Managing associated identifiers in ai / ml based positioning

Abstract

Example embodiments of the present disclosure relate to managing associated identifiers in AI / ML based positioning. A method includes receiving, from a second apparatus, information comprising a first configuration of a plurality of transmission-reception points (TRPs) and a first associated identifier, the first associated identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; receiving, from the second apparatus, information comprising a second configuration of the plurality of TRPs, the first associated identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and determining, for the first associated identifier, that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical properties.

Description

Cross-references to related applications

[0001] This application claims priority and interest in U.S. Provisional Application No. 63 / 747198, filed January 20, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0002] Various example embodiments of this disclosure generally relate to the telecommunications field, and more specifically to methods, apparatus, devices, and computer-readable storage media for managing associated identifiers (IDs) in location based on artificial intelligence machine learning (AI / ML). Background Technology

[0003] Efforts have been made to incorporate AI / ML models into relevant wireless communication standards to enhance positioning accuracy and manage lifecycle operations, thereby achieving consistency between the training and inference phases. AI / ML-based positioning systems rely on both UE-side and network-side models, requiring signaling mechanisms for model training, activation, switching, and performance monitoring. Achieving consistency between training and inference conditions is crucial, as differences between the two phases, especially those caused by network-side (NW-side) additional conditions (such as environmental factors or TRP configuration), can degrade model performance. Summary of the Invention

[0004] In a first aspect of this disclosure, a first apparatus is provided. The first apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus to at least: receive from a second apparatus information including a first configuration of a plurality of transport-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; receive from the second apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and, with respect to the first association identifier, determine that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical properties.

[0005] In a second aspect of this disclosure, a second apparatus is provided. The second apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the second apparatus to at least: transmit to a first apparatus information including a first configuration of a plurality of transmit-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; and transmit to the first apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, wherein, for the first association identifier, the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0006] In a third aspect of this disclosure, a first apparatus is provided. The first apparatus includes: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first apparatus to at least: receive from a second apparatus information including a first configuration of a plurality of transport-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs, and the first configuration of the plurality of TRPs being received for data collection for model training; receive from the second apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, and the second configuration of the plurality of TRPs being received for inference; receive, for the first association identifier, a positioning signal transmission from the at least one TRP of the second configuration of the plurality of TRPs; collect measurements based on the received positioning signal transmission for the first association identifier; and select a positioning model corresponding to the first association identifier for inference, wherein the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0007] In a fourth aspect of this disclosure, a method is provided. The method includes: receiving from a second device information including a first configuration of a plurality of transport-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; receiving from the second device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and determining, with respect to the first association identifier, that at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical properties.

[0008] In a fifth aspect of this disclosure, a method is provided. The method includes: transmitting to a first device information including a first configuration of a plurality of transmit-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; and transmitting to the first device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, wherein, for the first association identifier, the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0009] In a sixth aspect of this disclosure, a method is provided. The method includes: receiving from a second device information including a first configuration of a plurality of transmit-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs, and the first configuration of the plurality of TRPs being received for data collection for model training; receiving from the second device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, and the second configuration of the plurality of TRPs being received for inference; receiving, for the first association identifier, a positioning signal transmission from the at least one TRP of the second configuration of the plurality of TRPs; collecting measurements based on the received positioning signal transmission for the first association identifier; and selecting a positioning model corresponding to the first association identifier for inference, wherein the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0010] In a seventh aspect of this disclosure, a first apparatus is provided. The first apparatus includes: components for receiving from a second apparatus information including a first configuration and a first association identifier of a plurality of transport-receive points (TRPs), the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; components for receiving from the second apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and components for determining, based on the first association identifier, that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical properties.

[0011] In an eighth aspect of this disclosure, a second apparatus is provided. The second apparatus includes: components for transmitting to a first apparatus information including a first configuration of a plurality of Transmission-Receiving Points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; and components for transmitting to the first apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, wherein, for the first association identifier, the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0012] In a ninth aspect of this disclosure, a first apparatus is provided. The first apparatus includes: means for receiving from a second apparatus information including a first configuration of a plurality of transmit-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs, and the first configuration of the plurality of TRPs being received for data collection for model training; means for receiving from the second apparatus information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, and the second configuration of the plurality of TRPs being received for inference; means for receiving, for reference to the first association identifier, positioning signal transmissions from the at least one TRP of the second configuration of the plurality of TRPs; means for collecting measurements based on the received positioning signal transmissions for reference to the first association identifier; and means for selecting a positioning model corresponding to the first association identifier for inference, wherein the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0013] In a tenth aspect of this disclosure, a computer-readable medium is provided. The computer-readable medium includes instructions stored thereon for causing a device to at least execute the method according to a fourth aspect.

[0014] In the eleventh aspect of this disclosure, a computer-readable medium is provided. The computer-readable medium includes instructions stored thereon for causing a device to at least execute the method according to the fifth aspect.

[0015] In a twelfth aspect of this disclosure, a computer-readable medium is provided. The computer-readable medium includes instructions stored thereon for causing a device to at least execute the method according to the sixth aspect.

[0016] It should be understood that the summary portion is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0017] Some exemplary embodiments will now be described with reference to the accompanying drawings, in which: Figure 1 An example communication environment in which example embodiments of the present disclosure may be implemented is shown; Figure 2 Example signaling procedures according to some embodiments of this disclosure are shown; Figure 3 A flowchart is shown illustrating a method implemented at a first device according to some exemplary embodiments of the present disclosure; Figure 4 A flowchart is shown illustrating a method implemented at a second device according to some example embodiments of the present disclosure; Figure 5 A flowchart is shown illustrating a method implemented at a first device according to some exemplary embodiments of the present disclosure; Figure 6 A simplified block diagram of a device suitable for implementing example embodiments of the present disclosure is shown; and Figure 7 A block diagram of an example computer-readable medium according to some example embodiments of the present disclosure is shown.

[0018] Throughout the accompanying drawings, the same or similar reference numerals denote the same or similar elements. Detailed Implementation

[0019] The principles of this disclosure will now be described with reference to some exemplary embodiments. It should be understood that these embodiments are described for illustrative purposes only and to help those skilled in the art to understand and implement this disclosure, without implying any limitation on the scope of this disclosure. The embodiments described herein can be implemented in various ways other than those described below.

[0020] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0021] References to "an embodiment," "an embodiment," "an example embodiment," etc., in this disclosure indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment includes that particular feature, structure, or characteristic. Furthermore, these phrases do not necessarily refer to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is to be noted that those skilled in the art will recognize, whether explicitly described or not, that such features, structures, or characteristics apply in conjunction with other embodiments.

[0022] It should be understood that although terms such as "first," "second," etc., may be used before names (or similar designations) to describe various elements herein, these elements should not be limited by these terms. These terms are used only to distinguish one element from another, and they do not restrict the order of the nouns (or similar designations). For example, without departing from the scope of the exemplary embodiments, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0023] As used herein, “at least one of the following: ” and “at least one of ” and similar expressions, wherein the list of two or more elements is connected by “and” or “or”, means at least any one of these elements, or at least any two or more of these elements, or at least all of these elements.

[0024] As used herein, unless explicitly stated otherwise, the action “in response to A” does not indicate that the action is performed immediately after “A” occurs and may include one or more intervention steps.

[0025] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. As used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising,” “including,” “having,” “possessing,” “containing,” and / or “covering,” as used herein, specify the presence of the stated features, elements, and / or components, but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0026] As used in this application, the term "circuit" may refer to one or more or all of the following: (a) Hardware circuit implementation only (e.g., implemented with purely analog and / or digital circuits) and (b) A combination of hardware circuitry and software, such as (if applicable): (i) A combination of (multiple) analog and / or digital hardware circuits and software / firmware, and (ii) Any part of a hardware processor having software (including (multiple) digital signal processors, software, and (multiple) memories, which work together to enable a device (such as a mobile phone or server) to perform various functions) and (c) The operation requires software (e.g., firmware) for the operation of (multiple) hardware circuits and / or (multiple) processors, such as (multiple) microprocessors or parts thereof, but the software may be absent when the operation does not require the software.

[0027] This definition of "circuit" applies to all uses of the term in this application. As a further example, as used in this application, the term "circuit" also covers only hardware circuitry or processors (or processors), or portions of hardware circuitry or servers and their accompanying software and / or firmware implementations. For example, where applicable to certain claim elements, the term "circuit" also covers baseband integrated circuits or processor integrated circuits for mobile devices or similar integrated circuits in servers, cellular network devices, or other computing or networking devices.

[0028] As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as New Radio (NR), Long Term Evolution (LTE), LTE-A Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), Narrowband Internet of Things (NB-IoT), etc. Furthermore, communication between terminal devices and network devices in a communication network can be performed according to any suitable generation of communication protocol, including but not limited to first-generation (1G), second-generation (2G), 2.5G, 2.75G, third-generation (3G), fourth-generation (4G), 4.5G, fifth-generation (5G), 5.5G, sixth-generation (6G) communication protocols, and / or any other currently known or under development protocols. Embodiments of this disclosure can be applied to various communication systems. Given the rapid development of communications, future types of communication technologies and systems that can implement this disclosure will inevitably emerge. The scope of this disclosure should not be considered limited to the systems described above.

[0029] As used herein, the term "network device" refers to a node in a communications network through which terminal devices access the network and receive services. Depending on the terminology and technology applied, a network device can refer to a base station (BS) or access point (AP), such as a Node B (NodeB or NB), an evolved Node B (eNodeB or eNB), an NR NB (also known as a gNB), a Remote Radio Unit (RRU), a Radio Head (RH), a Remote Radio Head (RRH), a relay, an Integrated Access and Backhaul (IAB) node, a low-power node (such as femtoseconds, picoseconds, non-terrestrial network (NTN) or non-terrestrial network equipment (such as satellite network equipment), low Earth orbit (LEO) satellites and geostationary Earth orbit (GEO) satellites, spacecraft network equipment, etc.). In some example embodiments, the Radio Access Network (RAN) separation architecture includes a centralized unit (CU) and a distributed unit (DU) at the IAB donor node. The IAB node includes a mobile terminal (IAB-MT) portion that behaves similarly to a UE toward its parent node, and the DU portion of the IAB node behaves similarly to a base station toward the next-hop IAB node.

[0030] The term "terminal device" refers to any end device with wireless communication capabilities. By way of example and not limitation, terminal device may also refer to communication equipment, user equipment (UE), subscriber station (SS), portable subscriber station, mobile station (MS), or access terminal (AT). Terminal devices can include, but are not limited to, mobile phones, cellular phones, smartphones, Voice over IP (VoIP) phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image acquisition terminal devices (such as digital cameras), gaming terminal devices, music storage and playback devices, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop embedded devices (LEE), laptop mounted devices (LME), USB dongles, smart devices, wireless client devices (CPE), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in the context of industrial and / or automated processing chains), consumer electronics devices, devices operating on commercial and / or industrial wireless networks, etc. Terminal equipment may also correspond to the mobile terminal (MT) portion of an IAB node (e.g., a relay node). In the following description, the terms "terminal equipment," "communication equipment," "terminal," "user equipment," and "UE" are used interchangeably.

[0031] As used herein, the terms “resource,” “transmission resource,” “resource block,” “physical resource block” (PRB), “uplink resource,” or “downlink resource” can refer to any resource used to perform communication, such as communication between a terminal device and a network device, including resources in the time domain, frequency domain, spatial domain, code domain, or any other combination of time-domain, frequency-domain, spatial-domain, and / or code-domain resources used to implement communication. In the following, unless explicitly stated otherwise, resources in both the frequency and time domains will be used as examples of transmission resources used to describe some exemplary embodiments of this disclosure. It should be noted that the exemplary embodiments of this disclosure are equally applicable to other resources in other domains.

[0032] The exemplary embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0033] Figure 1 An example communication environment 100 in which exemplary embodiments of the present disclosure may be implemented is shown. In communication environment 100, multiple communication devices, including terminal device 110 and network device 120, can communicate with each other. Figure 1 In the example, terminal device 110 can be a UE, and network device 120 can be a base station serving the UE. The service area of ​​network device 120 can be referred to as a cell.

[0034] It should be understood that Figure 1 The number of devices and their connections shown are for illustrative purposes only and do not impose any limitations. Communication environment 100 may include any suitable number of devices configured to implement the exemplary embodiments of this disclosure. Although not shown, it should be understood that one or more additional devices may be located in a cell, and one or more additional cells may be deployed in communication environment 100. Note that although shown as a network device, network device 120 may be another device besides a network device. Although shown as a terminal device, terminal device 110 may be another device besides a terminal device.

[0035] In the following description, for illustrative purposes, some example embodiments are depicted in which terminal device 110 operates as a UE and network device 120 operates as a base station. However, in some example embodiments, the operations described in connection with the terminal device can be implemented at the network device or other devices, and the operations described in connection with the network device can be implemented at the terminal device or other devices.

[0036] In some example embodiments, the transmission direction from network device 120 to terminal device 110 is referred to as the downlink (DL), and the transmission direction from terminal device 110 to network device 120 is referred to as the uplink (UL). In the DL, network device 120 is a transmit (TX) device (or transmitter), and terminal device 110 is a receive (RX) device (or receiver). In the UL, terminal device 110 is a TX device (or transmitter), and network device 120 is an RX device (or receiver).

[0037] Communication in communication environment 100 can be implemented according to any suitable communication protocol, including but not limited to cellular communication protocols, wireless local area network communication protocols (such as IEEE 802.11, etc.), and / or any other currently known or future-developed protocols. Furthermore, communication can utilize any suitable wireless communication technology, including but not limited to: Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Frequency Division Duplex (FDD), Time Division Duplex (TDD), Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiple Access (OFDM), Discrete Fourier Transform Extended OFDM (DFT-s-OFDM), and / or any other currently known or future-developed technologies.

[0038] In the context of 5G and 6G networks, gNB (e.g., Figure 1 Network devices 120 in the network typically operate in conjunction with physical transmit-receive point (TRP) clusters, which are distributed radio units (RUs) that enable efficient communication and positioning capabilities. These physical TRPs are essential for UEs (e.g., Figure 1 The terminal device 110 in the cluster is not fully visible; instead, the network (NW) implementation determines which TRPs within the cluster are selected for specific tasks, such as Positioning Reference Signal (PRS) transmission. Depending on the requirements of the UE positioning method, the network can configure one or more TRPs from the cluster for PRS transmission. This selection is entirely determined by the NW implementation, enabling dynamic and flexible resource allocation.

[0039] When a positioning method is supported, the NW can also decide to use a subset of TRPs from the cluster, whether based on AI / ML or traditional (non-AI / ML). Here, TRP refers to a physical unit managed by the NW, and there are no restrictions in the LTE Positioning Protocol (LPP) or New Radio Positioning Protocol Annex (NRPPa) specifications regarding mapping multiple physical TRPs to a single logical TRP. This mapping can change over time based on NW preferences. For example, when the Location Management Function (LMF) configures a Physical Cell Identifier (PCI) for a TRP (optional configuration), the UE can be aware of a logical TRP under that PCI. However, in practice, the NW can use two or more physical TRPs under the same PCI and has the flexibility to switch between these physical TRPs as needed over time.

[0040] In traditional non-AI / ML localization methods, such dynamic changes in TRP selection do not pose a significant problem. These methods typically rely on the most recent measurements from currently active TRPs to determine the UE's location. Earlier measurements (even if collected hours, days, or months ago from different combinations of TRPs) are irrelevant to localization estimation. Therefore, the ability of NW to dynamically change TRPs over time does not affect the accuracy or reliability of non-AI / ML localization methods.

[0041] In contrast, AI / ML-based localization methods introduce challenges when the TRP selected during the data collection (training) phase differs from the TRP selected during (or later) the inference phase. AI / ML-based localization methods typically rely on data collected from specific TRPs and the exact locations of those TRPs to train a model predicting the UE's location. Inconsistencies can arise between the training and inference phases if the NW dynamically changes the physical TRP over time or during inference. These inconsistencies can reduce the accuracy of the AI / ML model, as localization predictions depend on the consistency and reliability of the TRP data used during training.

[0042] One proposed solution to this problem with AI / ML-based localization methods is to provide explicit information about the location of physical TRPs. This would allow the UE to track data collected from different TRPs and use this information to evaluate the suitability of the trained model during the inference phase. However, disclosing TRP locations introduces significant concerns for network operators (NWs) because these locations often contain proprietary information that network operators may be unwilling to share. Examining such details could harm the network's competitive advantage or expose sensitive deployment strategies.

[0043] To address this challenge, there has been discussion about introducing "associated IDs" for positioning purposes. These associated IDs can serve as a reference indicating which TRPs are used during the training phase without explicitly revealing their location. While this approach has the potential to solve the consistency problem between training and inference, the exact details of how the associated ID mechanism will work are still under consideration. Associated IDs could allow the UE to associate the data used during training with the data available during inference, thus achieving alignment without requiring the network to expose proprietary information.

[0044] Maintaining network confidentiality and achieving robustness in AI / ML-based localization methods remains a key area of ​​exploration. By carefully designing mechanisms such as associated IDs, networks can support high-precision localization methods while protecting their proprietary assets. However, further research and standardization efforts are needed to refine these solutions and fully address the challenges introduced by dynamic TRP selection in AI / ML-based localization.

[0045] To address the consistency issue in AI / ML-based localization systems, this disclosure proposes a process utilizing the concept of associated IDs. This approach ensures consistency between the physical TRP and its logical representation across the data collection and inference phases, thereby enhancing the reliability of the AI / ML model. The core concepts presented in this disclosure will be briefly discussed below.

[0046] In this proposed solution, the network provider can assign associated IDs to represent the physical attributes of a selected subset of TRPs within the cluster. For example, in a cluster containing eight TRPs, if only four TRPs are selected for configuration at any given time, the network can assign at least one unique associated ID to represent the physical attributes of these four TRPs. This mapping allows the network to maintain a clear and consistent association between logical TRPs and their physical counterparts over time.

[0047] From a signaling perspective, the LMF can receive associated IDs from NG RAN nodes, such as gNBs, as part of a TRP information response. NG RAN nodes can assign associated IDs to represent the geographic location and configuration of a specific TRP set at a given time. In some cases, the LMF may receive multiple associated IDs from different NG RAN nodes. These IDs can then be used by the LMF during the data collection and inference phases to achieve alignment in location calculations. Further details regarding the signaling mechanism will be described in detail later in this disclosure.

[0048] The associated ID linked to a specific TRP can also be transmitted to the UE by the LMF (via LTE positioning protocol or LPP) or gNB (via Radio Resource Control or RRC). This information can be shared during both data collection and configuration inference. When the UE receives the same associated ID for a TRP set over time within a defined cell area (e.g., represented by AreaID-CellList), the UE can assume similar physical properties for that TRP set. These assumptions are based on consistency rules that implement the following: 1. Number of TRPs: The same associated ID always represents the same number of TRPs. For example, if associated ID #1 is configured for three TRPs (TRP1, TRP2, TRP3) in the initial configuration, then associated ID #1 should always be associated with three TRPs in future configurations.

[0049] 2. Physical TRP Ordering: Although the logical ordering of TRPs may change, the underlying mapping to physical TRPs remains consistent. For example, if the associated ID#1 initially maps TRP1, TRP2, and TRP3 to physical TRPs P-TRP2, P-TRP5, and P-TRP7, then the same mapping (P-TRP2, P-TRP5, P-TRP7) should be maintained in subsequent configurations.

[0050] 3. Geographical Consistency: TRPs represented by the same associated ID have similar geographic locations over time. If the associated ID #1 initially maps a TRP to geographic locations G1, G2, and G3, the network ensures that future TRPs mapped to the associated ID #1 remain geographically close to G1, G2, and G3 within a predefined margin.

[0051] 4. Reference TRP Consistency: If a reference TRP is bound to an associated ID, the same physical TRP should always be used as the reference TRP for that associated ID. For example, if TRP1 (mapped to P-TRP1) is the reference TRP under associated ID#1, then this relationship should remain unchanged during both the training and inference phases.

[0052] These consistency rules are communicated to the UE to ensure alignment during the training and inference phases. By adhering to these rules, the UE can accurately interpret the data collected during training and apply it during inference, even when the network dynamically reconfigures the TRP within the cluster.

[0053] The proposed method addresses potential concerns regarding network confidentiality. By using associated IDs instead of directly exposing TRP details (e.g., geographic location or physical configuration), the network can protect proprietary information while achieving the consistency required for AI / ML-based localization. This method strikes a balance between maintaining high localization accuracy and preserving network confidentiality, thus enabling robust and efficient localization in dynamic and complex network environments.

[0054] Now for reference Figure 2 This document illustrates example signaling procedures according to some embodiments of the present disclosure. Below, an overview of the procedures is first provided, followed by a detailed description.

[0055] Network provider's allocation of associated IDs Network providers can assign IDs associated with 201 and 202 to represent the physical attributes of TRPs grouped or selected from the cluster. For example, in a cluster of four physical TRPs (P_TRPs), if two TRPs are selected to enable the positioning method at UE 110, the associated IDs can be assigned to represent the specific physical characteristics of these two TRPs. This allows the network and UE 110 to consistently understand the subset of TRPs used for positioning operations.

[0056] Each unique combination of TRPs selected from the cluster requires a distinct associated ID to accurately reflect their physical attributes. For example, associated ID_1 could represent P_TRP1 and P_TRP2 in 202, while associated ID_2 could represent P_TRP1 and P_TRP3 in 210. These TRPs do not necessarily belong to the same gNB, but can be managed by different gNBs within the same mobile network operator (MNO). This flexibility allows the network to dynamically adjust TRP selection across its infrastructure while maintaining consistency for the UE through associated IDs.

[0057] When the selection of TRP changes over time, the network can reuse an earlier assigned associated ID or assign a new, unique associated ID. The reuse or reassignment of IDs depends on specific configuration requirements and is typically limited to a defined area (such as an area represented by AreaID-CellList).

[0058] Signaling between LMF 122 and gNB Communication between LMF 122 and gNB plays a crucial role in managing and distributing associated IDs. Sections 203 and 204 describe how LMF 120 communicates with NG RAN node 121 (such as gNB) via NRPPa to obtain information about associated IDs and their corresponding TRPs. This signaling enables the associated IDs to efficiently transmit the physical attributes of the TRP, allowing LMF 122 to configure UE 110 with accurate and consistent information.

[0059] As network conditions evolve, any changes to the associated IDs or TRP configurations can be transmitted to the LMF 122. Sections 211 and 218 outline the process for updating the LMF 122 using the new associated ID information and TRP configuration. These updates enable the LMF 122 to provide the UE 110 with the latest configuration data during both the data collection and inference phases. In some scenarios, the LMF 122 may receive multiple associated IDs from different NG RAN nodes 121, as shown in section 218. These IDs can then be used for AI / ML model training and inference, achieving consistency across different phases of the positioning operation.

[0060] Alternatively, in scenarios where the associated ID is directly transmitted to UE 110 via RRC by NG RAN node 121, similar information exchange may occur between the gNB and UE 110. This approach provides flexibility in managing and distributing associated IDs while maintaining alignment between network and UE configurations.

[0061] Receive the associated ID at UE 110 UE 110 can receive at least one associated ID and TRP information from LMF 122 (via LPP) or gNB 121 (via RRC). 205 and 212 describe how this information is delivered to UE 110, including configuration details for data collection. During inference, additional configuration is provided to UE 110, as described in 219. The associated ID allows UE 110 to maintain consistency in its understanding of the TRP used for location operations.

[0062] When UE 110 receives an associated ID representing a specific TRP group, it assumes that the physical attributes for that group are consistent, even if the associated ID is reused within a cell area (e.g., AreaID-CellList). This assumption holds during Location Reference Signal (PRS) transmissions, as described in 208, 215, and 223. The associated ID is directly bound to the PRS transmission, enabling UE 110 to associate measurements with the correct TRP. For example, the PRS transmissions in 206 and 207 are associated with associated ID_1, linking the signal to P_TRP1 and P_TRP2.

[0063] For measurements associated with a specific ID, UE 110 can interpret and assume the following consistent properties: 1. Number of TRPs: The number of TRPs represented by the associated IDs should remain consistent. If associated ID_1 was initially configured for three TRPs (e.g., TRP1, TRP2, TRP3), it should always represent the three TRPs in a future configuration.

[0064] 2. Physical TRP Ordering: The logical ordering of TRP IDs can change dynamically, but the underlying physical TRP layout remains stable. For example, if the associated ID_1 maps TRP1, TRP2, and TRP3 to physical TRPs P_TRP2, P_TRP5, and P_TRP7, then this mapping should remain consistent over time.

[0065] 3. Geographical Consistency: The geographical locations of TRPs represented by associated IDs remain similar. For example, if associated ID_1 maps a TRP to locations G1, G2, and G3, the network ensures that future TRPs mapped to associated ID_1 are located in similar locations, thus allowing for some leeway in variation.

[0066] 4. Reference TRP Consistency: If a reference TRP is included in a group represented by an associated ID, its geographical location should remain the same. For example, if TRP1 is a reference TRP for associated ID_1, then the corresponding physical TRP (e.g., P_TRP1) should always be used as the reference TRP.

[0067] UE 110 can use these assumptions to classify data into datasets for model training 216 and select an appropriate model during inference 220. This enables alignment between the training and inference phases, resulting in accurate and reliable localization in dynamic network environments. This mechanism balances network flexibility and UE consistency while protecting localization accuracy across different configurations.

[0068] The signaling process will now be described in detail.

[0069] The network can select 201 active P_TRPs from the available TRP clusters used for positioning tasks. For example, TRP1 can be mapped to P_TRP1, and TRP2 can be mapped to P_TRP2. These selected TRPs will be used as the source of the Positioning Reference Signal (PRS) for UE positioning.

[0070] An associated ID can be defined to represent the selected combination of P_TRPs. For example, a combination of P_TRP1 and P_TRP2 is associated with ID_1. This ID uniquely identifies the physical properties of the selected TRPs and ensures their consistency in data collection and inference.

[0071] LMF 122 can transmit a 203 TRP information request to the NG RAN node (e.g., gNB) 121 via NRPPa. This request may include details related to data collection for AI / ML positioning scenario 1. The purpose of this communication is to retrieve information about active P_TRPs and their associated IDs to enable appropriate UE configuration.

[0072] NG RAN node 121 can respond to LMF 122 with TRP information. This response may include an associated ID_1 and an indication of the active P_TRPs it represents (e.g., P_TRP1 and P_TRP2). LMF 122 can use this information to configure UE 110 for data collection in subsequent steps.

[0073] LMF 122 can transmit 205 data collection configuration to UE 110, explicitly indicating the inclusion of the associated ID_1. This allows UE 110 to align its location measurements with the specific TRP associated with the ID.

[0074] PRS transmissions can be made from the active P_TRP to UE 110. Specifically, P_TRP1 and P_TRP2, represented by the associated ID_1, can transmit PRS 206 and 207 to UE 110.

[0075] The UE can assume that data samples collected under the same associated ID (in this case, associated ID_1) correspond to TRPs with similar physical properties. This assumption simplifies the management of the collected data and ensures consistency during model training and inference.

[0076] After a period of time, the network can select 209 new active P_TRPs. For example, TRP1 remains mapped to P_TRP1, but TRP2 is now mapped to P_TRP3.

[0077] A new associated ID can be defined 210 to represent the updated P_TRP combination. For example, P_TRP1 and P_TRP3 are now associated with associated ID_2, allowing UE 110 to distinguish this configuration from the previous configuration.

[0078] TRP information can be updated / exchanged between LMF 122 and NG RAN node 121 211, and the updated data collection configuration can then be transmitted 212 to UE 110. LMF 122 can notify UE 110 to include the associated ID_2, enabling UE 110 to align its data collection process with the new configuration.

[0079] PRS transmissions can be made from new active P_TRPs to UE 110. Specifically, P_TRP1 and P_TRP3, represented by the associated ID_2, can transmit PRS 213, 214 to UE 110. These signals allow the UE to continue collecting location data with the updated configuration.

[0080] UE 110 can assume that the data samples collected by 215 under the associated ID_2 correspond to TRPs with similar physical properties, just as they are processed with the associated ID_1. This consistency enables seamless data management across different configurations.

[0081] UE 110 can use the data collected under each associated ID to perform model training 216. The models are linked to their respective IDs, such as associated ID_1 and associated ID_2, such that the training process reflects the physical properties of the TRP used during data collection.

[0082] After a period of time, the network can again select the 217 active P_TRPs. For example, TRP1 is mapped back to P_TRP1, and TRP2 is mapped back to P_TRP2. The network reuses the previously defined associated ID_1 to represent this configuration.

[0083] TRP information can be updated / exchanged between LMF 122 and NG RAN node 121 218, and the inferred configuration can be transmitted 219 to UE 110. LMF 122 can notify UE 110 including the associated ID_1 for inference purposes, thereby achieving alignment with earlier data collection phases.

[0084] The UE can select the appropriate model 220 based on the associated ID_1 and process PRS transmissions from the active P_TRP. PRS 211 and 212 are transmitted to the UE 110 by P_TRP1 and P_TRP2 indicated by the associated ID_1, supporting inference operations.

[0085] The UE can perform inference by assuming that PRS measurements under the same associated ID have the same or similar physical properties as during the training phase.223 This consistency enables AI / ML-based localization systems to provide accurate and reliable results even as the network dynamically manages TRP over time.

[0086] Figure 3 A flowchart of an example method 300 implemented at a first device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 300 is described by the angle of the first device 110 in the middle.

[0087] At block 310, information including a first configuration and a first association identifier of a plurality of transmit-receive points (TRPs) is received from the second device, the first association identifier being associated with at least one TRP of the first configuration among the plurality of TRPs.

[0088] At block 320, information of a second configuration including a plurality of TRPs is received from the second device, wherein a first association identifier is associated with at least one TRP of the second configuration among the plurality of TRPs.

[0089] At box 330, for a first association identifier, it is determined that the at least one TRP of the first configuration among a plurality of TRPs and the at least one TRP of the second configuration among a plurality of TRPs have consistent physical attributes.

[0090] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0091] In some example embodiments, method 300 further includes: receiving a positioning signal transmission from at least one TRP of a first configuration among a plurality of TRPs for a first associated identifier; and collecting measurements based on the received positioning signal transmission for the first associated identifier.

[0092] In some example embodiments, method 300 further includes: training a positioning model corresponding to a first associated identifier based on the received positioning signal transmission.

[0093] In some example embodiments, method 300 further includes: receiving a positioning signal transmission from at least one TRP of a second configuration of a plurality of TRPs for a first associated identifier; and collecting measurements based on the received positioning signal transmission for the first associated identifier.

[0094] In some example embodiments, method 300 further includes: selecting a location model corresponding to the first associated identifier for inference.

[0095] In some example embodiments, method 300 further includes: receiving from a second device information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; receiving from the second device information including a second configuration of the plurality of additional TRPs, the second association identifier being associated with at least one TRP of the second configuration of the plurality of additional TRPs; and determining, with respect to the second association identifier, that the at least one TRP of the first configuration of the plurality of additional TRPs and the at least one TRP of the second configuration of the plurality of additional TRPs have consistent physical attributes.

[0096] In some example embodiments, the first association identifier or the second association identifier is associated with a defined cell area.

[0097] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0098] In some example embodiments, the number of TRPs remains constant over time.

[0099] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0100] In some example embodiments, the reference TRP remains consistent over time.

[0101] In some example embodiments, the first association identifier is directly associated with the location signal transmission.

[0102] In some example embodiments, a first association identifier or a second association identifier is received via Radio Resource Control (RRC).

[0103] In some example embodiments, a first associated identifier or a second associated identifier is received via the LTE Location Protocol (LPP).

[0104] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0105] Figure 4 A flowchart of an example method 400 implemented at a second device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 400 is described by the angle of the second device 120 in the middle.

[0106] At block 410, information including a first configuration of a plurality of Transmit-Receive Points (TRPs) and a first association identifier is transmitted to the first device, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs.

[0107] At block 420, information comprising a second configuration of multiple TRPs is transmitted to the first device, wherein a first association identifier is associated with at least one TRP of the second configuration of the multiple TRPs, wherein for the first association identifier, at least one TRP of the first configuration of the multiple TRPs and at least one TRP of the second configuration of the multiple TRPs are determined to have consistent physical attributes.

[0108] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0109] In some example embodiments, method 400 further includes: transmitting to a first device information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; and transmitting to the first device information including a second configuration of the plurality of additional TRPs, the second association identifier being associated with at least one TRP of the second configuration of the plurality of additional TRPs, wherein for the second association identifier, at least one TRP of the first configuration of the plurality of additional TRPs and at least one TRP of the second configuration of the plurality of additional TRPs are determined to have consistent physical properties.

[0110] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0111] In some example embodiments, the number of TRPs remains constant over time.

[0112] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0113] In some example embodiments, the reference TRP remains consistent over time.

[0114] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0115] Figure 5 A flowchart of an example method 500 implemented at a first device according to some example embodiments of the present disclosure is shown. For the purposes of discussion, [the following will be discussed]. Figure 1 Method 500 is described by the angle of the first device 110 in the middle.

[0116] At block 510, information including a first configuration of a plurality of transmit-receive points (TRPs) and a first association identifier is received from the second device, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs, and the first configuration of the plurality of TRPs is received for data collection for model training.

[0117] At block 520, information including a second configuration of a plurality of TRPs is received from the second device, a first association identifier is associated with at least one TRP of the second configuration among the plurality of TRPs, and the second configuration of the plurality of TRPs is received for inference.

[0118] At box 530, for a first associated identifier, a positioning signal transmission is received from at least one TRP of a second configuration among a plurality of TRPs.

[0119] At box 540, measurements are collected based on the received positioning signal transmission for the first associated identifier.

[0120] In box 550, a location model corresponding to the first associated identifier is selected for inference, wherein the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0121] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0122] In some example implementations, the first association identifier is associated with a defined cell area.

[0123] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0124] In some example embodiments, the number of TRPs remains constant over time.

[0125] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0126] In some example embodiments, the reference TRP remains consistent over time.

[0127] In some example embodiments, method 500 further includes: receiving a positioning signal transmission from at least one TRP of a first configuration among a plurality of TRPs for a first associated identifier; and collecting measurements based on the received positioning signal transmission for the first associated identifier.

[0128] In some example embodiments, method 500 further includes: training a positioning model corresponding to a first associated identifier based on the received positioning signal transmission.

[0129] In some example embodiments, the first association identifier is directly associated with the location signal transmission.

[0130] In some example embodiments, the first associated identifier is received via Radio Resource Control (RRC).

[0131] In some example implementations, the first associated identifier is received via the LTE Location Protocol (LPP).

[0132] In some example embodiments, any of the first means of method 300 can be performed (e.g., Figure 1 The first device 110 may include a component for performing the corresponding operation of method 300. This component may be implemented in any suitable form. For example, the component may be implemented in a circuit or software module. The first device may be implemented as or included in... Figure 1 The first device 110 or Figure 2 In UE 110.

[0133] In some example embodiments, the first device includes: components for receiving from the second device information including a first configuration and a first association identifier of a plurality of transport-receive points (TRPs), the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; components for receiving from the second device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and components for determining, based on the first association identifier, that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical properties.

[0134] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0135] In some example embodiments, the first device further includes: a component for receiving a location signal transmission from at least one TRP of a first configuration among a plurality of TRPs for a first associated identifier; and a component for collecting measurements based on the received location signal transmission for the first associated identifier.

[0136] In some example embodiments, the first device further includes a component for training a positioning model corresponding to a first associated identifier based on the received positioning signal transmission.

[0137] In some example embodiments, the first device further includes: a component for receiving a location signal transmission from at least one TRP of a second configuration of a plurality of TRPs for a first associated identifier; and a component for collecting measurements based on the received location signal transmission for the first associated identifier.

[0138] In some example embodiments, the first device further includes a component for selecting a positioning model corresponding to the first associated identifier for inference.

[0139] In some example embodiments, the first device further includes: a component for receiving from the second device information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; a component for receiving from the second device information including a second configuration of the plurality of additional TRPs, the second association identifier being associated with at least one TRP of the second configuration of the plurality of additional TRPs; and a component for determining, for the second association identifier, that at least one TRP of the first configuration of the plurality of additional TRPs and at least one TRP of the second configuration of the plurality of additional TRPs have consistent physical properties.

[0140] In some example embodiments, the first association identifier or the second association identifier is associated with a defined cell area.

[0141] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0142] In some example embodiments, the number of TRPs remains constant over time.

[0143] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0144] In some example embodiments, the reference TRP remains consistent over time.

[0145] In some example embodiments, the first association identifier is directly associated with the location signal transmission.

[0146] In some example embodiments, the first association identifier or the second association identifier is received via Radio Resource Control (RRC).

[0147] In some example embodiments, the first associated identifier or the second associated identifier is received via the LTE Location Protocol (LPP).

[0148] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0149] In some example embodiments, any of the second means in method 400 can be executed (e.g., Figure 1The second device 120 may include a component for performing the corresponding operation of method 400. This component may be implemented in any suitable form. For example, the component may be implemented in a circuit or software module. The second device may be implemented as or included in... Figure 1 The second device 120 or Figure 2 In NG RAN 121 or LMF 122.

[0150] In some example embodiments, the second device includes: a component for transmitting to the first device information including a first configuration and a first association identifier of a plurality of transmit-receive points (TRPs), the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; and a component for transmitting to the first device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, wherein, for the first association identifier, the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0151] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0152] In some example embodiments, the second device further includes: a component for transmitting to the first device information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; and a component for transmitting to the first device information including a second configuration of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the second configuration of the plurality of additional TRPs, wherein for the second association identifier, at least one TRP of the first configuration of the plurality of additional TRPs and at least one TRP of the second configuration of the plurality of additional TRPs are determined to have consistent physical properties.

[0153] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0154] In some example embodiments, the number of TRPs remains constant over time.

[0155] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0156] In some example embodiments, the reference TRP remains consistent over time.

[0157] In some example embodiments, the first device is a terminal device or is included in a terminal device, and the second device is a network device or is included in a network device.

[0158] In some example embodiments, any of the first means of method 500 can be performed (e.g., Figure 1 The first device 110 may include a component for performing the corresponding operation of method 500. This component may be implemented in any suitable form. For example, the component may be implemented in a circuit or software module. The first device may be implemented as or included in... Figure 1 The first device 110 or Figure 2 In UE 110.

[0159] In some example embodiments, the first device includes: components for receiving from the second device information including a first configuration of a plurality of transport-receive points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs, and the first configuration of the plurality of TRPs being received for data collection for model training; components for receiving from the second device information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, and the second configuration of the plurality of TRPs being received for inference; components for receiving, for the first association identifier, positioning signal transmissions from the at least one TRP of the second configuration of the plurality of TRPs; components for collecting measurements based on the received positioning signal transmissions for the first association identifier; and components for selecting a positioning model corresponding to the first association identifier for inference, wherein the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical properties.

[0160] In some example embodiments, physical attributes include at least one of the following: the geographic location of the TRP, the number of TRPs, the order of physical TRPs, or the reference TRP.

[0161] In some example implementations, the first association identifier is associated with a defined cell area.

[0162] In some example embodiments, the geographical location of the TRP remains the same or similar over time.

[0163] In some example embodiments, the number of TRPs remains constant over time.

[0164] In some example implementations, the ordering of physical TRPs remains consistent over time.

[0165] In some example embodiments, the reference TRP remains consistent over time.

[0166] In some example embodiments, the first device further includes: a component for receiving a location signal transmission from at least one TRP of a first configuration among a plurality of TRPs for a first associated identifier; and a component for collecting measurements based on the received location signal transmission for the first associated identifier.

[0167] In some example embodiments, the first device further includes a component for training a positioning model corresponding to a first associated identifier based on the received positioning signal transmission.

[0168] In some example embodiments, the first association identifier is directly associated with the location signal transmission.

[0169] In some example embodiments, the first association identifier is received via Radio Resource Control (RRC).

[0170] In some example embodiments, the first associated identifier is received via the LTE Location Protocol (LPP).

[0171] Figure 6 This is a simplified block diagram of a device 600 suitable for implementing an example embodiment of the present disclosure. Device 600 can be provided to implement a communication device, such as... Figure 1 The terminal device 110 or network device 120 shown, or Figure 2 The UE 110, NGRAN 121, or LMF 122 are shown in the figure. As shown, the device 600 includes one or more processors 610, one or more memories 620 coupled to the processors 610, and one or more communication modules 640 coupled to the processors 610.

[0172] Communication module 640 is used for bidirectional communication. Communication module 640 has one or more communication interfaces to facilitate communication with one or more other modules or devices. The communication interface can represent any interface necessary for communication with other network elements. In some example embodiments, communication module 640 may include at least one antenna.

[0173] As a non-limiting example, processor 610 can be any type suitable for a local technology network and can include one or more of the following: general-purpose computer, special-purpose computer, microprocessor, digital signal processor (DSP), and processor based on a multi-core processor architecture. Device 600 can have multiple processors, such as application-specific integrated circuit chips that are time-dependent on a clock synchronized with the main processor.

[0174] Memory 620 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 624, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disc (CD), digital video disc (DVD), optical disc, laser disc, and other magnetic and / or optical storage. Examples of volatile memories include, but are not limited to, random access memory (RAM) 622 and other volatile memories that will not be retained during power loss.

[0175] Computer program 630 includes computer-executable instructions that are executed by an associated processor 610. The instructions of program 630 may include instructions for performing operations / actions of some example embodiments of this disclosure. Program 630 may be stored in memory (e.g., ROM 624). Processor 610 can perform any suitable actions and processes by loading program 630 into RAM 622.

[0176] Example embodiments of this disclosure can be implemented by means of program 630, such that device 600 can perform as described in the reference. Figures 2 to 5 Any process discussed in this disclosure. Exemplary embodiments of this disclosure may also be implemented by hardware or by a combination of software and hardware.

[0177] In some example embodiments, program 630 may be tangibly included in a computer-readable medium, which may be included in device 600 (such as in memory 620) or in other storage devices accessible by device 600. Device 600 may load program 630 from the computer-readable medium into RAM 622 for execution. In some example embodiments, the computer-readable medium may include any type of non-transitory storage medium, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. As used herein, the term "non-transitory" is a limitation of the medium itself (i.e., tangible, not tactile), rather than a limitation of the persistence of data storage (e.g., RAM versus ROM).

[0178] Figure 7 An example of a computer-readable medium 700 is shown, which may be in the form of a CD, DVD, or other optical storage disc. The computer-readable medium 700 has a program 630 stored thereon.

[0179] In general, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, and others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are shown and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof, as non-limiting examples.

[0180] Some exemplary embodiments of this disclosure also provide at least one computer program product tangibly stored on a computer-readable medium, such as a non-transitory computer-readable medium. The computer program product includes computer-executable instructions, such as those included in a program module, which are executed in a device on a target physical or virtual processor to perform any of the methods described above. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform a particular task or implement a particular abstract data type. In various embodiments, the functionality of a program module can be combined or split among program modules as needed. The machine-executable instructions for a program module can execute within a local or distributed device. In a distributed device, the program module can reside on both local and remote storage media.

[0181] Program code for performing the methods of this disclosure may be written in any combination of one or more programming languages. The program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that, when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be performed. The program code may be executed entirely on a machine, partially on a machine, as a stand-alone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0182] In the context of this disclosure, computer program code or related data may be carried by any suitable carrier wave to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carrier waves include signals, computer-readable media, etc.

[0183] Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination thereof. More specific examples of computer-readable storage media will include electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0184] Furthermore, although operations are described in a specific order, this should not be construed as requiring that such operations be performed in the specific order shown or sequentially, or requiring that all shown operations be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this disclosure, but rather as a description of features that may be specific to particular embodiments. Unless explicitly stated otherwise, certain features described in the context of a single embodiment may also be implemented in combination in a single embodiment. Conversely, unless explicitly stated otherwise, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0185] Although this disclosure has been described in language specific to structural features and / or methodological actions, it should be understood that the disclosure as defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are disclosed as exemplary forms for implementing the claims.

[0186] Furthermore, the various implementations of this disclosure can be described with reference to the following terms, and their features can be combined in any reasonable manner.

[0187] Clause 1. A first means for communication, comprising: at least one processor; and at least one memory storing instructions, which, when executed by the at least one processor, cause the first means to at least: receive from a second means information including a first configuration of a plurality of Transmit-Receive Points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; receive from the second means information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and, for the first association identifier, determine that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical attributes.

[0188] Clause 2. The first device according to Clause 1, wherein the physical attributes include at least one of the following: the geographical location of the TRP, the number of TRPs, the order of the physical TRPs, or the reference TRP.

[0189] Clause 3. The first device pursuant to Clause 2, wherein at least one of the following: the geographical location of the TRPs remains the same or similar over time; the number of TRPs remains consistent over time; the ordering of the physical TRPs remains consistent over time; or the reference TRPs remain consistent over time.

[0190] Clause 4. The first means according to Clause 1, wherein the first means is configured to: receive a positioning signal transmission from at least one TRP of a first configuration of a plurality of TRPs for a first associated identifier; and collect measurements based on the received positioning signal transmission for the first associated identifier.

[0191] Clause 5. The first apparatus according to Clause 1, wherein a first configuration of a plurality of TRPs is received for data collection for model training, and the first apparatus is configured to: train a localization model corresponding to a first associated identifier based on the received localization signal transmission.

[0192] Clause 6. The first device according to Clause 1, wherein the first device is configured to: receive a positioning signal transmission from at least one TRP of a second configuration of a plurality of TRPs for a first associated identifier; and collect measurements based on the received positioning signal transmission for the first associated identifier.

[0193] Clause 7. The first device according to Clause 1, wherein a second configuration of a plurality of TRPs is received for inference, and the first device is configured to: select a positioning model corresponding to a first associated identifier for inference.

[0194] Clause 8. The first apparatus according to Clause 7, wherein the first apparatus is configured to: receive from the second apparatus information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; receive from the second apparatus information including a second configuration of the plurality of additional TRPs, the second association identifier being associated with at least one TRP of the second configuration of the plurality of additional TRPs; and, with respect to the second association identifier, determine that the at least one TRP of the first configuration of the plurality of additional TRPs and the at least one TRP of the second configuration of the plurality of additional TRPs have consistent physical properties.

[0195] Clause 9. The first device according to Clause 1, wherein at least one of the following: the first associated identifier or the second associated identifier is associated with a defined cell area; wherein the first associated identifier or the second associated identifier is received on Radio Resource Control (RRC); or the first associated identifier or the second associated identifier is received on the LTE Positioning Protocol (LPP).

[0196] Clause 10. A second means for communication, comprising: at least one processor; and at least one memory storing instructions, which, when executed by the at least one processor, cause the second means to at least: transmit to a first means information including a first configuration of a plurality of Transmit-Receive Points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; and transmit to the first means information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs, wherein, for the first association identifier, the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical attributes.

[0197] Clause 11. A method for communication, comprising: receiving from a second means information including a first configuration of a plurality of Transmit-Receive Points (TRPs) and a first association identifier, the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; receiving from the second means information including a second configuration of the plurality of TRPs, the first association identifier being associated with at least one TRP of the second configuration of the plurality of TRPs; and determining, with respect to the first association identifier, that the at least one TRP of the first configuration of the plurality of TRPs and the at least one TRP of the second configuration of the plurality of TRPs have consistent physical attributes.

Claims

1. A first device for communication, comprising: At least one processor; as well as At least one memory, the at least one memory storing instructions, the instructions, when executed by the at least one processor, cause the first device to at least: The second device receives information including a first configuration and a first association identifier of a plurality of Transmission-Receiving Points (TRPs), the first association identifier being associated with at least one TRP of the first configuration of the plurality of TRPs; The second device receives information including a second configuration of a plurality of TRPs, wherein the first association identifier is associated with at least one TRP of the second configuration of the plurality of TRPs; as well as Based on the first association identifier, it is determined that at least one TRP in the first configuration of the plurality of TRPs and at least one TRP in the second configuration of the plurality of TRPs have consistent physical attributes.

2. The first device according to claim 1, wherein the physical property includes at least one of the following: TRP's geographical location The number of TRPs, The ordering of the physical TRPs, or Refer to TRP.

3. The first device according to claim 2, wherein at least one of the following: The geographical location of the TRP remains the same or similar over time; The number of TRPs remains constant over time; The ordering of the physical TRP remains consistent over time; or The reference TRP remains consistent over time.

4. The first device according to claim 1, wherein the first device is configured to: For the first associated identifier, receive location signal transmission from at least one TRP of the first configuration of the plurality of TRPs; and For the first associated identifier, measurements are collected based on the received positioning signal transmission.

5. The first apparatus of claim 1, wherein the first configuration of the plurality of TRPs is received for data collection for model training, and the first apparatus is configured such that: The location model corresponding to the first associated identifier is trained based on the received location signal transmission.

6. The first device according to claim 1, wherein the first device is configured to: For the first associated identifier, receive location signal transmission from at least one TRP of the second configuration of the plurality of TRPs; and For the first associated identifier, measurements are collected based on the received positioning signal transmission.

7. The first apparatus of claim 1, wherein the second configuration of the plurality of TRPs is received for inference, and the first apparatus is configured such that: Select the location model corresponding to the first associated identifier for inference.

8. The first device according to claim 7, wherein the first device is configured to: The second device receives information including a first configuration and a second association identifier of a plurality of additional TRPs, the second association identifier being associated with at least one TRP of the first configuration of the plurality of additional TRPs, one of the plurality of additional TRPs being different from the plurality of TRPs associated with the first association identifier; The second device receives information on a second configuration including a plurality of additional TRPs, wherein the second association identifier is associated with at least one TRP of the second configuration of the plurality of additional TRPs; as well as For the second association identifier, it is determined that at least one TRP of the first configuration of the plurality of other TRPs and at least one TRP of the second configuration of the plurality of other TRPs have consistent physical attributes.

9. The first device according to claim 1, wherein at least one of the following: The first or second association identifier is associated with a defined cell area; Wherein the first association identifier or the second association identifier is received on Radio Resource Control (RRC); or The first or second association identifier is received on the LTE Location Protocol (LPP).

10. A second means for communication, comprising: At least one processor; as well as At least one memory, the at least one memory storing instructions, the instructions, when executed by the at least one processor, cause the second device to at least: The first device transmits information including a first configuration and a first association identifier of a plurality of Transmit-Receive Points (TRPs), wherein the first association identifier is associated with at least one TRP of the first configuration of the plurality of TRPs, and The first device is transmitted information including a second configuration of multiple TRPs, wherein the first association identifier is associated with at least one TRP of the second configuration of the multiple TRPs. Specifically, for the first association identifier, at least one TRP of the first configuration of the plurality of TRPs and at least one TRP of the second configuration of the plurality of TRPs are determined to have consistent physical attributes.

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