Signaling assistance for artifical intelligence / machine learning model validation

Abstract

A method (500) performed by a first radio node (102, 206, 202, 306, 302, 406, 402) for performing positioning includes receiving (502), from a second radio node (104, 204, 304, 404), assistance information for validating an Artificial Intelligence / Machine Learning, AI / ML, model at a wireless device.

Description

[0001] P110692WO01 (017997.4111) PATENT APPLICATION SIGNALING ASSISTANCE FOR ARTIFICAL INTELLIGENCE / MACHINE LEARNING MODEL VALIDATION TECHNICAL FIELD The present disclosure relates, in general, to wireless communications and, more particularly, systems and methods for signalling assistance for Artificial Intelligence / Machine Learning model validation. BACKGROUND Artificial intelligence (AI) and machine learning (ML) have been investigated, both in academia and industry, as promising tools to optimize the design of the air interface in wireless communication networks. Example use cases include using autoencoders for channel state information (CSI) compression to reduce the feedback overhead and improve channel prediction accuracy; using deep neural networks for classifying line-of-sight (LOS) and non-LOS (NLOS) conditions to enhance positioning accuracy; using reinforcement learning for beam selection at the network side and / or the user equipment (UE) side to reduce the signaling overhead and beam alignment latency; and using deep reinforcement learning to learn an optimal precoding policy for complex multiple input multiple output (MIMO) precoding problems. The Third Generation Partnership Project (3GPP) New Radio (NR) standardization work for Release 18 (Rel. 18) included a study item (SI) on AI / ML for the NR air interface. The work explores the benefits of augmenting the air interface with features enabling improved support of AI / ML-based algorithms for enhanced performance and / or reduced complexity / overhead. Through studying and specifying a few selected use cases (CSI feedback, beam management, and positioning), the works aim to design the mechanisms to accommodate AI / ML into the 3rdGeneration Partnership Project (3GPP) standard. Building an AI / ML model includes several development steps where the actual training of the AI model is just one step in a training pipeline. An important part in AI / ML development is the AI / ML model lifecycle management (LCM), which is illustrated in FIGURE 1. Specifically, FIGURE 1 is a flow diagram illustrating training and inference pipelines, and their interactions within a model lifecycle management procedure. The AI model lifecycle management typically consists of a training (re-training) pipeline. Data ingestion refers to gathering raw (training) data from a data storage. After data ingestion, P110692WO01 (017997.4111) PATENT APPLICATION there may also be a step that controls the validity of the gathered data. Data pre-processing refers to feature engineering applied to the gathered data, for example, it may include data normalization and possibly a data transformation required for the input data to the AI / ML model. The actual model training steps is where a model is obtained using the training dataset. Model evaluation refers to benchmarking the performance to a baseline. The iterative steps of model training and model evaluation continues until the acceptable level of performance is achieved. Model registration refers to registering the AI / ML model, including any corresponding AI / ML-meta data that provides information on how the AI / ML model was developed, and possibly AI / ML model evaluations performance outcomes. The AI model lifecycle management also typically consists of a deployment stage to make the trained (or re-trained) AI / ML model part of the inference pipeline. The AI model lifecycle management also typically consists of an inference pipeline. Data ingestion refers to gathering raw (inference) data from a data storage. The data pre-processing stage is typically identical to corresponding processing that occurs in the training pipeline. Model operational refers to using the trained and deployed model in an operational mode. Data and model monitoring refers to validating that the inference data are from a distribution that aligns well with the training data, as well as monitoring model outputs for detecting any performance, or operational, drifts. The AI model lifecycle management also typically consists of a drift detection stage that informs about any drifts in the model operations. One important AI / ML physical (PHY) use case is the positioning of a target UE. Both positioning approaches below have been shown to be effective in obtaining target UE's location. One is direct AI / ML positioning, where the AI / ML model output is UE location. Direct AI / ML positioning typically refers to radio fingerprinting, where channel observation is used as the input of AI / ML model. Another is AI / ML assisted positioning, where the AI / ML model output is new measurement and / or enhancement of existing measurement. The model output can be, for example, LOS / NLOS identification, timing and / or angle measurement, likelihood or reliability of the measurement. The model input is also channel observations. When applying the direct and assisted AI / ML positioning to NR wireless communication network, the following cases are further identified for investigation. ^Case 1: UE-based positioning with UE-side model, direct AI / ML or AI / ML P110692WO01 (017997.4111) PATENT APPLICATION assisted positioning ^Case 2a: UE-assisted / location management function (LMF)-basedpositioning with UE-side model, AI / ML assisted positioning ^Case 2b: UE-assisted / LMF-based positioning with LMF-side model, directAI / ML positioning ^Case 3a: NG-RAN node assisted positioning with gNodeB (gNB)-sidemodel, AI / ML assisted positioning ^Case 3b: NG-RAN node assisted positioning with LMF-side model, directAI / ML positioning For radio signal based positioning methods, conventional methods rely on a sufficient number of LOS links, typically at least three to five LOS links depending on the positioning method, and whether vertical position is estimated in addition to horizontal position. In a cluttered environment, there is often a low probability of line-of-sight for a radio link between a UE and a transmission reception point (TRP). For example, for InF-DH (Indoor Factory with Dense clutter and High base station height (Tx or Rx elevated above the clutter)) environment, Table 1 shows the LOS probabilities of a radio link between TRP and UE when assuming different InF-DH clutter parameter settings. It is observed that the LOS probability ranges from 44.9% in a mildly cluttered environment to only 0.8% in a heavily cluttered environment. Table 1 Environment clutter parameter LoS Probability setting {40%, 2m, 2m} 0.449 {50%, 2m, 2m} 0.352 {60%, 2m, 2m} 0.268 {40%, 6m, 2m} 0.014 {50%, 6m, 2m} 0.025 {60%, 6m, 2m} 0.008 Thus, conventional positioning methods struggle to locate a target UE in a heavily cluttered environment. Evaluations show that the 90%-tile positioning accuracy of conventional positioning methods is more than 15 meters in an InF-DH {60%, 6m, 2m} environment, due to the unavailability of sufficient LOS links. This motivates the application of AI / ML based positioning P110692WO01 (017997.4111) PATENT APPLICATION in such challenging deployment environments. Evaluations show that an AI / ML model can be trained to deliver 90%-tile positioning accuracy below 1 meter. While a well-functioning model can accurately determine the target UE's location in model inference, it has also been observed that the model performance can be sensitive to environment changes. Therefore model monitoring is important in the life-cycle management of AI / ML models for positioning. There currently exist certain challenges, however. For example, for AI / ML based positioning, model monitoring has been investigated. Most methods will rely on validating the model via comparison toward an external, ideally independent source of information. For example, for downlink positioning using AI / ML assisted UE based positioning, the model may be validated by comparing the result versus a parallel uplink positioning estimator. In general, the positioning framework in 3GPP is well suited for assisting a node (gNB, UE, LMF) for the purpose of positioning. The framework, however, lacks signaling to assist validation of the position estimate. Some validation methods may use line-of-sight (LOS) information as well as distance information between the transmitting and receiving nodes (UE- gNB) to validate the output of a model. To support such new functionality, the positioning framework needs to be updated. SUMMARY Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, particular embodiments include signaling in the form of Long Term Evolution Positioning Protocol (LPP), New Radio Positioning Protoccol A (NRPPa), F1 Application Protocol (F1AP), or Radio Resource Control (RRC) signaling to support model validation. Particular embodiments depend on the different cases considered for AI / ML positioning and the origin of the assistance data used for model monitoring. According to certain embodiments, a method performed by a first radio node for performing positioning includes receiving, from a second radio node, assistance information for validating an AI / ML model at a wireless device. According to certain embodiments, a first radio node for performing positioning is configured to receive, from a second radio node, assistance information for validating an AI / ML model at a wireless device. According to certain embodiments, a method performed by a second radio node for providing assistance information for positioning includes receiving a request from a first radio P110692WO01 (017997.4111) PATENT APPLICATION node to provide assistance information for validating an AI / ML model at a wireless device. The second radio node transmits, to the first radio node, the assistance information for validating the AI / ML model at the wireless device. According to certain embodiments, a second radio node for providing assistance information for positioning is configured to receive a request from a first radio node to provide assistance information for validating an AI / ML model at a wireless device. The second radio node is configured to transmit, to the first radio node, the assistance information for validating the AI / ML model at the wireless device. Certain embodiments may provide one or more of the following technical advantages. For example, particular embodiments enable the LMF to receive a request and provide accurate assistance data to the UE and periodically update the UE with information useful to validate its own AI positioning model. Particular embodiments enable the LMF to receive a request and provide accurate assistance data to the gNB and periodically update the gNB with information useful to validate its own AI positioning model. Particular embodiments may be used for the LMF own AI model. In that case, the LMF requests specific model validation measurements report from the gNB but does not need to relay the information to the UE. The receiving entity (e.g., LMF) may take decision of model validation, e.g., disabling the model if the provided LOS / distance information are not useful for UE location. BRIEF DESCRIPTION OF THE DRAWINGS For a more complete understanding of the disclosed embodiments and their features and advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which: FIGURE 1 illustrates the AI / ML model LCM; FIGURE 2 illustrates example signaling for UE-assisted / LMF-based positioning with UE- side model, AI / ML assisted positioning, according to certain embodiments; FIGURE 3 illustrates example signaling enabling an LMF to generate the model validation parameters by configuring the TRPs to perform the procedure, according to certain embodiments; FIGURE 4 illustrates an example of sliding windows for model performance monitoring, according to certain embodiments; FIGURE 5 illustrates example signaling of steps that may be taken by the LMF to request a gNB 406 to report LOS, Distance information to LMF for a UE, according to certain P110692WO01 (017997.4111) PATENT APPLICATION embodiments; FIGURE 6 illustrates an example method by a first radio node for performing positioning, according to certain embodiments; FIGURE 7 illustrates an example method for providing assistance information for positioning, according to certain embodiments; FIGURE 8 illustrates an example communication system, according to certain embodiments; FIGURE 9 illustrates an example UE, according to certain embodiments; FIGURE 10 illustrates an example network node, according to certain embodiments; and FIGURE 11 illustrates a virtualization environment in which functions implemented by some embodiments may be virtualized, according to certain embodiments. DETAILED DESCRIPTION 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. According to certain embodiments described herein, signaling in the form of LPP, NRPPa, F1AP, or RRC signaling is used to support model validation. Particular embodiments depend on the different cases considered for AI / ML positioning and the origin of the assistance data used for model monitoring. In general, for AI / ML based positioning, particular embodiments enable a UE to request assistance information to support self-monitoring of the UE’s own AI model for positioning. Particular embodiments enable the LMF to request measurement reports from the gNB (from gNB- CU to gNB-DU for split F1 architecture) with the intent of using these measurements to provide assistance information to the UE. Particular embodiments enable the gNB to request LOS+distance reports from the LMF (from gNB-DU to gNB-CU in case of split F1 architecture) with the intent of using these measurements for assisting model monitoring. Certain embodiments described herein include UE-LMF embodiments. For example, in a particular embodiment, the UE may request the LMF to assist the UE by sending additional information for UE-side model validation. The request may take the form of an additional indicator in a positioning assistance data request. Alternatively, the request can take the form of a separate request. In a further particular embodiment, the UE may request the LMF to provide the additional assistance information either in a one-shot, semi-persistent, or periodic manner. For semi- P110692WO01 (017997.4111) PATENT APPLICATION persistent or periodic reporting, the UE may include the time interval (periodicity) or the assistance information update rate in the request. In another particular embodiment, the LMF provides the UE with additional assistance information as part of the main assistance information provided to the UE for positioning purpose. In yet another particular embodiment, the LMF may provide the UE with the additional assistance information separately from the main positioning assistance data. Table 2 provides a summary of interactions between nodes for a variety of use cases for the purpose of receiving additional assistance data for model validation, according to certain embodiments. Table 2 Case Origin of model New procedures New procedures New procedure monitoring between LMF and between LMF and between UE and assistance data TRP / gNB UE gNB Case 1 TRP based UL LMF Request and UE Request and Configuration of measurements TRP reporting of LMF forwarding the UL SRS NLOS+distance of reference signal Case 2a TRP based UL information for NLOS+distance transmission for measurements the purpose of information for the purpose of assisting model the purpose of assisting model monitoring assisting model monitoring. monitoring Case 2b TRP based UL none measurements Case 2b UE based DL none LMF Request and none legacy UE reporting of measurement NLOS+distance information for the purpose of assisting model monitoring Case 3a TRP based UL None none none measurements New procedure could be introduced between CU and DU Case 3a UE based DL gNB Request and LMF Request and none legacy LMF forwarding UE reporting of measurement of NLOS+distance NLOS+distance information for information for the purpose of the purpose of assisting model assisting model monitoring monitoring Case 3b TRP based UL LMF Request and none none measurements TRP reporting of P110692WO01 (017997.4111) PATENT APPLICATION NLOS+distance information for the purpose of assisting model monitoring Case 3b UE based DL none LMF Request and none legacy UE reporting of measurement NLOS+distance information for the purpose of assisting model monitoring Downlink measurements based on classical positioning (i.e., non-AI ML) may be used by the UE for model monitoring in case 1 and 2a. This does not require additional signaling and may be done by UE implementation, because both the measured signals for monitoring as well as the model being monitored reside in the same node. Thus the following new signaling are proposed to be introduced for various particular embodiments: 1. Between LMF and UE (LPP signaling)o UE Request and LMF forwarding of NLOS+distance information for thepurpose of assisting model monitoring oLMF Request and UE reporting of NLOS+distance information for thepurpose of assisting model monitoring 2. Between LMF and gNB / TRP (NRPPa signaling)o gNB Request via new NRPPa procedure for AI / ML positioning assistancedata and LMF forwarding of NLOS+distance information for the purpose of assisting model monitoring ^For split gNB architecture, the request of NLOS+distanceinformation is priorly sent from the gNB-DU to the gNB-CU, over F1AP via a new F1 procedure for AI / ML assistance data provisioning. oLMF Request and TRP reporting of NLOS+distance information for thepurpose of assisting model monitoring ^LMF sends a new message over NRPPa for AI / ML assistance dataprovisioning, enquiring gNB of LOS Distance; P110692WO01 (017997.4111) PATENT APPLICATION ^For split gNB architecture, the measurement request ofNLOS+distance information is subsequently sent from the gNB- CU to the gNB-DU, over F1AP via a new procedure for AI / ML assistance data provisioning. Such messages are integrated in the positioning framework, and can be of a one-shot, or periodic nature. FIGURE 2 illustrates example signaling 100 for UE-assisted / LMF-based positioning with UE-side model, AI / ML assisted positioning, according to certain embodiments. More specifically, the illustrated embodiment corresponds to Case 2a in Table 2 and shows example signalling between UE 102 and LMF 104. At step 106, the UE 102 provides its AI / ML capability where the capability may indicate the UE 102 is able to infer which measurements, such as time of arrival, UE Rx-Tx, RSTD, etc. As shown, the UE 102 may optionally also provide the model ID the UE 102 is using. The LMF 104 may understand from the model ID what are the characteristics of the model (e.g., which input parameters are taken by the model and which output parameters are produced and for which area the model is valid). Additionally or alternatively, the LMF 104 may be fed by OAM node with the details regarding different model ID. Model characteristics may include inference capability (input / output parameters) and area. However, the UE 102 may also explicitly request the parameters that it needs to validate the model it is using. At step 108, the LMF 104 determines the model validation parameter. At step 110, the LMF 104 provides the model validation parameter to the UE 102 via assistance data. FIGURE 3 illustrates example signaling 200 enabling an LMF 204 to generate the model validation parameters by configuring the TRPs to perform the procedure, according to certain embodiments. The LMF 204 may generate the assistance data with the assistance from gNB 206. For example, in the illustrated embodiment, the LMF 204 requests the gNB 206 to perform measurement for AI / ML model validation, at step 208. At step 210, the gNB 206 configures the Sounding Reference Signal (SRS). At step 212, the UE 202 transmit SRS. At step 214, multiple gNB / TRPs 206 perform the measurement and from the path report (multipath) deduce the probability of LOS / NLOS detection and distance. For example, in P110692WO01 (017997.4111) PATENT APPLICATION particular embodiments, TRPs in DU provide the information to gNB-Centralized Unit (gNB-CU) over F1 interface. At step 216, the gNB 206 reports LOS / NLOS detection and distance to the LMF 204. For example, in a particular embodiment, the gNB-CU provides the measurement report to LMF 204 over NRPPa. At step 218, LMF 204 provides assistance data to the UE 202 via LPP signaling for model validation. Below is an example of LPP signaling for requesting AI / ML validation parameter by a UE. Specifically, in a particular embodiment, the RequestAssistanceData message body in a LPP message is used by the target device to request assistance data from the location server. -- ASN1START RequestAssistanceData ::= SEQUENCE { criticalExtensions CHOICE { c1 CHOICE { requestAssistanceData-r9 RequestAssistanceData-r9-IEs, spare3 NULL, spare2 NULL, spare1 NULL }, criticalExtensionsFuture SEQUENCE {} } } RequestAssistanceData-r9-IEs ::= SEQUENCE { commonIEsRequestAssistanceData CommonIEsRequestAssistanceData OPTIONAL, a-gnss-RequestAssistanceData A-GNSS-RequestAssistanceData OPTIONAL, otdoa-RequestAssistanceData OTDOA-RequestAssistanceData OPTIONAL, epdu-RequestAssistanceData EPDU-Sequence OPTIONAL, ..., [[ sensor-RequestAssistanceData-r14 Sensor-RequestAssistanceData-r14 OPTIONAL, tbs-RequestAssistanceData-r14TBS-RequestAssistanceData-r14 OPTIONAL, wlan-RequestAssistanceData-r14 WLAN-RequestAssistanceData- r14 OPTIONAL ]], [[ nr-Multi-RTT-RequestAssistanceData-r16 NR-Multi-RTT- RequestAssistanceData-r16 OPTIONAL, P110692WO01 (017997.4111) PATENT APPLICATION nr-DL-AoD-RequestAssistanceData-r16 NR-DL-AoD- RequestAssistanceData-r16 OPTIONAL, nr-DL-TDOA-RequestAssistanceData-r16 NR-DL-TDOA- RequestAssistanceData-r16 OPTIONAL ]], [[ bt-RequestAssistanceData-r18 BT- RequestAssistanceData-r18 OPTIONAL ]], [[ aiml-ModelValidationRequestAssistanceData-r19AIML- ModelValidationRequestAssistanceData-r19 ]] } -- ASN1STOP AIML-ModelValidationRequestAssistanceData-r19 ::= SEQUENCE { modelID-r19 INTEGER (1..100) areaID-r19 INTEGER(1..256) -- where each area is a cell or group of cells modelInferenceParameters-r19 SEQUENCE { xInput-r19 ENUMERATED {cir, pdp, dp} yOutput-r19 ENUMERATED {LOS, NLOS, RSTD,RSRPP, TOA, AoD,UERx-Tx} } requestedParameters ENUMERATED {los, nlos, distance} In a particular embodiment, the ProvideAssistanceData message body in a LPP message is used by the location server to provide assistance data to the target device either in response to a request from the target device or in an unsolicited manner. -- ASN1START ProvideAssistanceData ::= SEQUENCE { criticalExtensions CHOICE { c1 CHOICE { provideAssistanceData-r9 ProvideAssistanceData-r9-IEs, spare3 NULL, spare2 NULL, spare1 NULL }, criticalExtensionsFuture SEQUENCE {} } } ProvideAssistanceData-r9-IEs ::= SEQUENCE { commonIEsProvideAssistanceData CommonIEsProvideAssistanceData OPTIONAL, -- Need ON P110692WO01 (017997.4111) PATENT APPLICATION a-gnss-ProvideAssistanceData A-GNSS-ProvideAssistanceData OPTIONAL, -- Need ON otdoa-ProvideAssistanceData OTDOA-ProvideAssistanceData OPTIONAL, -- Need ON epdu-Provide-Assistance-Data EPDU-Sequence OPTIONAL, -- Need ON ..., [[ sensor-ProvideAssistanceData-r14 Sensor- ProvideAssistanceData-r14 OPTIONAL, -- Need ON tbs-ProvideAssistanceData-r14 TBS-ProvideAssistanceData-r14 OPTIONAL, -- Need ON wlan-ProvideAssistanceData-r14 WLAN-ProvideAssistanceData- r14 OPTIONAL -- Need ON ]], [[ nr-Multi-RTT-ProvideAssistanceData-r16 NR-Multi-RTT-ProvideAssistanceData-r16 OPTIONAL, -- Need ON nr-DL-AoD-ProvideAssistanceData-r16 NR-DL-AoD-ProvideAssistanceData-r16 OPTIONAL, -- Need ON nr-DL-TDOA-ProvideAssistanceData-r16 NR-DL-TDOA-ProvideAssistanceData-r16 OPTIONAL -- Need ON ]], [[ bt-ProvideAssistanceData-r18 BT-ProvideAssistanceData-r18 OPTIONAL -- Need ON ]], [[ aiml-ModelValidationProvideAssistanceData-r19 AIML- ModelValidationRequestAssistanceData-r19 ]] } -- ASN1STOP AIML-ModelValidationrovideAssistanceData-r19 ::= SEQUENCE { trpMeasurementList SEQUENCE { SIZE (1..10} OF TRPMeasurements } TRPMeasurements ::= SEQUENCE trpID INTEGER (1..65536) los BOOLEAB distance INTEGER (1..5000) distanceUnit ENUMERATED {cm, dcm, m} } P110692WO01 (017997.4111) PATENT APPLICATION Certain embodiments include LMF-gNB embodiments. FIGURE 4 is a signalling diagram 300 illustrating the steps taken by the gNB 306 (e.g., TRP) to request AI / ML assistance information from the LMF 304 to get LOS+distance measurements based on DL measurements from the UE 302, according to certain embodiments. Thus, the gNB 304 requests LOS, Distance from LMF, and the LMF 304 generates the assistance data with the assistance from UE 302. The signalling begins with an optional step 308 with the introduction of a new NRPPa procedure, whereby the LMF 304 requests gNB 306 if any assistance information is needed for model validation. Upon receiving this new message, the gNB 306 sends to LMF 304 a request for assistance data for AI / ML model validation. Alternatively, in a particular embodiment, step 308 may be omitted and gNB 306 may send, at step 310, a request over NRPPa to LMF 304 via a new procedure for requesting of NLOS+distance information for the purpose of assisting model monitoring. Upon receiving the request from gNB 306, LMF 304 requests the UE 302 to report of NLOS+distance information and provide this information to gNB 306, at step 312. For example, the LMF 304 may configure DL PRS and transmit a request for LOS, Distance info At step 314, UE 302 performs measurements. The UE 302 sends DL PRS measurement reports with LOS, Distance information, at step 316. At step 318, LMF 304 sends, via NRRPa, an AI / ML assistance data message with LOS and distance information. The gNB 306 uses this information when performing AI / ML positioning measurements prediction. The above steps may be implemented when the model is located in the gNB-CU. However, when the model is at gNB-DU, further signaling is sent from gNB-DU to gNB-CU to request, from LMF, the LOS,Distance information. In another particular embodiment, the gNB 306 may also request the LMF 304 to provide the additional assistance information either in a one-shot, semi-persistent, or periodic manner. For semi-persistent or periodic reporting, the gNB 306 also includes the time interval (periodicity) or the assistance information update rate in the request. In another particular embodiment, the LMF 304 provides the gNB 306 with additional assistance information as part of the main assistance information provided to the gNB 306 for positioning purpose. P110692WO01 (017997.4111) PATENT APPLICATION In another particular embodiment, the LMF 304 may provide the gNB 306 with the additional assistance information separately from the main positioning assistance data. Table 3 below is an example of NRPPa signaling where gNB 306 requests LMF 304 for LOS, distance information AI / ML validation parameters with new NRPPa message. For split F1, equivalent positioning procedures are also impacted. The AI / ML Positioning Assistance Data request message is sent by the NG-RAN node to request AI / ML assistance data. The direction of the signalling is from NG-RAN node 306 to LMF 304. Table 3 IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality Message Type M 9.2.3 YES reject NRPPa Transaction ID M 9.2.4 - AI ML model validaiton O ENUMERATED YES ignore request info (los, nlos, distance, …) periodicity O ENUMERATED (1…N) Report type O ENUMERATED (one-shot, periodic, semi- persistent, …) Table 4 provides example content of the AI / ML Positioning Assistance Data response message sent by the LMF 304 to provide NG-RAN 306 with AI / ML positioning information data. The direction of the signalling is LMF 304 to NG-RAN node 306. Table 4 IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality Message Type M 9.2.3 YES reject NRPPa Transaction ID M 9.2.4 - AI ML model validation1 YES rejectassistance info List > AI ML model 1..<maxno EACH reject validation assistance ofMeasTR P110692WO01 (017997.4111) PATENT APPLICATION IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality info Item Ps> >>TRP ID M 9.2.24 - O YES ignore >los / nlos O ENUMERATED - (los, nlos,) >distance O INTEGER(0..50 - 00, …) >measurement unit O ENUMERATED - (mm, dm, cm, m, …) FIGURE 5 illustrates example signaling 400 of steps that may be taken by the LMF 404 to request a gNB 406 to report LOS, Distance information to LMF 404 for a UE 402, according to certain embodiments. In a first example embodiment, a specific procedure is used for the LMF 404 to request a gNB 406 (e.g., TRP) to report the LOS+distance information for a given UE 402. At step 408, the LMF 402 requests the gNB 406 to provide the LOS / distance information for a set of measurements for the purpose of model validation. At step 410, the gNB 406 configures the SRS for the UE 402. At step 412, the gNB 406 sends a positioning information response to LMF 404. At step 414, the LMF 404 sends a measurement request with LOS, Distance request indicator to gNB 406. At step 416, the gNB 406 performs measurements. At step 418, the gNB 406 sends a measurement response with AI / ML predicted measurements with LOS and Distance information to LMF 404. In a first particular embodiment, separate NRPPa procedures (e.g., class 1 procedure with request and response messages) is defined to be used by the LMF to request a LOS / distance information from the gNB for the purpose of model validation at step 408 and for the reporting from the gNB 406 to LMF 404 at step 418. The new message transmitted from LMF 404 at step 408 indicates to the gNB 406 that the LMF 404 requests LOS / distance information for a set of positioning measurements for the purpose of model validation and tasking the gNB 406 to respond with the requested information. The response message transmitted from the gNB 406 at 418 includes the LOS-distance indication configured to the reported positioning measurements. P110692WO01 (017997.4111) PATENT APPLICATION In a second particular embodiment, the procedure for UL positioning is reused, and extended to include a report including LOS coupled to distance information between a TRP and a gNB. In a related embodiment, the requested LOS / distance information for model validation may be requested as part of the existing NRPPa MEASUREMENT REQUEST message, as new bit via the NRPPa Measurement Characteristics Request Indicator IE. In a related embodiment, the LOS / distance information of the requested measurements are reported by the gNB as part of an existing positioning Measurement procedure: e.g., in the MEASUREMENT RESPONSE and MEASUREMENT REPORT messages, as shown in 418. The existing Measurement messages from the gNB 406 to LMF 404 are extended to contain at least but not limited to a report of a line of sight / distance estimate attached to the reference signal the measurement report is based on. The reference signal may be, for example, a SRS for positioning resource the UE 402 has been configured to transmit. In positioning, LMF requests for measurement are typically attached to measurement quality requirements, which in turn map to an accuracy target in the positioning method. For LMF requests and TRP reports of measurements only for model monitoring / validation, such requirements may not be applicable, because the purpose is to enable comparing a model output with another source of distance estimation, for example, UL SRS based UL positioning, but it is not to position the target. Therefore, either no requirements or a specific requirement for the quality of the LOS+distance report, different from the measurement requirement for the purpose of deriving the UE location, may be introduced. In a particular embodiment, the measurement report containing the LOS / distance information is not attached to legacy positioning accuracy performance requirements. In a particular embodiment, the measurement report may be attached to specific condition for reporting, such as confidence in the line of sight indication, in form of a confidence threshold, under which the gNB may either be tasked to respond with no transmission of the measurement report until the confidence threshold is exceeded, or task to report measurement failure if the threshold is not met. Example of implementation of the embodiments described above are shown below.: <<START OF ST 38.455 v18.0.0 SPEC implementation>> 9.1.4.1 MEASUREMENT REQUEST This message is sent by the LMF to request the NG-RAN node to configure a positioning measurement. P110692WO01 (017997.4111) PATENT APPLICATION Direction: LMF ^ NG-RAN node. IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality Message Type M 9.2.3 YES reject NRPPa Transaction ID M 9.2.4 - LMF Measurement ID M INTEGER YES reject (1..65536, …) TRP Measurement1 YES rejectRequest List >TRP Measurement 1..<maxno EACH reject Request Item ofMeasTR Ps> >>TRP ID M 9.2.24 - >>Search Window O 9.2.26 - Information >>Cell ID O NR CGI The Cell ID of the YES ignore 9.2.9 TRP identified by the TRP ID IE. >>AoA Search O UL-AoA YES ignore Window Information Assistance Information 9.2.66 >>Number of TRP O ENUMERATED YES ignore Rx TEGs (2, 3, 4, 6, 8, …) >>Number of TRP O ENUMERATED YES ignore RxTx TEGs (2, 3, 4, 6, 8, …) Report Characteristics M ENUMERATED YES reject (OnDemand, Periodic, ...) Measurement C- ENUMERATED The codepoint YES reject Periodicity ifReportCh (120ms, 240ms, 120ms, 240ms, aracteristi 480ms, 640ms, 480ms, 1024ms, csPeriodic 1024ms, 2048ms, 1min, 2048ms, 6min, 12min, 5120ms, 30min, and 60min 10240ms, 1min, are not applicable 6min, 12min, 30min, 60min,…, 20480ms, 40960ms, P110692WO01 (017997.4111) PATENT APPLICATION IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality extended) TRP Measurement 1 YES reject Quantities >TRP Measurement 1.. EACH reject Quantities Item <maxnoP osMeas> >>TRP M ENUMERATED - Measurement Type (gNB- RxTxTimeDiff, UL-SRS-RSRP, UL-AoA, UL- RTOA,…, Multiple UL- AoA, UL SRS- RSRPP) >>Timing Reporting O INTEGER (0..5) Value (0..5) - Granularity Factor corresponds to (k0..k5) TS 38.133

[0016] SFN initialisation Time O Relative Time If this IE is not YES ignore 1900 present, the TRP 9.2.36 may assume that the value is same as its own SFN initialisation time. SRS Configuration O 9.2.28 YES ignore Measurement Beam O ENUMERATED This IE is ignored YES ignore Information Request (true,...) when the Measurement Characteristics Request Indicator IE is included. System Frame Number O INTEGER(0..10 YES ignore 23) Slot Number O INTEGER(0..79 YES ignore ) Measurement C- ENUMERATED YES reject Periodicity Extended ifMeasPer (160ms, 320ms, Ext 1280ms, 2560ms, 61440ms, 81920ms, P110692WO01 (017997.4111) PATENT APPLICATION IE / Group Name Presence Range IE type and Semantics Criticality Assigned reference description Criticality 368640ms, 737280ms, 1843200ms, …) Response Time O 9.2.68 This IE is ignored YES ignore when the Report Characteristics IE is set to “periodic”. Measurement O 9.2.81 YES ignore Characteristics Request Indicator Measurement Time O ENUMERATED YES ignore Occasion (o1, o4, …) Measurement Amount O ENUMERATED This IE is ignored YES ignore (0, 1, 2, 4, 8, if the Report 16, 32, 64) Characteristics IE is set to ‘OnDemand’. Value 0 represents an infinite number of periodic reporting. Condition Explanation ifReportCharacteristicsPeriodic This IE shall be present if the Report Characteristics IE is set to the value "Periodic". ifMeasPerExt This IE shall be present if the Measurement Periodicity IE is set to the value "extended". Range bound Explanation maxnoPosMeas Maximum no. of measured quantities that can be configured and reported with one positioning measurement message. Value is 16384. maxnoofMeasTRPs Maximum no. of TRPs that can be included within one message. Value is 64. 9.2.81 Measurement Characteristics Request Indicator This IE contains the measurement characteristic information requested by LMF. P110692WO01 (017997.4111) PATENT APPLICATION IE / Group Name Presence Range IE Type and Semantics Description Reference Measurement M BIT STRING Each position in the bitmap characteristic request (SIZE(16)) represents a requested indicator measurement characteristic: first bit: Measurement Beam Information Second bit: Extended Additional Path List Third bit: Additional Path Power Fourth Bit: Multiple UL AoA of Additional Path Fifth bit: LoS / NLoS Information Sixth bit: TRP Rx TEG association for UL-TDOA Seventh bit: TRP RxTxTEG-ID information for DL+UL positioning. Eighth bit: SRS Resource Type Ninth bit: Multiple Measurement Instances Tenth bit: Mobile TRP location information Eleventh bit: LOS distance information Other bits reserved for future use. Value ‘1’ indicates ‘requested measurement characteristic’, Value ‘0’ indicates ‘not requested’. 9.2.37 TRP Measurement Result P110692WO01 (017997.4111) PATENT APPLICATION This information element contains the measurement result. IE / Group Name Presence Range IE Type and Semantics Criticality Assigned Reference Description Criticality Measured Result Item 1.. - <maxnoP osMeas> >CHOICE Measured M - Results Value >>UL Angle of 9.2.38 Arrival >>UL SRS-RSRP INTEGER (0..126) >>UL RTOA 9.2.39 >>gNB Rx-Tx Time 9.2.40 Difference >>Z-AoA 9.2.67 YES reject >>Multiple UL-AoA 9.2.71 YES reject >>UL SRS-RSRPP 9.2.72 YES reject >Time Stamp M 9.2.42 - >Measurement O 9.2.43 - Quality >Measurement Beam O 9.2.57 - Information >SRS Resource type O 9.2.73 YES ignore >ARP ID O 9.2.75 YES ignore >LoS / NLoS O 9.2.77 YES ignore Information >Mobile TRP Location O 9.2.88 YES ignore Information >LOS distance O 9.2.X YES ignore Information Range bound Explanation maxnoPosMeas Maximum no. of measured quantities that can be configured and reported with one positioning measurement message. Value is 16384. 9.2.X LOS distance This information element contains the LOS distance information. IE / Group Name Presence Range IE Type and Semantics Description Reference P110692WO01 (017997.4111) PATENT APPLICATION Measurement M ENUMERATED(mm , dm, cm, m, …) distance M INTEGER(0..5000, …) LOS M ENUMERATED(los, NLOS) <<END OF ST 38.455 v18.0.0 SPEC implementation>> According to certain embodiments, F1AP signaling is used between gNB-CU and gNB- DU. Two examples include introduction of LOS coupled with distance information in existing F1 positioning measurement report for the purpose to support model validation and introduction of a new LOS / distance in existing F1 positioning measurement report explicitly for the purpose of model validation. According to certain embodiments, the gNB-CU requests the gNB-DU to provide the LOS / distance information for a set of TRP measurements for the purpose of model validation. In a particular embodiment, the requested LOS / distance information for model validation may be requested as part of the existing F1 POSITIONING MEASUREMENT REQUEST message, as new bit via the F1AP Measurement Characteristics Request Indicator IE. In a particular embodiment, the LOS / distance information of the requested measurements are reported by the gNB-DU as part of an existing positioning Measurement procedure such as, for example, in the F1AP POSITIONING MEASUREMENT RESPONSE and F1AP POSITIONING MEASUREMENT REPORT messages. In a particular embodiment, the existing Positioning Measurement messages from the gNB- DU to gNB-CU are extended to contain at least, but not limited to, a report of a line of sight / distance estimate attached to the reference signal the measurement report is based on. In a particular embodiment, the reference signal may be, for example, an SRS for positioning resource the UE has been configured to transmit. In a particular embodiment, separate F1AP procedures (e.g., class 1 procedure with request and response messages) is defined to be used by the gNB-CU to request a LOS / distance information from the gNB-DU for the purpose of model validation and for the reporting from the gNB-DU to gNB-CU. In a particular embodiment, the new message from gNB-CU indicates to the gNB-DU that it requests LOS / distance information for a set of positioning measurements for the purpose of model validation and tasking the gNB-DU to respond with the requested information. P110692WO01 (017997.4111) PATENT APPLICATION In a particular embodiment, the response message from the gNB-DU includes the LOS- distance indication configured to the reported positioning measurements. According to certain embodiments, the F1AP measurement report containing the LOS / distance information is not attached to legacy positioning accuracy performance requirements. The F1AP measurement report may be attached to specific condition for reporting, such as confidence in the line of sight indication, in form of a confidence threshold, under which the gNB-DU may either be tasked to respond with no transmission of the measurement report until the confidence threshold is exceeded, or task to report F1AP measurement failure if the threshold is not met. In one non-limiting example embodiment, the specification impacts to F1AP may mimic the ones for NRPPa messages (i.e., impacts to Measurement Characteristics Request Indicator and Positioning Measurement Result IE in TS 38.473), as described above. FIGURE 6 illustrates an example method 500 by a first radio node for performing positioning, according to certain embodiments. In the illustrated embodiment, the method begins at step 502 when the radio node receives, from a second radio node, assistance information for validating an AI / ML model at a wireless device. In a particular embodiment, the assistance information is at least one of: LOS information, and / or distance information. In a particular embodiment, the first radio node transmits, to the second radio node, a request for the assistance information for validating the AI / ML model for the wireless device. In a further particular embodiment, the request for assistance information indicates a request for at least one of: LOS information and / or distance information. In a particular embodiment, the request indicates that the assistance information is to be provided as: a one-shot report; a semi-persistent reporting; a periodic reporting according to an update rate. In a particular embodiment, the first radio node transmits, to the second radio node, at least one of: an AI / ML capability, at least one measurement that the radio node is able to infer, an AI / ML identifier, at least one input parameter taken by the AI / ML model, at least one output parameter provided by the AI / ML model, an area for which the AI / ML model is valid, and at least one validation parameter to be used for validating the AI / ML model at the wireless device. In a particular embodiment, the first radio node is the wireless device, and the second radio node is a gNB or an LMF. In a particular embodiment, the first radio node is a gNB or a base station, and the second P110692WO01 (017997.4111) PATENT APPLICATION radio node is an LMF. In a particular embodiment, the gNB or base station receives signaling from the LMF enquiring whether the assistance information is needed. In a particular embodiment, the request for the assistance information is received from the LMF over NRPPA. In a particular embodiment, the first radio node validates the accuracy of the AI / ML model. In a further particular embodiment, validating the accuracy of the AI / ML model includes performing model monitoring. In a particular embodiment, the first radio node is an LMF, and the second radio node is gNB or a base station. In a further particular embodiment, the gNB or base station receives signaling from the LMF enquiring whether the assistance information is needed. In a particular embodiment, the request for the assistance information is received from the LMF over NRPPA. In a particular embodiment, the first radio node uses the assistance information to perform AI / ML positioning measurement prediction. FIGURE 7 illustrates an example method 600 by a second radio node for providing assistance information for positioning, according to certain embodiments. In the illustrated embodiment, the method begins at step 602 when the second radio node receives a request from a first radio node to provide assistance information for validating an AI / ML model at a wireless device. At step 604, the second radio node transmits, to the first radio node, the assistance information for validating the AI / ML model at the wireless device. In a particular embodiment, the assistance information is at least one of: LOS information and / or distance information. In a particular embodiment, the second radio node receives, from the first radio node, a request for the assistance information for validating the AI / ML model for the wireless device. In a particular embodiment, the request for assistance information indicates a request for at least one of: LOS information and / or distance information. In a particular embodiment, the request indicates that the assistance information is to be provided as: a one-shot report; a semi-persistent reporting; a periodic reporting according to an update rate. In a particular embodiment, the second radio node receives, from the first radio node, at least one of: an AI / ML capability, at least one measurement that the radio node is able to infer, an P110692WO01 (017997.4111) PATENT APPLICATION AI / ML identifier, at least one input parameter taken by the AI / ML model, at least one output parameter provided by the AI / ML model, an area for which the AI / ML model is valid, and at least one validation parameter to be used for validating the AI / ML model at the wireless device. In a particular embodiment, the first radio node is the wireless device, and the second radio node is a gNB or an LMF. In a particular embodiment, the first radio node is a gNB or a base station, and the second radio node is an LMF. In a further particular embodiment, the gNB or base station receives signaling from the LMF enquiring whether the assistance information is needed. In a particular embodiment, the request for the assistance information is received from the LMF over NRPPA. In a particular embodiment, the second radio node validates the accuracy of the AI / ML model. In a further particular embodiment, validating the accuracy of the AI / ML model includes performing model monitoring. In a particular embodiment, the first radio node is an LMF, and the second radio node gNB or a base station. In a particular embodiment, the gNB or base station receives signaling from the LMF enquiring whether the assistance information is needed. In a particular embodiment, the request for the assistance information is received from the LMF over NRPPA. FIGURE 8 shows an example of a communication system 700 in accordance with some embodiments. In the example, the communication system 700 includes a telecommunication network 702 that includes an access network 704, such as a radio access network (RAN), and a core network 706, which includes one or more core network nodes 708. The access network 704 includes one or more access network nodes, such as network nodes 710a and 710b (one or more of which may be generally referred to as network nodes 710), or any other similar 3rd Generation Partnership Project (3GPP) access node or non-3GPP access point. The network nodes 710 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 712a, 712b, 712c, and 712d (one or more of which may be generally referred to as UEs 712) to the core network 706 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 P110692WO01 (017997.4111) PATENT APPLICATION types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 700 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 700 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system. The UEs 712 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 710 and other communication devices. Similarly, the network nodes 710 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 712 and / or with other network nodes or equipment in the telecommunication network 702 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network 702. In the depicted example, the core network 706 connects the network nodes 710 to one or more hosts, such as host 716. 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 706 includes one more core network nodes (e.g., core network node 708) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 708. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF). The host 716 may be under the ownership or control of a service provider other than an operator or provider of the access network 704 and / or the telecommunication network 702 and may be operated by the service provider or on behalf of the service provider. The host 716 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 P110692WO01 (017997.4111) PATENT APPLICATION functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server. As a whole, the communication system 700 of FIGURE 8 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox. In some examples, the telecommunication network 702 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 702 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 702. For example, the telecommunications network 702 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 IoT services to yet further UEs. In some examples, the UEs 712 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 704 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 704. 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). In the example, the hub 714 communicates with the access network 704 to facilitate indirect communication between one or more UEs (e.g., UE 712c and / or 712d) and network nodes (e.g., network node 710b). In some examples, the hub 714 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 714 may be a broadband router enabling access to the core network 706 for the P110692WO01 (017997.4111) PATENT APPLICATION UEs. As another example, the hub 714 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 710, or by executable code, script, process, or other instructions in the hub 714. As another example, the hub 714 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 714 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub 714 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 714 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 714 acts as a proxy server or orchestrator for the UEs, in particular in if one or more of the UEs are low energy IoT devices. The hub 714 may have a constant / persistent or intermittent connection to the network node 710b. The hub 714 may also allow for a different communication scheme and / or schedule between the hub 714 and UEs (e.g., UE 712c and / or 712d), and between the hub 714 and the core network 706. In other examples, the hub 714 is connected to the core network 706 and / or one or more UEs via a wired connection. Moreover, the hub 714 may be configured to connect to an M2M service provider over the access network 704 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 710 while still connected via the hub 714 via a wired or wireless connection. In some embodiments, the hub 714 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 710b. In other embodiments, the hub 714 may be a non- dedicated hub – that is, a device which is capable of operating to route communications between the UEs and network node 710b, but which is additionally capable of operating as a communication start and / or end point for certain data channels. FIGURE 9 shows a UE 800 in accordance with some embodiments. As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage 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-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd P110692WO01 (017997.4111) PATENT APPLICATION Generation Partnership Project (3GPP), including a narrow band internet of things (NB-IoT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE. A UE may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to-everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter). The UE 800 includes processing circuitry 802 that is operatively coupled via a bus 804 to an input / output interface 806, a power source 808, a memory 810, a communication interface 812, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in FIGURE 9. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc. The processing circuitry 802 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 810. The processing circuitry 802 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 802 may include multiple central processing units (CPUs). In the example, the input / output interface 806 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 800. 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 P110692WO01 (017997.4111) PATENT APPLICATION directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device. In some embodiments, the power source 808 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used. The power source 808 may further include power circuitry for delivering power from the power source 808 itself, and / or an external power source, to the various parts of the UE 800 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 808. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 808 to make the power suitable for the respective components of the UE 800 to which power is supplied. The memory 810 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 810 includes one or more application programs 814, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 816. The memory 810 may store, for use by the UE 800, any of a variety of various operating systems or combinations of operating systems. The memory 810 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 810 may P110692WO01 (017997.4111) PATENT APPLICATION allow the UE 800 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 810, which may be or comprise a device-readable storage medium. The processing circuitry 802 may be configured to communicate with an access network or other network using the communication interface 812. The communication interface 812 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 822. The communication interface 812 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter 818 and / or a receiver 820 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 818 and receiver 820 may be coupled to one or more antennas (e.g., antenna 822) and may share circuit components, software or firmware, or alternatively be implemented separately. In the illustrated embodiment, communication functions of the communication interface 812 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division 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. Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 812, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected, an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient). P110692WO01 (017997.4111) PATENT APPLICATION As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input. A UE, when in the form of an Internet of Things (IoT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Non-limiting examples of such an IoT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or Virtual Reality (VR), a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item- tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an IoT device comprises circuitry and / or software in dependence of the intended application of the IoT device in addition to other components as described in relation to the UE 800 shown in FIGURE 9. As yet another specific example, in an IoT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements and transmits the results of such monitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation. In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. P110692WO01 (017997.4111) PATENT APPLICATION When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators. FIGURE 10 shows a network node 900 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)). Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units 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). Other examples of network nodes include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs). The network node 900 includes a processing circuitry 902, a memory 904, a communication interface 906, and a power source 908. The network node 900 may be composed of multiple physically separate components (e.g., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 900 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be P110692WO01 (017997.4111) PATENT APPLICATION 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 900 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 904 for different RATs) and some components may be reused (e.g., a same antenna 910 may be shared by different RATs). The network node 900 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 900, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 900. The processing circuitry 902 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other network node 900 components, such as the memory 904, to provide network node 900 functionality. In some embodiments, the processing circuitry 902 includes a system on a chip (SOC). In some embodiments, the processing circuitry 902 includes one or more of radio frequency (RF) transceiver circuitry 912 and baseband processing circuitry 914. In some embodiments, the radio frequency (RF) transceiver circuitry 912 and the baseband processing circuitry 914 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 912 and baseband processing circuitry 914 may be on the same chip or set of chips, boards, or units. The memory 904 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 902. The memory 904 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 P110692WO01 (017997.4111) PATENT APPLICATION instructions capable of being executed by the processing circuitry 902 and utilized by the network node 900. The memory 904 may be used to store any calculations made by the processing circuitry 902 and / or any data received via the communication interface 906. In some embodiments, the processing circuitry 902 and memory 904 is integrated. The communication interface 906 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface 906 comprises port(s) / terminal(s) 916 to send and receive data, for example to and from a network over a wired connection. The communication interface 906 also includes radio front- end circuitry 918 that may be coupled to, or in certain embodiments a part of, the antenna 910. Radio front-end circuitry 918 comprises filters 920 and amplifiers 922. The radio front-end circuitry 918 may be connected to an antenna 910 and processing circuitry 902. The radio front- end circuitry may be configured to condition signals communicated between antenna 910 and processing circuitry 902. The radio front-end circuitry 918 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 918 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 920 and / or amplifiers 922. The radio signal may then be transmitted via the antenna 910. Similarly, when receiving data, the antenna 910 may collect radio signals which are then converted into digital data by the radio front-end circuitry 918. The digital data may be passed to the processing circuitry 902. In other embodiments, the communication interface may comprise different components and / or different combinations of components. In certain alternative embodiments, the network node 900 does not include separate radio front-end circuitry 918, instead, the processing circuitry 902 includes radio front-end circuitry and is connected to the antenna 910. Similarly, in some embodiments, all or some of the RF transceiver circuitry 912 is part of the communication interface 906. In still other embodiments, the communication interface 906 includes one or more ports or terminals 916, the radio front-end circuitry 918, and the RF transceiver circuitry 912, as part of a radio unit (not shown), and the communication interface 906 communicates with the baseband processing circuitry 914, which is part of a digital unit (not shown). The antenna 910 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 910 may be coupled to the radio front-end circuitry 918 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 910 is separate from the network node 900 and connectable to the network node 900 through an interface or port. P110692WO01 (017997.4111) PATENT APPLICATION The antenna 910, communication interface 906, and / or the processing circuitry 902 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 910, the communication interface 906, and / or the processing circuitry 902 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment. The power source 908 provides power to the various components of network node 900 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 908 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 900 with power for performing the functionality described herein. For example, the network node 900 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 908. As a further example, the power source 908 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail. Embodiments of the network node 900 may include additional components beyond those shown in FIGURE 10 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 900 may include user interface equipment to allow input of information into the network node 900 and to allow output of information from the network node 900. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 900. FIGURE 11 is a block diagram illustrating a virtualization environment 1000 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 P110692WO01 (017997.4111) PATENT APPLICATION components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 1000 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. Applications 1002 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein. Hardware 1004 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 1006 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 1008a and 1008b (one or more of which may be generally referred to as VMs 1008), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 1006 may present a virtual operating platform that appears like networking hardware to the VMs 1008. The VMs 1008 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 1006. Different embodiments of the instance of a virtual appliance 1002 may be implemented on one or more of VMs 1008, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment. In the context of NFV, a VM 1008 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 1008, and that part of hardware 1004 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 1008 on top of the hardware 1004 and corresponds to the application 1002. P110692WO01 (017997.4111) PATENT APPLICATION Hardware 1004 may be implemented in a standalone network node with generic or specific components. Hardware 1004 may implement some functions via virtualization. Alternatively, hardware 1004 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 1010, which, among others, oversees lifecycle management of applications 1002. In some embodiments, hardware 1004 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 1012 which may alternatively be used for communication between hardware nodes and radio units. Although the computing devices described herein (e.g., UEs, network nodes, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware. In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments P110692WO01 (017997.4111) PATENT APPLICATION 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 functionalities 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. EXAMPLE EMBODIMENTS Group A Example Embodiments Example Embodiment 1. A method performed by a wireless device for performing positioning, the method comprising: transmitting a request to a network node for assistance information for validating AI / ML based positioning for the wireless device; receiving the assistance information from the network node; and validating an accuracy of the AI / ML based positioning based on the assistance information. Example Embodiment 2. The method of the previous embodiment, wherein the network node comprises a location management function (LMF) or a base station. Example Embodiment 3. The method of any one of the previous embodiments, the method further comprising transmitting AI / ML capability information to the network node. Example Embodiment 4. The method of any one of the previous embodiments, wherein the model monitoring node comprises an LMF or a base station. Example Embodiment 5. A method performed by a wireless device, the method comprising: any of the wireless device steps, features, or functions described above, either alone or in combination with other steps, features, or functions described above. Example Embodiment 6. The method of the previous embodiment, further comprising one or more additional wireless device steps, features or functions described above. Example Embodiment 7. The method of any of the previous two embodiments, further comprising: providing user data; and forwarding the user data to a host computer via the transmission to the base station. Group B Embodiments P110692WO01 (017997.4111) PATENT APPLICATION Example Embodiment 8. A method performed by a base station for providing positioning assistance information, the method comprising: receiving a request from a network node to provide positioning assistance information; performing positioning measurements with a wireless device; and transmitting positioning assistance information to the network node based on the positioning measurements. Example Embodiment 9. The method of the previous embodiment, wherein the network node comprises a location management function (LMF). Example Embodiment 10. A method performed by a base station, the method comprising: any of the steps, features, or functions described above with respect to base stations, either alone or in combination with other steps, features, or functions described above. Example Embodiment 11. The method of the previous embodiment, further comprising one or more additional base station steps, features or functions described above. Example Embodiment 12. The method of any of the previous embodiments, further comprising: obtaining user data; and forwarding the user data to a host computer or a wireless device. Group C Embodiments Example Embodiment 13. A mobile terminal comprising: processing circuitry configured to perform any of the steps of any of the Group A embodiments; and power supply circuitry configured to supply power to the wireless device. Example Embodiment 14. A base station comprising: processing circuitry configured to perform any of the steps of any of the Group B embodiments; power supply circuitry configured to supply power to the wireless device. Example Embodiment 15. A user equipment (UE) comprising: an antenna configured to send and receive wireless signals; radio front-end circuitry connected to the antenna and to processing circuitry, and configured to condition signals communicated between the antenna and the processing circuitry; the processing circuitry being configured to perform any of the steps of any of the Group A embodiments; an input interface connected to the processing circuitry and configured to allow input of information into the UE to be processed by the processing circuitry; an output interface connected to the processing circuitry and configured to output information from the UE that has been processed by the processing circuitry; and a battery connected to the processing circuitry and configured to supply power to the UE. Example Embodiment 16. A communication system including a host computer P110692WO01 (017997.4111) PATENT APPLICATION comprising: processing circuitry configured to provide user data; and a communication interface configured to forward the user data to a cellular network for transmission to a user equipment (UE), wherein the cellular network comprises a base station having a radio interface and processing circuitry, the base station’s processing circuitry configured to perform any of the steps of any of the Group B embodiments. Example Embodiment 17. The communication system of the pervious embodiment further including the base station. Example Embodiment 18. The communication system of the previous 2 embodiments, further including the UE, wherein the UE is configured to communicate with the base station. Example Embodiment 19. The communication system of the previous 3 embodiments, wherein: the processing circuitry of the host computer is configured to execute a host application, thereby providing the user data; and the UE comprises processing circuitry configured to execute a client application associated with the host application. Example Embodiment 20. A method implemented in a communication system including a host computer, a base station and a user equipment (UE), the method comprising: at the host computer, providing user data; and at the host computer, initiating a transmission carrying the user data to the UE via a cellular network comprising the base station, wherein the base station performs any of the steps of any of the Group B embodiments. Example Embodiment 21. The method of the previous embodiment, further comprising, at the base station, transmitting the user data. Example Embodiment 22. The method of the previous 2 embodiments, wherein the user data is provided at the host computer by executing a host application, the method further comprising, at the UE, executing a client application associated with the host application. Example Embodiment 23. A user equipment (UE) configured to communicate with a base station, the UE comprising a radio interface and processing circuitry configured to performs any of the previous 3 embodiments. Example Embodiment 24. A communication system including a host computer comprising: processing circuitry configured to provide user data; and a communication interface configured to forward user data to a cellular network for transmission to a user equipment (UE), wherein the UE comprises a radio interface and processing circuitry, the UE’s components configured to perform any of the steps of any of the Group A embodiments. Example Embodiment 25. The communication system of the previous embodiment, wherein the cellular network further includes a base station configured to communicate with the P110692WO01 (017997.4111) PATENT APPLICATION UE. Example Embodiment 26. The communication system of the previous 2 embodiments, wherein: the processing circuitry of the host computer is configured to execute a host application, thereby providing the user data; and the UE’s processing circuitry is configured to execute a client application associated with the host application. Example Embodiment 27. A method implemented in a communication system including a host computer, a base station and a user equipment (UE), the method comprising: at the host computer, providing user data; and at the host computer, initiating a transmission carrying the user data to the UE via a cellular network comprising the base station, wherein the UE performs any of the steps of any of the Group A embodiments. Example Embodiment 28. The method of the previous embodiment, further comprising at the UE, receiving the user data from the base station. Example Embodiment 29. A communication system including a host computer comprising: communication interface configured to receive user data originating from a transmission from a user equipment (UE) to a base station, wherein the UE comprises a radio interface and processing circuitry, the UE’s processing circuitry configured to perform any of the steps of any of the Group A embodiments. Example Embodiment 30. The communication system of the previous embodiment, further including the UE. Example Embodiment 31. The communication system of the previous 2 embodiments, further including the base station, wherein the base station comprises a radio interface configured to communicate with the UE and a communication interface configured to forward to the host computer the user data carried by a transmission from the UE to the base station. Example Embodiment 32. The communication system of the previous 3 embodiments, wherein: the processing circuitry of the host computer is configured to execute a host application; and the UE’s processing circuitry is configured to execute a client application associated with the host application, thereby providing the user data. Example Embodiment 33. The communication system of the previous 4 embodiments, wherein: the processing circuitry of the host computer is configured to execute a host application, thereby providing request data; and the UE’s processing circuitry is configured to execute a client application associated with the host application, thereby providing the user data in response to the request data. Example Embodiment 34. A method implemented in a communication system including a P110692WO01 (017997.4111) PATENT APPLICATION host computer, a base station and a user equipment (UE), the method comprising: at the host computer, receiving user data transmitted to the base station from the UE, wherein the UE performs any of the steps of any of the Group A embodiments. Example Embodiment 35. The method of the previous embodiment, further comprising, at the UE, providing the user data to the base station. Example Embodiment 36. The method of the previous 2 embodiments, further comprising: at the UE, executing a client application, thereby providing the user data to be transmitted; and at the host computer, executing a host application associated with the client application. Example Embodiment 37. The method of the previous 3 embodiments, further comprising: at the UE, executing a client application; and at the UE, receiving input data to the client application, the input data being provided at the host computer by executing a host application associated with the client application, wherein the user data to be transmitted is provided by the client application in response to the input data. Example Embodiment 38. A communication system including a host computer comprising a communication interface configured to receive user data originating from a transmission from a user equipment (UE) to a base station, wherein the base station comprises a radio interface and processing circuitry, the base station’s processing circuitry configured to perform any of the steps of any of the Group B embodiments. Example Embodiment 39. The communication system of the previous embodiment further including the base station. Example Embodiment 40. The communication system of the previous 2 embodiments, further including the UE, wherein the UE is configured to communicate with the base station. Example Embodiment 41. The communication system of the previous 3 embodiments, wherein: the processing circuitry of the host computer is configured to execute a host application; the UE is configured to execute a client application associated with the host application, thereby providing the user data to be received by the host computer. Example Embodiment 42. A method implemented in a communication system including a host computer, a base station and a user equipment (UE), the method comprising: at the host computer, receiving, from the base station, user data originating from a transmission which the base station has received from the UE, wherein the UE performs any of the steps of any of the Group A embodiments. Example Embodiment 43. The method of the previous embodiment, further comprising at the base station, receiving the user data from the UE. P110692WO01 (017997.4111) PATENT APPLICATION Example Embodiment 44. The method of the previous 2 embodiments, further comprising at the base station, initiating a transmission of the received user data to the host computer.

Claims

P110692WO01 (017997.4111) PATENT APPLICATION CLAIMS1. A method (500) performed by a first radio node (102, 206, 202, 306, 302, 406, 402) forperforming positioning, the method comprising: receiving (502), from a second radio node (104, 204, 304, 404), assistance information for validating an Artificial Intelligence / Machine Learning, AI / ML, model at a wireless device.

2. The method of Claim 1, wherein the assistance information is at least one of:Line-of-Sight, LOS, information, and / or distance information.

3. The method of any one of Claims 1 to 2, comprising transmitting, to the second radio node,a request for the assistance information for validating the AI / ML model for the wireless device.

4. The method of Claim 3, wherein the request for assistance information indicates a requestfor at least one of: Line-of-Sight, LOS, information, and / or distance information.

5. The method of any one of Claims 3 to 4, wherein the request indicates that the assistanceinformation is to be provided as: a one-shot report; a semi-persistent reporting; a periodic reporting according to an update rate.

6. The method of any one of Claims 1 to 5, comprising transmitting, to the second radio node,at least one of: an AI / ML capability, at least one measurement that the radio node is able to infer, an AI / ML identifier, at least one input parameter taken by the AI / ML model, at least one output parameter provided by the AI / ML model, an area for which the AI / ML model is valid, and at least one validation parameter to be used for validating the AI / ML model at the wireless device.

7. The method of any one of Claims 1 to 6, wherein:the first radio node is the wireless device, andP110692WO01 (017997.4111) PATENT APPLICATION the second radio node is a gNodeB, gNB, or a Location Management Function, LMF.

8. The method of any one of Claims 1 to 6, wherein:the first radio node is a gNodeB, gNB, or a base station, and the second radio node is a Location Management Function, LMF.

9. The method of Claim 8, wherein the gNB or base station receives signaling from the LMFenquiring whether the assistance information is needed.

10. The method of any one of Claims 8 to 9, wherein the request for the assistance informationis received from the LMF over NRPPA.

11. The method of any one of Claims 7 to 10, comprising validating the accuracy of the AI / MLmodel.

12. The method of Claim 11, wherein validating the accuracy of the AI / ML model comprisesperforming model monitoring.

13. The method of any one of Claims 1 to 6, wherein:the first radio node is a Location Management Function, LMF, and the second radio node is gNodeB, gNB, or a base station.

14. The method of Claim 13, wherein the gNB or base station receives signaling from the LMFenquiring whether the assistance information is needed.

15. The method of any one of Claims 13 to 14, wherein the request for the assistance informationis received from the LMF over NRPPA.

16. The method of any one of Claims 1 to 15, comprising using the assistance information toperform AI / ML positioning measurement prediction.

17. A method (600) performed second radio node (104, 204, 304, 404), for providingassistance information for positioning, the method comprising: receiving (602) a request from a first radio node (102, 202, 302, 402) to provide assistance information for validating an Artificial Intelligence / Machine Learning, AI / ML, model at a wireless device; transmitting (604), to the first radio node, the assistance information for validating the AI / ML model at the wireless device.

18. The method of Claim 17, wherein the assistance information is at least one of:Line-of-Sight, LOS, information, and / orP110692WO01 (017997.4111) PATENT APPLICATION distance information.

19. The method of any one of Claims 17 to 18, comprising receiving, from the first radio node,a request for the assistance information for validating the AI / ML model for the wireless device.

20. The method of Claim 19, wherein the request for assistance information indicates a requestfor at least one of: Line-of-Sight, LOS, information, and / or distance information.

21. The method of any one of Claims 19 to 20, wherein the request indicates that the assistanceinformation is to be provided as: a one-shot report; a semi-persistent reporting; a periodic reporting according to an update rate.

22. The method of any one of Claims 17 to 21, comprising receiving, from the first radio node,at least one of: an AI / ML capability, at least one measurement that the radio node is able to infer, an AI / ML identifier, at least one input parameter taken by the AI / ML model, at least one output parameter provided by the AI / ML model, an area for which the AI / ML model is valid, and at least one validation parameter to be used for validating the AI / ML model at the wireless device.

23. The method of any one of Claims 17 to 22, wherein:the first radio node is the wireless device, and the second radio node is a gNodeB, gNB, or a Location Management Function, LMF.

24. The method of any one of Claims 17 to 23, wherein:the first radio node is a gNodeB, gNB, or a base station, and the second radio node is a Location Management Function, LMF.

25. The method of Claim 24, wherein the gNB or base station receives signaling from the LMFenquiring whether the assistance information is needed.

26. The method of any one of Claims 24 to 59, wherein the request for the assistanceP110692WO01 (017997.4111) PATENT APPLICATION information is received from the LMF over NRPPA.

27. The method of any one of Claims 17 to 26, comprising validating the accuracy of theAI / ML model.

28. The method of Claim 27, wherein validating the accuracy of the AI / ML model comprisesperforming model monitoring.

29. The method of any one of Claims 17 to 28, wherein:the first radio node is a Location Management Function, LMF, and the second radio node is gNodeB, gNB, or a base station.

30. The method of Claim 29, wherein the gNB or base station receives signaling from the LMFenquiring whether the assistance information is needed.

31. The method of any one of Claims 29 to 30, wherein the request for the assistance informationis received from the LMF over NRPPA.

32. A radio node (102, 206, 202, 306, 302, 406, 402) for performing positioning, the radionode configured to: receive (502), from a second radio node (104, 204, 304, 404), assistance information for validating an Artificial Intelligence / Machine Learning, AI / ML, model at a wireless device.

33. The radio node of Claim 32, configured to perform any of the methods of Claims 2 to 16.

34. A Location Management Function, LMF (104, 204, 304, 404), for providing assistanceinformation for positioning, the LMF configured to: receiving a request from a first radio node (102, 206, 202, 306, 302, 406, 402) to provide assistance information for validating an Artificial Intelligence / Machine Learning, AI / ML, model at a wireless device; transmitting, to the first radio node, the assistance information for validating the AI / ML model at the wireless device.

35. The LMF of Claim 34, configured to perform any of the methods of Claims 18 to 31.

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