Wireless device, location management node and methods performed thereby in a wireless communication network

Abstract

A method, performed by a wireless device, for handling location estimation in a wireless communication network. The method comprising receiving (403) a location request message for location estimation from a location management node. The request indicating one or more positioning methods for obtaining the location estimation including a UE-based direct AI / ML positioning method. The method comprising estimating (405) a location of the wireless device based on the UE-based direct AI / ML positioning method. The method comprising sending (406) a location response message comprising the obtained location estimation to the location management node, the location response message indicating the UE-based direct AI / ML positioning method.

Description

[0001] WIRELESS DEVICE, LOCATION MANAGEMENT NODE AND METHODS PERFORMED THEREBY IN A WIRELESS COMMUNICATION NETWORK

[0002] TECHNICAL FIELD

[0003] The present disclosure relates generally to a wireless device and methods performed thereby for handling location estimations. The present disclosure also relates generally to a location management node and methods performed thereby for handling location estimations.

[0004] BACKGROUND

[0005] In a typical wireless communication network, wireless devices, also known as wireless communication devices, mobile stations, stations (STA) and / or User Equipment (UE), communicate via a Wide Area Network or a Local Area Network such as a Wi-Fi network or a cellular network comprising a Radio Access Network (RAN) part and a Core Network (CN) part. The RAN covers a geographical area which is divided into service areas or cell areas, which may also be referred to as a beam or a beam group, with each service area or cell area being served by a radio network node such as a radio access node e.g., a Wi-Fi access point, a Base Station (BS) or a radio base station (RBS), which in some networks may also be denoted, for example, a Base Station (BS), a NodeB, eNodeB (eNB), or gNodeB (gNB) as denoted in Fifth Generation (5G) telecommunications. A service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node communicates over an air interface operating on a radio frequency with the wireless devices within the range of the radio network node.

[0006] 3rd Generation Partnership Project (3GPP) is the standardization body for specifying the standards for the cellular system evolution, e.g., including 3G, 4G, 5G and the future evolutions. Specifications for Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Packet System (EPS) have been completed within the 3GPP. In 4G, also called a Fourth Generation (4G) network, EPS is core network and E-UTRA is radio access network. In 5G, 5GC is core network, NR is radio access network. As a continued network evolution, the new release of 3GPP specifies a 5G network also referred to as 5G New Radio (NR) and 5G Core (5GC).

[0007] Frequency bands for 5G NR are being separated into two different frequency ranges, Frequency Range 1 (FR1) and Frequency Range 2 (FR2). FR1 comprises sub-6 GHz frequency bands. Some of these bands are bands traditionally used by legacy standards but have been extended to cover potential new spectrum offerings from 410 MHz to 7125 MHz.FR2 comprises frequency bands from 24.25 GHz to 52.6 GHz. Bands in this millimeter wave range have shorter range but higher available bandwidth than bands in the FR1.

[0008] Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. For a wireless connection between a single user, such as UE, and a base station (BS), the performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a Multiple-Input Multiple-Output (MIMO) communication channel. This may be referred to as Single-User (SU)-MIMO. In the scenario where MIMO techniques is used for the wireless connection between multiple users and the base station, MIMO enables the users to communicate with the base station simultaneously using the same time-frequency resources by spatially separating the users, which increases further the cell capacity. This may be referred to as Multi-User (MU)-MIMO. Note that MU-MIMO may benefit when each UE only has one antenna. The cell capacity can be increased linearly with respect to the number of antennas at the BS side. Due to that, more and more antennas are employed in BS. Such systems and / or related techniques are commonly referred to as massive MIMO.

[0009] AI / ML modeling and associated principles

[0010] Artificial intelligence (Al) or machine learning (ML) technique comprises of one or more algorithms, which use a set of data as input for training one or more AI / ML models. The output of the AI / ML model is used by the device, e.g. a UE, base station (BS) or another node, for performing certain operations or taking certain decisions, e.g., handover etc., fully or partially based on the prediction, which in turn depends on the trained model. The AI / ML model can be trained in the device online, or on-the-fly while processing the data, or offline in the background. More specifically:

[0011] • Online training is an AI / ML training process where the model being used for inference is (typically continuously) trained in (near) real-time with the arrival of new training samples or data.

[0012] • Offline training is an AI / ML training process where the model is trained based on collected samples or data, and where the trained model is later used or delivered for inference.

[0013] AI / ML model inference refers to a process of using a trained AI / ML model to produce a set of outputs based on a set of inputs.

[0014] The AL / ML models can be trained in a device, which can be a UE, a network node, or another node. In this respect the AI / ML modes can be broadly classified as:

[0015] • Case I: UE-side (AI / ML) model. It is an AI / ML model whose inference is performed entirely at the UE.• Case II: Network-side (AI / ML) model. It is an AI / ML model whose inference is performed entirely at the network.

[0016] • Case III: One-sided (AI / ML) model. It is a UE-side (AI / ML) model or a Network-side (AI / ML) model.

[0017] • Case IV: Two-sided (AI / ML) model. It is a paired AI / ML model(s) over which joint inference is performed, where joint inference comprises AI / ML Inference whose inference is performed jointly across the UE and the network, i.e., the first part of inference is firstly performed by UE and then the remaining part is performed by gNB, or vice versa.

[0018] An AI / ML model can be transferred or delivered over the air interface either in terms of one or more parameters of a model structure known at the receiving end or a new model with parameters. The model delivery may contain a full model or a partial model.

[0019] The term lifecycle management (LCM) of an AI / ML model refers to the process of developing, deploying and maintaining the AI / ML model. An AI / ML model training pipeline includes several processing stages as gathering unprocessed input data from data repositories (data ingestion), finding high-quality input features (data pre-processing), finding the optimal mapping of the model input features to a desired model output target in a sense determined by a loss function (model training), evaluate model performance on unseen data from a functional level as well as from a system level when relevant (model evaluation). The training pipeline typically ends with a model registration stage, which may comprise of operations to make the ML model runnable via compilation to a specific HW and of steps like versioning and packaging of the model so that it can be executed. An example of the AI / ML model training pipeline illustrating different stages is shown in Figure 1.

[0020] AI / ML model based positioning

[0021] AI / ML model can be used for UE positioning. A UE or a gNB, depending on capability, can have a trained model stored inside the device, or have an untrained AI / ML that can be trained on-the-fly to either produce measurements that are required to localize a UE within a radio access network (RAN) coverage area or directly predict / determine the UE location by exploiting the measurements performed by the UE or gNB on reference signals such as positioning reference signal (PRS), sounding reference signal (SRS) etc. within a RAN coverage area.

[0022] Measurements predicted / determined by the UE by exploiting an AI / ML model can be defined as, but not limited to:

[0023] • RSTD: It is reference signal time difference between the positioning node j and the reference positioning node i. It is measured on the DL PRS signals and alwaysinvolves two cells (cell may be interchangeably called Transmission and Reception Point (TRP).

[0024] • UE Rx-Tx time difference: It is defined as TUE-RX -TUE-TX.

[0025] Where:

[0026] o TUE-RX is the UE received timing of downlink subframe #i from a positioning node, defined by the first detected path in time. It is measured on PRS signals received from the gNB.

[0027] o TUE-TX is the UE transmit timing of uplink subframe #j that is closest in time to the subframe #i received from the positioning node.

[0028] Measurements p red icted / d etermined by the gNB by exploiting an AI / ML model can be defined as, but not limited to:

[0029] • gNB Rx-Tx time difference: It is defined as TgNB-RX - TgNB-TX.

[0030] Where:

[0031] o TgNB-RX is the positioning node received timing of uplink subframe #i containing SRS associated with the UE, defined by the first detected path in time. It is measured on SRS signals received from the UE.

[0032] o TgNB-TX is the positioning node transmit timing of downlink subframe #j that is closest in time to the subframe #i received from the UE.

[0033] • Timing advance (TADV): It is defined as the time difference TADV = (TgNB-RX - TgNB-TX),

[0034] Where:

[0035] o TgNB-RX is the Transmission and Reception Point (TRP) received timing of uplink subframe #i containing PRACH transmitted from UE, defined by the first detected path in time.

[0036] o TgNB-TX is the TRP transmit timing of downlink subframe #j that is closest in time to the subframe #i received from the UE.

[0037] o The detected PRACH is used to determine the start of one subframe containing that PRACH.

[0038] • UL Relative Time of Arrival (UL RTOA): It is defined as the beginning of subframe i containing SRS received in positioning node j, relative to the configurable reference time. For example, nodel (e.g., base station etc) measures the reception time of signals transmitted by the UE with respect to a reference time.

[0039] In addition to these, UE or gNB may also perform power measurements such as reference signal received power (RSRP) and / or reference signal received path power (RSRPP). These measurements can be performed on reference signals such as PRS and SRS.Depending on the capability, a UE may also perform positioning measurements on the sidelink (SL) resources by exploiting an AI / ML model, e.g. on the SL-PRS transmitted between the target UE and one or more assisting or anchor UEs. The UE performing the positioning measurement is called a target UE and the UE(s) assisting the target UE to perform the SL positioning measurements is called the anchor or assisting UE.

[0040] Assisted positioning

[0041] In this mode, the positioning measurements are performed by the UE / gNB by using the AI / ML model. After completion, the positioning measurements are then reported to the location server. The location server upon receiving measurements determines the location of the UE within the RAN coverage area. The location server depending on the need may forward the UE location to another node within the network to facilitate provisioning of UE location information to the application layer or a third party that is interested or has requested the positioning of the UE within the RAN coverage area for further action to be taken.

[0042] Direct positioning

[0043] In this mode, the AI / ML model takes the measurement as input and produces the positioning of the UE.r. The positioning engine or the AI / ML model to predict or determine the UE location within the RAN coverage area resides within the UE node or the gNB node or the location server. After determining the UE position within the RAN coverage area, the estimated UE positioning may then be reported to the location server in a deployment or scenario where the Location management Function (LMF) is not deployed with AI / ML capability to localize a UE. The location server depending on the need may forward the UE location to another node within the network to facilitate provisioning of UE location information to the application layer or the third party that is interested or has requested the positioning of UE within the RAN coverage area for further action to be taken.

[0044] Release 19 WID for AI / ML positioning

[0045] 3GPP Work Item Description” of R19 has the following Information on Work Item:

[0046] “Title: New WID on Artificial Intelligence (Al) / Machine Learning (ML) for NR Air Interface”:

[0047] “Positioning accuracy enhancements, encompassing [RAN1 / RAN2 / RAN3]:

[0048] o Direct AI / ML positioning:

[0049] ■ (1st priority) Case 1: UE-based positioning with UE-side model, direct AI / ML positioning

[0050] ■ (2nd priority) Case 2b: UE-assisted / LMF-based positioning with LMF- side model, direct AI / ML positioning■ (1st priority) Case 3b: NG-RAN node assisted positioning with LMF-side model, direct AI / ML positioning.

[0051] o AI / ML assisted positioning

[0052] ■ (2nd priority) Case 2a: UE-assisted / LMF-based positioning with UE-side model, AI / ML assisted positioning

[0053] ■ (1st priority) Case 3a: NG-RAN node assisted positioning with gNB-side model, AI / ML assisted positioning.

[0054] o Specify necessary measurements, signaling / mechanism(s) to facilitate LCM operations specific to the Positioning accuracy enhancements use cases, if any o Investigate and specify the necessary signaling of necessary measurement enhancements (if any)

[0055] o Enabling method(s) to ensure consistency between training and inference regarding NW-side additional conditions (if identified) for inference at UE for relevant positioning sub use cases.

[0056] Core requirements for the above two use cases for AI / ML LCM procedures and UE features [RAN 4]:

[0057] o Specify necessary RAN4 core requirements for the above two use cases. o Specify necessary RAN4 core requirements for LCM procedures including performance monitoring.”

[0058] Positioning architecture

[0059] Before Rel. 16, LTE based positioning was one the prevalent RAT-based positioning solutions available. Starting from Rel. 16 specification, positioning is also supported in New Radio (NR). Positioning in NR is supported by the architecture shown in Figure 2. The interactions between the gNodeB and the UE is supported via the Radio Resource Control (RRC) protocol, while the location node interfaces with the UE via the LTE positioning protocol (LPP). LPP is a common protocol to both NR and LTE. LMF is the location node in NR. There are also interactions between the location node and the gNodeB via the NRPPa protocol.

[0060] The positioning architecture in Figure 2 will also be used to support AI / ML-based positioning. Rel. 19 work on introducing AI / ML-based positioning will not only exploit the legacy protocol but will also rely on already defined / existing reference signals that are used for positioning.

[0061] RAN2#129 Agreements

[0062] 1: Introduce AI / ML positioning Case 1 as a new positioning method.SUMMARY

[0063] An object of embodiments herein is to handle location estimation in a wireless communication network in an efficient manner and improve the performance of the wireless communication network.

[0064] According to a first aspect, the object is achieved by a method, performed by a wireless device, for handling location estimation in a wireless communication network.

[0065] The method comprises receiving a location request message for location estimation from a location management node. The request indicating one or more positioning methods for obtaining the location estimation including a UE-based direct AI / ML positioning method.

[0066] The method comprises estimating a location of the wireless device based on the UE-based direct AI / ML positioning method.

[0067] The method comprises sending a location response message comprising the obtained location estimation to the location management node. The location response message indicates the UE-based direct AI / ML positioning method.

[0068] According to a second aspect, the object is achieved by a wireless device configured to handle location estimation in a wireless communication network. The wireless device is further configured to receive a location request message for location estimation from a location management node. The request indicating one or more positioning methods for obtaining the location estimation.

[0069] The wireless device is further configured to estimate a location of the wireless device based on the UE-based direct AI / ML positioning method.

[0070] The wireless device is further configured to send a location response message comprising the obtained location estimation to the location management node. The location response message further indicates the UE-based direct AI / ML positioning method.

[0071] According to a third aspect, the object is achieved by a method performed by a location management node, for handling location estimation in a wireless communication network.

[0072] The method comprises sending a location request message for location estimation to a wireless device. The request indicates one or more positioning methods for obtaining the location estimation including a UE-based direct AI / ML positioning method.

[0073] The method comprises receiving a location response message comprising the obtained location estimation from the wireless device. The location response message indicates the UE-based direct AI / ML positioning method used to obtain the location estimation.According to a fourth aspect, the object is achieved by a location management node configured to handle location estimation in a wireless communication network. The location management node is further configured to send a location request message for location estimation to a wireless device. The request indicating one or more positioning methods for obtaining the location estimation and further indicating a UE-based direct A I / ML positioning method.

[0074] The location management node is further configured to receive a location response message adapted to comprise the obtained location estimation from the wireless device. The location response message further indicating the UE-based direct AI / ML positioning method.

[0075] According to a further aspect, the object is achieved by a computer program comprising instructions, which when executed by a processor, causes the processor to perform actions according to any of the aspects above.

[0076] According to a further aspect, the object is achieved by a carrier comprising the computer program of the aspect above, wherein the carrier is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

[0077] An advantage of embodiments disclosed herein is that they enable the wireless device to indicate that a location estimate is obtained by UE-based direct AI / ML positioning, which makes the specification complete.

[0078] BRIEF DESCRIPTION OF THE DRAWINGS

[0079] The various aspects of embodiments disclosed herein, including particular features and advantages thereof, will be readily understood from the following detailed description and the accompanying drawings, in which:

[0080] Figure 1 is a block diagram schematically illustrating an example of an AI / ML model training pipeline,

[0081] Figure 2 is a block diagram schematically illustrating a positioning architecture in NR,

[0082] Figure 3 is a drawing schematically illustrating a wireless communication network according to some embodiments disclosed herein,

[0083] Figure 4a is a flowchart illustrating a method performed by a wireless device according to embodiments disclosed herein,Figure 4b is a flowchart illustrating a method performed by a wireless device according to some further embodiments disclosed herein,

[0084] Figure 5 is a flowchart illustrating a method performed by a location management node according to embodiments disclosed herein,

[0085] Figure 6 is a drawing schematically illustrating a scenario in which embodiments disclosed herein may be used,

[0086] Figure 7 is a signalling diagram schematically illustrating some embodiments disclosed herein,

[0087] Figure 8 is a signalling diagram schematically illustrating some further embodiments disclosed herein,

[0088] Figure 9 is a block diagram illustrating a wireless device according to embodiments disclosed herein,

[0089] Figure 10 is a block diagram schematically illustrating a location management node according to embodiments disclosed herein,

[0090] Figure 11 is a diagram schematically illustrating a communication system in accordance with some embodiments,

[0091] Figure 12 is a diagram schematically illustrating a communication system in accordance with some embodiments,

[0092] Figure 13 is a block diagram illustrating a wireless device,

[0093] Figure 14 is a block diagram illustrating a network node,

[0094] Figure 15 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized.

[0095] DETAILED DESCRIPTION

[0096] As a part of developing embodiments herein the inventors identified a problem which first will be discussed.

[0097] When an LMF receives a Location Service (LCS) request with Quality of Service (QoS) requirement, it is up to the LMF to select one or multiple positioning methods for the UE. If the UE receives an LTE positioning protocol (LPP) RequestLocationlnformation msg with multiple positioning methods and location estimate to provide, it will provide the location estimate and also indicate the method(s) to derive the location estimate. Now Case 1 direct AI / ML positioning with UE-sided model is introduced as a new positioning method. However, there is no support to indicate it as a location source.

[0098] In certain scenarios / areas, the LMF may prefer the UE to perform AI / ML positioning method to achieve high positioning accuracy, however the LMF may include both AI / MLpositioning method (e.g., Case 1) and non-AI / ML positioning method in the same LPP RequestLocationlnformation msg to save latency in case the UE fails to perform AI / ML positioning. Currently, when the LMF provides multiple methods to the UE, the UE may handle both in parallel or chose to perform in sequence. This is up to UE implementation. Currently there is no standardized mechanism which govern the UE behavior with respect to which method the UE should prioritize and whether to use one method or multiple.

[0099] Embodiments herein relate to location estimation and handling thereof.

[0100] As mentioned above, an object of embodiments herein is to handle location estimation in a wireless communication network in an efficient manner and improve the performance of the wireless communication network.

[0101] Embodiments herein provides extensions to LPP, e.g., by adding AI / ML in IE LocationSource in LPP provideLocationlnformation msg, and further by adding e.g., aiLocationEstimatePreferred in LocationlnformationType in RequestLocationlnformation msg.

[0102] Embodiments disclosed herein provide for methods performed by a wireless device, such as a UE, that enables the UE to indicate that the location estimate is obtained by a UE-based direct AI / ML positioning method.

[0103] Further, embodiments disclosed herein, provide for methods performed by a location management node, such as an LMF, that enable the LMF to request the UE to prioritize AI / ML positioning method if both AI / ML and non-AI / ML positioning methods are requested.

[0104] As mentioned above, embodiments herein may e.g., bring the advantage of enabling the UE to indicate that a location estimate is obtained by UE-based direct AI / ML positioning, which makes the specification complete.

[0105] Embodiments herein may further e.g., bring the advantage of the LMF being able to request UE to prioritize AI / ML positioning method if both AI / ML and non-AI / ML positioning methods are requested, which enables better control by the network and is helpful to achieve good positioning QoS including accuracy and latency.

[0106] Embodiments herein relate to wireless communication networks in general. Figure 3 is a schematic overview depicting a wireless communication network 100. The wireless communication network 100 comprises one or more RANs and one or more CNs. The wireless communication network 100 may be a 5G system, or a newer system supporting similar functionality, such as for example, a Sixth Generation (6G) system. In some examples, the wireless communication network may support, additionally or alternatively, a Long-TermEvolution (LTE) network and may support other technologies such as a for example, LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), LTE Half-Duplex Frequency Division Duplex (HD-FDD), and LTE operating in an unlicensed band. The telecommunications system may also support other technologies, such as Wideband Code Division Multiple Access (WCDMA), Universal Mobile Telecommunications System Terrestrial Radio Access (UTRA) TDD, Global System for Mobile communications (GSM) network, GSM / Enhanced Data Rate for GSM Evolution (EDGE) Radio Access Network (GERAN) network, Ultra-Mobile Broadband (UMB), EDGE network, network comprising any combination of Radio Access Technologies (RATs) such as e.g. Multi-Standard Radio (MSR) base stations, multi-RAT base stations etc., any 3rd Generation Partnership Project (3GPP) cellular network, Wireless Local Area Network / s (WLAN) or WiFi network / s, Worldwide Interoperability for Microwave Access (WiMax), IEEE 802.15.4-based low-power short-range networks such as IPv6 over Low-Power Wireless Personal Area Networks (6LowPAN), Zigbee, Z-Wave, Bluetooth Low Energy (BLE), or any cellular network or system. The telecommunications system may for example support a Low Power Wide Area Network (LPWAN). LPWAN technologies may comprise Long Range physical layer protocol (LoRa), Haystack, SigFox, LTE-M, and Narrow-Band IoT (NB-IoT).

[0107] A number of network nodes operate in the wireless communication network 100 such as e.g. a radio network node 101. These nodes provide radio coverage in a number of cells which may also be referred to as a beam or a group of beams.

[0108] The radio network node 101 may be any of a NG-RAN node, a transmission and reception point e.g. a base station, a radio access network node such as a Wireless Local Area Network (WLAN) access point or an Access Point Station (AP STA), an access controller, a base station, e.g. a radio base station such as a NodeB, an evolved Node B (eNB, eNode B), a gNB, a base transceiver station, a radio remote unit, an Access Point Base Station, a base station router, a transmission arrangement of a radio base station, a standalone access point, a network controlled repeater or any other network unit capable of communicating with a wireless device within the service area served by the radio network node 101 depending e.g. on the first radio access technology and terminology used. The radio network node 101 may be referred to as a serving radio network node and communicates with a UE with Downlink (DL) transmissions to the UE 121 and Uplink (UL) transmissions from the UE.

[0109] In some examples, the wireless communication network 100 may comprise an access network, such as a radio access network (RAN), and a core network, which may include one or more core network nodes. The access network may include one or more access network nodes, such as the radio network node 101, e.g., which may be generally referred to as network nodes, or any other similar 3rd Generation Partnership Project (3GPP) access nodesor non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes may include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network may include one or more Open-RAN (ORAN) network nodes. An ORAN network node may be understood as a node in the telecommunication network that may support an ORAN specification, e.g., a specification published by the O-RAN Alliance, or any similar organization, and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network, including one or more network nodes and / or core network nodes.

[0110] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller, near-real time or non-real time, hosting software or software plug-ins, such as a near-real time control application, e.g., xApp, or a non-real time control application, e.g., rApp, or any combination thereof, the adjective “open” designating support of an ORAN specification. The radio network node 101 may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment, in which one or more network functions may be virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies. The radio network node 101 may facilitate direct or indirect connection of a UE, such as by connecting the UE to the core network over one or more wireless connections.

[0111] In the wireless communication network 100, one or more wireless devices operate, such as e.g. a wireless device 121. The wireless device 121 may be a UE. The wireless device 121 may be also known as a e.g., device, mobile terminal, wireless terminal and / or mobile station, mobile telephone, cellular telephone, or laptop with wireless capability, an Internet of Things (IoT) device, or a Customer Premises Equipment (CPE), just to mention some further examples. The wireless device 121 in the present context may be, for example, portable, pocket-storable, hand-held, computer-comprised, or a vehicle-mounted mobile device, enabled to communicate voice and / or data, via a RAN, with another entity, such as a server, a laptop, a Personal Digital Assistant (PDA), or a tablet, a Machine-to-Machine (M2M) device, an Internet of Things (IoT) device, e.g., a sensor or a camera, a device equipped with a wireless interface, such as a printer or a file storage device, modem, Laptop EmbeddedEquipped (LEE), Laptop Mounted Equipment (LME), USB dongles, CPE or any other radio network unit capable of communicating over a radio link in the wireless communication network 100. The wireless device 121 may be wireless, i.e., it may be enabled to communicate wirelessly in the wireless communication network 100 and, in some particular examples, may be able support transmission using beamforming. The communication may be performed e.g., between two devices, between a device and a radio network node, and / or between a device and a server. The communication may be performed e.g., via a RAN and possibly one or more core networks, comprised, respectively, within the wireless communication network 100. The wireless communication network 100 further comprises a location management node 130 for controlling positioning and location estimation of e.g., the wireless device 121.

[0112] Methods herein may be performed by the wireless device 121 and the location management node 130 respectively. As an alternative, a Distributed Node (DN) and functionality, e.g. comprised in a cloud 190 as shown in Figure 3, may be used for performing or partly performing the methods herein.

[0113] The above-described problems are addressed in a number of embodiments, some of which may be seen as alternatives, while some may be used in combination. Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Other embodiments, however, are contained within the scope of the subject matter disclosed herein, the disclosed subject matter should not be construed as limited to only the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0114] A method according to embodiments will now be described from the view of the wireless device 121 together with Figure 4. Figure 4 shows example embodiments of a method performed by the wireless device 121 for handling location estimation in the wireless communication network 100. The method comprises the following actions, which actions may be taken in any suitable order. Actions that are optional are presented in dashed boxes in Figure 4.

[0115] Action 402

[0116] In some embodiments, the wireless device 121 sends a message to the location management node 130. The message indicates that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning. This may mean that the wireless device 121 has the capability to perform UE-based direct AI / ML positioning using said model. It may further mean that the model the wireless device 121 has could be used to perform location estimation according to one or more conditions. The message may e.g., be sent to the location management node 130 after indicating to the location management node 130 that the wirelessdevice 130 has capability to perform UE-based direct AI / ML positioning and further receiving assistance data related to positioning from the location management node 130.

[0117] There may be an applicable condition for using the AI / ML model for UE-based direct AI / ML positioning. Even when the wireless device 121 has a capability to use the AI / ML model, if the condition is not met then the wireless device 121 may not use it. For example, the wireless device 121 may have performed training in a cell with 3 TRPs and now the cell is using only 1 TRP, which means the AI / ML model is not applicable for the current situation. A similar situation is if the wireless device 121 has trained the AI / ML model when the wireless device 121 travelled with a speed of 50 km / h but now the wireless device 121 is travelling at 200 km / h.

[0118] Action 403

[0119] The wireless device 121 receives a location request message for location estimation from a location management node 130. The request indicates one or more positioning methods for obtaining the location estimation including a UE-based direct AI / ML positioning method. The request may further indicate the UE-based direct AI / ML positioning method as a preferred positioning method. This way, the location management node 130 may indicate to the wireless device to prioritize the use of the UE-base direct AI / ML method for the location estimation. The location request message may e.g., be an LPP Request Location Information message. UE-based direct AI / ML positioning as used herein, may be understood as the wireless device 121 comprises a trained AI / ML model, and that inference is performed entirely at the wireless device 121.

[0120] In some embodiments, the preferred positioning method is indicated in an Information Element, IE, in the location request message. The IE indicates that the UE-based direct AI / ML direct positioning method is the preferred positioning method. The IE may e.g., be a LocationlnformationType IE. The indication that the UE-based direct AI / ML direct positioning method is the preferred positioning method may comprise a new parameter in the IE, such as the LocationlnformationType IE.

[0121] In some embodiments, the location request message comprises a response time parameter. The response time parameter indicates to the wireless device to select the positioning method that takes the shortest amount of time of the one or more positioning methods. This may e.g., mean that the presence of the response time parameter indicates that the fastest positioning method should be used by the wireless device 121. This allows the wireless device 121 to override the indication of the preferred positioning method if the preferred positioning method is not the fastest of the one or more positioning methods.

[0122] Action 404The wireless device 121 may select a positioning method from the one or more positioning methods, and may take the indication of the preferred positioning method into account.

[0123] In some embodiments, selecting the positioning method comprises selecting the preferred positioning method. This may comprise selecting the UE-based direct AI / ML positioning method.

[0124] As mentioned above, in some embodiments the location request message comprises the response time parameter. The response time parameter may indicate that the wireless device 121 should select the positioning method which takes the shortest amount of time of the one or more positioning methods. Thus, when the location request message comprises the response time parameter, selecting the positioning method may comprise selecting the positioning method that takes the shortest amount of time to estimate the location of the one or more positioning methods.

[0125] Action 405

[0126] The wireless device 121 estimates a location of the wireless device 121 based on a positioning method of the one or more indicated positioning methods. Specifically, the wireless device 121 estimates the location of the wireless device 121 based on the UE-based direct AI / ML positioning method.

[0127] This may mean that the wireless device 121 estimates the location based on the selected positioning method, as selected in Action 404 above.

[0128] Action 406

[0129] The wireless device 121 sends a location response message comprising the obtained location estimation to the location management node 130. The location response message indicates the positioning method used to obtain the location estimation. Specifically, the location response message indicates the UE-based direct AI / ML positioning method. In other words, the location response message comprises not only the estimated location of the wireless device 121, but also the positioning method used to estimate the location. The location response message may e.g., be a Provide Location Information message.

[0130] In some embodiments, the positioning method used to obtain the location estimation is indicated in an IE in the location response message. The IE indicates that the UE-based direct AI / ML direct positioning method was used to estimate the location. The IE may e.g., be a Location Source IE. The positioning method used to estimate the location may e.g., comprise a parameter in the IE, such as the LocationSource IE.A method according to embodiments will now be described from the view of the location management node 130 together with Figure 5. Figure 5 shows example embodiments of a method performed by the location management node 130 for handling location estimation in the wireless communication network 100. The method comprises the following actions, which actions may be taken in any suitable order. Actions that are optional are presented in dashed boxes in Figure 5.

[0131] Action 503

[0132] In some embodiments, the location management node receives a message from the wireless device 121. The message is adapted to indicate that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning. This may mean that the wireless device 121 has the capability to perform UE-based direct AI / ML positioning using said model. It may further mean that the model the wireless device 121 has could be used to perform location estimation according to one or more conditions. The message may e.g., sent to the location management node 130 after indicating to the location management node 130 that the wireless device 130 has capability to perform UE-based direct AI / ML positioning and further receiving assistance data related to positioning from the location management node.

[0133] Action 504

[0134] The location management node sends a location request message for location estimation to the wireless device 121. The request indicates one or more positioning methods for obtaining the location estimation. The one or more positioning methods for obtaining the location estimation includes the UE-based direct AI / ML positioning method. The request may further indicate a UE-based direct AI / ML positioning method as a preferred positioning method. This way, the location management node 130 may indicate to the wireless device to prioritize the use of the UE-base direct AI / ML method for the location estimation. The location request message may e.g., be an LPP Request Location Information message. UE-based direct AI / ML positioning as used herein, may be understood as the wireless device 121 comprises a trained AI / ML model, and that inference is performed entirely at the wireless device 121.

[0135] In some embodiments, the preferred positioning method is indicated in an Information Element, IE, in the location request message. The IE indicates that the UE-based direct AI / ML direct positioning method is the preferred positioning method. The IE may e.g., be a LocationlnformationType IE. The indication that the UE-based direct AI / ML direct positioning method is the preferred positioning method may comprise a new parameter in the IE, such as the LocationlnformationType IE.In some embodiments, the location request message comprises a response time parameter. The response time parameter indicates the wireless device to select the positioning method that takes the shortest amount of time of the one or more positioning methods. This may e.g., mean that the presence of the response time parameter indicates that the fastest positioning method should be used by the wireless device 121. This allows the wireless device 121 to override the indication of the preferred positioning method if the preferred positioning method is not the fastest of the one or more positioning methods.

[0136] Action 505

[0137] The location management node 130 receives a location response message comprising the obtained location estimation from the wireless device 121. The location response message indicates the positioning method used to obtain the location estimation. Specifically, the location response message indicates the UE-based direct AI / ML positioning method. In other words, the location response message comprises not only the estimated location of the wireless device 121, but also the positioning method used to estimate the location. The location response message may e.g., be a Provide Location Information message.

[0138] In some embodiments, the positioning method used to obtain the location estimation is indicated in an IE in the location response message. The IE indicates that the UE-based direct AI / ML direct positioning method was used to estimate the location. The IE may e.g., be a Location Source IE. The positioning method used to estimate the location may e.g., comprise a parameter in the IE, such as the LocationSource IE.

[0139] Embodiments herein such as the embodiments mentioned above will now be further described and exemplified. The text below is applicable to embodiments herein and may be combined with any suitable embodiment described above.

[0140] Examples of embodiments herein target the scenarios where a UE 121, such as the wireless device 121, holds the AI / ML model for positioning and the output of the model are a location estimate. This scenario maps to AI / ML positioning Case 1 in Release 19 Wl, see e.g., Figure 6.

[0141] Figure 7 shows an example of a UE, such as the wireless device 121, indicating location estimate by Case 1 AI / ML positioning.

[0142] S700. The UE sends the supported capabilities to the LMF, such as the location management node 130, including capability of Case 1 UE-based direct AI / ML positioning.

[0143] S701. The LMF sends Assistance data including DL-PRS configuration for UE-based direct AI / ML positioning.S702. After receiving assistance data, the UE reports whether it has an applicable model for UE-based direct AI / ML positioning.

[0144] S703. After the LMF receives the report that the UE is capable of UE-based direct AI / ML positioning, the LMF requests the UE to provide a location estimate based on one or more positioning methods including UE-based direct AI / ML positioning.

[0145] S704. The UE measures on DL-PRS and obtains a location estimate by UE-based direct AI / ML positioning.

[0146] S705. The UE sends the location estimate to the LMF and indicates UE-based direct AI / ML positioning as a source.

[0147] Figure 8 shows an example of the LMF requesting the UE to prioritize AI / ML positioning.

[0148] S800. The UE send the supported capabilities to LMF including capability of Case 1 UE-based direct AI / ML positioning.

[0149] S801. The LMF sends Assistance data including DL-PRS configuration for UE-based direct AI / ML positioning.

[0150] S802. After receiving assistance data, the UE reports whether it has applicable model for UE-based direct AI / ML positioning.

[0151] S803. After the LMF receives the report that the UE is applicable for UE-based direct AI / ML positioning, the LMF requests the UE to provide location estimate, multiple positioning methods selected including both AI / ML and non-AI / ML positioning methods, and indicating to prioritize using AI / ML positioning.

[0152] S804. The UE measures on DL-PRS and prioritize AI / ML positioning to obtain location estimate.

[0153] S805. The UE sends location estimate to the LMF and indicates positioning method(s) used.

[0154] Method Selection based upon response time

[0155] For positioning, latency is an important QoS parameters. In some scenarios, the client may prefer to obtain positioning within certain time and the client may be able to sacrifice the accuracy at the cost of latency (i.e. prefer to obtain location as soon as possible; in a very short response time, latency). Thus, at times, it is critical to know where the UE is located within certain responseTime rather than taking a longer time to find the UE with very high accurate positioning.

[0156] In an example according to embodiments herein, it is claimed that NW node such as LMF configures the responseTime which acts implicitly as a threshold for the UE to decide which mechanism should be applied. That is, the UE selects a method which takes less duration.In order to enable such selection, the UE logs the time duration that it takes to execute for non-AI / ML method (e.g: DL-TDOA, DL-AOD) and AI / ML method; and compares which takes shorter duration.

[0157] The embodiments presented above, introduce specification extension of lEs in LPP 3GPP TS 37.355 V18.4.0.

[0158] CommonlEsProvideLocationlnformation

[0159] The CommonlEsProvideLocationlnformation carries common lEs for a Provide Location Information LPP message Type.

[0160] — ASN1START

[0161] CommonlEsProvideLocationlnformation:: = SEQUENCE {

[0162] locationEstimate LocationCoordinates OPTIONAL,

[0163] velocityEstimate Velocity OPTIONAL,

[0164] locationError LocationError OPTIONAL,

[0165] [ [ earlyFixReport-r12 EarlyFixReport-r12 OPTIONAL

[0166] ] ],

[0167] [ [ locationSource-r 13 LocationSource-r 13 OPTIONAL

[0168] locationTimestamp-rl3 UTCTime OPTIONAL

[0169] ] ],

[0170] [ [

[0171] segmentationInfo-r14 SegmentationInfo-r14 OPTIONAL -- Cond Segmentation]],

[0172] [ [

[0173] integrityInfo-r17 IntegrityInfo-r17 OPTIONAL

[0174] ] ],

[0175] [[ locationSource-r19 LocationSource-r19 OPTIONAL

[0176] LocationCoordinates:: = CHOICE {

[0177] ellipsoidPoint Ellipsoid-Point, ellipsoidPointWithUncertaintyCircle Ellipsoid-PointWithUncertaintyCircle, ellipsoidPointWithUncertaintyEllipse EllipsoidPointWithUncertaintyEllipse, polygon Polygon,

[0178] ellipsoidPointWithAltitude EllipsoidPointWithAltitude, ellipsoidPointWithAltitudeAndUncertaintyEllipsoid EllipsoidPointWithAltitudeAndUncertaintyEllipsoid,

[0179] ellipsoidArc EllipsoidArc, highAccuracyEllipsoidPointWithUncertaintyEllipse-v1510

[0180] HighAccuracyEllipsoidPointWithUncertaintyEllipse-r15, highAccuracyEllipsoidPointWithAltitudeAndUncertaintyEllipsoid-v1510

[0181] HighAccuracyEllipsoidPointWithAltitudeAndUncertaintyEllipsoid-r15,

[0182] ha-EllipsoidPointWithScalableUncertaintyEllipse-v1680

[0183] HA-EllipsoidPointWithScalableUncertaintyEllipse-r16, ha-EllipsoidPointWithAltitudeAndScalableUncertaintyEllipsoid-v1680

[0184] HA-EllipsoidPointWithAltitudeAndScalableUncertaintyEllipsoid-r16,

[0185] local2dPointWithUncertaintyEllipse-v1800 Local2dPointWithUncertaintyEllipse-r18, local3dPointWithUncertaintyEllipsoid-v1800 Local3dPointWithUncertaintyEllipsoid-r18 }

[0186] Velocity ::= CHOICE {

[0187] horizontalVelocity HorizontalVelocity, horizontalWithVerticalVelocity HorizontalWithVerticalVelocity, horizontalVelocityWithUncertainty HorizontalVelocityWithUncertainty, horizontalWithVerticalVelocityAndUncertainty

[0188] HorizontalWithVerticalVelocityAndUncertainty

[0189]

[0190] }

[0191] LocationError ::= SEQUENCE {

[0192] locationfailurecause LocationFailureCause,

[0193] }

[0194] LocationFailureCause:: = ENUMERATED {

[0195] undefined,

[0196] requestedMethodNotSupported,

[0197] positionMethodFailure,

[0198] periodicLocationMeasurementsNotAvailable,

[0199] EarlyFixReport-r12 ::= ENUMERATED {

[0200] noMoreMessages,

[0201] moreMessagesOnTheWay

[0202] }

[0203] LocationSource-r13 ::= BIT STRING { a-gnss (0),

[0204] wlan ( 1 ),

[0205] bt ( 2 ),

[0206] tbs ( 3 ),

[0207] sensor ( 4 ),

[0208] ha-gnss-v1510 (5),

[0209] motion-sensor-vl550 ( 6 ),

[0210] dl-tdoa-r16 (7),

[0211] dl-aod-r16 (8) } (SIZE(1..16)) IntegrityInfo-r17 ::= SEQUENCE {

[0212] horizontalProtectionLevel-r17 INTEGER (0..50000), verticalProtectionLevel-r17 INTEGER (0..50000) OPTIONAL, achievableTargetIntegrityRisk-r17 INTEGER (10..90) OPTIONAL, }

[0213] LocationSource-r19 ::= BIT STRING { a-gnss (0),

[0214] wlan ( 1 ),

[0215] bt ( 2 ),

[0216] tbs ( 3 ),

[0217] sensor ( 4 ),

[0218] ha-gnss-v1510 (5),

[0219] motion-sensor-vl550 ( 6 ),

[0220] dl-tdoa-r16 (7),

[0221] dl-aod-rl 6 ( 8 ),

[0222] ai-ml-r19 (9) } (SIZE(1..16))

[0223]

[0224] ASN1STOPConditional presence Explanation

[0225] : Segmentation: This field is optionally present, need OP, if ipp-message-segmentation-req has been

[0226] i received from the location server with bit 1 (targetToServer) set to value 1. The field shall i be omitted if Ipp-message-segmentation-req has not been received in this location

[0227]

[0228]

[0229] I session, or has been received with bit 1 (targetToServer) set to value 0.

[0230] CommonlEsProvideLocationlnformation field descriptions

[0231] I

[0232]

[0233] locationEstimate

[0234] i This field provides a location estimate using one of the geographic shapes defined in TS 23.032

[0015] , Coding of the i values of the various fields internal to each geographic shape follow the rules in TS 23.032

[0015] , The conditions for; including this field are defined for the locationlnformationType field in a Request Location Information message.

[0235] i velocityEstimate

[0236] i This field provides a velocity estimate using one of the velocity shapes defined in TS 23.032

[0015] , Coding of the values i I of the various fields internal to each velocity shape follow the rules in TS 23.032

[0015] ,

[0237] i locationError

[0238] i This field shall be included if and only if a location estimate and measurements are not included in the LPP PDU. The I field includes information concerning the reason for the lack of location information. The LocationFailureCause i 'periodicLocationMeasurementsNotAvailable' shall be used by the target device if periodic location reporting was I requested, but no measurements or location estimate are available when the reportinginterval expired.

[0239] i eariyFixReport

[0240] i This field shall be included if and only if the ProvideLocationlnformation message contains early location

[0241] i measurements or an early location estimate. The target device shall set the values of this field as follows:

[0242] - noMoreMessages: This is the only or last ProvideLocationlnformation message used to deliver the entire set of i early location information.

[0243] - moreMessagesOnTheWay: This is one of multiple ProvideLocationlnformation messages used to deliver the entire set of early location information (if early location information will not fit into a single message).

[0244] : If this field is included, the IE Segmentationinfo shall not be included.

[0245] : locationsource

[0246] : This field provides the source positioning technology for the location estimate.

[0247] i NOTE 1: In this version of the specification, the entry 'tbs' is used only for TBS positioning based on MBS signals. i NOTE 2: The entry 'sensor' is used only for positioning technology that uses barometric pressure sensor. The entry 'motion-sensor' is used for positioning technology that uses sensor(s) to detect displacement and: movement, e.g. accelerometers, gyros, magnetometers.

[0248] i locationTimestamp

[0249] : This field provides the UTC time when the location estimate is valid and should take the form of YYMMDDhhmmssZ. i segmentationinfo

[0250] i This field indicates whether this ProvideLocationlnformation message is one of many segments, as specified in clause i 4.3.5 ] i integrityinfo

[0251] : This field provides the integrity result for the locationEstimate.

[0252] - horizontalProtectionLevel provides the HPL for the locationEstimate along the semi-major axis of the error ellipse. Scale factor 0.01 metre; range 0 - 500 metres.

[0253] - verticalProtectionLevel provides the VPL for the locationEstimate. Scale factor 0.01 metre; range 0 - 500 metres.

[0254] - achievableTargetlntegrityRisk indicates the achievable TIR forwhich the HPL and VPL are provided. The achievable TIR is given by P=10-0.1n[hour-1] where n is the value of achievableTargetlntegrityRisk and the range is 10-1to 10-9per hour. If this field is absent, the achievable TIR is the same as the targetlntegrityRisk in

[0255]

[0256] CommonlEsRequestLocationlnformation.

[0257] LMF request UE to prioritize AI / ML positioning

[0258] CommonlEsRequestLocationlnformation

[0259] The CommonlEsRequestLocationlnformation carries common lEs for a Request Location Information LPP message Type.

[0260] — ASN1START

[0261] CommonlEsRequestLocationlnf ormation:: = SEQUENCE {

[0262] locationlnf ormationType Locationlnf ormationType,

[0263] triggeredReporting TriggeredReportingCriteria OPTIONAL, — Cond ECID

[0264]

[0265] periodicalReporting PeriodicalReportingCriteria OPTIONAL, — Need ONadditionallnf ormation Additionallnf ormation OPTIONAL, — Need ON qos QoS OPTIONAL, — Need ON environment Environment OPTIONAL, — Need ON locationCoordinat e Types LocationCoordinat eTypes OPTIONAL, — Need ON velocityTypes VelocityTypes OPTIONAL, — Need ON

[0266] [ [

[0267] messageSizeLimitNB-r 14 MessageSizeLimitNB-r 14 OPTIONAL — Need ON ] ]r

[0268] [ [

[0269] segment a tionlnf o-r 1 Segmentationlnf o-r 14 OPTIONAL — Need ON ] ]r

[0270] [ [

[0271] scheduledLocationTime- 17

[0272] ScheduledLocationTime-r 17 OPTIONAL, — Need ON targetlntegrityRisk-r

[0273] TargetlntegrityRisk-r 17 OPTIONAL — Need ON ] ]

[0274] Locationlnf ormationType:: = ENUMERATED {

[0275] locationEstimateRequired,

[0276] locationMeasurements Required,

[0277] locationEstimatePref erred,

[0278] locationMeasurements Preferred,

[0279] • • • r

[0280] locationEstimateAndMeasurementsRequired-r 18,

[0281] IccationEstimateRequiredAiPref erred

[0282] 1

[0283] PeriodicalReportingCriteria:: = SEQUENCE {

[0284] reportingAmount ENUMERATED {

[0285] ral, ra2, ra4, ra8, ral6, ra32,

[0286] ra64, ra-Infinity

[0287] } DEFAULT ra-Infinity,

[0288] reportinginterval ENUMERATED {

[0289] noPeriodicalReporting, riO-25,

[0290] riO-5, ril, ri2, ri4, ri8, ril6, ri32, ri64 }

[0291] }

[0292] TriggeredReportingCriteria:: = SEQUENCE {

[0293] cellchange BOOLEAN,

[0294] reportingDuration ReportingDuration,

[0295] }

[0296] ReportingDuration:: = INTEGER ( 0..255 )

[0297] Additionallnf ormation = ENUMERATED {

[0298] onlyReturnlnf ormationRequested,

[0299] mayReturnAdditionallnf ormation,

[0300] }

[0301] QoS SEQUENCE {

[0302] horizontalAccuracy HorizontalAccuracy OPTIONAL — Need ON vertical Co ordinate Re quest BOOLEAN,

[0303] verticalAc curacy VerticalAccuracy OPTIONAL — Need ON

[0304] re spons eTime Re spons eTime OPTIONAL — Need ON

[0305] ve 1 o ci tyRe quest BOOLEAN,

[0306] • • • r

[0307] [ [ responseTimeNB-r 14 ResponseTimeNB-r 14 OPTIONAL — Need ON

[0308] ] ]r

[0309] [ [ horizontalAccuracyExt-rl5 HorizontalAccuracyExt-r 15 OPTIONAL, Need ON verticalAccuracyExt-r 15 VerticalAccuracyExt-r 15 OPTIONAL Need ON ] ]

[0310] }

[0311] HorizontalAccuracy SEQUENCE {

[0312] accuracy INTEGER ( 0.. 127 ),

[0313] confidence INTEGER ( 0.. 100 ),

[0314] VerticalAccuracy: = SEQUENCE {

[0315]

[0316] accuracy INTEGER ( 0.. 127 ),confidence INTEGER ( 0.. 100 )r

[0317] }

[0318] Hori zontalAccuracyExt-rl5:: = SEQUENCE {

[0319] accuracyExt-rl5 INTEGER ( 0.. 255 ),

[0320] conf idence-rl5 INTEGER ( 0.. 100 ),

[0321] VerticalAccuracyExt-r 15 SEQUENCE {

[0322] accuracyExt-r 15 INTEGER ( 0.. 255 ),

[0323] conf idence-r 15 INTEGER ( 0.. 100 ),

[0324] ResponseTime SEQUENCE {

[0325] time INTEGER ( 1.. 128 ),

[0326] [ [ responseTimeEarlyFix-r 12 INTEGER ( 1.. 128 ) OPTIONAL — Need ON ] ],

[0327] [ [ unit-rl5 ENUMERATED { ten-seconds,..., ten-milli-seconds-vl700 } OPTIONAL — Need ON ] ]

[0328] ResponseTimeNB-r 14 SEQUENCE {

[0329] timeNB-rl4 INTEGER ( 1.. 512 ),

[0330] responseTimeEarlyFixNB-r 14 INTEGER ( 1.. 512 ) OPTIONAL, — Need ON [ [ unitNB-rl5 ENUMERATED { ten-seconds,... } OPTIONAL — Need ON ] ]

[0331] }

[0332] Environment ENUMERATED {

[0333] badArea,

[0334] notBadArea,

[0335] mixedArea,

[0336] Mes sageSi zeLimitNB-rl4:: = SEQUENCE {

[0337] measurementLimit-r 14 INTEGER ( 1.. 512 ) OPTIONAL, — Need ON

[0338] ScheduledLocationTime-r 17 SEQUENCE {

[0339] utcTime-rl7 UTCTime OPTIONAL, — Need ON gns sTime-rl7 SEQUENCE {

[0340] gns s-TOD-msec-r 17 INTEGER ( 0.. 3599999 ),

[0341] gns s-TimeID-rl7 GNSS-ID

[0342] } OPTIONAL, — Need ON networkTime-r 17 CHOICE {

[0343] e-utraTime-r 17 SEQUENCE {

[0344] Ite-PhysCellld-r 17 INTEGER ( 0.. 503 ),

[0345] ite-Ar f cnEUTRA-r 17 ARFCN-ValueEUTRA,

[0346] lte-CellGlobalId-rl7 CellGloballdEUTRA-AndUTRA OPTIONAL — Need ON Ite-SystemFrameNumber-r 17 INTEGER ( 0.. 1023 )

[0347] nrTime-r 17 SEQUENCE {

[0348] nr-PhysCelllD-r 17 NR-PhysCellID-rl 6,

[0349] nr-ARFCN-rl7 ARFCN-ValueNR-r 15,

[0350] nr-CellGloballD-r 17 NCGI-rl5 OPTIONAL, — Need ON nr-SFN-rl7 INTEGER ( 0.. 1023 ),

[0351] nr-Slot-r 17 CHOICE {

[0352] s cs l5-rl7 INTEGER ( 0.. 9 ),

[0353] s cs 30-rl7 INTEGER ( 0.. 19 ),

[0354] s cs 60-rl7 INTEGER ( 0.. 39 ),

[0355] s cs l20-rl7 INTEGER ( 0.. 79 )

[0356] } OPTIONAL — Need ON

[0357] } OPTIONAL, — Need ON relativeTime-r 17 INTEGER ( 1.. 1024 ) OPTIONAL — Need ONTargetIntegrityRisk-rl7 INTEGER ( 10.. 90 )

[0358]

[0359] — ASN1STOP

[0360] Editor Notes: FFS exact IE structure of the request for location+measurements in the agreement of RAN2#123bis.

[0361] Conditional presence Explanation

[0362] I ECID I The field is optionally present, need ON, if E-CID or NR E-CID is requested. Otherwise it

[0363]

[0364] i is not present.

[0365] CommonlEsRequestLocationlnformation field descriptions

[0366] i locationlnformationType

[0367] i This IE indicates whether the server requires a location estimate or measurements. For 'locationEstimateRequired', i

[0368]

[0369] the target device shall return a location estimate if possible, or indicate a location error if not possible. For

[0370] i ' location Measurements Require, the target device shall return measurements if possible, or indicate a location error if i i not possible. For 'locationEstimatePreferred', the target device shall return a location estimate if possible, but may also i i or instead return measurements for any requested position methods for which a location estimate is not possible. For i 'locationMeasurementsPreferred', the target device shall return location measurements if possible, but may also or i instead return a location estimate for any requested position methods forwhich return of location measurements is not i i possible. For 'locationEstimateAndMeasurementsRequired', the PRU shall return both location estimate and i measurements if possible, or indicate a location error if not possible. For 'locationEstimateRequiredAiPreferred1, the i UE is scheduled with both Al and non-AI postioninq method (multiple methods), and UE shall prioritize using Al

[0371] : positioning mehtod to derive the location estimate.

[0372] i NOTE: If the PRU is requested to return both location estimate and measurements, the location information is I determined independently of the reported measurements.

[0373] i triggeredReporting

[0374] I This IE indicates that triggered reporting is requested and comprises the following subfields:

[0375] - cellChange If this field is set to TRUE, the target device provides requested location information each time the i primary cell has changed.

[0376] - reportingDuration. Maximum duration of triggered reporting in seconds. A value of zero is interpreted to mean i an unlimited (i.e. "infinite") duration. The target device should continue triggered reporting for the reportingDuration or until an LPP Abort or LPP Error message is received.

[0377] i The triggeredReporting field should not be included by the location server and shall be ignored by the target device if i the periodicalReporting IE or responseTime IE or responseTimeNB IE is included in

[0378] I CommonlEsRequestLocationlnformation.

[0379] i periodicalReporting

[0380] I This IE indicates that periodic reporting is requested and comprises the following subfields:

[0381] - reporting A mount indicates the number of periodic location information reports requested. Enumerated values: correspond to 1, 2, 4, 8, 16, 32, 64, or infinite / indefinite number of reports. If the reportingAmount is 'infinite / indefinite', the target device shou-ld continue periodic reporting until an LPP Abort message is received, i The value 'ra shall not be used by a sender.

[0382] - reportinginterval indicates the interval between location information reports and the response time requirement forthe first location information report. Enumerated values riO-25, riO-5, ri1, ri2, ri4, ri8, ri16, ri32, ri64 correspond to reporting intervals of 1, 2, 4, 8, 10, 16, 20, 32, and 64 seconds, respectively. Measurement reports containing no measurements or no location estimate are required when a reportinginterval expires before a target device is able to obtain new measurements or obtain a new location estimate. The value I 'noPeriodicalReporting' shall not be used by a sender.

[0383] i addiiionaiin formation

[0384] i This IE indicates whether a target device is allowed to return additional information to that requested. If this IE

[0385] : indicates 'onlyReturnlnformationRequested' then the target device shall not return any additional information to that i requested by the server. If this IE indicates 'mayReturnAdditionallnformation' then the target device may return i additional information to that requested by the server. If a location estimate is returned, any additional information is: restricted to that associated with a location estimate (e.g. might include velocity if velocity was not requested but i cannot include measurements). If measurements are returned, any additional information is restricted to additional: measurements (e.g. might include E-CID measurements if A-GNSS measurements were requested but not E-CID i measurements).

[0386] : qos

[0387] i This IE indicates the quality of service and comprises a number of sub-fields. In the case of measurements, some of i the sub-fields apply to the location estimate that could be obtained by the server from the measurements provided by: the target device assuming that the measurements are the only sources of error. Fields are as follows:CommonlEsRequestLocationlnformation field descriptions

[0388] - horizontalAccuracy indicates the maximum horizontal error in the location estimate at an indicated confidence level. The 'accuracy1corresponds to the encoded uncertainty as defined in TS 23.032

[0015] and 'confidence' corresponds to confidence as defined in TS 23.032

[0015] ,

[0389] - verticalCoordinateRequest indicates whether a vertical coordinate is required (TRUE) or not (FALSE)

[0390] - verticalAccuracy indicates the maximum vertical error in the location estimate at an indicated confidence level and is only applicable when a vertical coordinate is requested. The 'accuracy1corresponds to the encoded uncertainty altitude as defined in TS 23.032

[0015] and 'confidence' corresponds to confidence as defined in TS 23.032

[0015] ,

[0391] - responseTime

[0392] - time indicates the maximum response time as measured between receipt of the RequestLocationlnformation and transmission of a ProvideLocationlnformation. If the unit field is absent, this is given as an integer number of seconds between 1 and 128. If the unit field is present with enumerated value 'ten-seconds', the maximum response time is given in units of 10-seconds, between 10 and 1280 seconds. If the unit field is present with enumerated value 'ten-milli-seconds', the maximum response time is given in units of 10-milli-seconds, between 0.01 and 1.28 seconds. If the periodicalReporting IE is included in CommonlEsRequestLocationlnformation, this field should not be included by the location server and shall be ignored by the target device (if included).

[0393] - responseTimeEarlyFix indicates the maximum response time as measured between receipt of the RequestLocationlnformation and transmission of a ProvideLocationlnformation containing early location measurements or an early location estimate. If the unit field is absent, this is given as an integer number of seconds between 1 and 128. If the unit field is present with enumerated value 'ten-seconds', the maximum response time is given in units of 10-seconds, between 10 and 1280 seconds. If the unit field is present with enumerated value 'ten-milli-seconds', the maximum response time is given in units of 10-milli-seconds, between 0.01 and 1.28 seconds. When this IE is included, a target should send a ProvideLocationlnformation (or more than one ProvideLocationlnformation if location information will not fit into a single message) containing early location information according to the responseTimeEarlyFix IE and a subsequent ProvideLocationlnformation (or more than one ProvideLocationlnformation if location information will not fit into a single message) containing final location information according to the time IE. A target shall omit sending a ProvideLocationlnformation if the early location information is not available at the expiration of the time value in the responseTimeEarlyFix IE. A server should set the responseTimeEarlyFix IE to a value less than that for the time IE. A target shall ignore the responseTimeEarlyFix IE if its value is not less than that for the time IE.

[0394] - unit indicates the unit of the time and responseTimeEarlyFix fields. Enumerated value 'ten-seconds' corresponds to a resolution of 10 seconds. Enumerated value 'ten-milli-seconds' corresponds to a resolution of 0.01 seconds. If this field is absent, the unit / resolution is 1 second. Enumerated value 'ten- milli-seconds' is only applicable for NR E-CID Positioning, NR DL-TDOA Positioning, NR DL-AoD Positioning, and NR Multi-RTT Positioning. If the enumerated value 'ten-milli-seconds' is included for methods others than NR E-CID Positioning, NR DL-TDOA Positioning, NR DL-AoD Positioning, and NR Multi-RTT Positioning the target device shall ignore the unit field.

[0395] - velocityRequest indicates whether velocity (or measurements related to velocity) is requested (TRUE) or not (FALSE).

[0396] - responseTimeNB

[0397] If the periodicalReporting IE or responseTime IE is included in Common! EsRequestLocationlnformation, this field should not be included by the location server and shall be ignored by the target device (if included). The UE may decides the AI / ML method to be used or not based upon the configured response Time.

[0398] - timeNB indicates the maximum response time as measured between receipt of the RequestLocationlnformation and transmission of a ProvideLocationlnformation. If the unitNB field is absent, this is given as an integer number of seconds between 1 and 512. If the unitNB field is present, the maximum response time is given in units of 10-seconds, between 10 and 5120 seconds.

[0399] - responseTimeEarlyFixNB indicates the maximum response time as measured between receipt of the RequestLocationlnformation and transmission of a ProvideLocationlnformation containing early location measurements or an early location estimate. If the unitNB field is absent, this is given as an integer number of seconds between 1 and 512. If the unitNB field is present, the maximum response time is given in units of 10-seconds, between 10 and 5120 seconds. When this IE is included, a target should send a ProvideLocationlnformation (or more than one ProvideLocationlnformation if location information will not fit into a single message) containing early location information according to the responseTimeEarlyFixNB IE and a subsequent ProvideLocationlnformation (or more than one ProvideLocationlnformation if location information will not fit into a single message) containing final location information according to the timeNB IE. A target shall omit sending a ProvideLocationlnformation if the early location information is not available at the expiration of the time value in the responseTimeEarlyFixNB IE. A server should set the responseTimeEarlyFixNB IE to a value less than that for the timeNB IE. A target shall ignore the responseTimeEarlyFixNB IE if its value is not less than that for the timeNB IE.

[0400] - unitNB indicates the unit of the timeNB and responseTimeEarlyFixNB fields. Enumerated value 'ten-

[0401]

[0402] second corresponds to a resolution of 10 seconds. If this field is absent, the unit / resolution is 1 second.CommonlEsRequestLocationlnformation field descriptions

[0403] - horizontalAccuracyExt indicates the maximum horizontal error in the location estimate at an indicated confidence level. The 'accuracyExf corresponds to the encoded high accuracy uncertainty as defined in TS 23.032

[0015] and 'confidence' corresponds to confidence as defined in TS 23.032

[0015] , This field should not be included by the location server and shall be ignored by the target device if the horizontalAccuracy field is included in QoS.

[0404] - verticalAccuracyExt indicates the maximum vertical error in the location estimate at an indicated confidence level and is only applicable when a vertical coordinate is requested. The 'accuracyExf corresponds to the encoded high accuracy uncertainty as defined in TS 23.032

[0015] and 'confidence' corresponds to confidence as defined in TS 23.032

[0015] , This field should not be included by the location server and shall be ignored by the target device if the verticalAccuracy field is included in QoS.

[0405] i All QoS requirements shall be obtained by the target device to the degree possible but it is permitted to return a i response that does not fulfill all QoS requirements if some were not attainable. The single exception is time and I timeNB which shall always be fulfilled - even if that means not fulfilling other QoS requirements.

[0406] i A target device supporting NB-loT access shall support the responseTimeNB IE.

[0407] I A target device supporting HA GNSS shall support the HorizontalAccuracyExt, VerticalAccuracyEx, and unit fields with i enumerated value 'ten-seconds'.

[0408] I A target device supporting NB-loT access and HA GNSS shall support the unitNB field.

[0409] : environment

[0410] i This field provides the target device with information about expected multipath and non line of sight (NLOS) in the I current area. The following values are defined:

[0411] - badArea: possibly heavy multipath and NLOS conditions (e.g. bad urban or urban).

[0412] - notBadArea: no or light multipath and usually LOS conditions (e.g. suburban or rural).

[0413] - mixedArea: environment that is mixed or not defined.

[0414] i If this field is absent, a default value of 'mixedArea' applies.

[0415] : locationCoordinateTypes

[0416] i This field provides a list of the types of location estimate that the target device may return when a location estimate is [ obtained by the target.

[0417] i velocityTypes

[0418] i This fields provides a list of the types of velocity estimate that the target device may return when a velocity estimate is I obtained by the target.

[0419] i messageSizeLimitNB

[0420] i This field provides an octet limit on the amount of location information a target device can return.

[0421] - measurementLimit indicates the maximum amount of location information the target device should return in response to the RequestLocationlnformation message received from the location server.

[0422] The limit applies to the overall size of the LPP message at LPP level (LPP Provide Location Information), and is specified in steps of 100 octets. The message size limit is then given by the value provided in

[0423] i measurementLimit ti mes 100 octets.

[0424] i segmentationinfo

[0425] i This field indicates whether this RequestLocationlnformation message is one of many segments, as specified in I clause 4.3.5

[0426] i scheduledLocationTime

[0427] i This field indicates that the target device is requested to obtain location measurements or location estimate valid at i the scheduledLocationTime T and comprises the following subfields:

[0428] - utcTime provides Tin UTC in the form of YYMMDDhhmmssZ.

[0429] - gnssTime provides Tin GNSS system time of the GNSS indicated by gnss-TimelD.

[0430] - gnss-TOD-msec specifies the GNSS TOD in 1-milli-second resolution rounded down to the nearest millisecond unit.

[0431] - networkTime provides Tin E-UTRA or NR network time.

[0432] - Ite-PhysCellld, Ite-ArfcnEUTRA, Ite-CellGloballd identifies the reference cell (E-UTRA) that is used for the network time.

[0433] - Ite-systemFrameNumber specifies the system frame number in E-UTRA.

[0434] - nr-PhysCelllD, nr-ARFCN, nr-CellGloballD identifies the reference cell (NR) that is used for the network time.

[0435] - nr-SFN specifies the system frame number in NR.

[0436] - nr-Slot specifies the slot number in NR for the indicated subcarrier spacing (SCS). The total NR network time is given by nr-SFN + nr-Slot.

[0437] - relativeTime provides T in seconds from current time, where current time is defined as the time the CommonlEsRequestLocationlnformation was received.

[0438] : NOTE 1: A location estimate returned to an LCS Client, AF or UE for a scheduled location time can be treated by the LCS Client, AF or UE as an estimate of the location of the UE at the scheduled location time (see TS 23.273

[0042] ).

[0439] i NOTE 2: If this field is present, at least one of utcTime, gnssTime, networkTime, or relativeTime shall be present. i targetlntegrityRisk

[0440] i This field indicates the TIR forwhich the PL is requested. The TIR is calculated by P=10-0.1n[hour-1] where n is the:

[0441]

[0442] value of targetlntegrityRisk and the range is 10-1to 10-9per hour.Figure 9 depicts an example of the arrangement that the wireless device 121 may comprise to perform the method described in Figure 4. The wireless device 121 is configured to operate in the wireless communication network 100.

[0443] Several embodiments are comprised herein. It should be noted that the examples herein are not mutually exclusive. One or more embodiments may be combined, where applicable. All possible combinations are not described to simplify the description. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the wireless device 121 and will thus not be repeated here to simplify the description.

[0444] The wireless device 121 may comprise an input and output interface 10 configured to communicate with each other. The input and output interface 10 may comprise a receiver, e.g. wired and / or wireless, (not shown) and a transmitter, e.g. wired and / or wireless, (not shown).

[0445] The embodiments herein may be implemented through a respective processor or one or more processors, such as at least one processor 11 of a processing circuitry in the wireless device 121 depicted in Figure 9, together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the wireless device 121. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the wireless device 121.

[0446] The wireless device 121 and / or processor 11 is configured to handle location estimation in the wireless communication network

[0447] The wireless device 121 and / or processor 11 is configured to receive a location request message for location estimation from a location management node 130. The request indicates one or more positioning methods for obtaining the location estimation, including a UE-based direct AI / ML positioning method. The request may further indicate a UE-based direct AI / ML positioning method as a preferred positioning method.

[0448] The wireless device 121 and / or processor 11 is configured to select a positioning method from the one or more positioning methods, taking the indication of the preferred positioning method into account. In some embodiments disclosed herein the wireless device 121 and / or processor 11 is configured to select the preferred positioning method from the one or more positioning methods.The wireless device 121 and / or processor 11 is configured to estimate a location of the wireless device 121 based on a positioning method of the one or more indicated positioning methods. Specifically, the wireless device 121 and / or processor 11 is configured to estimate a location of the wireless device 121 based on the UE-based direct A I / ML positioning method.

[0449] The wireless device 121 and / or processor 11 is configured to send a location response message comprising the obtained location estimation to the location management node 130. The location message indicates the positioning method used to obtain the location estimation. Specifically, the location response message further indicates the UE-based direct AI / ML positioning method.

[0450] In some embodiments, the wireless device 121 and / or processor may further be configured to send a message to the location management node 130. The message is adapted to indicate that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0451] In some embodiments, the wireless device 121 and / or processor may further be configured to indicate the UE-based direct AI / ML positioning method in an IE in the location response message.

[0452] In some embodiments herein the location request message further indicates the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods. In other words, the wireless device 121 and / or processor may further be configured to indicate the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods in the location request message.

[0453] In some embodiments, the preferred positioning method is indicated in an IE in the location request message.

[0454] In some embodiments, the wireless device 121 is configured to select the positioning method by selecting the preferred positioning method from the one or more positioning methods.

[0455] In some embodiments, the location request message is adapted to comprise a response time parameter indicating the wireless device 121 to select the positioning method that takes the shortest amount of time of the one or more positioning methods.

[0456] The wireless device 121 may further comprise respective a memory 12 comprising one or more memory units. The memory 12 comprises instructions executable by the processor 11 in the wireless device 121.

[0457] The memory 12 is arranged to be used to store instructions, data, configurations, packets, AI / MAL models, capabilities, location estimations, measurements, estimation times,positioning methods, and applications to perform the methods herein when being executed in the wireless device 121.

[0458] In some embodiments, a computer program 13 comprises instructions, which when executed by the at least one processor 11, cause the at least one processor 11 of the wireless device 121 to perform the actions above.

[0459] In some embodiments, a respective carrier 14 comprises the respective computer program 13, wherein the carrier 14 is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

[0460] Thus, embodiments herein may disclose the wireless device 121 configured to handle location estimation. The wireless device 121 is configured to operate in the wireless communication network 100. The wireless device 121 comprises the processor 11 and the memory 12, said memory 12 comprising instructions executable by said processor 11 whereby said wireless device 121 is operative to perform any of the methods herein.

[0461] As will be readily understood by those familiar with communications design, that functions means or modules may be implemented using digital logic and / or one or more microcontrollers, microprocessors, or other digital hardware. In some embodiments, several or all of the various functions may be implemented together, such as in a single applicationspecific integrated circuit (ASIC), or in two or more separate devices with appropriate hardware and / or software interfaces between them. Several of the functions may be implemented on a processor shared with other functional components of a radio network node, for example.

[0462] Alternatively, several of the functional elements of the processing means discussed may be provided through the use of dedicated hardware, while others are provided with hardware for executing software, in association with the appropriate software or firmware. Thus, the term “processor” or “controller” as used herein does not exclusively refer to hardware capable of executing software and may implicitly include, without limitation, digital signal processor (DSP) hardware, read-only memory (ROM) for storing software, random-access memory for storing software and / or program or application data, and non-volatile memory. Other hardware, conventional and / or custom, may also be included. Designers of communications receivers will appreciate the cost, performance, and maintenance trade-offs inherent in these design choices.

[0463] Any appropriate steps, methods, features, functions, or benefits disclosed herein may be performed through one or more functional units or modules of one or more virtual apparatuses. Each virtual apparatus may comprise a number of these functional units. These functional units may be implemented via processing circuitry, which may include one or more microprocessor or microcontrollers, as well as other digital hardware, which may include digitalsignal processors (DSPs), special-purpose digital logic, and the like. The processing circuitry may be configured to execute program code stored in memory, which may include one or several types of memory such as read-only memory (ROM), random-access memory (RAM), cache memory, flash memory devices, optical storage devices, etc. Program code stored in memory includes program instructions for executing one or more telecommunications and / or data communications protocols as well as instructions for carrying out one or more of the techniques described herein. In some implementations, the processing circuitry may be used to cause the respective functional unit to perform corresponding functions according one or more embodiments of the present disclosure.

[0464] Figure 10 depicts an example of the arrangement that the location management node 130 may comprise to perform the method described in Figure 5. The location management node 130 is configured to operate in the wireless communication network 100.

[0465] Several embodiments are comprised herein. It should be noted that the examples herein are not mutually exclusive. One or more embodiments may be combined, where applicable. All possible combinations are not described to simplify the description. Components from one embodiment may be tacitly assumed to be present in another embodiment and it will be obvious to a person skilled in the art how those components may be used in the other exemplary embodiments. The detailed description of some of the following corresponds to the same references provided above, in relation to the actions described for the location management node 130 and will thus not be repeated here to simplify the description.

[0466] The location management node 130 may comprise an input and output interface 20 configured to communicate with each other. The input and output interface 20 may comprise a receiver, e.g. wired and / or wireless, (not shown) and a transmitter, e.g. wired and / or wireless, (not shown).

[0467] The embodiments herein may be implemented through a respective processor or one or more processors, such as at least one processor 21 of a processing circuitry in the location management node 130 depicted in Figure 10, together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the location management node 130. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the location management node 130.

[0468] The location management node 130 and / or processor 21 is configured to handle location estimation in the wireless communication network 100.The location management node 130 and / or processor 21 is configured to send a location request message for location estimation to a wireless device 121. The request adapted to indicate one or more positioning methods for obtaining the location estimation and further to indicate a UE-based direct AI / ML positioning method. In some embodiments disclosed herein the UE-based direct AI / ML positioning method is indicated as a preferred positioning method of the one or more positioning methods.

[0469] The location management node 130 and / or processor 21 is configured to receive a location message comprising the obtained location estimation from the wireless device 121. The location response message indicates the positioning method used to obtain the location estimation. Specifically, the location response message further indicates the UE-based direct AI / ML positioning method.

[0470] In some embodiments, the location management node 130 and / or processor 21 may further be configured to receive a message from the wireless device 121. The message is adapted to indicate that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0471] In some embodiments herein the location management node 130 is further configured to receive the indication of the UE-based direct AI / ML positioning method in the IE in the location response message.

[0472] In some embodiments, the positioning method used to estimate the location is indicated in an Information Element, IE, in the location response message.

[0473] In some embodiments, the preferred positioning method is adapted to be indicated in an IE in the location request message.

[0474] In some embodiments, the location request message is adapted to comprise a response time parameter, and wherein the response time parameter is adapted to indicate the wireless device 121 to select a positioning method taking the shortest amount of time of the one or more positioning methods.

[0475] The location management node 130 may further comprise respective a memory 22 comprising one or more memory units. The memory 22 comprises instructions executable by the processor 21 in the location management node 130.

[0476] The memory 22 is arranged to be used to store instructions, data, configurations, packets, AI / MAL models, capabilities, location estimations, measurements, estimation times, positioning methods, and applications to perform the methods herein when being executed in the location management node 130.

[0477] In some embodiments, a computer program 23 comprises instructions, which when executed by the at least one processor 21, cause the at least one processor 21 of the location management node 130 to perform the actions above.In some embodiments, a respective carrier 24 comprises the respective computer program 23, wherein the carrier 24 is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

[0478] Thus, embodiments herein may disclose the location management node 130 configured to handle location estimation. The location management node 130 is configured to operate in the wireless communication network 100. The location management node 130 comprises the processor 21 and the memory 22, said memory 22 comprising instructions executable by said processor 21 whereby said location management node 130 is operative to perform any of the methods herein.

[0479] As will be readily understood by those familiar with communications design, that functions means or modules may be implemented using digital logic and / or one or more microcontrollers, microprocessors, or other digital hardware. In some embodiments, several or all of the various functions may be implemented together, such as in a single applicationspecific integrated circuit (ASIC), or in two or more separate devices with appropriate hardware and / or software interfaces between them. Several of the functions may be implemented on a processor shared with other functional components of a radio network node, for example.

[0480] Alternatively, several of the functional elements of the processing means discussed may be provided through the use of dedicated hardware, while others are provided with hardware for executing software, in association with the appropriate software or firmware. Thus, the term “processor” or “controller” as used herein does not exclusively refer to hardware capable of executing software and may implicitly include, without limitation, digital signal processor (DSP) hardware, read-only memory (ROM) for storing software, random-access memory for storing software and / or program or application data, and non-volatile memory. Other hardware, conventional and / or custom, may also be included. Designers of communications receivers will appreciate the cost, performance, and maintenance trade-offs inherent in these design choices.

[0481] Any appropriate steps, methods, features, functions, or benefits disclosed herein may be performed through one or more functional units or modules of one or more virtual apparatuses. Each virtual apparatus may comprise a number of these functional units. These functional units may be implemented via processing circuitry, which may include one or more microprocessor or microcontrollers, as well as other digital hardware, which may include digital signal processors (DSPs), special-purpose digital logic, and the like. The processing circuitry may be configured to execute program code stored in memory, which may include one or several types of memory such as read-only memory (ROM), random-access memory (RAM), cache memory, flash memory devices, optical storage devices, etc. Program code stored inmemory includes program instructions for executing one or more telecommunications and / or data communications protocols as well as instructions for carrying out one or more of the techniques described herein. In some implementations, the processing circuitry may be used to cause the respective functional unit to perform corresponding functions according one or more embodiments of the present disclosure.

[0482] Embodiments

[0483] Below, some example Embodiments 1-24 are shortly described. See e.g., Figures 3-10.

[0484] Embodiment 1. A method performed by a wireless device 121 e.g., for handling location estimation in a wireless communication network 100, the method comprising any one or more out of:

[0485] receiving 403 a location request message for location estimation from a location management node 130, the request indicating one or more positioning methods for obtaining the location estimation and further indicating a UE-based direct AI / ML positioning method as a preferred positioning method,

[0486] selecting 404 a positioning method from the one or more positioning methods, taking the indication of the preferred positioning method into account.

[0487] estimating 405 a location of the wireless device 121 based on a positioning method of the one or more indicated positioning methods, and

[0488] sending 406 a location response message comprising the obtained location estimation to the location management node 130, the location response message indicating the positioning method used to obtain the location estimation.

[0489] Embodiment 2. The method according to embodiment 1, wherein the method further comprises:

[0490] sending 402 a message to the location management node 130, which message indicates that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0491] Embodiment 3. The method according to any of embodiments 1-2, wherein the positioning method used to estimate the location is indicated in an Information Element, IE, in the location response message.

[0492] Embodiment 4. The method according to any of embodiments 1-3, wherein the preferred positioning method is indicated in an IE in the location request message.Embodiment 5. The method according to any of embodiments 1-4, wherein selecting 404 the positioning method comprises selecting the preferred positioning method.

[0493] Embodiment 6. The method according to any of embodiments 1-4, wherein the location request message comprises a response time parameter indicating the wireless device 121 to select 404 the positioning method that takes the shortest amount of time of the one or more positioning methods.

[0494] Embodiment 7. A method performed by a location management node 130 e.g., for handling location estimation in a wireless communication network 100, the method comprising any one or more out of:

[0495] sending 504 a location request message for location estimation to a wireless device 121, the request indicating one or more positioning methods for obtaining the location estimation and further indicating a UE-based direct AI / ML positioning method as a preferred positioning method,

[0496] receiving 505 a location response message comprising the obtained location estimation from the wireless device 121, the location response message indicating the positioning method used to obtain the location estimation.

[0497] Embodiment 8. The method according to embodiment 7, wherein the method further comprises:

[0498] receiving 503 a message from the wireless device 121, which message indicates that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0499] Embodiment 9. The method according to any of embodiments 7-8, wherein the positioning method used to estimate the location is indicated in an Information Element, IE, in the location response message.

[0500] Embodiment 10. The method according to any of embodiments 7-9, wherein the preferred positioning method is indicated in an IE in the location request message.

[0501] Embodiment 11. The method according to any of embodiments 7-10, wherein the location request message comprises a response time parameter, and wherein the response time parameter indicates the wireless device 121 to select a positioning method taking the shortest amount of time of the one or more positioning methods.Embodiment 12. A wireless device 121 e.g., configured to handle location estimation in a wireless communication network 100, the wireless device 121 further being configured to: receive a location request message for location estimation from a location management node 130, the request adapted to indicate one or more positioning methods for obtaining the location estimation and further to indicate a UE-based direct AI / ML positioning method as a preferred positioning method,

[0502] select a positioning method from the one or more positioning methods, taking the indication of the preferred positioning method into account.

[0503] estimate a location of the wireless device 121 based on a positioning method of the one or more indicated positioning methods, and

[0504] send a location response message adapted to comprise the obtained location estimation to the location management node 130, the location response message adapted to indicate the positioning method used to obtain the location estimation.

[0505] Embodiment 13. The wireless device 121 according to embodiment 12, wherein the wireless device 121 is further configured to:

[0506] send a message to the location management node 130, which message is adapted to indicate that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0507] Embodiment 14. The wireless device 121 according to any of embodiments 12-13, wherein the positioning method used to estimate the location is adapted to be indicated in an Information Element, IE, in the location response message.

[0508] Embodiment 15. The wireless device 121 according to any of embodiments 12-14, wherein the preferred positioning method is indicated in an IE in the location request message.

[0509] Embodiment 16. The wireless device 121 according to any of embodiments 12-15, wherein the wireless device 121 is configured to select the positioning method by selecting the preferred positioning method.

[0510] Embodiment 17. The wireless device 121 according to any of embodiments 12-15, wherein the location request message is adapted to comprise a response time parameter indicating the wireless device 121 to select the positioning method that takes the shortest amount of time of the one or more positioning methods.Embodiment 18. A location management node 130 e.g., configured to handle location estimation in a wireless communication network 100, the location management node 130 further being configured to:

[0511] send a location request message for location estimation to a wireless device 121, the request adapted to indicate one or more positioning methods for obtaining the location estimation and further to indicate a UE-based direct AI / ML positioning method as a preferred positioning method,

[0512] receive a location response message adapted to comprise the obtained location estimation from the wireless device 121, the location response message adapted to indicate the positioning method used to obtain the location estimation.

[0513] Embodiment 19. The location management node 130 according to embodiment 18, wherein the location management node 130 is further configured to:

[0514] receive a message from the wireless device 121, which message is adapted to indicate that the wireless device 121 has an applicable model for UE-based direct AI / ML positioning.

[0515] Embodiment 20. The location management node 130 according to any of embodiments 18-19, wherein the positioning method used to estimate the location is adapted to be indicated in an Information Element, IE, in the location response message.

[0516] Embodiment 21. The location management node 130 according to any of embodiments 18-20, wherein the preferred positioning method is adapted to be indicated in an IE in the location request message.

[0517] Embodiment 22. The location management node 130 according to any of embodiments 18-21, wherein the location request message is adapted to comprise a response time parameter, and wherein the response time parameter is adapted to indicate the wireless device 121 to select a positioning method taking the shortest amount of time of the one or more positioning methods.

[0518] Embodiment 23. A computer program comprising instructions, which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the embodiments 1-11, as performed by the wireless device 121, and the location management node 130, respectively.

[0519] Embodiment 24. A carrier comprising the computer program of embodiment 23, wherein the carrier is one of an electronic signal, an optical signal, an electromagnetic signal,a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

[0520] ADDITIONAL EXPLANATION

[0521] 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.

[0522] Figure 11 shows an example of a communication system QQ100 in accordance with some embodiments.

[0523] In the example, the communication system QQ100 includes a telecommunications network QQ102 that includes an access network QQ104, such as a radio access network (RAN), and a core network QQ106, which includes one or more core network nodes QQ108. The access network QQ104 includes one or more access network nodes or base stations of various types, access network nodes QQ110A and QQ110B are depicted (which may be collectively referred to as network nodes QQ110), or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points (APs). Some embodiments of the access network QQ104 may include more than one access network technology. The network nodes QQ110 of access network QQ104 facilitate direct or indirect connection of wireless devices, also referred to as user equipments (UEs), such as by connecting UEs QQ112A, QQ112B, QQ112C, and QQ112D (one or more of which may be generally referred to as UEs QQ112) to the core network QQ106 over one or more wireless connections.

[0524] Moreover, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunications network QQ102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a network node in the telecommunications network QQ102 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other network nodes to implement one or more functionalities of any network node in the telecommunications network QQ102, including one or more access network nodes QQ110 and / or core network nodes QQ108.

[0525] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (theadjective “open” designating support of an ORAN specification). An ORAN network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1, F1, W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN network node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies.

[0526] The network nodes QQ110 facilitate direct or indirect connection of one or more UEs QQ112 to the core network QQ106 over one or more wireless connections. Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system QQ100 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system QQ100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0527] The UEs QQ112 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes QQ110 and other communication devices. Similarly, the network nodes QQ108, QQ110 are arranged, capable, configured, and / or operable to communicate directly or indirectly (e.g., via other devices of telecommunications network QQ102) with the UEs QQ112 and / or with other network nodes or equipment in the telecommunications network QQ102 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunications network QQ102. More specifically, UEs QQ112 may send messages, data, and / or other signals to network nodes QQ108, QQ110 or other elements of the telecommunications network QQ102 by transmitting such signals to the relevant device directly without the signals passing through any intervening devices or by transmitting such signals to the relevant device indirectly through an intervening device (or multiple intervening devices) that then transmit the signal to the relevant device. Similarly, network nodes QQ108, QQ110 may send messages, data, and other signals to UEs QQ1122, other network nodes QQ108, QQ110, and other devices in telecommunications network QQ102 directly or indirectly. As one specific example, a core network node 108 may transmit a particular message to a UE QQ112 by transmitting the message to an accessnetwork node QQ110 that will then transmit the message to the intended UE QQ112. Similarly, a core network node 108 may receive a particular message from a UE QQ112 by receiving the message from an access network node QQ110 that itself received the message from the UE QQ112.

[0528] In the depicted example, the core network QQ106 connects elements of the access network QQ104 (e.g., one or more of the network nodes QQ110) to one or more host computing systems, such as host QQ116. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network QQ106 includes one or more core network nodes (e.g., core network node QQ108) of various types, one or more of which may be generally referred to as network nodes QQ108. Network nodes QQ108 are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, access network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node QQ108. Example core network nodes provide functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0529] The host QQ116 may be under the ownership or control of a service provider other than an operator or provider of the access network QQ104 and / or the telecommunications network QQ102. The host QQ116 may be operated by the service provider or on behalf of the service provider. The host QQ116 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0530] As a whole, the communication system QQ100 of Figure 11 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system QQ100 may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (Wi-Fi); and / or any other appropriatewireless communication standard, such as the Worldwide Interoperability for Microwave Access (Wi-Max), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, Li-Fi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox. Moreover, the communication system QQ100 may be configured to support multiple different standards, protocols, or other rule sets, with individual components supporting all of the relevant rule sets or with different components or sub-systems within the communication system QQ100 supporting different standards, protocols, or rule sets.

[0531] As one example, in certain embodiments, access network QQ104 may contain some access network nodes QQ110 that support 3GPP radio access technologies (RAT), such as LTE or NR, while other access network nodes QQ110 support (or the same access network nodes QQ110 additionally support) non-3GPP RATs, such as Wi-Fi or a proprietary RAT. As another example, telecommunications network QQ102 may support multiple generations of related communication standards (e.g., 4G and 5G 3GPP communication standards) and, as a result, may include an access network 104 and / or a core network 106 that supports multiple different standard generations or may include multiple access networks 104 and / or multiple core networks 106 with individual networks 104, 106 supporting different standard generations.

[0532] Telecommunications network QQ102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunications network QQ102. For example, the telecommunications network QQ102 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and / or Massive Machine Type Communication (mMTC) / Massive loT services to yet further UEs.

[0533] In some examples, one or more of the UEs QQ112 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network QQ104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network QQ104. Additionally, a UE may be configured for operating in single- or multi-RAT or multistandard 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).

[0534] In the example, the hub QQ114 communicates with the access network QQ104 to facilitate indirect communication between one or more UEs (e.g., UE QQ112C and / or QQ112D) and network nodes (e.g., network node QQ110B). In some examples, the hub QQ114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub QQ114 may bea broadband router enabling access to the core network QQ106 for the UEs. As another example, the hub QQ114 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes QQ110, or by executable code, script, process, or other instructions in the hub QQ114.

[0535] As another example, the hub QQ114 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub QQ114 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub QQ114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub QQ114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub QQ114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0536] The hub QQ114 may have a constant / persistent or intermittent connection to the network node QQ110B. The hub QQ114 may also allow for a different communication scheme and / or schedule between the hub QQ114 and UEs (e.g., UE QQ112C and / or QQ112D), and between the hub QQ114 and the core network QQ106. In other examples, the hub QQ114 is connected to the core network QQ106 and / or one or more UEs via a wired connection.

[0537] Moreover, the hub QQ114 may be configured to connect to an M2M service provider over the access network QQ104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes QQ110 while still connected via the hub QQ114 via a wired or wireless connection. In some embodiments, the hub QQ114 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node QQ110B. In other embodiments, the hub QQ114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node QQ110B, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0538] Figure 12 is another example of a communication system QQ200 according to some embodiments. As used herein, the communication system QQ200 includes multiple access points (APs) QQ210 (with four exemplary APs QQ210A, QQ210B, QQ210C, and QQ210D being depicted) and multiple wireless devices, referred to in the context of communication system QQ200 as stations (STAs) QQ212 (referred to individually as STA QQ212A, STA QQ212B, STA QQ212C, STA QQ212D, and STA QQ212E). STA QQ212A is served by AP QQ210A in a first basic service set (BSS) QQ220A. STA QQ210B and STA QQ210C are served by AP QQ210B in a second BSS, BSS QQ220B. STA QQ212D is served by AP QQ210C in a third BSS, BSS QQ220C. STA QQ212E is served by AP QQ210D in a fourth BSS, BSS QQ220D. Stations QQ212 may be non-AP STAs and correspond to various kindsof wireless devices, for example, user terminals, such as mobile or stationary computing devices like smartphones, laptop computers, desktop computers, tablet computers, gaming devices, head-mounted displays (HMDs) for Augmented Reality (AR) or Virtual Reality (VR), or the like. Further, stations QQ212 could, for example, correspond to other kinds of equipment like smart home devices, printers, multimedia devices, data storage devices, or the like.

[0539] Each of STAs QQ212 may connect through a radio link to one of APs QQ210. For example, depending on location or channel conditions experienced by a given STA QQ212, the STA may select an appropriate AP and BSS for establishing the radio link. The radio link may be based on one or more orthogonal frequency-division multiplexing (OFDM) carriers from a frequency spectrum that is shared on the basis of a contention-based mechanism, e.g., an unlicensed or license exempt band like 2.4 GHz Industrial, Scientific, and Medical (ISM) band, the 5 GHz band, the 6 GHz band, or the 60 GHz band.

[0540] Each AP QQ210 may provide data connectivity to STAs QQ212 connected to a particular AP QQ210. As illustrated, APs QQ210 may be connected to a data network QQ230. In this way, APs QQ210 may also provide data connectivity between STAs QQ212 and other entities, e.g., to one or more servers, service providers, data sources, data sinks, user terminals, or the like. Accordingly, the radio link established between a given STA QQ212 and its serving AP QQ210 may be used for providing various kinds of services to STA QQ212, e.g., a voice service, a multimedia service, or other data service. Such services may be based on applications that are executed on STA QQ212 and / or on a device linked to STA QQ212. By way of example, Figure 12 illustrates an application service platform QQ232 provided in data network QQ230. The application(s) executed on STA QQ212 and / or on one or more other devices linked to STA QQ212 may use the radio link for data communication with one or more other STA QQ212 and / or the application service platform QQ232, thereby enabling utilization of the corresponding service(s) at STA QQ212.

[0541] Figure 13 shows a wireless device QQ300, which may be configured to operate in communication system QQ100 of Figure 11 or in communication system QQ200 of Figure 12. The wireless device QQ300 may be alternatively referred to as a UE QQ300, like a UE QQ112 within the context of communication system QQ100, or as a station (STA) QQ300 or as a non-access-point station (non-AP STA) QQ300, like a STA QQ212 within the context of the communication system QQ200, in accordance with respective embodiments. As used herein, a wireless device refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other wireless devices. Examples of a wireless device include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage device, playbackappliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, and wireless terminal. Other examples include any type of UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-IoT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0542] A wireless device QQ300 may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to-everything (V2X). In other examples, wireless device QQ300 may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, wireless device QQ300 may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, wireless device QQ300 may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0543] In particular embodiments, wireless device QQ300 includes processing circuitry QQ302 that is operatively coupled via a bus QQ304 to an input / output interface QQ306, a power source QQ308, a memory QQ310, a communication interface QQ312, and / or any other component, or any combination thereof. Certain embodiments of wireless device QQ300 may include all or a subset of the components shown in Figure 13. The level of integration between the components may vary from one embodiment of wireless device QQ300 to another. In general, in a particular embodiment of wireless device QQ300, processing circuitry QQ302, input / output interface QQ306, power source QQ308, memory QQ310, and communication interface QQ312 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of wireless device QQ300. Further, certain embodiments of wireless devices QQ300 may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0544] The processing circuitry QQ302 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory QQ310. The processing circuitry QQ302 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above.For example, the processing circuitry QQ302 may include multiple central processing units (CPUs).

[0545] In the example, the input / output interface QQ306 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into wireless device QQ300. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0546] In some embodiments, the power source QQ308 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used to supply power to circuitry or to charge an associated battery. The power source QQ308 may further include power circuitry for delivering power from the power source QQ308 itself, and / or an external power source, to the various parts of wireless device QQ300 via input circuitry or an interface such as an electrical power cable. Power source QQ308 may perform any formatting, converting, or other modification to make accessible power suitable for the respective components of the wireless device QQ300 to which power is supplied.

[0547] The memory QQ310 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory QQ310 includes one or more programs QQ314, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data QQ316. The memory QQ310 may store, for use by wireless device QQ300, any of a variety of various operating systems or combinations of operating systems.

[0548] The memory QQ310 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD)optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (IIICC) including one or more subscriber identity modules (SIMs), such as a IISIM and / or ISIM, other memory, or any combination thereof. The IIICC may for example be an embedded IIICC (elllCC), integrated IIICC (illlCC) or a removable IIICC commonly known as ‘SIM card.’ The memory QQ310 may allow wireless device QQ300 to access instructions, programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory QQ310, which may be or comprise a device-readable storage medium.

[0549] The processing circuitry QQ302 may be configured to communicate with an access network or other network via or using the communication interface QQ312. The communication interface QQ312 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna QQ322. The communication interface QQ312 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another wireless device or a network node in an access network). Each transceiver may include a transmitter QQ318 and / or a receiver QQ320 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth).

[0550] Moreover, the transmitter QQ318 and receiver QQ320 may be coupled to one or more antennas (e.g., antenna QQ322) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0551] In the illustrated embodiment, communication functions of the communication interface QQ312 may include cellular communication, Wi-Fi communication (e.g., according to an IEEE 802.11 family standard), LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.In particular embodiments, wireless device QQ300 may provide an output of data captured via a sensor, through its communication interface QQ312, via a wireless connection to a network node, and / or in any appropriate manner. Data captured by sensors of a wireless device QQ300 can be communicated through a wireless connection to a network node via another wireless device QQ300. In particular embodiments, such output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0552] As another example, wireless device QQ300 comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, wireless device QQ300 may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0553] Wireless device QQ300, 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, 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 wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. In particular embodiments, wireless device QQ300 represents an IoT device that 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 example embodiment of wireless device QQ300 shown in Figure 13.

[0554] As yet another specific example, in an IoT scenario, wireless device QQ300 may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another wireless device and / or a network node. Wireless device QQ300 may in this case be an M2M device, whichmay in a 3GPP context be referred to as an MTC device. As one particular example, wireless device QQ300 may implement the 3GPP NB-IoT standard. In other scenarios, wireless device QQ300 may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0555] In practice, any number of wireless devices QQ300 may be used together with respect to a single use case. For example, a first wireless device QQ300 might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second wireless device QQ300 that is a remote controller operating the drone. When a user makes changes from the remote controller, the first wireless device QQ300 may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second wireless device QQ300 can also include more than one of the functionalities described above. For example, wireless device QQ300 might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0556] Figure 14 shows a network node QQ400 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunications network. In accordance with respective embodiments, network node QQ400 may be configured to operate in communication system QQ100 of Figure 11, like network nodes QQ108 or QQ110, or in communication system QQ200 of Figure 12, like an AP QQ210 or a station QQ212. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU).

[0557] Network nodes QQ400 may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. Network node QQ400 may be a relay node or a relay donor node controlling a relay. Network nodes QQ400 may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0558] Other examples of network nodes QQ400 include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, networkcontrollers 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).

[0559] In particular embodiments, network node QQ400 includes a processing circuitry QQ402, a memory QQ404, a communication interface QQ406, and a power source QQ408. In general, in a particular embodiment of network node QQ400, processing circuitry QQ402, memory QQ404, communication interface QQ406, and power source QQ408 may, in whole or in part, represent or include physical components common to or shared by one or more of the other elements of network node QQ400.

[0560] The network node QQ400 may be composed of multiple distinct network entities (e.g., a NodeB entity and a RNC entity, or a BTS entity and a BSC entity, etc.), which may each have or utilize their own respective physical components. In certain scenarios in which the network node QQ400 comprises multiple such entities (e.g., BTS and BSC), one or more of the separate entities may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network node QQ400 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memories QQ404 or portions of memory QQ404 for different RATs) and some components may be reused (e.g., a same antenna QQ410 may be shared by different RATs). The network node QQ400 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node QQ400, for example GSM, WCDMA, LTE, NR, Wi-Fi (e.g., according to an IEEE 802.11 family standard), Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node QQ400.

[0561] The processing circuitry QQ402 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other components, such as the memory QQ404, to provide network node QQ400 functionality.

[0562] In some embodiments, the processing circuitry QQ402 includes a system on a chip (SOC). In some embodiments, the processing circuitry QQ402 includes one or more of radio frequency (RF) transceiver circuitry QQ412 and baseband processing circuitry QQ414. Insome embodiments, the RF transceiver circuitry QQ412 and the baseband processing circuitry QQ414 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry QQ412 and baseband processing circuitry QQ414 may be on the same chip or set of chips, boards, or units.

[0563] The memory QQ404 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 QQ402. The memory QQ404 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry QQ402 and utilized by the network node QQ400. The memory QQ404 may be used to store any calculations made by the processing circuitry QQ402 and / or any data received via the communication interface QQ406. In some embodiments, the processing circuitry QQ402 and memory QQ404 is integrated.

[0564] The communication interface QQ406 is used in wired or wireless communication of signaling and / or data with UEs, other network nodes, and / or any other network equipment. In the illustrated embodiment, communication interface QQ406 comprises port(s) / terminal(s) QQ416 to send and receive data, for example to and from a network over a wired connection. In particular embodiments, network node QQ300 may be capable of wireless communication and communication interface QQ406 may also include radio front-end circuitry QQ418 that may be coupled to, or in certain embodiments a part of, an antenna QQ410. Particular embodiments of radio front-end circuitry QQ418 include filter(s) QQ420 and amplifier(s) QQ422. The radio front-end circuitry QQ418 may be connected to an antenna QQ410 and processing circuitry QQ402. The radio front-end circuitry may be configured to condition signals communicated between antenna QQ410 and processing circuitry QQ402. The radio front-end circuitry QQ418 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry QQ418 may convert the digital data into a radio signal(s) having the appropriate channel and bandwidth parameters using a combination of filters QQ420 and / or amplifiers QQ422. The radio signal(s) may then be transmitted via the antenna QQ410. Similarly, when receiving data, the antenna QQ410 may collect radio signals which are then converted into digital data by the radio front-end circuitry QQ418. The digital data may be passed to the processing circuitry QQ402. In otherembodiments, the communication interface may comprise different components and / or different combinations of components.

[0565] In certain alternative embodiments, network node QQ400 may be capable of wireless communication but does not include separate radio front-end circuitry QQ418, instead, the processing circuitry QQ402 includes radio front-end circuitry and is connected to the antenna QQ410. Similarly, in some embodiments, all or some of the RF transceiver circuitry QQ412 is part of the communication interface QQ406. In still other embodiments, the communication interface QQ406 includes one or more ports or terminals QQ416, the radio front-end circuitry QQ418, and the RF transceiver circuitry QQ412, as part of a radio unit (not shown), and the communication interface QQ406 communicates with the baseband processing circuitry QQ414, which is part of a digital unit (not shown).

[0566] The antenna QQ410 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna QQ410 may be coupled to the radio front-end circuitry QQ418 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna QQ410 is separate from the network node QQ400 and connectable to the network node QQ400 through one or more interfaces or ports.

[0567] The antenna QQ410, communication interface QQ406, and / or the processing circuitry QQ402 may be configured to perform some or all of the receiving operations and / or obtaining operations described herein as being performed by the network node QQ400. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna QQ410, the communication interface QQ406, and / or the processing circuitry QQ402 may be configured to perform some or all of the transmitting or sending operations described herein as being performed by the network node QQ400. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0568] The power source QQ408 provides power to the various components of network node QQ400 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source QQ408 may further comprise, or be coupled to, power management circuitry to supply the components of the network node QQ400 with power for performing the functionality described herein. For example, the network node QQ400 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source QQ408. As a further example, the power source QQ408 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.Embodiments of the network node QQ400 may include additional components beyond those shown in Figure 14 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node QQ400 may include user interface equipment to allow input of information into the network node QQ400 and to allow output of information from the network node QQ400. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node QQ400.

[0569] Figure 15 is a block diagram illustrating a virtualization environment QQ500 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments QQ500 hosted by one or more of hardware nodes, such as a hardware computing device that operates as an access network node, UE, core network node, or host. Further, in embodiments in which a virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment QQ500 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

[0570] Applications QQ502 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0571] Hardware QQ504 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers QQ506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VM QQ508A and VM QQ508B (which may be collectively referred to as VMs QQ508), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer QQ506 may present a virtual operating platform that appears like networking hardware to one or more of the VMs QQ508.The VMs QQ508 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by virtualization layer QQ506. Different embodiments of the instance of a virtual appliance QQ502 may be implemented on one or more of VMs QQ508, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0572] In the context of NFV, each of the VMs QQ508 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs QQ508, and that part of hardware QQ504 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more of the VMs QQ508 on top of the hardware QQ504 and corresponds to an application QQ502.

[0573] Hardware QQ504 may be implemented in a standalone network node with generic or specific components. Hardware QQ504 may implement some functions via virtualization. Alternatively, hardware QQ504 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration QQ510, which, among others, oversees lifecycle management of applications QQ502. In some embodiments, hardware QQ504 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system QQ512 which may alternatively be used for communication between hardware nodes and radio units.

[0574] 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.

[0575] 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 moreoperations 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.

[0576] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

[0577] ABBREVIATIONS

[0578] At least some of the following abbreviations may be used in this disclosure. If there is an inconsistency between abbreviations, preference should be given to how it is used above. If listed multiple times below, the first listing should be preferred over any subsequent listing(s).

[0579] 3GPP 3rd Generation Partnership Project

[0580] 5G 5th Generation

[0581] 6G 6th Generation

[0582] ABS Almost Blank Subframe

[0583] ARQ Automatic Repeat Request

[0584] AWGN Additive White Gaussian Noise

[0585] BCCH Broadcast Control Channel

[0586] BCH Broadcast Channel

[0587] CA Carrier Aggregation

[0588] CC Carrier Component

[0589] CCCH SDU Common Control Channel SDUCDMA Code Division Multiplex Access

[0590] CE Control Element

[0591] CGI Cell Global Identity

[0592] CHO Conditional Handover

[0593] CIR Channel Impulse Response

[0594] CP Cyclic Prefix

[0595] CPICH Common Pilot Channel

[0596] CQI Channel Quality Information

[0597] C-RNTI Cell RNTI

[0598] CSI Channel State Information

[0599] DCCH Dedicated Control Channel

[0600] DL Downlink

[0601] DM Demodulation

[0602] DMRS Demodulation Reference Signal

[0603] DRX Discontinuous Reception

[0604] DTX Discontinuous Transmission

[0605] DTCH Dedicated Traffic Channel

[0606] DUT Device Under Test

[0607] E-CID Enhanced Cell-ID (positioning method)

[0608] Ec / No Received energy per chip divided by the power density in the band eMBMS Evolved Multimedia Broadcast Multicast Services

[0609] ECGI Evolved CGI

[0610] eNB E-UTRAN NodeB

[0611] ePDCCH Enhanced Physical Downlink Control Channel

[0612] E-SMLC Evolved Serving Mobile Location Center

[0613] E-UTRAN Evolved Universal Terrestrial Radio Access Network

[0614] FDD Frequency Division Duplex

[0615] FFS For Further Study

[0616] gNB Base station in NR

[0617] GNSS Global Navigation Satellite System

[0618] HARQ Hybrid Automatic Repeat Request

[0619] HO Handover

[0620] HOF Handover Failure

[0621] HSPA High Speed Packet Access

[0622] HRPD High Rate Packet Data

[0623] LOS Line of Sight

[0624] LPP LTE Positioning ProtocolLTE Long-Term Evolution

[0625] LTM L1 / L2 Triggered Mobility

[0626] MAC Medium Access Control

[0627] MAC Message Authentication Code

[0628] MBSFN Multimedia Broadcast Multicast Service Single Frequency Network MBSFN ABS MBSFN Almost Blank Subframe

[0629] MCG Master Cell Group

[0630] MDT Minimization of Drive Tests

[0631] MIB Master Information Block

[0632] MME Mobility Management Entity

[0633] MN Master Node

[0634] MRO Mobility Robustness Optimization

[0635] MSC Mobile Switching Center

[0636] Msg Message

[0637] NPDCCH Narrowband Physical Downlink Control Channel

[0638] NR New Radio

[0639] OCNG OFDMA Channel Noise Generator

[0640] OFDM Orthogonal Frequency Division Multiplexing

[0641] OFDMA Orthogonal Frequency Division Multiple Access

[0642] OSS Operations Support System

[0643] OTDOA Observed Time Difference of Arrival

[0644] O& M Operation and Maintenance

[0645] PBCH Physical Broadcast Channel

[0646] P-CCPCH Primary Common Control Physical Channel

[0647] PCell Primary Cell

[0648] PCFICH Physical Control Format Indicator Channel

[0649] PDCCH Physical Downlink Control Channel

[0650] PDCP Packet Data Convergence Protocol

[0651] PDP Power Delay Profile

[0652] PDSCH Physical Downlink Shared Channel

[0653] PGW Packet Gateway

[0654] PHICH Physical Hybrid-ARQ Indicator Channel

[0655] PLMN Public Land Mobile Network

[0656] PMI Precoding Matrix Indicator

[0657] PRACH Physical Random Access Channel

[0658] PRS Positioning Reference Signal

[0659] PSCell Primary Secondary CellPSS Primary Synchronization Signal PUCCH Physical Uplink Control Channel PUSCH Physical Uplink Shared Channel QAM Quadrature Amplitude Modulation QCL Quasi Co-Location / Quasi Co-Located RA Random Access

[0660] RACH Random Access Channel

[0661] RAN Radio Access Network

[0662] RAR Random Access Response

[0663] RAT Radio Access Technology

[0664] RLC Radio Link Control

[0665] RLF Radio Link Failure

[0666] RLM Radio Link Monitoring

[0667] RNC Radio Network Controller

[0668] RNTI Radio Network Temporary Identifier RRC Radio Resource Control

[0669] RRM Radio Resource Management

[0670] RS Reference Signal

[0671] RSCP Received Signal Code Power

[0672] RSRP Reference Symbol Received Power OR Reference Signal Received Power RSRQ Reference Signal Received Quality OR Reference Symbol Received Quality RSSI Received Signal Strength Indicator RSTD Reference Signal Time Difference SCH Synchronization Channel

[0673] Scell Secondary Cell

[0674] SCG Secondary Cell Group

[0675] SDAP Service Data Adaptation Protocol SDU Service Data Unit

[0676] SFN System Frame Number

[0677] SGW Serving Gateway

[0678] SHR Successful Handover Report

[0679] SI System Information

[0680] SIB System Information Block

[0681] SN Secondary Node

[0682] SNR Signal to Noise RatioSON Self-Organizing Network

[0683] SPR Successful PSCell Report

[0684] SS Synchronization Signal

[0685] SSB Synchronization Signal Block (also know as SS / PBCH)

[0686] SSS Secondary Synchronization Signal

[0687] sync / synch Synchronization

[0688] TA Timing Advance

[0689] TCI Transmission Configuration Indicator

[0690] TDD Time Division Duplex

[0691] TDOA Time Difference of Arrival

[0692] TOA Time of Arrival

[0693] TSS Tertiary Synchronization Signal

[0694] TTI Transmission Time Interval

[0695] UE User Equipment

[0696] UL Uplink

[0697] UMTS Universal Mobile Telecommunications System

[0698] USIM Universal Subscriber Identity Module

[0699] UTDOA Uplink Time Difference of Arrival

[0700] WCDMA Wideband CDMA

[0701] WLAN Wireless Local Area Network

[0702] When using the word "comprise" or “comprising”, it shall be interpreted as non- limiting, i.e., meaning "consist at least of".

[0703] The embodiments herein are not limited to the above-described preferred embodiments. Various alternatives, modifications and equivalents may be used. Therefore, the above embodiments should not be taken as limiting the scope of the invention.

[0704] Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and / or is implied from the context in which it is used. All references to a / an / the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any otherembodiments, and vice versa. Other objectives, features and advantages of the enclosed embodiments will be apparent from the following description.

[0705] As used herein, the expression “at least one of:” followed by a list of alternatives separated by commas, and wherein the last alternative is preceded by the “and” term, may be understood to mean that only one of the list of alternatives may apply, more than one of the list of alternatives may apply or all of the list of alternatives may apply. This expression may be understood to be equivalent to the expression “at least one of:” followed by a list of alternatives separated by commas, and wherein the last alternative is preceded by the “or” term.

[0706] Any of the terms processor and circuitry may be understood herein as a hardware component.

[0707] As used herein, the expression “in some embodiments” has been used to indicate that the features of the embodiment described may be combined with any other embodiment or example disclosed herein.

[0708] As used herein, the expression “in some examples” has been used to indicate that the features of the example described may be combined with any other embodiment or example disclosed herein.

Claims

1. CLAIMS1. A method, performed by a wireless device (121), for handling location estimation in a wireless communication network (100), the method comprising:- receiving (403) a location request message for location estimation from a location management node (130), the request indicating one or more positioning methods for obtaining the location estimation, including a UE-based direct AI / ML positioning method,- estimating (405) a location of the wireless device (121) based on the UE-based direct AI / ML positioning method, and- sending (406) a location response message comprising the obtained location estimation to the location management node (130), the location response message indicating the UE-based direct AI / ML positioning method.

2. The method according to claim 1, wherein the method further comprises:- sending (402) a message to the location management node (130), which message indicates that the wireless device (121) has an applicable model for UE-based direct AI / ML positioning.

3. The method according to any of the claims 1-2, wherein the UE-based direct AI / ML positioning method is indicated in an Information Element, IE, in the location response message.

4. The method according to any of claims 1-3, wherein the location request message further indicates the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods.

5. The method according to claim 4, further comprising selecting (404) the preferred positioning method from the one or more positioning methods.

6. A method performed by a location management node (130), for handling location estimation in a wireless communication network (100), the method comprising:- sending (504) a location request message for location estimation to a wireless device (121), the request indicating one or more positioning methods for obtaining the location estimation including a UE-based direct AI / ML positioning method, and- receiving (505) a location response message comprising the obtained location estimation from the wireless device (121), the location response message indicating the UE-based direct AI / ML positioning method used to obtain the location estimation.

7. The method according to claim 6, wherein the method further comprises:- receiving (503) a message from the wireless device (121), which message indicates that the wireless device (121) has an applicable model for UE-based direct AI / ML positioning.

8. The method according to any of claims 6-7, wherein the UE-based direct AI / ML positioning method is indicated in an Information Element, IE, in the location response message.

9. The method according to any of claims 6-8, wherein the location request message further indicates the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods.

10. A wireless device (121) configured to handle location estimation in a wireless communication network 100, the wireless device 121 further configured to:receive a location request message for location estimation from a location management node (130), the request indicating one or more positioning methods for obtaining the location estimation, including a UE-based direct AI / ML positioning method,estimate a location of the wireless device (121) based on the UE-based direct AI / ML positioning method, andsend a location response message comprising the obtained location estimation to the location management node (130), the location response message further indicates the UE-based direct AI / ML positioning method.

11. The wireless device (121) according to claim 10, further configured to:send a message to the location management node (130), which message is adapted to indicate that the wireless device (121) has an applicable model for UE-based direct AI / ML positioning.

12. The wireless device (121) according to any of claims 10-11, further configured to indicate the UE-based direct AI / ML positioning method in an Information Element, IE, in the location response message.

13. The wireless device (121) according to any of claims 10-12, wherein the location request message further indicates the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods.

14. The wireless device (121) according to claim 13, further configured to select the preferred positioning method from the one or more positioning methods.

15. A location management node (130) configured to handle location estimation in a wireless communication network (100), the location management node (130) further configured to: send a location request message for location estimation to a wireless device (121), the request indicating one or more positioning methods for obtaining the location estimation and further indicating a UE-based direct AI / ML positioning method,receive a location response message adapted to comprise the obtained location estimation from the wireless device (121), the location response message further indicating the UE-based direct AI / ML positioning method.

16. The location management node (130) according to claim 15, further configured to:receive a message from the wireless device (121), which message indicates that the wireless device (121) has an applicable model for UE-based direct AI / ML positioning.

17. The location management node (130) according to any of claims 15-16, further configured to receive an indication of the UE-based direct AI / ML positioning method in an Information Element, IE, in the location response message.

18. The location management node (130) according to any of claims 15-17, wherein the location request message further indicates the UE-based direct AI / ML positioning method as a preferred positioning method of the one or more positioning methods.

19. A computer program (13, 23) comprising instructions, which, when executed on at least one processor (11, 21), cause the at least one processor (11, 21) to carry out the method according to any of the claims 1-9, as performed by the wireless device (121), and the location management node (130), respectively.

20. A carrier (14, 24) comprising the computer program of claim 19, wherein the carrier (14, 24) is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

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