communication system in accordance with some embodiments;

[0061] Figure 14 shows a wireless device in accordance with some embodiments;

[0062] Figure 15 shows a network node in accordance with some embodiments; and Figure 16 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized.

[0063] Detailed Description

[0064] Examples of this disclosure cover different solutions (for these different example scenarios):

[0065] - Autonomous release of an inference configuration (i.e. periodic inference configuration) which is determined to be non-applicable (either during initial configuration or when the applicability changes from applicable to non-applicable); this method also comprising the UE ignoring the fields / parameters included in the said inference configuration (which may also be called prediction configuration), and not taking any action on them

[0066] - Autonomous activation of a periodic inference configuration when the applicability is modified from non-applicable to applicable

[0067] Use of a new MAC Control Element (CE) for explicit activation of a periodic inference configuration reported to have its applicability modified from non-applicable to applicable.Use of a Semi-Persistent (SP) MAC CE for periodic inference configuration for explicit activation of a periodic inference configuration reported to have its applicability modified from non-applicable to applicable.

[0068] Examples of this disclosure also provide methods for the gNB to handle the configuration of periodic inferences, the methods comprising the gNB releasing the one or more periodic inference configurations that the UE indicates as non-applicable in the applicability report.

[0069] Since these are applied for different scenarios, the example solutions are not necessarily mutually exclusive.

[0070] Certain embodiments may provide one or more of the following technical advantage(s). For example, the various examples of this disclosure may have different benefits.

[0071] Examples relying on the UE autonomous release may have the benefit that the UE does not have to store a non-applicable inference configuration, which would just occupy memory unnecessarily. Another benefit is reduced signaling and lower energy consumption since the UE is configured because network intended to receive periodic inferences (for a given AI / ML functionality) in case such inference configuration would have been applicable; but, once that stops to be received, since that inference configuration becomes not applicable, the UE autonomously releasing the non-applicable inference configuration prevents the need for an additional RRC Reconfiguration loop, for releasing that non-applicable periodic inference configuration.

[0072] Examples relying on autonomous activation of a periodic inference configuration when the applicability is modified from non-applicable to applicable, may have the benefit of reducing the signaling and UE energy consumption, since the UE would not need any additional network signaling when a stored inference configuration changes from non-applicable to applicable.

[0073] Examples relying on a MAC CE to activate the periodic inference configuration may have the benefit that the network is under control of activating or not a periodic inference configuration which became applicable, either with a new MAC CE or repurposing an existing MAC CE to be used for the new functionality.

[0074] 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.Figure 5 depicts a method 500 in accordance with particular embodiments, for example a method performed by a wireless communication device for activating or releasing an inference configuration. The method 500 may be performed by a wireless device (e.g. UE QQ112, station QQ212 or wireless device QQ300 as described later with reference to Figures 12, 13 and 14 respectively). The term User Equipment (UE) is used interchangeably with the term wireless communication device in examples of this disclosure.

[0075] The method 500 begins at step 502, comprising obtaining an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node. Step 504 comprises determining applicability of the inference configuration at the wireless communication device. Step 506 comprises, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration. Step 508 comprises, if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration.

[0076] Figure 6 depicts a method 600 in accordance with particular embodiments, for example method performed by a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information. The method 600 may be performed by a network node (e.g. network node QQ110, access point QQ210 or network node QQ400 as described later with reference to Figures 12, 13 and 15 respectively).

[0077] The method 600 begins at step 602, comprising receiving, from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device. Step 604 comprises releasing the inference configuration.

[0078] The following describes illustrative example embodiments.

[0079] The following provides example methods in which a UE receives a message (e.g. Radio Resource Control, RRC, Reconfiguration, RRC Resume) including at least one periodic inference configuration (which may be called a periodic prediction configuration, or an AI / ML functionality configuration, including an inference configuration and / or an applicability reporting configuration for a periodic inference reporting), which may be simply called inference configuration (even if that is referring specifically to a periodic inference configuration), received by the UE per cell group and / or per serving cell within the cell group.An inference configuration may also be called a prediction configuration, so that a periodic inference configuration may be called a periodic prediction configuration.

[0080] The periodic inference (prediction) configuration can in some examples be represented by a Channel State Information (CSI) reporting configuration (CSI-ReportConfig) for which the report configuration type (reportConfigType is set to periodic), which points to a set of resources to be predicted (set A of beams / reference signals) and point to a set of resources assumed to be transmitted by the network (set B of of beams / reference signals), e.g., to be measured and possibly used by the UE as input to an inference configuration.

[0081] Furthermore, an inference (prediction) configuration may in some examples be one inference configuration or may be one inference related parameter set which is configured for applicability report only. For example, for Al-based beam management, one inference configuration may include associated ID, Channel State Information-Reference Signal (CSI-RS) resource information of Set B for measurement, CSI-RS resource related information of Set A for prediction, report content related information; while one inference related parameter set may include associated ID, Set A related information, Set B related information, report content related information, time instances related information for measurements, time instances related information for prediction and so on.

[0082] In examples of this disclosure, the term “AI / ML functionality” may be called a “supported functionality” the UE can indicate by using UE capability signaling, which is configured at the UE by the UE receiving an inference configuration i.e. the UE is configured with an AI / ML functionality when it receives an inference configuration. And in examples of this disclosure, the periodic inference configuration, for an AI / ML functionality, leads the UE to report inference(s) periodically. A supported functionality is one or more functionalities for and / or associated to beam management and / or CSI reporting, or mobility operations, such as the reporting of time domain and / or spatial domain or frequency domain predictions (inference), configured by the reception of an inference configuration. It could be said as the ability the UE has to produce an output of an inference function, when the UE is configured with an inference configuration. For example, reporting of time-domain prediction(s) of SSB and / or CSI-RS measurement information (e.g. predicted RSRP) may be considered as an AI / ML functionality which is a “supported functionality” by the UE when the UE reports a capability associated to it (via RRC or LPP signaling) and receives in response an inference configuration.

[0083] For example, “spatial domain prediction for beam management or for a mobility procedure e.g., handover or reconfiguration with sync, or Primary cell (PCell) change,or Primary Secondary Cell Group cell (PSCell) change” or a related functionality (e.g. reporting and inference of spatial domain info) may be a supported functionality in which the UE may report that is capable of performing and reporting (e.g. periodically) inference / prediction of a set A of beams or cells (e.g. predicted Layer 1, L1, Reference Signal Received Power, RSRP, values of one or more beams or one or more Synchronization Signal Block, SSB, indexes of a cell or predicted L1 or Layer 3, L3, RSRP values of one or more cells) based on measurements performed on a set B of beams (e.g. measured L1 / L3 RSRP values of one or more beams or one or more SSB indexes of a cell), in the case of spatial domain predictions.

[0084] For example, “frequency domain prediction for beam management or mobility procedure e.g., handover” or a related functionality (e.g. periodically reporting and inference of frequency domain info) may be a supported functionality in which the UE may indicate that is capable of performing and reporting periodically inference (e.g., prediction of the radio link quality of a set A of beams or cells (e.g. predicted L1 RSRP values of one or more beams or one or more SSB indexes of a cell or predicted L1 or L3 RSRP values of one or more cells) based on measurements performed on a set B of beams (e.g. measured L1 / L3 RSRP values of one or more beams or one or more SSB indexes of a cell or one or more cells), in the case of frequency domain predictions.

[0085] For example, “time domain prediction for beam management or a mobility procedure e.g., handover or reconfiguration with sync, or Primary cell (PCell) change, or Primary Secondary Cell Group cell (PSCell) change” or a related functionality (e.g. reporting and inference of time domain info) may be a supported functionality in which the UE may report that is capable of performing and reporting inference of a set of A of beams (e.g. predicted L1 / L3 RSRP values of one or more beams or one or more SSB indexes of a cell in future time instances or the L1 / L3 RSRP value of one or more cells in the future time instances) based on measurements performed on a set B of beams or cells (e.g. measured L1 / L3 RSRP values of one or more beams or one or more SSB indexes of a cell and / or L1 / L3 RSRP value of one or more cells), in the case of time domain predictions.

[0086] For example, beam management - Downlink (DL) Transmit (Tx) beam prediction for both UE-sided model and NW-sided model, including:

[0087] o Spatial-domain DL Transmitted (Tx) beam prediction for Set A of beams based on measurement results of Set B of beams (“BM-Case1”)

[0088] o Temporal DL Tx beam prediction for Set A of beams based on the historic measurement results of Set B of beams (“BM-Case2”)

[0089] For example, positioning accuracy enhancements, including:o Direct AI / ML positioning, such as:

[0090] ■ UE-based positioning with UE-side model, direct AI / ML positioning ■ UE-assisted / Location Management Function (LMF)-based positioning with LMF-side model, direct AI / ML positioning

[0091] ■ NG-RAN node assisted positioning with LMF-side model, direct AI / ML positioning

[0092] o AI / ML assisted positioning, such as:

[0093] UE-assisted / LMF-based positioning with UE-side model, AI / ML assisted positioning

[0094] NG-RAN node assisted positioning with gNodeB (gNB)-side model, AI / ML assisted positioning

[0095] For example, CSI compression e.g., considering extending the spatial / frequency compression to spatial / temporal / frequency compression, cell / site specific models, CSI compression plus prediction (compared to Rel-18 non-AI / ML based approach).

[0096] An inference configuration may also in some examples be represented by a CSI-ReportConfig instance which includes a pointer or indication to a configuration of a set B of resources that are assumed by the UE to be transmitted by the network, so the UE is able to perform measurements which may be used as input to an AI / ML model to produce one or more inferences / predictions of a set A of resources. The point or indication to set B is shown in an example below as the field ‘resourcesForChannelPrediction-r19’ of IE ‘CSI-ResourceConfigld’ and its presence indicates that the CSI reporting configuration is an inference configuration.

[0097] CSI-ReportConfig : : = SEQUENCE {

[0098]

[0099] }

[0100] ]]

[0101] According to examples of this disclosure, the UE receives from the network (NW) a message (e.g. RRC Reconfiguration, RRC Resume), including at least one periodic inference configuration (which may be called a AI / ML functionality configuration, e.g. including aninference configuration in a CSI reporting configuration) based on which the UE is configured to report to the network applicability information (e.g. including an applicability indication for an AI / ML functionality) for the periodic inference configuration. And, in addition, the UE may be configured to report updates to the applicability information for the periodic inference configuration e.g. when the periodic inference configuration changes from applicable to non-applicable, or when the periodic inference configuration changes from non-applicable to applicable.

[0102] Prior to reporting the applicability information, either the first time or when there is an update, the UE in some examples determines whether the periodic inference configuration (i.e. an AI / ML functionality) is applicable or not applicable. An inference configuration (for an AI / ML functionality) determined to be applicable is an “applicable AI / ML functionality” i.e. is a functionality the UE is ready to apply for model inference, or, in other words, the UE is able to perform the inference and / or report the inference and / or perform further actions based on the inference configuration. So, when the UE is provided with a periodic inference configuration for performing inference(s) using an AI / ML model (e.g. perform predicted L1 RSRP for beams and / or SSB indexes and / o CSI-RS resource indicator(s) and / or L1 RSRP measurements for beams and / or SSB indexes and / o CSI-RS resource indicator(s) to be used as input to an AI / ML model) and report periodically inference information derived from the inference(s)), whether the UE can perform inference(s) using an AI / ML model and report inference information derived from the inference(s)) according to the at least one periodic inference related configuration. In this context, periodic inference configuration may include one or more parameters for CSI resources (e.g. a CSI resource configuration) to be measured and / or predicted and / or one or more parameters for reporting (e.g. in a CSI reporting configuration); thus, it may be said that an inference related configuration includes a measurement configuration.

[0103] According to examples of this disclosure, the UE may use one or more “applicability condition(s)” which represent a set of conditions for determining whether an AI / ML model / functionality (also denoted a “supported functionality”) is applicable or not. An AI / ML functionality (and / or AI / ML model) is applicable when there is at least an inference related configuration (or simply inference configuration, in the case of examples of this disclosure, a periodic inference configuration) received by the UE (provided by the gNodeB) out of multiple inference related configurations received (e.g. in a single RRC Reconfiguration message) for which the AI / ML model / functionality (the supported functionality) is applicable i.e. the UE is able to produce outputs of an AI / ML model, wherein the outputs are called inference(s).According to some examples, the UE determines whether a periodic inference configuration (and / or associated AI / ML functionality) is applicable or not possibly based on one or more UE-side additional condition(s), such as UE speed, scenario, location, cell the UE is connected to, hardware capabilities, etc.

[0104] According to some examples, the UE determines whether a periodic inference configuration (and / or AI / ML functionality) is applicable or not possibly based on one or more network (NW)-side additional conditions, such as one or more of the following examples:

[0105] Set A and / or Set B

[0106] Mapping relationship of Set A and Set B, including ordering to (a set of ID, or resource )

[0107] Consistency of downlink spatial domain transmission filters corresponding to the beams in Set A and Set B.

[0108] Quasi Co-Location (QCL) assumption

[0109] - The order of model input and model output between RS and Tx beams can be predefined.

[0110] - Transmission power

[0111] UE distribution

[0112] antenna height and / or other antenna properties

[0113] Deployment scenarios (e.g., ISD, Umi / Uma)

[0114] NW-side resource config uration(s) which may be considered as NW implementationbased configurations which may possibly impact the inference performance for a UE sided model. For instance, beam and Tx port mapping relationship in the gNodeB for a given cell, NW antenna shape, Antenna dip angle, height of the tower / gNB, etc.

[0115] The NW-side additional conditions, configured for the UE to determine the applicability of an inference configuration (and / or associated AI / ML functionality), may also in some examples be characterized as network implementation-based configurations (settings) which can impact the consistency between training and inference for UE side model. For example, if the UE has performed training for an AI / ML model and / or inference configuration and / or functionality in the first and / or the second cell for a given set of network configuration(s) (settings), the inference is expected to produce accurate outputs under similar conditions.

[0116] Each NW-side additional condition may be identified by an associated ID in some examples.

[0117] It may also be the case in some examples that for an inference configuration (or / and AI / ML-functionality, or AI / ML-enabled feature / FG), additional conditions refer to any aspects thatare assumed for the training of the model but are not a part of UE capability for the AI / ML-enabled feature / FG. It does not imply that additional conditions are necessarily specified. Additional conditions can be divided into two categories: NW-side additional conditions and UE-side additional conditions.

[0118] To determine whether an inference configuration (and / or AI / ML functionality) is applicable or not, in some examples, the UE may receive one or more AI / ML functionality configuration(s) (or one or more inference configuration(s)) which may include one or more NW-side additional conditions, such as the ones listed above and / or based on UE-side additional conditions, known at the UE e.g. the cell the UE is connected to, its current location, UE speed, etc.

[0119] AI / ML functionality configuration (e.g. inference configuration, prediction configuration)

[0120] In examples of this disclosure, an AI / ML functionality configuration (which may also be called a periodic inference configuration, when configuring the UE to report one or more inference(s) in a periodically manner i.e. with a periodicity) may in one option include one or more parameters, I E(s), fields and / or configuration(s) necessary and / or sufficient for the UE to operate the AI / ML functionality, such as an inference configuration (or an inference related configuration) which may also be considered a full and / or complete inference configuration, sufficient for the operation of the AI / ML functionality in the second cell. In examples of this disclosure, a periodic inference configuration configures the UE to report inference information with a certain periodicity.

[0121] In other words, in some examples, when the UE receives the periodic inference configuration, for an AI / ML functionality, for a given serving cell in a given cell group the UE can generate inference information (e.g. as output of an AI / ML model associated with the AI / ML functionality) and possibly report to the serving cell, in a periodic manner (when that inference configuration is applicable).

[0122] In examples of this disclosure, a periodic inference configuration may correspond to a Channel State information (CSI) measurement configuration (e.g. in an IE CSI-MeasConfig, CSI-ReportConfig, CSI-ResourceConfig) associated to a set A and or set B of beams for a beam management AI / ML functionality. The inference configuration may further include one or more of the following examples:

[0123] Synchronization Signal Block (SSB) identifiers associated to a serving cell and / or a neighbour cell;

[0124] CSI-RS resource identifiers associated to a serving cell and / or a neighbour cell;Beam identifiers associated to a serving cell and / or a neighbour cell;

[0125] Mobility Reference Signal(s) identifiers associated to a serving cell and / or a neighbour cell;

[0126] One or more timing related parameters, such as a reporting periodicity in which the UE needs to report the inference related information. That may be configured at the UE in terms of one or more time units such as number of time slots, sub-frames, radio frames, OFDM symbols, etc.

[0127] Candidate inference configuration(s) Set A and / or B (1); Set A and / or B (2); Set A and / or B (3), etc.

[0128] In examples of this disclosure, a periodic inference configuration may include and / or point to or indicate a first set (set A) of measurement resources (e.g. beams, SSB indexes and / or CSI-RS resource identifiers, Mobility Refence Signal identifiers) in which the UE performs radio measurement predictions (inferences, such as predicted RSRP values), and a second set (set B) of radio measurement resources (e.g. beams, SSB indexes and / or CSI-RS resource identifiers, Mobility Refence Signal identifiers) in which the UE can perform radio measurement in order to determine the radio measurement predictions on the first set, to be reported periodically. That may also include one or more configuration(s) associated to network side (NW-side) additional conditions reflecting the NW operational properties, such as:

[0129] • Mapping relationship of Set A and Set B, including ordering to (a set of IDs, or resources)

[0130] • Consistency of downlink spatial domain transmission filters corresponding to the beams in Set A and Set B.

[0131] • QCL assumption

[0132] • The order of model input and model output.

[0133] • between RS and Tx beams can be pre-defined.

[0134] • Transmission power

[0135] • UE distribution

[0136] • antenna height

[0137] • Deployment scenarios (e.g., ISD, Umi / Uma / rural / indoor / indoor office / indoor factory, specific area(s))

[0138] • UE speedThe periodic inference configuration may in some examples include a list of IDs referring to the set A and set B (or to the resources within the set A / B), and referring to one or more NW-side additional conditions.

[0139] In some examples, the periodic inference configuration is configured as an instance of the information element CSI-ReportConFigure

[0140] In examples of this disclosure, the AI / ML functionality configuration may include one or more of the following examples:

[0141] - A periodic inference configuration for a beam management functionality (e.g. timedomain prediction of beam information)

[0142] o In one example, the inference configuration includes the CSI reporting configuration including parameters indicating how the UE is to periodically report time-domain predictions of beam information (e.g. beam indexes and / or SSB indexes and / or time-domain prediction of beam measurements) and / or spatial-domain predictions of beam information.

[0143] o In one example, the inference configuration includes the CSI resource configuration for resources (e.g. SSB indexes and / or CSI-RS resources) which the UE measures and provides as input to an AI / ML model (or inference function) to produce inference outputs e.g. the actual time-domain predictions of beam information (e.g. beam indexes and / or SSB indexes and / or time-domain prediction of beam measurements) and / or spatial-domain predictions of beam information to be included in a report.

[0144] - A periodic inference configuration for positioning functionality

[0145] - A periodic inference configuration for CSI reporting functionality

[0146] - A configuration enabling the UE to determine whether the AI / ML functionality is applicable or not.

[0147] Network conditions such as Set A / set B configuration(s).

[0148] - A state indication for the AI / ML functionality, e.g., ‘activated’, ‘inactivated’, ‘deactivated’.

[0149] - An indication on whether the UE is allowed to consider the AI / ML functionality as ‘activated’ when the functionality is determined by the UE to be applicable.

[0150] The AI / ML functionality configuration may also in some examples include an identifier of the AI / ML functionality to which the configuration (e.g. inference configuration) is referred to, wherein the AI / ML functionality could be for example, beam management functionality, spatial beam management functionality, temporal beam management functionality, L3mobility functionality, positioning functionality, CSI compression functionality, CSI prediction functionality, etc.

[0151] According to examples of this disclosure, the AI / ML functionality configuration includes an identifier of that configuration, which is later to be reported by the UE to the network when the UE indicates whether that particular AI / ML functionality configuration is applicable or not. The main examples of identification of the configuration of the AI / ML functionality are: i) a CSI reporting configuration identifier in which the inference configuration is received by the UE, ii) an identification of the serving cell in which the UE is to report the inference, iii) a cell group identification for the cell group (e.g. MCG, SCG) of that serving cell. In other words, a periodic inference configuration may be associated to an inference configuration identifier (e.g. reporting configuration identity), a serving cell identifier, and / or cell group configuration.

[0152] In examples of this disclosure, an AI / ML functionality configuration may in another option include one or more parameters, I E(s), fields and / or configuration(s) necessary and / or sufficient for the UE to report the applicability of the AI / ML functionality in the second cell, such as an applicability reporting configuration. In other words, when the UE receives the applicability reporting configuration for an AI / ML functionality the UE can determine whether the AI / ML functionality, supported by the UE, and / or associated configuration(s) of that AI / ML functionality, is applicable or not applicable.

[0153] Examples of this disclosure may address different scenarios and different solutions to handle a periodic inference configuration the UE has received which is determined to be non-applicable, and / or is determined to change from applicable to non-applicable, and / or is determined to change from non-applicable to applicable.

[0154] Autonomous release of a non-applicable periodic inference configuration

[0155] In one set of embodiments, a UE configured with a periodic inference configuration releases the periodic inference configuration when the periodic inference configuration is determined to be non-applicable.

[0156] In some examples, the UE releases the periodic inference configuration when the UE receives the inference configuration the first time, e.g., in an RRC Reconfiguration, before it transmits the RRC Reconfiguration Complete including an indication that the periodic inference configuration is non-applicable. In other words, the UE autonomously releases the periodic inference configuration upon reception of the inference configuration in an RRC Reconfiguration, before it transmits the RRC Reconfiguration Complete including the indication that the periodic inferenceconfiguration is non-applicable. The benefit of this option is reduced signaling and lower energy consumption since the UE is initially configured because network intended to receive periodic inferences (for a given AI / ML functionality) in case such inference configuration would have been applicable; but, since that inference configuration was not applicable, the UE autonomously releasing the non-applicable inference configuration prevents the need for an additional RRC Reconfiguration loop, for releasing that non-applicable periodic inference configuration.

[0157] o In some examples, the UE behavior is controlled by a parameter the UE receives. In other words, when the UE receives this parameter, the UE configured with a periodic inference configuration releases the periodic inference configuration when the periodic inference configuration is determined to be non-applicable.

[0158] ■ In one sub-option, the parameter is associated with the inference configuration, by being included in a reporting configuration in which the inference configuration is configure e.g. an instance of the IE CSI- ReportConFigure

[0159] ■ In one sub-option, the parameter is associated with multiple inference configurations, e.g., for the same serving cell, by being included in a serving cell configuration in which one or more inference configurations are included.

[0160] Figure 7 illustrates a signaling diagram of an example of autonomous release of periodic inference configuration during initial inference configuration.

[0161] In some examples, the UE releases the periodic inference configuration when an inference configuration the UE has stored has changed its applicability from applicable to non-applicable i.e. when it becomes non-applicable. In other words, the UE initially has a periodic inference configuration which is applicable i.e. the UE is transmitting inference(s) to the network, periodically, and determines that the inference configuration (which is up and running) becomes non-applicable (e.g. when the UE changes its speed, and / or enter an area for which the inference is not possible to be performed). Then, upon determining that the inference configuration is changed to non-applicable, the UE releases the periodic inference configuration when the periodic inference configuration is determined to be non-applicable. The benefit of this option is also reduced signaling and lower energy consumption since the UE is configured because network intended to receive periodic inferences (for a given AI / ML functionality) in case such inference configuration would have beenapplicable; but, once that stops to be received, since that inference configuration becomes not applicable, the UE autonomously releasing the non-applicable inference configuration prevents the need for an additional RRC Reconfiguration loop, for releasing that non-applicable periodic inference configuration.

[0162] o In some examples, the UE behavior is controlled by a parameter the UE receives. In other words, when the UE receives this parameter, the UE configured with a periodic inference configuration releases the periodic inference configuration when the periodic inference configuration is updated from applicable to non-applicable.

[0163] ■ In one sub-option, the parameter is associated with the inference configuration, by being included in a reporting configuration in which the inference configuration is configure e.g. an instance of the IE CSI- ReportConFigure

[0164] ■ In one sub-option, the parameter is associated with multiple inference configurations, e.g., for the same serving cell, by being included in a serving cell configuration in which one or more inference configurations are included.

[0165] Figure 8 illustrates a signaling diagram of an example of autonomous release of periodic inference configuration when that is changed from applicable to non-applicable.

[0166] The release of the periodic inference configuration (which is also called an autonomous release) means in some examples that the UE deletes the periodic inference configuration i.e. this is not just stop using it. In other words, in case the network wants the UE to again operate according to that periodic inference configuration, the network would have to transmit another periodic inference configuration to the UE, since it is assumed that the previously transmitted has been deleted (i.e. released) by the UE.

[0167] In some examples, the UE may be configured with multiple periodic inference configurations. The UE selects one of the multiple periodic inference configurations that is applicable if any, and it releases all the others. In case there are multiple inference configurations that are applicable, the UE selects one or more of those, and releases all the others that are not selected (irrespective of whether they are applicable or not). The one or more of the multiple inference configurations that is selected is included by the UE in the applicability report and indicated as applicable. The periodic inference configurations that are not selected are released (not stored), and the fields / parameters included in such inference configurations are ignored, and the UE does not take any action on them.Autonomous activation of periodic inference configuration

[0168] In examples of this disclosure, a UE configured with a periodic inference configuration has that periodic inference configuration as deactivated in response to the UE determining that the periodic inference configuration is non-applicable (i.e. the UE does not transmit periodic inferences associated with the periodic inference configuration), and the UE further determines (e.g. after some time) that the inference configuration becomes applicable again (i.e. changes its applicability), reports to the network an indication that the inference configuration became applicable (e.g. in a UE Assistance Information message) and autonomously activates the periodic inference configuration for which the applicability is updated from non-applicable to applicable i.e. the UE starts to perform the inferences and to transmit inferences periodically according to the inference configuration.

[0169] In some examples, the autonomous activation of a periodic inference configuration is controlled by a parameter. In other words, the UE autonomously activate the periodic inference configuration when that changes to applicable (from non-applicable) when the inference configuration includes a parameter indicating that is to be done e.g. within the CSI reporting configuration in which the periodic inference configuration is included.

[0170] In some examples, the autonomous activation of a periodic inference configuration is performed by the UE if configured to report to the network that the periodic inference configuration has changed its applicability e.g. from non-applicable to applicable. o In one sub-option, the autonomous activation occurs at the UE after a certain time duration after the UE reports to the network that the periodic inference configuration has changed its applicability. The said time duration can be controlled by a parameter, e.g. configured by the network in the inference configuration. This is useful to allow the network to receive the report from the UE, process it, and start sending the measurement signals (e.g. CSI-RS) needed by the UE to perform inference according to the periodic inference configuration.

[0171] Figure 9 illustrates a signaling diagram of autonomous activation of a periodic inference configuration when that is changed from non-applicable to applicable.

[0172] In some examples, the UE may be configured with multiple periodic inference configurations. In case there are multiple inference configurations that are applicable, the UE selects one or more of those and activates them, while it deactivates or keeps deactivated all the others that are not selected (irrespective of whether they are applicable or not). In one method,whether for the specific periodic inference configuration the UE can perform autonomous activation it is indicated in the periodic inference configuration.

[0173] New MAC Control Element (CE) for explicit activation

[0174] In examples of this disclosure, a UE configured with a periodic inference configuration is deactivated in response to the UE determining that the periodic inference configuration is non-applicable (i.e. the UE does not transmit periodic inferences associated with the periodic inference configuration). Then, the UE further determines (e.g. after some time) that the inference configuration becomes applicable again (i.e. changes its applicability), and reports to the network e.g. an indication that the inference configuration became applicable. Then, the UE receives from the network a Medium Access Control (MAC) Control Element (CE) including an indication of the inference configuration and in response to the MAC CE the UE activates the inference configuration indicated by the indication i.e. the UE starts to perform the inferences and to transmit inferences periodically according to the inference configuration. In other words, the UE receives a MAC CE which indicates an inference configuration to be activated and in response to it activates, wherein the indicated inference configuration was deactivated in response to the inference configuration being non-applicable.

[0175] In some examples, the indication of the inference configuration corresponds to an inference configuration identifier.

[0176] In some examples, the indication of the inference configuration corresponds to an reporting configuration identifier, associated to an instance of the IE CSI- ReportConfig in which the inference configuration is received by the UE. In other words, the UE receives the MAC CE which includes the reporting configuration identifier pointing to the inference configuration which is to be activated.

[0177] In one option, the MAC CE is a new MAC CE defined for activating a periodic reporting of inference configuration

[0178] o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Periodic CSI reporting on Physical Uplink Control Channel (PUCCH) o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Periodic CSI reporting on Physical Uplink Shared Channel (PUSCH) o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Periodic inference reporting on PUCCH

[0179] o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Periodic inference reporting on PUSCHFigure 10 illustrates a signaling diagram of an example of activation of a periodic inference configuration when that is changed from non-applicable to applicable, based on reception of a new MAC CE for periodic inference configuration.

[0180] Semi-Persistent (SP) MAC CE used for periodic inference configuration

[0181] In examples of this disclosure, a UE configured with a periodic inference configuration is deactivated in response to the UE determining that the periodic inference configuration is non-applicable (i.e. the UE does not transmit periodic inferences associated with the periodic inference configuration). Then, the UE further determines (e.g. after some time) that the inference configuration becomes applicable again (i.e. changes its applicability), and reports to the network e.g. an indication that the inference configuration became applicable. Then, the UE receives from the network an Activation I Deactivation Semi-Persistent MAC CE including an indication of the inference configuration and in response to the Activation / deactivation Semi-Persistent MAC CE the UE activates the inference configuration indicated by the indication i.e. the UE starts to perform the inferences and to transmit inferences periodically according to the inference configuration. In other words, the UE receives an activation / deactivation SP MAC CE which indicates an inference configuration to be activated and in response to it activates, wherein the indicated inference configuration was deactivated in response to the inference configuration being non-applicable.

[0182] In some examples, the indication of the inference configuration corresponds to an inference configuration identifier.

[0183] In some examples, the indication of the inference configuration corresponds to a reporting configuration identifier, associated to an instance of the IE CSI- ReportConfig in which the inference configuration is received by the UE. In other words, the UE receives the MAC CE which includes the reporting configuration identifier pointing to the inference configuration which is to be activated.

[0184] In one option, the SP MAC CE is received for a periodic reporting configuration in case the periodic reporting configuration is associated to an inference configuration o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Semi-Persistent CSI reporting on Physical Uplink Control Channel (PUCCH) o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Semi-Persistent CSI reporting on Physical Uplink Shared Channel (PUSCH) o In one sub-option the MAC CE corresponds to an Activation / Deactivation of Semi-Persistent inference reporting on PUCCHFigure 11 illustrates a signaling diagram of an example of activation of a periodic inference configuration when that is changed from non-applicable to applicable, based on reception of a MAC CE for Semi-Persistent CSI reporting (used for periodic inference configuration).

[0185] RRCReconfiguration for periodic inference configuration that changes applicability

[0186] In examples of this disclosure, a periodic inference configuration configured at the UE is deactivated in response to the UE determining that the periodic inference configuration is non-applicable (i.e. the UE does not transmit periodic inferences associated with the periodic inference configuration). Then, the UE further determines (e.g. after some time) that the inference configuration becomes applicable again (i.e. changes its applicability), and reports to the network e.g. an indication that the inference configuration became applicable. Then, the UE receives from the network an RRCReconfiguration including an indication / configuration of the inference configuration and in response to the RRCReconfiguration the UE activates the inference configuration indicated.

[0187] • In some examples, the UE activates the inference configuration indicated upon determining it is the same inference configuration for which it reported the applicability change. Further, upon determining it is the same inference configuration, the UE omits sending an additional applicability report for this configuration after receiving the RRCReconfiguration.

[0188] • In some examples, upon receiving an additional indication / parameter from the network in the RRCReconfiguration (e.g. in the inference configuration), the UE activates the inference configuration indicated and omits sending an additional applicability report for this configuration after receiving the RRCReconfiguration.

[0189] Examples of this disclosure may also provide methods for the gNB to handle the configuration of periodic inferences, the methods comprising the gNB releasing the one or more periodic inference configurations that the UE indicates as non applicable in the applicability report. According to this method, the UE does not perform are autonomous release or deactivation of the periodic inference configurations that are not selected as applicable. Rather, the gNB releases those configurations to the UE upon receiving the applicability report. In order to determine whether a certain periodic inference configuration which was indicated as non applicable becomes applicable at a later point in time, the gNB transmits an RRC reconfiguration message containing again such periodic inference configuration. And the UE transmits in response an applicable report and applies the methods disclosed herein related to how to handle such periodic inference configuration depending on whether that is applicable or not.Figure 12 shows an example of a communication system QQ100 in accordance with some embodiments.

[0190] In the example, the communication system QQ100 includes a telecommunications network QQ102 that includes an access network QQ104, such as a radio access network (RAN), and a core network QQ106, which includes one or more core network nodes QQ108. The access network QQ104 includes one or more access network nodes or base stations of various types, access network nodes QQ110A and QQ110B are depicted (which may be collectively referred to as network nodes QQ110), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points (APs). Some embodiments of the access network QQ104 may include more than one access network technology. The network nodes QQ110 of access network QQ104 facilitate direct or indirect connection of wireless devices, also referred to as user equipments (UEs), such as by connecting UEs QQ112A, QQ112B, QQ112C, and QQ112D (one or more of which may be generally referred to as UEs QQ112) to the core network QQ106 over one or more wireless connections.

[0191] Moreover, 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 telecommunications network QQ102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a network node in the telecommunications network QQ102 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 network nodes to implement one or more functionalities of any network node in the telecommunications network QQ102, including one or more access network nodes QQ110 and / or core network nodes QQ108.

[0192] 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). An ORAN network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN network node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one ormore network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies.

[0193] The network nodes QQ110 facilitate direct or indirect connection of one or more UEs QQ112 to the core network QQ106 over one or more wireless connections. 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 QQ100 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 QQ100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0194] The UEs QQ112 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 QQ110 and other communication devices. Similarly, the network nodes QQ108, QQ110 are arranged, capable, configured, and / or operable to communicate directly or indirectly (e.g., via other devices of telecommunications network QQ102) with the UEs QQ112 and / or with other network nodes or equipment in the telecommunications network QQ102 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunications network QQ102. More specifically, UEs QQ112 may send messages, data, and / or other signals to network nodes QQ108, QQ110 or other elements of the telecommunications network QQ102 by transmitting such signals to the relevant device directly without the signals passing through any intervening devices or by transmitting such signals to the relevant device indirectly through an intervening device (or multiple intervening devices) that then transmit the signal to the relevant device. Similarly, network nodes QQ108, QQ110 may send messages, data, and other signals to UEs QQ1122, other network nodes QQ108, QQ110, and other devices in telecommunications network QQ102 directly or indirectly. As one specific example, a core network node 108 may transmit a particular message to a UE QQ112 by transmitting the message to an access network node QQ110 that will then transmit the message to the intended UE QQ112. Similarly, a core network node 108 may receive a particular messagefrom a UE QQ112 by receiving the message from an access network node QQ110 that itself received the message from the UE QQ112.

[0195] In the depicted example, the core network QQ106 connects elements of the access network QQ104 (e.g., one or more of the network nodes QQ110) to one or more host computing systems, such as host QQ116. 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 QQ106 includes one or more core network nodes (e.g., core network node QQ108) of various types, one or more of which may be generally referred to as network nodes QQ108. Network nodes QQ108 are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, access network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node QQ108. Example core network nodes provide 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).

[0196] The host QQ116 may be under the ownership or control of a service provider other than an operator or provider of the access network QQ104 and / or the telecommunications network QQ102. The host QQ116 may be operated by the service provider or on behalf of the service provider. The host QQ116 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.

[0197] As a whole, the communication system QQ100 of Figure 12 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system QQ100 may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (Wi-Fi); and / or any otherappropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (Wi-Max), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, Li-Fi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox. Moreover, the communication system QQ100 may be configured to support multiple different standards, protocols, or other rule sets, with individual components supporting all of the relevant rule sets or with different components or sub-systems within the communication system QQ100 supporting different standards, protocols, or rule sets.

[0198] As one example, in certain embodiments, access network QQ104 may contain some access network nodes QQ110 that support 3GPP radio access technologies (RAT), such as LTE or NR, while other access network nodes QQ110 support (or the same access network nodes QQ110 additionally support) non-3GPP RATs, such as Wi-Fi or a proprietary RAT. As another example, telecommunications network QQ102 may support multiple generations of related communication standards (e.g., 4G and 5G 3GPP communication standards) and, as a result, may include an access network 104 and / or a core network 106 that supports multiple different standard generations or may include multiple access networks 104 and / or multiple core networks 106 with individual networks 104, 106 supporting different standard generations.

[0199] Telecommunications network QQ102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunications network QQ102. For example, the telecommunications network QQ102 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 loT services to yet further UEs.

[0200] In some examples, one or more of the UEs QQ112 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 QQ104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network QQ104. Additionally, a UE may be configured for operating in single- or multi-RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).

[0201] In the example, the hub QQ114 communicates with the access network QQ104 to facilitate indirect communication between one or more UEs (e.g., UE QQ112C and / or QQ112D) andnetwork nodes (e.g., network node QQ110B). In some examples, the hub QQ114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub QQ114 may be a broadband router enabling access to the core network QQ106 for the UEs. As another example, the hub QQ114 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 QQ110, or by executable code, script, process, or other instructions in the hub QQ114.

[0202] As another example, the hub QQ114 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 QQ114 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub QQ114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub QQ114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub QQ114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0203] The hub QQ114 may have a constant / persistent or intermittent connection to the network node QQ110B. The hub QQ114 may also allow for a different communication scheme and / or schedule between the hub QQ114 and UEs (e.g., UE QQ112C and / or QQ112D), and between the hub QQ114 and the core network QQ106. In other examples, the hub QQ114 is connected to the core network QQ106 and / or one or more UEs via a wired connection.

[0204] Moreover, the hub QQ114 may be configured to connect to an M2M service provider over the access network QQ104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes QQ110 while still connected via the hub QQ114 via a wired or wireless connection. In some embodiments, the hub QQ114 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node QQ110B. In other embodiments, the hub QQ114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node QQ110B, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0205] Figure 13 is another example of a communication system QQ200 according to some embodiments. As used herein, the communication system QQ200 includes multiple access points (APs) QQ210 (with four exemplary APs QQ210A, QQ210B, QQ210C, and QQ210D being depicted) and multiple wireless devices, referred to in the context of communicationsystem QQ200 as stations (STAs) QQ212 (referred to individually as STA QQ212A, STA QQ212B, STA QQ212C, STA QQ212D, and STA QQ212E). STA QQ212A is served by AP QQ210A in a first basic service set (BSS) QQ220A. STA QQ210B and STA QQ210C are served by AP QQ210B in a second BSS, BSS QQ220B. STA QQ212D is served by AP QQ210C in a third BSS, BSS QQ220C. STA QQ212E is served by AP QQ210D in a fourth BSS, BSS QQ220D. Stations QQ212 may be non-AP STAs and correspond to various kinds of wireless devices, for example, user terminals, such as mobile or stationary computing devices like smartphones, laptop computers, desktop computers, tablet computers, gaming devices, head-mounted displays (HMDs) for Augmented Reality (AR) or Virtual Reality (VR), or the like. Further, stations QQ212 could, for example, correspond to other kinds of equipment like smart home devices, printers, multimedia devices, data storage devices, or the like.

[0206] Each of STAs QQ212 may connect through a radio link to one of APs QQ210. For example, depending on location or channel conditions experienced by a given STA QQ212, the STA may select an appropriate AP and BSS for establishing the radio link. The radio link may be based on one or more orthogonal frequency-division multiplexing (OFDM) carriers from a frequency spectrum that is shared on the basis of a contention-based mechanism, e.g., an unlicensed or license exempt band like 2.4 GHz Industrial, Scientific, and Medical (ISM) band, the 5 GHz band, the 6 GHz band, or the 60 GHz band.

[0207] Each AP QQ210 may provide data connectivity to STAs QQ212 connected to a particular AP QQ210. As illustrated, APs QQ210 may be connected to a data network QQ230. In this way, APs QQ210 may also provide data connectivity between STAs QQ212 and other entities, e.g., to one or more servers, service providers, data sources, data sinks, user terminals, or the like. Accordingly, the radio link established between a given STA QQ212 and its serving AP QQ210 may be used for providing various kinds of services to STA QQ212, e.g., a voice service, a multimedia service, or other data service. Such services may be based on applications that are executed on STA QQ212 and / or on a device linked to STA QQ212. By way of example, Figure 13 illustrates an application service platform QQ232 provided in data network QQ230. The application(s) executed on STA QQ212 and / or on one or more other devices linked to STA QQ212 may use the radio link for data communication with one or more other STA QQ212 and / or the application service platform QQ232, thereby enabling utilization of the corresponding service(s) at STA QQ212.

[0208] Figure 14 shows a wireless device QQ300, which may be configured to operate in communication system QQ100 of Figure 12 or in communication system QQ200 of Figure 13. The wireless device QQ300 may be alternatively referred to as a UE QQ300, like a UEQQ112 within the context of communication system QQ100, or as a station (STA) QQ300 or as a non-access-point station (non-AP STA) QQ300, like a STA QQ212 within the context of the communication system QQ200, in accordance with respective embodiments. As used herein, a wireless device refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other wireless devices. Examples of a wireless device include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage 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, and wireless terminal. Other examples include any type of UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0209] A wireless device QQ300 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), orvehicle-to-everything (V2X). In other examples, wireless device QQ300 may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, wireless device QQ300 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, wireless device QQ300 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).

[0210] In particular embodiments, wireless device QQ300 includes processing circuitry QQ302 that is operatively coupled via a bus QQ304 to an input / output interface QQ306, a power source QQ308, a memory QQ310, a communication interface QQ312, and / or any other component, or any combination thereof. Certain embodiments of wireless device QQ300 may include all or a subset of the components shown in Figure 14. The level of integration between the components may vary from one embodiment of wireless device QQ300 to another. In general, in a particular embodiment of wireless device QQ300, processing circuitry QQ302, input / output interface QQ306, power source QQ308, memory QQ310, and communication interface QQ312 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of wireless device QQ300.Further, certain embodiments of wireless devices QQ300 may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0211] The processing circuitry QQ302 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 QQ310. The processing circuitry QQ302 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 QQ302 may include multiple central processing units (CPUs). The processing circuitry QQ302 may be configured to cause the wireless device QQ300 to perform the methods as described with reference to Figure 5.

[0212] In the example, the input / output interface QQ306 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 wireless device QQ300. 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.

[0213] In some embodiments, the power source QQ308 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 to supply power to circuitry or to charge an associated battery. The power source QQ308 may further include power circuitry for delivering power from the power source QQ308 itself, and / or an external power source, to the various parts of wireless device QQ300 via input circuitry or an interface such as anelectrical power cable. Power source QQ308 may perform any formatting, converting, or other modification to make accessible power suitable for the respective components of the wireless device QQ300 to which power is supplied.

[0214] The memory QQ310 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory QQ310 includes one or more programs QQ314, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data QQ316. The memory QQ310 may store, for use by wireless device QQ300, any of a variety of various operating systems or combinations of operating systems.

[0215] The memory QQ310 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUlCC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory QQ310 may allow wireless device QQ300 to access instructions, programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory QQ310, which may be or comprise a device-readable storage medium.

[0216] The processing circuitry QQ302 may be configured to communicate with an access network or other network via or using the communication interface QQ312. The communication interface QQ312 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna QQ322. The communication interface QQ312 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 wireless device or a network node in an access network). Each transceiver may include a transmitter QQ318 and / or a receiver QQ320 appropriate to provide networkcommunications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter QQ318 and receiver QQ320 may be coupled to one or more antennas (e.g., antenna QQ322) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0217] In the illustrated embodiment, communication functions of the communication interface QQ312 may include cellular communication, Wi-Fi communication (e.g., according to an IEEE 802.11 family standard), LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0218] In particular embodiments, wireless device QQ300 may provide an output of data captured via a sensor, through its communication interface QQ312, via a wireless connection to a network node, and / or in any appropriate manner. Data captured by sensors of a wireless device QQ300 can be communicated through a wireless connection to a network node via another wireless device QQ300. In particular embodiments, such 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).

[0219] As another example, wireless device QQ300 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, wireless device QQ300 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.

[0220] Wireless device QQ300, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limitedto, wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smartwatch, a fitness tracker, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. In particular embodiments, wireless device QQ300 represents an loT device that comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the example embodiment of wireless device QQ300 shown in Figure 14.

[0221] As yet another specific example, in an loT scenario, wireless device QQ300 may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another wireless device and / or a network node. Wireless device QQ300 may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, wireless device QQ300 may implement the 3GPP NB-loT standard. In other scenarios, wireless device QQ300 may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0222] In practice, any number of wireless devices QQ300 may be used together with respect to a single use case. For example, a first wireless device QQ300 might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second wireless device QQ300 that is a remote controller operating the drone. When a user makes changes from the remote controller, the first wireless device QQ300 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 wireless device QQ300 can also include more than one of the functionalities described above. For example, wireless device QQ300 might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.Figure 15 shows a network node QQ400 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunications network. In accordance with respective embodiments, network node QQ400 may be configured to operate in communication system QQ100 of Figure 12, like network nodes QQ108 or QQ110, or in communication system QQ200 of Figure 13, like an AP QQ210 or a station QQ212. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., 0-Rll, 0-Dll, O-CU).

[0223] Network nodes QQ400 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. Network node QQ400 may be a relay node or a relay donor node controlling a relay. Network nodes QQ400 may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0224] Other examples of network nodes QQ400 include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0225] In particular embodiments, network node QQ400 includes a processing circuitry QQ402, a memory QQ404, a communication interface QQ406, and a power source QQ408. In general, in a particular embodiment of network node QQ400, processing circuitry QQ402, memory QQ404, communication interface QQ406, and power source QQ408 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of network node QQ400.The network node QQ400 may be composed of multiple distinct network entities (e.g., a NodeB entity and a RNC entity, or a BTS entity and a BSC entity, etc.), which may each have or utilize their own respective physical components. In certain scenarios in which the network node QQ400 comprises multiple such entities (e.g., BTS and BSC), one or more of the separate entities 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 QQ400 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memories QQ404 or portions of memory QQ404 for different RATs) and some components may be reused (e.g., a same antenna QQ410 may be shared by different RATs). The network node QQ400 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node QQ400, for example GSM, WCDMA, LTE, NR, Wi-Fi (e.g., according to an IEEE 802.11 family standard), Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node QQ400.

[0226] The processing circuitry QQ402 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other components, such as the memory QQ404, to provide network node QQ400 functionality. For example, the processing circuitry QQ402 may be configured to cause the network node QQ400 to perform the methods as described with reference to Figure 6.

[0227] In some embodiments, the processing circuitry QQ402 includes a system on a chip (SOC). In some embodiments, the processing circuitry QQ402 includes one or more of radio frequency (RF) transceiver circuitry QQ412 and baseband processing circuitry QQ414. In some embodiments, the RF transceiver circuitry QQ412 and the baseband processing circuitry QQ414 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry QQ412 and baseband processing circuitry QQ414 may be on the same chip or set of chips, boards, or units.

[0228] The memory QQ404 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotelymounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry QQ402. The memory QQ404 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 QQ402 and utilized by the network node QQ400. The memory QQ404 may be used to store any calculations made by the processing circuitry QQ402 and / or any data received via the communication interface QQ406. In some embodiments, the processing circuitry QQ402 and memory QQ404 is integrated.

[0229] The communication interface QQ406 is used in wired or wireless communication of signaling and / or data with UEs, other network nodes, and / or any other network equipment. In the illustrated embodiment, communication interface QQ406 comprises port(s) / terminal(s) QQ416 to send and receive data, for example to and from a network over a wired connection. In particular embodiments, network node QQ300 may be capable of wireless communication and communication interface QQ406 may also include radio front-end circuitry QQ418 that may be coupled to, or in certain embodiments a part of, an antenna QQ410. Particular embodiments of radio front-end circuitry QQ418 include filter(s) QQ420 and amplifier(s) QQ422. The radio front-end circuitry QQ418 may be connected to an antenna QQ410 and processing circuitry QQ402. The radio front-end circuitry may be configured to condition signals communicated between antenna QQ410 and processing circuitry QQ402. The radio front-end circuitry QQ418 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 QQ418 may convert the digital data into a radio signal(s) having the appropriate channel and bandwidth parameters using a combination of filters QQ420 and / or amplifiers QQ422. The radio signal(s) may then be transmitted via the antenna QQ410. Similarly, when receiving data, the antenna QQ410 may collect radio signals which are then converted into digital data by the radio front-end circuitry QQ418. The digital data may be passed to the processing circuitry QQ402. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0230] In certain alternative embodiments, network node QQ400 may be capable of wireless communication but does not include separate radio front-end circuitry QQ418, instead, the processing circuitry QQ402 includes radio front-end circuitry and is connected to the antennaQQ410. Similarly, in some embodiments, all or some of the RF transceiver circuitry QQ412 is part of the communication interface QQ406. In still other embodiments, the communication interface QQ406 includes one or more ports or terminals QQ416, the radio front-end circuitry QQ418, and the RF transceiver circuitry QQ412, as part of a radio unit (not shown), and the communication interface QQ406 communicates with the baseband processing circuitry QQ414, which is part of a digital unit (not shown).

[0231] The antenna QQ410 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna QQ410 may be coupled to the radio frontend circuitry QQ418 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna QQ410 is separate from the network node QQ400 and connectable to the network node QQ400 through one or more interfaces or ports.

[0232] The antenna QQ410, communication interface QQ406, and / or the processing circuitry QQ402 may be configured to perform some or all of the receiving operations and / or obtaining operations described herein as being performed by the network node QQ400. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna QQ410, the communication interface QQ406, and / or the processing circuitry QQ402 may be configured to perform some or all of the transmitting or sending operations described herein as being performed by the network node QQ400. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0233] The power source QQ408 provides power to the various components of network node QQ400 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source QQ408 may further comprise, or be coupled to, power management circuitry to supply the components of the network node QQ400 with power for performing the functionality described herein. For example, the network node QQ400 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source QQ408. As a further example, the power source QQ408 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.

[0234] Embodiments of the network node QQ400 may include additional components beyond those shown in Figure 15 for providing certain aspects of the network node’s functionality,including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node QQ400 may include user interface equipment to allow input of information into the network node QQ400 and to allow output of information from the network node QQ400. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node QQ400.

[0235] Figure 16 is a block diagram illustrating a virtualization environment QQ500 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may 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 QQ500 hosted by one or more of hardware nodes, such as a hardware computing device that operates as an access network node, UE, core network node, or host. Further, in embodiments in which a 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 QQ500 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

[0236] Applications QQ502 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0237] Hardware QQ504 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers QQ506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VM QQ508A and VM QQ508B (which may be collectively referred to as VMs QQ508), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer QQ506 may present a virtual operating platform that appears like networking hardware to one or more of the VMs QQ508.The VMs QQ508 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by virtualization layer QQ506. Different embodiments of the instance of a virtual appliance QQ502 may be implemented on one or more of VMs QQ508, 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.

[0238] In the context of NFV, each of the VMs QQ508 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 QQ508, and that part of hardware QQ504 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more of the VMs QQ508 on top of the hardware QQ504 and corresponds to an application QQ502.

[0239] Hardware QQ504 may be implemented in a standalone network node with generic or specific components. Hardware QQ504 may implement some functions via virtualization. Alternatively, hardware QQ504 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 QQ510, which, among others, oversees lifecycle management of applications QQ502. In some embodiments, hardware QQ504 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system QQ512 which may alternatively be used for communication between hardware nodes and radio units.

[0240] 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.

[0241] Examples of this disclosure include the following enumerated embodiments.

[0242] Group A Embodiments

[0243] 1. A method performed by a wireless communication device for activating or releasing an inference configuration, the method comprising:

[0244] obtaining an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node;

[0245] determining applicability of the inference configuration at the wireless communication device; and

[0246] if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration; and / or

[0247] if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration.

[0248] 2. The method of embodiment 1, comprising reporting the applicability of the inference configuration at the wireless communication device to the network node.

[0249] 3. The method of embodiment 2, wherein the inference configuration includes an indication to report the applicability of the inference configuration at the wireless communication device to the network node.4. The method of embodiment 2 or 3, comprising, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, receiving, from the network node, an instruction to activate the inference configuration.

[0250] 5. The method of embodiment 4, wherein activating the inference configuration is performed after receiving the instruction to activate the inference configuration.

[0251] 6. The method of embodiment 5, wherein activating the inference configuration is performed a predetermined time period after receiving the instruction to activate the inference configuration.

[0252] 7. The method of embodiment 6, wherein an indication of the predetermined time period is included in the inference configuration or is received from the network node.

[0253] 8. The method of any of embodiments 2 to 7, comprising, if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, receiving, from the network node, an instruction to release the inference configuration.

[0254] 9. The method of embodiment 8, wherein releasing the inference configuration is performed after receiving the instruction to release the inference configuration.

[0255] 10. The method of any of embodiments 4 to 9, wherein the instruction is received according to one or more of:

[0256] in a Radio Resource Control (RRC) Reconfiguration message;

[0257] in a Medium Access Control (MAC) Control Element (CE);

[0258] in a semi-persistent MAC CE.

[0259] 11. The method of embodiment 2 or 3, comprising:

[0260] if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration before reporting the applicability of the inference configuration at the wireless communication device to the network node; and / orif the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing the inference configuration before reporting the applicability of the inference configuration at the wireless communication device to the network node.

[0261] 12. The method of any of embodiments 1 to 11, wherein determining the applicability of the inference configuration at the wireless communication device comprises:

[0262] determining a change of the applicability of the inference configuration at the wireless communication device; and / or

[0263] determining the applicability of the inference configuration at the wireless communication device in response to a change of the applicability of the inference configuration at the wireless communication device.

[0264] 13. The method of embodiment 12, wherein the change of the applicability of the inference configuration at the wireless communication device comprises:

[0265] a change in the applicability from applicable at the wireless communication device to not applicable at the wireless communication device; and / or

[0266] a change in the applicability from not applicable at the wireless communication device to applicable at the wireless communication device.

[0267] 14. The method of any of embodiments 1 to 13, wherein obtaining the inference configuration comprises receiving the inference configuration from the network node.

[0268] 15. The method of embodiment 14 when dependent on embodiment 2, wherein reporting the applicability of the inference configuration at the wireless communication device to the network node comprises sending, to the network node, an indication of the applicability of the inference configuration at the wireless communication device to the network node in a message responding to receiving the inference configuration from the network node.

[0269] 16. The method of embodiment 14 or 15, wherein the inference configuration is received in one or more of:

[0270] a RRC Reconfiguration message;

[0271] a Reconfiguration with Sync message;

[0272] a measurement reporting configuration.17. The method of any of embodiments 1 to 16, wherein the inference configuration includes an indication of or identifies a time period for periodically performing the inference and / or periodically reporting the inference information to the network node.

[0273] 18. The method of any of embodiments 1 to 17, wherein, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating the inference configuration is performed if an indication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device indicates to activate the inference configuration.

[0274] 19. The method of embodiment 18, wherein the indication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device is included in the inference configuration or is received from the network node.

[0275] 20. The method of any of embodiments 1 to 19, wherein activating the inference configuration comprises one or more of:

[0276] performing the inference and / or the reporting inference information to the network node;

[0277] starting performing the inference and / or the reporting inference information to the network node.

[0278] 21. The method of any of embodiments 1 to 20, wherein releasing the inference configuration comprises one or more of:

[0279] deactivating the inference configuration;

[0280] deleting the inference configuration;

[0281] stopping performing the inference and / or the reporting inference information to the network node;

[0282] refraining from applying the inference configuration.

[0283] 22. The method of any of embodiments 1 to 21, wherein the inference configuration is a configuration for periodically performing inference using an artificial intelligence or machine learning (AI / ML) model.

[0284] 23. The method of any of embodiments 1 to 24, wherein the inference configuration identifies one or more of:a first set of beams for measurement by the wireless communication device; and a second set of beams for measurement prediction using the functionality.

[0285] 24. The method of any of embodiments 1 to 23, wherein:

[0286] the applicability of the inference configuration comprises applicable at the wireless communication device if the inference configuration is currently applicable, useable or operable at the wireless communication device, and / or the wireless communication device is currently able to use the inference configuration for inference, and / or the wireless communication device is currently able to report inference using the inference configuration to the network node; and / or

[0287] the applicability of the inference configuration comprises not applicable at the wireless communication device if the inference configuration is currently not applicable, not useable or not operable at the wireless communication device, and / or the wireless communication device is currently not able to use the inference configuration for inference, and / or the wireless communication device is currently not able to report inference using the inference configuration to the network node.

[0288] 25. The method of any of embodiments 1 to 25, wherein the applicability of the inference configuration is determined based on one or more applicability conditions.

[0289] 26. The method of embodiment 25, wherein the one or more applicability conditions include one or more wireless communication device-side conditions and / or one or more network-side conditions.

[0290] 27. The method of any of embodiments 1 to 26, wherein the inference configuration comprises one or more of:

[0291] beam management functionality for managing beams for the wireless communication device;

[0292] beam information prediction functionality;

[0293] positioning functionality for determining a position of the wireless communication device;

[0294] measurement reporting functionality;

[0295] measurement prediction functionality;

[0296] measurement event prediction functionality;

[0297] radio link failure (RLF) prediction functionality;

[0298] handover failure (HOF) prediction functionality;

[0299] network conditions prediction functionality.28. The method of any of embodiments 1 to 27, wherein the inference configuration is associated with one or more cells, beams and / cell groups of the wireless communication device.

[0300] 29. The method of any of embodiments 1 to 28, wherein the network node comprises a base station, eNodeB or gNodeB.

[0301] Group B Embodiments

[0302] 30. A method performed by a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information, the method comprising:

[0303] receiving, from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device; and

[0304] releasing the inference configuration.

[0305] 31. The method of embodiment 30, wherein the inference configuration includes an indication to report the applicability of the inference configuration at the wireless communication device to the network node.

[0306] 32. The method of embodiment 30 or 31 , comprising, after receiving the indication that the inference configuration is not applicable at the wireless communication device, sending, to the wireless communication device, an instruction to release the inference configuration.

[0307] 33. The method of embodiment 32, wherein the instruction is sent in one or more of: in a Radio Resource Control (RRC) Reconfiguration message;

[0308] in a Medium Access Control (MAC) Control Element (CE);

[0309] in a semi-persistent MAC CE.

[0310] 34. The method of any of embodiments 30 to 33, wherein the indication that the inference configuration is not applicable at the wireless communication device indicates a change of the applicability of the inference configuration at the wireless communication device from applicable to not applicable.

[0311] 35. The method of any of embodiments 30 to 34, comprising sending the inference configuration to the wireless communication device.36. The method of embodiment 35, wherein the indication that the inference configuration is not applicable at the wireless communication device is received from the wireless communication device in a message responding to a message sending the inference configuration to the wireless communication device.

[0312] 37. The method of embodiment 35 or 36, wherein the inference configuration is sent in one or more of:

[0313] a RRC Reconfiguration message;

[0314] a Reconfiguration with Sync message;

[0315] a measurement reporting configuration.

[0316] 38. The method of any of embodiments 30 to 37, wherein the inference configuration includes an indication of or identifies a time period for periodically performing the inference and / or periodically reporting the inference information to the network node.

[0317] 39. The method of any of embodiments 30 to 38, wherein an indication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device is included in the inference configuration or is sent to the wireless communication device the network node.

[0318] 40. The method of any of embodiments 30 to 39, wherein releasing the inference configuration comprises one or more of:

[0319] deactivating the inference configuration;

[0320] deleting the inference configuration.

[0321] 41. The method of any of embodiments 30 to 40, wherein the inference configuration is a configuration for periodically performing inference using an artificial intelligence or machine learning (AI / ML) model.

[0322] 42. The method of any of embodiments 30 to 41 , wherein the inference configuration identifies one or more of:

[0323] a first set of beams for measurement by the wireless communication device; and a second set of beams for measurement prediction using the functionality.

[0324] 43. The method of any of embodiments 30 to 42, wherein:the applicability of the inference configuration comprises not applicable at the wireless communication device if the inference configuration is currently not applicable, not useable or not operable at the wireless communication device, and / or the wireless communication device is currently not able to use the inference configuration for inference, and / or the wireless communication device is currently not able to report inference using the inference configuration to the network node.

[0325] 44. The method of any of embodiments 30 to 43, wherein applicability of the inference configuration, or determining that the inference configuration is not applicable, is determined by the wireless communication device based on one or more applicability conditions.

[0326] 45. The method of embodiment 44, wherein the one or more applicability conditions include one or more wireless communication device-side conditions and / or one or more network-side conditions.

[0327] 46. The method of any of embodiments 30 to 45, wherein the inference configuration comprises one or more of:

[0328] beam management functionality for managing beams for the wireless communication device;

[0329] beam information prediction functionality;

[0330] positioning functionality for determining a position of the wireless communication device;

[0331] measurement reporting functionality;

[0332] measurement prediction functionality;

[0333] measurement event prediction functionality;

[0334] radio link failure (RLF) prediction functionality;

[0335] handover failure (HOF) prediction functionality;

[0336] network conditions prediction functionality.

[0337] 47. The method of any of embodiments 30 to 46, wherein the inference configuration is associated with one or more cells, beams and / cell groups of the wireless communication device.

[0338] 48. The method of any of embodiments 30 to 47, wherein the network node comprises a base station, eNodeB or gNodeB.

[0339] Group C Embodiments49. A wireless device (QQ112, QQ212, QQ300) for activating or releasing an inference configuration, comprising:

[0340] processing circuitry (QQ302) configured to cause the wireless device to perform any of the operations of any of the Group A embodiments; and

[0341] a power source (QQ308) configured to supply power to the processing circuitry (QQ302).

[0342] 50. A network node (QQ110, QQ210, QQ400) for releasing an inference configuration, the network node comprising:

[0343] processing circuitry (QQ402) configured to cause the network node to perform any of the operations of any of the Group B embodiments;

[0344] a power source (QQ408) configured to supply power to the processing circuitry (QQ402).

[0345] 51. A wireless device for activating or releasing an inference configuration, the wireless device comprising:

[0346] one or more antennas;

[0347] communication interface connected to the one or more antennas and to processing circuitry;

[0348] the processing circuitry being configured to cause the wireless device to perform any of the operations of any of the Group A embodiments;

[0349] an input interface connected to the processing circuitry and configured to allow input of information into the wireless device to be processed by the processing circuitry;

[0350] an output interface connected to the processing circuitry and configured to output information from the wireless device that has been processed by the processing circuitry; and

[0351] a power source connected to the processing circuitry and configured to supply power to the wireless device.

[0352] 52. A computer program product comprising a non-transitory computer-readable medium having computer-readable code embodied therein, the computer-readable code being configured such that, on execution by a suitable computer or processing circuitry, the computer or processing circuitry is caused to perform the method of any of the Group A embodiments and the Group B embodiments.

[0353] 53. A wireless device (QQ112, QQ212, QQ300) configured to perform the method of any of the Group A embodiments.54. A wireless device (QQ112, QQ212, QQ300) comprising processing circuitry (QQ302) and a memory (QQ310), said memory containing instructions executable by said processing circuitry whereby said wireless device is operative to perform the method of any of the Group A embodiments.

[0354] 55. A network node (QQ110, QQ210, QQ400), configured to perform the method of any of the Group B embodiments.

[0355] 56. A network node (QQ110, QQ210, QQ400) comprising processing circuitry (QQ402) and a memory (QQ404), said memory containing instructions executable by said processing circuitry whereby said network node is operative to perform the method of any of the Group B embodiments.

[0356] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

Claims

1. Claims1. A method (500) performed by a wireless communication device for activating or releasing an inference configuration, the method comprising:obtaining (502) an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node;determining (504) applicability of the inference configuration at the wireless communication device; andif the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating (506) the inference configuration; and / orif the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing (508) the inference configuration.

2. The method of claim 1, comprising reporting the applicability of the inference configuration at the wireless communication device to the network node.

3. The method of claim 2, comprising, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, receiving, from the network node, an instruction to activate the inference configuration, wherein activating the inference configuration is performed after receiving the instruction to activate the inference configuration or a predetermined time period after receiving the instruction to activate the inference configuration.

4. The method of any of claims 2 to 4, comprising, if the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, receiving, from the network node, an instruction to release the inference configuration, wherein releasing the inference configuration is performed after receiving the instruction to release the inference configuration.

5. The method of claim 2, comprising:if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating (506) the inference configuration before reporting the applicability of the inference configuration at the wireless communication device to the network node; and / orif the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing (508) the inference configuration before reporting the applicability of the inference configuration at the wireless communication device to the network node.

6. The method of any of claims 2 to 5, wherein obtaining (502) the inference configuration comprises receiving the inference configuration from the network node, wherein reporting the applicability of the inference configuration at the wireless communication device to the network node comprises sending, to the network node, an indication of the applicability of the inference configuration at the wireless communication device to the network node in a message responding to receiving the inference configuration from the network node.

7. The method of any of claims 1 to 6, wherein determining (504) the applicability of the inference configuration at the wireless communication device comprises:determining a change of the applicability of the inference configuration at the wireless communication device; and / ordetermining the applicability of the inference configuration at the wireless communication device in response to a change of the applicability of the inference configuration at the wireless communication device.

8. The method of claim 7, wherein the change of the applicability of the inference configuration at the wireless communication device comprises:a change in the applicability from applicable at the wireless communication device to not applicable at the wireless communication device; and / ora change in the applicability from not applicable at the wireless communication device to applicable at the wireless communication device.

9. The method of any of claims 1 to 8, wherein the inference configuration includes an indication of or identifies a time period for periodically performing the inference and / or periodically reporting the inference information to the network node.

10. The method of any of claims 1 to 9, wherein, if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating (506) the inference configuration is performed if an indication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device indicates to activate the inference configuration, wherein theindication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device is included in the inference configuration or is received from the network node.

11. The method of any of claims 1 to 10, wherein activating (506) the inference configuration comprises one or more of:performing the inference and / or the reporting inference information to the network node; andstarting performing the inference and / or the reporting inference information to the network node;and / or releasing the inference configuration comprises one or more of:deactivating the inference configuration;deleting the inference configuration;stopping performing the inference and / or the reporting inference information to the network node; andrefraining from applying the inference configuration.

12. The method of any of claims 1 to 11 , wherein:the applicability of the inference configuration comprises applicable at the wireless communication device if the inference configuration is currently applicable, useable or operable at the wireless communication device, and / or the wireless communication device is currently able to use the inference configuration for inference, and / or the wireless communication device is currently able to report inference using the inference configuration to the network node; and / orthe applicability of the inference configuration comprises not applicable at the wireless communication device if the inference configuration is currently not applicable, not useable or not operable at the wireless communication device, and / or the wireless communication device is currently not able to use the inference configuration for inference, and / or the wireless communication device is currently not able to report inference using the inference configuration to the network node.

13. The method of any of claims 1 to 12, wherein the applicability of the inference configuration is determined based on one or more applicability conditions, wherein the one or more applicability conditions include one or more wireless communication device-side conditions and / or one or more network-side conditions.

14. The method of any of claims 1 to 13, wherein the inference configuration comprises one or more of:beam management functionality for managing beams for the wireless communication device;beam information prediction functionality;positioning functionality for determining a position of the wireless communication device;measurement reporting functionality;measurement prediction functionality;measurement event prediction functionality;radio link failure (RLF) prediction functionality;handover failure (HOF) prediction functionality;network conditions prediction functionality.

15. A method (600) performed by a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information, the method comprising:receiving (602), from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device; and releasing (604) the inference configuration.

16. The method of claim 15, comprising, after receiving (602) the indication that the inference configuration is not applicable at the wireless communication device, sending, to the wireless communication device, an instruction to release the inference configuration.

17. The method of claim 15 or 16, wherein the indication that the inference configuration is not applicable at the wireless communication device indicates a change of the applicability of the inference configuration at the wireless communication device from applicable to not applicable.

18. The method of any of claims 15 to 17, comprising sending the inference configuration to the wireless communication device, wherein the indication that the inference configuration is not applicable at the wireless communication device is received from the wireless communication device in a message responding to a message sending the inference configuration to the wireless communication device.

19. The method of any of claims 15 to 18, wherein the inference configuration includes an indication of or identifies a time period for periodically performing the inference and / or periodically reporting the inference information to the network node.

20. The method of any of claims 15 to 19, wherein an indication of whether to activate the inference configuration if the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device is included in the inference configuration or is sent to the wireless communication device the network node.

21. The method of any of claims 15 to 20, wherein releasing (604) the inference configuration comprises one or more of:deactivating the inference configuration;deleting the inference configuration.

22. The method of any of claims 15 to 21, wherein the applicability of the inference configuration comprises not applicable at the wireless communication device if the inference configuration is currently not applicable, not useable or not operable at the wireless communication device, and / or the wireless communication device is currently not able to use the inference configuration for inference, and / or the wireless communication device is currently not able to report inference using the inference configuration to the network node.

23. The method of any of claims 15 to 22, wherein applicability of the inference configuration, or determining that the inference configuration is not applicable, is determined by the wireless communication device based on one or more applicability conditions, wherein the one or more applicability conditions include one or more wireless communication device-side conditions and / or one or more network-side conditions.

24. The method of any of claims 15 to 23, wherein the inference configuration comprises one or more of:beam management functionality for managing beams for the wireless communication device;beam information prediction functionality;positioning functionality for determining a position of the wireless communication device;measurement reporting functionality;measurement prediction functionality;measurement event prediction functionality;radio link failure (RLF) prediction functionality;handover failure (HOF) prediction functionality;network conditions prediction functionality.

25. A tangible, non-transient computer-readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations in a wireless communication device for activating or releasing an inference configuration, the operations comprising:obtaining (502) an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node;determining (504) applicability of the inference configuration at the wireless communication device; andif the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activating (506) the inference configuration; and / orif the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, releasing (508) the inference configuration.

26. The computer-readable medium of claim 25, comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform the method (500) of any of claims 2 to 14.

27. A tangible, non-transient computer-readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations in a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information, the operations comprising: receiving (602), from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device; and releasing (604) the inference configuration.

28. The computer-readable medium of claim 27, comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform the method (600) of any of claims 16 to 24.

29. A computer-readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to carry out the method (500, 600) according to any of claims 1 to 24.

30. A computer program, comprising instructions that, when executed by processing circuitry, cause the processing circuitry to carry out the method (500, 600) according to any of claims 1 to 24.

31. A carrier containing the computer program of claim 30, wherein the carrier is one of an electronic signal, optical signal, radio signal, or computer-readable medium.

32. Apparatus in a wireless communication device for activating or releasing an inference configuration, the apparatus comprising processing circuitry and a memory, the apparatus configured to:obtain (502) an inference configuration for periodically performing inference and / or periodically reporting inference information to a network node;determine (504) applicability of the inference configuration at the wireless communication device; andif the applicability of the inference configuration at the wireless communication device is applicable at the wireless communication device, activate (506) the inference configuration; and / orif the applicability of the inference configuration at the wireless communication device is not applicable at the wireless communication device, release (508) the inference configuration.

33. The apparatus of claim 32, wherein the apparatus is configured to perform the method (500) of any of claims 2 to 14.

34. Apparatus in a network node for releasing an inference configuration, wherein a wireless communication device has obtained the inference configuration for periodically performing inference and / or periodically reporting inference information, the apparatus comprising processing circuitry and a memory, the apparatus configured to:receive (602), from the wireless communication device, an indication that the inference configuration is not applicable at the wireless communication device; andrelease (604) the inference configuration.

35. The apparatus of claim 34, wherein the apparatus is configured to perform the method

Images