WO2026032071A1 - Procédé et appareil de transmission d'informations, et support de stockage - Google Patents

Procédé et appareil de transmission d'informations, et support de stockage

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Publication number
WO2026032071A1
WO2026032071A1 PCT/CN2025/111034 CN2025111034W WO2026032071A1 WO 2026032071 A1 WO2026032071 A1 WO 2026032071A1 CN 2025111034 W CN2025111034 W CN 2025111034W WO 2026032071 A1 WO2026032071 A1 WO 2026032071A1
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WO
WIPO (PCT)
Prior art keywords
identifier
region
trp
information
terminal
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2025/111034
Other languages
English (en)
Chinese (zh)
Inventor
苏俞婉
费永强
高秋彬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Datang Mobile Communications Equipment Co Ltd
Original Assignee
Datang Mobile Communications Equipment Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Datang Mobile Communications Equipment Co Ltd filed Critical Datang Mobile Communications Equipment Co Ltd
Publication of WO2026032071A1 publication Critical patent/WO2026032071A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence

Definitions

  • This disclosure relates to the field of communication technology, and more specifically, to an information transmission method, apparatus, and storage medium.
  • AI Artificial Intelligence
  • ML Machine Learning
  • UE positioning scenarios the AI/ML model needs to be trained first. This model can be used to predict or infer the UE's location and/or intermediate measurements used to determine the UE's location, such as ToA (Time of Arrival).
  • ToA Time of Arrival
  • the trained AI/ML model is used.
  • the training data or input data of AI/ML models can be collected measurements, which can be determined by the UE/gNB (Next generation NodeB)/TRP (Transmission-Reception Point) by measuring DL-PRS (Downlink Positioning Reference Signal)/UL-SRS-pos (Uplink Sounding Reference Signal Position).
  • UE/gNB Next generation NodeB
  • TRP Transmission-Reception Point
  • DL-PRS Downlink Positioning Reference Signal
  • UL-SRS-pos Uplink Sounding Reference Signal Position
  • the measurement conditions and/or network-side conditions for the collected measurements must be the same in both phases. Therefore, how to ensure the consistency of measurement conditions and/or network-side conditions between the training and inference phases is a technical problem that urgently needs to be solved.
  • embodiments of this disclosure provide an information transmission method applied to a terminal, comprising:
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • embodiments of this disclosure provide an information transmission method applied to a network device, comprising:
  • the terminal Send first information to the terminal, the first information including a first identifier and/or a first region;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • embodiments of this disclosure provide an information transmission device applied to a terminal, the device comprising:
  • a receiving unit is configured to receive first information sent by a network device, the first information including a first identifier and/or a first area;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • embodiments of this disclosure provide an information transmission device applied to a network device, the device comprising:
  • a sending unit is configured to send first information to a terminal, the first information including a first identifier and/or a first region;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • embodiments of this disclosure provide an information transmission device applied to a terminal, the device including a memory, a transceiver, and a processor.
  • the memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs in the memory and execute the method described in the first aspect.
  • embodiments of this disclosure provide an information transmission device applied to a network device, the device including a memory, a transceiver, and a processor.
  • the memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs in the memory and execute the method according to the second aspect of claim.
  • embodiments of this disclosure provide a non-transitory readable storage medium storing a computer program that causes a processor to execute the method described in the first aspect; or, to execute the method described in the second aspect.
  • a network device can send first information to a terminal, which may include a first identifier and/or a first region.
  • the first identifier is an identifier related to the conditions of a first element, and the first element is at least one of the following: a TRP, a TRP set, a cell, or a region.
  • the terminal obtains the identifier related to the conditions of at least one of the TRP, TRP set, cell, or region, thereby synchronizing the network-side identifiers related to the conditions with the terminal. This enables the terminal to maintain consistency with the network-side conditions through the first information, ensuring the performance of the AI/ML model or AI/ML function.
  • Figure 1 is a schematic diagram of the architecture of the communication system provided in an embodiment of this disclosure.
  • FIG. 2 is a flowchart of an information transmission method provided in an embodiment of this disclosure
  • Figure 3 is a signaling diagram of an information transmission method provided in an embodiment of this disclosure.
  • FIG. 4 is another flowchart of an information transmission method provided in an embodiment of this disclosure.
  • FIG. 5 is an example diagram of a TRP provided in an embodiment of this disclosure.
  • Figure 6 is another signaling diagram of an information transmission method provided in an embodiment of this disclosure.
  • Figure 7 is a schematic diagram of the structure of the information transmission device provided in an embodiment of this disclosure.
  • Figure 8 is another structural schematic diagram of the information transmission device provided in the embodiments of this disclosure.
  • Figure 9 is a schematic diagram of the structure of the information transmission device provided in an embodiment of this disclosure.
  • Figure 10 is another structural schematic diagram of the information transmission device provided in the embodiments of this disclosure.
  • multiple refers to two or more, and other quantifiers are similar.
  • This disclosure provides a communication method, apparatus, and storage medium that synchronizes network-side condition-related identifiers to the terminal, enabling the terminal to maintain consistency with network-side conditions through first information, thereby ensuring the accuracy and precision of AI/ML models or AI/ML functions.
  • the method and apparatus are based on the same concept of the application. Since the methods and apparatus solve problems in similar ways, the implementation of the apparatus and methods can refer to each other, and the repeated parts will not be described again.
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • LTE-A Long Term Evolution Advanced
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • 5G New Radio (NR) systems and their evolved communication systems and 6G (sixth generation mobile communication technology) systems.
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • LTE-A Long Term Evolution Advanced
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • 6G sixth generation mobile communication technology
  • the terminal devices involved in the embodiments of this disclosure can be devices that provide voice and/or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem.
  • the names of the terminal devices may differ in different systems; for example, in 5G or 6G systems, the terminal device may be called a User Equipment (UE).
  • UE User Equipment
  • Wireless terminal devices can be USB storage devices, other personal computer memory devices, and dongles. They can also communicate with one or more core networks (CNs) via a Radio Access Network (RAN).
  • RAN Radio Access Network
  • Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices. For example, they can be portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and/or data with the radio access network.
  • the network device involved in this disclosure can be a base station, which may include multiple cells providing services to terminals.
  • the base station may also be called an access point, or a device in the access network that communicates with wireless terminal devices through one or more sectors on the air interface, or other names.
  • the network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network.
  • IP Internet Protocol
  • the network device can also coordinate the attribute management of the air interface.
  • the network device involved in this disclosure can be an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, or a Home evolved Node B (HeNB), relay node, femto, pico, network testing equipment, etc., and is not limited in this disclosure.
  • eNB evolved Node B
  • gNB 5G base station
  • HeNB Home evolved Node B
  • relay node femto, pico, network testing equipment, etc.
  • CU centralized unit
  • DU distributed unit
  • Network devices and terminal devices can each use one or more antennas to perform multiple-input multiple-output (MIMO) transmission.
  • MIMO transmission can be single-user MIMO or multi-user MIMO.
  • MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, and can also be diversity transmission, precoding transmission, or beamforming transmission, etc.
  • the terminal sends relevant information or similar descriptions to the network-side device. This only indicates that the terminal sends relevant information via wireless signals, and the destination recipient is the network device.
  • the network device can obtain the relevant information by receiving the wireless signals.
  • Figure 1 is a schematic diagram of the architecture of a communication system provided in an embodiment of this disclosure. As shown in Figure 1, a communication system 100 is provided in an embodiment of this disclosure.
  • the communication system 100 includes a first network element 110, a second network element 120, and a terminal 130.
  • the first network element 110 can be connected to the second network element 120.
  • the second network element 120 can be connected to the terminal 130.
  • the first network element 110 is a network element in the core network.
  • the second network element 120 is a network element in the access network.
  • the first network element 110 can be a core network element, such as LMF (Location Management Function) or UDF (User Plane Function).
  • the second network element can be an access network element, such as TRP (Transmission-Reception Point), gNB, or NG-RAN (Next Generation Radio Access Network).
  • AI Artificial Intelligence
  • ML Machine Learning
  • the following section uses a positioning scenario as an example to briefly explain how AI/ML functions are applied to the communication system 100 provided in this disclosure.
  • the second network element 120 is, for example, a base station or a TRP.
  • the terminal, base station, or TRP determines the measurement quantity by measuring DL-PRS/UL-SRS-pos, and then uses the measurement quantity as the input of the AI/ML model to predict or infer the location of the terminal.
  • the first network element 110 is, for example, an LMF.
  • the terminal, base station, or TRP determines the measurement quantity by measuring DL-PRS/UL-SRS-pos, and the terminal, base station, or TRP sends the measurement quantity to the LMF.
  • the LMF uses the received measurement quantity as the input of the AI/ML model to predict or infer the location of the terminal.
  • the AI/ML model or AI/ML function can use the measured quantity as input data, and calculate the input data through the AI/ML model or AI/ML function to predict and obtain the location of the terminal.
  • Indirect location method - AI/ML model outputs intermediate quantities used to determine the terminal location.
  • the technical solution disclosed herein includes a network device that can send first information to a terminal.
  • This first information may include a first identifier and/or a first region.
  • the first identifier is an identifier related to the conditions of a first element, which is at least one of the following: TRP, TRP set, cell, or region.
  • the terminal obtains the identifier related to the conditions of at least one of the TRP, TRP set, cell, or region, thereby synchronizing the network-side identifiers related to the conditions with the terminal. This enables the terminal to maintain consistency with the network-side conditions through the first information, ensuring the AI/ML model or AI/ML functionality.
  • FIG. 2 is a flowchart of an information transmission method provided in an embodiment of this disclosure. As shown in Figure 2, the information transmission method may include:
  • Step 201 Receive first information sent by the network device.
  • the first information may include a first identifier and/or a first area.
  • the first identifier is an identifier related to the conditions of a first element.
  • the first element includes at least one of the following: TRP, TRP set, cell, and area, wherein the area includes at least one cell.
  • the condition may refer to the condition of a determination reference signal transmitted by the network device during the training or inference phase, which can be used to determine the measurement quantity.
  • the condition may include, for example, at least one of the following: DL-PRS configuration, DL-PRS beam configuration, etc.
  • the network device may be an LMF, an AI functional entity, a base station, or a TRP, etc.
  • the TPR set may include at least one TRP.
  • a cell can refer to an area within the coverage of a network element (such as a base station or TRP)'s wireless network.
  • An area may also be referred to as a cell set, meaning that the cell set may include at least one cell.
  • the first identifier is an identifier related to a condition of the first element. It is understood that the first identifier is a condition-related identifier.
  • the condition is generally set for the first element. For example, TRP corresponds to condition 1, and the cell corresponds to condition 2.
  • the first identifier may include identifiers related to condition 1 and identifiers related to condition 2.
  • the first identifier may not be the identifier of the first element itself. For example, if the first element is a TRP, then the first identifier is not the TRP identifier, but the first identifier can be associated with a TRP identifier; if the first element is a TRP set, then the first identifier is not the TRP set identifier, but the first identifier can be associated with a TRP set identifier; if the first element is a cell, then the first identifier is not the cell identifier, but the first identifier can be associated with a cell identifier; if the first element is a region, then the first identifier is not the region identifier, but the first identifier can be associated with a region identifier.
  • the terminal can receive first information sent by the network device.
  • This first information may specifically include a first identifier and/or a first region.
  • the first identifier is an identifier related to the conditions of a first element, which is at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • the terminal obtains the identifier related to the conditions of at least one of the TRPs, TRP sets, cells, or regions, thereby synchronizing the network-side identifiers related to the conditions to the terminal.
  • FIG. 3 is a signaling diagram of an information transmission method provided in an embodiment of this disclosure.
  • the information transmission method may include the following steps:
  • Step 301 The network device sends first information to the terminal. Accordingly, the terminal can receive the first information sent by the network device.
  • the first information may include a first identifier and/or a first area.
  • the first identifier is an identifier related to the conditions of a first element.
  • the first element includes at least one of the following: TRP, TRP set, cell, and area, wherein the area includes at least one cell.
  • the network device sending the first information to the terminal may refer to the network device sending the first signaling to the terminal, the first signaling carrying the first information.
  • the first signaling may be, for example, Downlink Control Information (DCI), MAC-CE (Media Access Control Element) signaling, or custom signaling.
  • the network device may be an LMF, an AI functional entity, a base station, or a TRP, etc.
  • the terminal may receive a first signaling sent by a network device and parse the first signaling to obtain first information.
  • sending first information to a terminal by a network device may mean sending the first information to the terminal as auxiliary information.
  • the first identifier may be an identifier associated with a condition.
  • the first identifier may be related to the condition of the first element.
  • the network device may first determine the condition of the first element, and then set an identifier for the condition of the first element to obtain the first identifier.
  • the network device may also determine first information. Specifically, the network device may determine the first information based on a conditionally associated first identifier and/or first region.
  • the first region can be a valid region for the network device to collect measurements, such as a valid region for reference signal configuration or a valid region for reference signal measurement.
  • the first region can be obtained through configuration.
  • a first field and/or a second field can be set in the first signaling.
  • the first field can be used to carry first information, and the second field can carry the first region.
  • the information transmission method provided in this disclosure embodiment further includes:
  • Step 302 The terminal sends second information to the network device.
  • the network device can receive the second information sent by the terminal.
  • the second information may include identification-related information and/or area-related information.
  • Identifier-related information refers to the information that the terminal needs to report back to the network device based on the first identifier after receiving it.
  • Region-related information refers to the information that the terminal needs to report back to the network device based on the first region after receiving it.
  • step 302 may include the terminal sending a second signaling message to the network device, the second signaling message carrying second information.
  • identifier-related information may refer to information associated with the identifier of the conditions required by the terminal.
  • Region-related information may refer to information associated with the valid region required by the terminal.
  • the network device can send first information to the terminal, which may include a first identifier and/or a first region.
  • the terminal obtains an identifier related to a condition in at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • This enables the network-side identifier related to the condition to be synchronized with the terminal, allowing the terminal to maintain consistency with the network-side conditions through the first information, thus ensuring the performance of the AI/ML model or AI/ML function.
  • the terminal sending second information to the network device allows the network device to promptly understand the terminal's needs and respond quickly, improving processing security while ensuring the accuracy and precision of the AI/ML model or AI/ML function.
  • FIG 4 is another flowchart of an information transmission method provided in this disclosure, which may include the following steps:
  • Step 401 The terminal may receive first information sent by the network device.
  • This first information may, for example, include a first identifier.
  • the first identifier is an identifier related to the conditions of a first element.
  • the first element includes at least one of the following: TRP, TRP set, cell, and area, wherein the area includes at least one cell.
  • a network device such as an LMF, an AI functional entity, a base station, or a TRP, sends first information to the terminal.
  • the conditions of the first identifier and the first element satisfy at least one of the following:
  • the first identifier is a condition-related identifier for TRP
  • the first identifier is the identifier related to the conditions of the TRP set
  • the first sign is related to the conditions of the community
  • the first identifier is a condition-related identifier for the region.
  • the first identifier can be set at the TRP level.
  • a condition of a TRP can be associated with a first identifier.
  • the conditions of a TRP can refer to the conditions of a single TRP device.
  • the first identifier is an identifier related to a condition of a TRP set
  • the first identifier can be set at the TRP set level.
  • a condition of a TRP set can be associated with a first identifier.
  • the conditions of a TRP set may refer to the conditions of one or more TRPs included in the TRP set. Instead of identifying the conditions of each TRP individually, the conditions of one or more TRPs included in the TRP set are identified together. The terminal only needs to know the identifier of the conditions of the TRP set, and does not need to know the identifier of the conditions of each TRP in the TRP set.
  • the first identifier can be set at the cell level. Specifically, a condition for one cell can be associated with one first identifier.
  • the conditions of a cell may refer to the conditions belonging to a single cell.
  • the first identifier is an identifier related to the conditions of a region
  • the first identifier can be set at the region level. Specifically, a condition of a region can be associated with a first identifier.
  • the conditions of a region may refer to the conditions of one or more cells included in the region. Instead of identifying the conditions of each cell individually, the conditions of one or more cells included in the region are identified as a joint identifier. The terminal only needs to recognize the identifier of the conditions of the region, and does not need to know the identifier of the conditions of each cell in the region.
  • the first information when the first identifier is related to the conditions of the TRP set, the first information further includes set information of the TRP set; wherein the set information of the TRP set includes a TRP set identifier, and/or, the identifier of at least one TRP in the TRP set.
  • sending the set information of the TRP set to the terminal through the first information enables the terminal to determine the TRPs included in the TRP set based on the set information, which facilitates the terminal to grasp the network-side conditions and improves the security and accuracy of AI/ML.
  • Step 402 The terminal determines whether the first condition is met. If yes, proceed to step 403; otherwise, proceed to step 404.
  • the first condition may refer to the condition that the network device is able to use the AI/ML model or AI/ML function normally.
  • satisfying the first condition includes at least one of the following:
  • the first identifier is different from the second identifier.
  • the second instruction Upon receiving the second instruction, the second instruction indicates that the identification-related information be reported.
  • the location request sent by the LMF carries second indication information. Accordingly, the terminal can receive the location request.
  • a field in the location request can be configured to carry second indication information. That is, when a network device sends a location request to a terminal, the location request may carry second indication information.
  • a field in the location request can be configured to carry this second indication information. For instance, assuming this field is 1 bit, a value of 1 indicates that the second indication information has been received. A value of 0 indicates that the second indication information has not been received.
  • the terminal when the terminal determines that the first identifier and the second identifier are different, it may send second information. And/or, when the terminal determines that it has received second indication information, it may send second information.
  • the terminal may receive second indication information after receiving the first information or before receiving the first information.
  • the second indication information may be carried in third signaling.
  • the third signaling may be, for example, DCI signaling, MAC CE signaling, or custom signaling; this embodiment does not impose excessive limitations on the signaling type.
  • the terminal may obtain the second indication information from the third signaling.
  • Step 403 The terminal sends second information to the network device, such as LMF.
  • the second information may include, for example, identification-related information.
  • the identification information includes at least one of the following:
  • the second identifier is an identifier related to the condition of the first element
  • the first instruction information indicates that the first identifier is different from the second identifier
  • a rollback request is used to request the network device to roll back to the first positioning function.
  • the first positioning function is a positioning function other than the positioning function based on AI/ML models or AI/ML functions, such as a traditional positioning function.
  • AI/ML models or AI/ML functions supported by the terminal are AI/ML models or AI/ML functions supported by the terminal;
  • an AI/ML model can refer to either an AI model or an ML model.
  • An AI/ML function can refer to either an AI function or an ML function.
  • the second identifier may be an identifier associated with a condition of the first element. If the second identifier is the same as the first identifier, then the condition associated with the second identifier is the same as the condition associated with the first identifier. If the second identifier is different from the first identifier, then the condition associated with the second identifier is different from the condition associated with the first identifier.
  • the network device can obtain first indication information and determine, under the guidance of the first indication information, that the first identifier and the second identifier are different. Therefore, the network device can determine that the conditions corresponding to the first identifier and the conditions corresponding to the second identifier are inconsistent, but the problem of inconsistent "conditions" still exists.
  • the terminal device sends a rollback request to the network device.
  • the network device receives the rollback request and responds accordingly. After receiving the response from the network device, the terminal can roll back to a first positioning function.
  • This first positioning function is a positioning function other than one that performs positioning based on an AI/ML model or AI/ML function.
  • the terminal may also provide the network device with AI/ML models or AI/ML functions supported by the terminal, invalid AI/ML models or AI/ML functions, and/or valid AI/ML models or AI/ML functions.
  • the identification information may include functional information about the AI/ML models or AI/ML functions supported by the terminal, functional information about invalid AI/ML models, or functional information about AI/ML functions and/or valid AI/ML models or AI/ML functions.
  • the network device After receiving the functional information of the AI/ML models or AI/ML functions supported by the terminal, the functional information of the invalid AI/ML models or AI/ML functions and/or the functional information of the valid AI/ML models or AI/ML functions, the network device can determine the AI/ML models or AI/ML functions supported by the terminal, the invalid AI/ML models or AI/ML functions and/or the valid AI/ML models or AI/ML functions based on the functional information of the AI/ML models or AI/ML functions supported by the terminal, the functional information of the invalid AI/ML models or AI/ML functions and/or the functional information of the valid AI/ML models or AI/ML functions.
  • the network device can exclude the failed AI/ML models or functions from the supported AI/ML models or functions, and then determine the target AI/ML model or function from the remaining AI/ML models or functions. Finally, it confirms the first element corresponding to the measurement quantity of the target AI/ML model or function. Then, it determines the new conditions for the first element corresponding to this type of measurement quantity. The identifier of the new conditions for the first element is carried as the first identifier in the first information.
  • the second identifier is any one of the following:
  • the identifier related to the conditions of the first element as expected by the terminal is the identifier related to the conditions of the first element as expected by the terminal.
  • the specific steps for obtaining the identifier related to the condition of the first element corresponding to the AI/ML model or AI/ML function of the terminal can include: determining the measurement quantity corresponding to the AI/ML model or AI/ML function of the terminal, and the measurement quantity is obtained by measuring the DL-PRS sent by at least one TRP respectively. Therefore, the condition of the first element of the at least one TRP of the measurement quantity can be obtained, thereby determining the identifier associated with the condition of the first element of the at least one TRP of the measurement quantity as the identifier related to the condition of the first element corresponding to the AI/ML model or AI/ML function of the terminal.
  • condition-related identifier of the first element expected by the terminal may mean that if the first element expected by the terminal is known, the condition of the first element is known. Therefore, the terminal sends the condition-related identifier of the known first element to the network device.
  • the second identifier and the first element satisfy at least one of the following conditions:
  • the second identifier is a condition-related identifier for the TRP set
  • the second identifier is related to the conditions of the community
  • the second identifier is an identifier related to the conditions of a TRP
  • the second identifier can be set at the TRP level.
  • a condition of a TRP can be associated with a second identifier.
  • the conditions of a TRP can refer to the conditions of a single TRP device.
  • the second identifier is an identifier related to a condition of a TRP set
  • the second identifier can be set at the TRP set level.
  • a condition of a TRP set can be associated with a second identifier.
  • the conditions of a TRP set may refer to the conditions of one or more TRPs included in the TRP set not individually identifying the conditions of each TRP, but rather combining the conditions of one or more TRPs included in the TRP set into a joint identifier.
  • the terminal only needs to recognize the identifier of the conditions of the TRP set, without needing to know the identifier of the conditions of each TRP in the TRP set.
  • the second identifier can be set at the cell level. Specifically, a cell's conditions can be associated with one second identifier.
  • the conditions of a cell may refer to the conditions belonging to a single cell.
  • the second identifier is a condition-related identifier for a region
  • the second identifier can be set at the region level.
  • a condition for a region can be associated with a second identifier.
  • the conditions of a region may refer to the conditions of one or more cells included in the region, where the conditions of each cell are not identified individually, but rather the conditions of one or more cells included in the region are identified together.
  • the terminal only needs to recognize the identifier of the conditions of the region, and does not need to know the identifier of the conditions of each cell in the region.
  • Step 404 The terminal performs positioning processing through AI/ML models or AI/ML functions.
  • step 404 may include: obtaining the measurement quantity corresponding to the first element, inputting the measurement quantity into an AI/ML model or AI/ML function, and obtaining the positioning result of the terminal.
  • the AI/ML model or AI/ML function can be the terminal's AI/ML model or AI/ML function.
  • the measurement quantity corresponding to the first element may refer to at least one of the following: the measurement quantity obtained by the terminal measuring the DL-PRS sent by the TRP in the first element; the measurement quantity obtained by the terminal measuring the DL-PRS sent by the TRP in the TRP set of the first element; the measurement quantity obtained by the terminal measuring the DL-PRS sent by the TRP in the region of the first element.
  • the measurement quantity corresponding to the first element may include the terminal detecting the DL-PRS sent by at least one TRP to obtain multiple measurement quantities.
  • the at least one TRP may be a TRP in the first element, a set of TRPs, a cell, or at least one TRP in a region.
  • At least one TRP can be one or more TRPs in the first element, or one or more TRPs in the TRP set, or one or more TRPs in the cell, or one or more TRPs in the area.
  • the terminal can determine whether a first condition is met.
  • the first condition can be set to determine whether it is consistent with the AI/ML model or AI/ML function on the network side. If the first condition is met but consistency is not possible, the terminal can send second information back to the network device, providing identification-related content to the network device to complete information synchronization promptly. If the first condition is not met, it can be determined that the AI/ML model or AI/ML function can be used for terminal positioning, obtaining the terminal's positioning result. This achieves secure and efficient terminal positioning.
  • the terminal can execute step 404 if it determines that the first condition is not met.
  • the failure to meet the first condition includes at least one of the following:
  • the first identifier is the same as the second identifier; the TRP corresponding to the first identifier is the same as the TRP corresponding to the second identifier.
  • the input to the AI/ML model can be a measurement quantity, which can be obtained by measuring the DL-PRS through a terminal.
  • the DL-PRS is then sent by the TRP.
  • the first identifier is an identifier related to the condition of the first element.
  • the second identifier can also be an identifier related to the condition of the first element.
  • the terminal can use the AI/ML model or AI/ML function corresponding to that condition. That is, having the first and second identifiers the same can solve the problem of consistency of "conditions" at different stages.
  • the terminal can measure the DL-PRS sent by each of the multiple TRPs to obtain multiple measurements, which together constitute the input-related measurements of the AI/ML model.
  • Figure 5 shows an example diagram of a TRP. Referring to Figure 5, assuming there are 18 TRPs numbered 0-17 in region 501, the terminal can obtain the measurements corresponding to each of the 18 TRPs by detecting the DL-PRS sent by each of the 18 TRPs.
  • the first identifier can, for example, be associated with one or more TRPs.
  • the terminal can determine a first identifier corresponding to each of the multiple TRPs. That is, the multiple TRPs correspond to an identifier set, which includes the first identifiers corresponding to each of the multiple TRPs.
  • the multiple TRPs related to the model input determined by the terminal are consistent with the multiple TRPs in the training phase, and the identifier set corresponding to the multiple TRPs in the inference phase is consistent with the identifier set of the multiple TRPs in the training phase.
  • the network-side conditions are consistent with the terminal-side conditions, and the UE can use the measurements corresponding to these multiple TRPs for model inference.
  • the consistency of multiple TRPs in the inference phase and multiple TRPs in the training phase can mean that the conditions of multiple TRPs in the inference phase are the same as the conditions of multiple TRPs in the training phase.
  • the terminal uses the measurement quantities corresponding to the TRP set with the same first identifier to train the AI model; during model inference, the terminal determines the TRP set of the measurement quantities related to the model input. If the TRP set in the inference stage is consistent with the TRP set in the training stage, and the first identifier of the TRP set in the inference stage is consistent with the first identifier of the TRP set in the training stage, then it can be determined that the conditions in the training stage and the conditions in the inference stage are consistent, and the terminal can use the measurement quantities corresponding to the TRP set for model inference.
  • the network device configures a cell list while configuring DL-PRS to the terminal.
  • This cell list consists of 1 to 256 cell identifiers.
  • one cell in the cell list can correspond to one first identifier. That is, the cell list includes not only 1 to 256 cell identifiers, but also the first identifier corresponding to each cell identifier.
  • the first identifier is at the region level, with one region corresponding to one first identifier.
  • the network device can configure a cell list while configuring DL-PRS to the terminal.
  • This cell list includes at least one cell identifier belonging to the same region; in this case, one cell list as a whole corresponds to one first identifier.
  • satisfying the first condition may include the first identifier and the second identifier being different.
  • the conditions associated with the first identifier are also different from those associated with the second identifier.
  • the difference between the first identifier and the second identifier still presents the problem of inconsistent "conditions" at different stages.
  • the first identifier and the second identifier can be different if at least one of the following conditions is met:
  • the first and second identifiers corresponding to TRP are different;
  • the first and second identifiers corresponding to the TRP sets are different;
  • the first and second signs for the residential area are different.
  • the first and second identifiers for the cell set are different.
  • the difference between the first identifier and the second identifier can satisfy any of the following:
  • the first identifier and the second identifier are different M times consecutively, where M is a positive integer.
  • the first identifier and the second identifier are different N times within the first time period, where N is a positive integer.
  • the first identifier and the second identifier are different M times can mean that the first identifier and the second identifier corresponding to the TRP are different M times consecutively.
  • the M different first identifiers and second identifiers can mean that the first identifier and the second identifier are different in each of the M consecutive positioning processes. Specifically, in the first positioning process, the first identifier corresponding to the first TRP is received, and the second identifier corresponding to this first TRP is different from the first identifier. Then, in the second positioning process, the first identifier corresponding to the second TRP is received, and the second identifier corresponding to this second TRP is different from the first identifier. In this case, the two consecutive differences can be recorded, and M is set to 2.
  • the first time period can be a predefined time period or a time period negotiated between the terminal and the network device.
  • the network device can send a first duration to the terminal.
  • the terminal receives the sum of the first durations and confirms them. After confirmation, the first duration can be used to determine the first time period.
  • the fact that the first identifier and the second identifier differ N times within a first time period can mean that the first identifier and the second identifier corresponding to the TRP are different in each of the N positioning processes within the first time period. It is understood that the N positioning processes within the first time period can be continuous or discontinuous.
  • the fact that the first identifier and the second identifier are different N times within a first time period can mean that the first identifier and the second identifier corresponding to the TRP set are different N times within a first time period.
  • the differences between the first identifier and the second identifier can be categorized into the following cases:
  • the first element includes P TRPs (measurements corresponding to the P TRPs from the input of the terminal's AI/ML model or AI/ML function), and the first identifier and the second identifier are different, satisfying any one of the following:
  • the first and second identifiers for each of the P TRPs are different;
  • At least one of the P TRPs has a different first identifier and a different second identifier
  • the first and second identifiers of Q TRPs in P TRPs are different, and Q is greater than or equal to the first quantity threshold, or the ratio of Q to P is greater than or equal to the first ratio threshold.
  • P is a positive integer
  • Q is a positive integer
  • the fact that the first identifier and the second identifier corresponding to the P TRPs are both different may include: the first identifier corresponding to the P TRPs indicated by the first information is different from the second identifier corresponding to the P TRPs corresponding to the AI/ML model or AI/ML function expected by the terminal.
  • the fact that the first identifier and the second identifier corresponding to the P TRPs are both different may include: the first identifier and the second identifier corresponding to the TRP set to which the P TRPs are located are different.
  • the difference between the first identifier and the second identifier corresponding to each of the P TRPs may include: the first identifier of the P TRPs included in the inference data of the AI model is different from the second identifier of the P TRPs included in the training data.
  • the difference between the first and second identifiers for Q TRPs out of P TRPs may include the number of TRPs whose first identifiers in the inference data of the AI model and the second identifiers in the training data are different, which is Q.
  • Q is greater than or equal to a first quantity threshold
  • the ratio of Q to P is greater than or equal to a first ratio threshold.
  • the first identifier includes P′ cells (the terminal's AI/ML model or the input of the AI/ML function corresponds to P′ TRP measurements), and the first identifier and the second identifier are different if any of the following conditions are met:
  • Each of the P′ cells has a different first and second identifier
  • At least one of the P′ cells has a different first identifier and a different second identifier
  • Q′ cells have different first and second identifiers, and Q′ is greater than or equal to the second quantity threshold, or the ratio of Q′ to P′ is greater than or equal to the second ratio threshold;
  • P′ is a positive integer
  • Q′ is a positive integer
  • the conditions of P′ cells on the network side are respectively associated with a first identifier.
  • the conditions of P′ cells on the terminal side are respectively associated with a second identifier.
  • the fact that the first and second identifiers of the P′ cells are different can mean that the first and second identifiers of the condition associations of each of the P′ cells are different.
  • the difference between the first identifier and the second identifier of at least one of the P′ cells may mean that at least one of the P′ cells is referred to as cell #1, and the first identifier and the second identifier of each cell #1 are different.
  • the difference between the first identifier and the second identifier for Q′ cells out of P′ cells may mean that there are Q′ cells out of P′ cells, and all Q′ cells use cell #2, in which case the first identifier and the second identifier for each cell #2 are different.
  • the first element includes P′′ regions (the terminal's AI/ML model or the input of the AI/ML function corresponds to P′′ TRP measurements), and the first identifier and the second identifier are different, satisfying any one of the following:
  • the first and second identifiers for each of the P′′ regions are different;
  • At least one region has a different first identifier and a different second identifier
  • the first and second identifiers corresponding to Q' regions in P' regions are different, and Q' is greater than or equal to the third quantity threshold, or the ratio of Q' to P' is greater than or equal to the third ratio threshold.
  • P′′ is a positive integer
  • Q′′ is a positive integer
  • the difference between the first identifier and the second identifier corresponding to the P′′ regions may mean that the first identifier corresponding to the P′′ regions sent by the network device is different from the second identifier corresponding to the P′′ regions of the AI/ML model or AI/ML function of the terminal device.
  • the first element includes P′′′ TPR sets (the measurement quantities of P′′′ TPRs corresponding to the input of the terminal's AI/ML model or AI/ML function), and the first identifier and the second identifier are different, satisfying any one of the following:
  • the first and second identifiers of the P′′′ TPR sets are different;
  • At least one of the P′′′ TPR sets has a different first identifier and a different second identifier
  • the first and second identifiers of Q′′′ TPR sets in P′′′ are different, and Q′′′ is greater than or equal to the fourth quantity threshold, or the ratio of Q′′′ to P′′′ is greater than or equal to the fourth ratio threshold;
  • P′′′ is a positive integer
  • Q′′′ is a positive integer
  • the difference between the first identifier and the second identifier corresponding to the P′′′ TPR sets may mean that the first identifier corresponding to the P′′′ TPR sets sent by the network device is different from the second identifier corresponding to the P′′′ TPR sets of the AI/ML model or AI/ML function of the terminal device.
  • the network device can issue DCI or other commands or information to configure the aforementioned parameters. These parameters can be configured all at once or in multiple steps. For example, the network device can issue a first configuration signaling to configure M and N, then issue a second configuration signaling to configure P, Q, a first quantity threshold, and a first proportion threshold. Finally, a third configuration signaling can be issued to configure P′, Q′, a second quantity threshold, and a second proportion threshold.
  • the similarity or difference between the first identifier and the second identifier is described in detail, enabling the terminal to quickly complete the consistency identification of "conditions" at different stages based on the first identifier and the second identifier. This effectively improves the efficiency and accuracy of "condition” consistency identification. Furthermore, the transmission of the first identifier avoids the direct transmission of "conditions," preventing direct information leakage during communication and improving communication security.
  • FIG. 6 is another signaling diagram of an information transmission method provided in an embodiment of this disclosure.
  • the information transmission method may include the following steps:
  • a network device such as an LMF, sends first information to a terminal.
  • the terminal can then receive this first information.
  • This first information may, for example, include a first area.
  • the first region includes at least one of the following:
  • the effective area for measuring the reference signal is the effective area for measuring the reference signal
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device.
  • the network device may send a reference signal to the terminal, which may be, for example, a DL-PRS.
  • the reference signal may contain configuration information of the valid area.
  • the reference signal may carry an area identifier.
  • the area identifier may be, for example, an area tracking code or other identifier. In this embodiment, there are no excessive limitations on how the area is divided and how the area identifier is defined.
  • the effective area configured by the reference signal may refer to the effective area directly defined by the reference signal.
  • the effective region can refer to the region where assistance data is available. Assistance data could be, for example, nr-dl-tdoa-ProvideAssistanceData.
  • the effective area for reference signal measurement can refer to the signal coverage area that can be measured by a terminal after the reference signal is emitted. For example, if a terminal within 100 meters can measure the reference signal after it is emitted by the TRP, then the effective area for reference signal measurement can refer to the signal coverage area formed by a circle with the TRP emitting the reference signal as the center and a radius of 100 meters.
  • the effective region corresponding to the AI/ML model or AI/ML function can be obtained through the following steps: determining the measurement quantity corresponding to the AI/ML model or AI/ML function, obtaining the TRP corresponding to the measurement quantity, and determining the effective region based on the TRP corresponding to each measurement quantity.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device includes at least one of the following: TRP, TRP set, cell or region.
  • the AI/ML model or AI/ML function of the network device can correspond to a measurement quantity, and the TRP corresponding to the measurement quantity can be used to determine at least one of the TRP, TRP set, cell, or area.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device may include at least one of the following: the area corresponding to the TRP, the area corresponding to the set of TRPs, the area corresponding to the cell, or the area corresponding to at least one cell in the area.
  • the area corresponding to a TRP can refer to the radiation range of the signal emitted by the TRP, that is, the range within which the signal can be detected.
  • the area corresponding to a TRP can also refer to the radiation range formed by one or more TRPs.
  • the area corresponding to a set of TRPs can refer to the radiation range formed by one or more TRPs in the set of TRPs.
  • the area corresponding to a cell can refer to the coverage area of the cell.
  • An area can indicate the area obtained by merging the coverage areas corresponding to at least one cell in the area.
  • the terminal sends second information to the network device.
  • the network device can receive this second information.
  • the second information may, for example, include area-related information.
  • the terminal sends second information when a second condition is met.
  • satisfying the second condition may include: receiving third indication information, the third indication information indicating that the first region currently configured by the network device is different from the first region maintained by the terminal device (i.e., the first identifier previously configured by the network device); the first region is different from the second region.
  • the location request sent by the LMF may carry the third indication information. Accordingly, the terminal may receive the location request.
  • a field in the location request can be configured to carry third-party indication information. That is, when a network device sends a location request to a terminal, the location request may include third-party indication information.
  • a field in the location request can be configured to carry this third-party indication information. For instance, assuming this field is 1 bit, a value of 1 indicates that third-party indication information has been received. A value of 0 indicates that third-party indication information has not been received.
  • the terminal may execute step 602 based on the third instruction information.
  • the difference between the first region and the second region can refer to the difference between the region information of the first region and the region information of the second region. Specifically, when the terminal receives the first region, it receives the region information of the first region. If the region information of the terminal's second region is different from the region information of the first region, it indicates that the first region and the second region are different.
  • the region information may include, for example, a region identifier, a region name, etc.
  • the region-related information includes a third region, which is any one of the following: the effective region corresponding to the terminal's AI/ML model or AI/ML function, or the effective region expected by the terminal.
  • the effective area corresponding to the terminal's AI/ML model or AI/ML function can be determined by the measurement quantity corresponding to the terminal's AI/ML model or AI/ML function.
  • the TRP corresponding to the measurement quantity can be obtained through the terminal's AI/ML model or AI/ML function, thereby obtaining at least one of the following: the TRP corresponding to the measurement quantity, the TRP set to which the TRP corresponding to the measurement quantity belongs, the cell to which the TRP corresponding to the measurement quantity belongs, or the area to which the TRP corresponding to the measurement quantity belongs.
  • a third area is then determined based on the TRP corresponding to the measurement quantity, the TRP set to which the TRP corresponding to the measurement quantity belongs, the cell to which the TRP corresponding to the measurement quantity belongs, or the area to which the TRP corresponding to the measurement quantity belongs.
  • the third region includes at least one of the following: TRP, TRP set, cell, or region.
  • the third region may include the region corresponding to a TRP. And/or, the third region may include the region corresponding to a set of TRPs. And/or, the third region may include the region corresponding to a cell. And/or, the third region may include a region, i.e., the region corresponding to at least one cell.
  • the third region is located in the first region.
  • the TRP, TRP set, cell, or cell set corresponding to the terminal's AI/ML model or AI/ML function is located in the valid area configured by the network device for the terminal device.
  • the information transmission method provided in this disclosure embodiment further includes...
  • Step 603 The terminal sends a first measurement quantity and/or a second region to the network device.
  • the second region is at least one of the following: the TRP, TRP set, cell, or region corresponding to the first measurement quantity.
  • the first measurement quantity is a measurement quantity determined based on a reference signal.
  • the second region is the region corresponding to at least one of the TRP, TRP set, cell, or region corresponding to the first measurement.
  • the second region may be the region corresponding to the TRP.
  • the TRP corresponding to the first measurement belongs to the TRP configured by the network device
  • the set of TRPs corresponding to the first measurement belongs to the set of TRPs configured by the network device
  • the cell corresponding to the first measurement belongs to the cell configured by the network device
  • the area corresponding to the first measurement belongs to the area configured by the network device.
  • the measured quantities may include at least one of the following: CIR (Channel Impulse Response), PDR (Power Delay Profile), and DP (Delay Profile).
  • CIR can refer to time information, power information, and phase information related to the channel response.
  • PDR may include time information and power information related to the channel response.
  • DP may include time information related to the channel response.
  • step 603 may include: sending the first measurement and/or the second region to the network device if the second region belongs to the effective region corresponding to the AI/ML model or AI/ML function of the network device.
  • the terminal can receive the first information.
  • the first information may include a first region.
  • the first region can be a region configured by the network device for the terminal, enabling the terminal to clearly understand the regional situation on the network side.
  • the terminal can send second information to the network device, the second information containing region-related information, enabling the network side to promptly know the terminal's regional needs and achieve regional synchronization between the two. This can solve the problem of low positioning accuracy caused by regional asynchrony.
  • the first information in this embodiment may exist in the stages of data collection, model or function inference, and model or function performance monitoring of AI/ML models or functions.
  • Step 1 The LMF determines first information, which includes a first identifier.
  • the first identifier is an identifier related to the conditions of a first element.
  • the first element includes at least one of the following: TRP, TRP set, cell, and region.
  • the region includes at least one cell.
  • the first identifier of the network-side "condition" which can also be called the associated ID, is related to the TRP or TRP set or cell or region.
  • Step 2 LMF sends the first information to the terminal.
  • the number of TRPs can be multiple. Therefore, the relationship between the association identifier determined or sent by the LMF and multiple TRPs can be one of the following possibilities:
  • Possibility 1 The association identifier is related to TRP.
  • the association identifier is related to the TRP, and one TRP corresponds to one association identifier.
  • the TRP ID is generally represented by dl-PRS-ID, but it can be extended to one TRP-ID, one dl-PRS-ID, or one PRS configuration corresponding to one association identifier.
  • the UE uses the measurements corresponding to multiple TRPs to train the AI model.
  • the UE maintains the association identifiers corresponding to each TRP in the multiple TRPs, and each multiple TRP corresponds to one set of association identifiers.
  • model inference if the multiple TRPs of the model input related to the UE are consistent with the multiple TRPs in the training phase, and the set of association identifiers corresponding to the multiple TRPs in the inference phase is consistent with the set of association identifiers of the multiple TRPs in the training phase, then the network-side "conditions" are consistent, and the UE can use the measurements corresponding to the multiple TRPs for model inference.
  • the association identifier is related to the TRP set, with one association identifier corresponding to one TRP set.
  • the LMF indicates the TRP set while configuring the association identifier to the UE. Specifically, the LMF indicates the TRPs included in the TRP set; for example, the LMF indicates that the TRP set includes M dl-PRS-IDs corresponding to M TRPs. Alternatively, the LMF indicates the association identifier simultaneously when indicating the dl-PRS-ID corresponding to each of the M TRPs included in the TRP set. In this case, the association identifier corresponding to each of the M TRPs included in the TRP set is the same.
  • the UE uses the measurement quantities corresponding to the TRP set with the same association identifier to train the AI model.
  • model inference if the TRP set of the measurement quantities related to the model input determined by the UE is consistent with the TRP set in the training phase, and the association identifier of the TRP set in the inference phase is consistent with the association identifier of the TRP set in the training phase, then the network-side "condition or additional condition" is consistent, and the UE can use the measurement quantities corresponding to the TRP set for model inference.
  • Possibility 3 The associated identifier is related to the community.
  • the association identifier is cell-related, with one cell corresponding to one association identifier.
  • the LMF configures a region ID-cell list along with the DL-PRS to the UE.
  • This region ID-cell list includes 1 to 256 NR cell IDs.
  • one NR cell ID in the region ID-cell list can correspond to one association identifier. That is, the region ID-cell list includes not only 1 to 256 NR cell IDs, but also the association identifier corresponding to each NR cell ID.
  • Possibility 4 The association identifier is related to the region (cell set).
  • the association identifier is related to the region (cell set), and one region corresponds to one association identifier.
  • the LMF configures DL-PRS to the UE, it also configures the region ID-cell list.
  • one region ID-cell list corresponds to one association identifier.
  • the terminal may also send a second information to the LMF, which may specifically include the information in action 1 and/or action 2.
  • Action 1 The terminal sends the network-side "condition” association identifier (second identifier) corresponding to the AI model or AI function to the LMF, or sends the preferred network-side "condition” association identifier (second identifier), or sends the network-side "condition” association identifier (second identifier) corresponding to the training data or inference data of the AI model or AI function.
  • Behavior 2 The terminal does not need to report the association identifier (second identifier) corresponding to its own AI model. Instead, it relies on the consistency of the association identifiers indicated by the LMF during the training and inference phases. For example, if it is determined that the association identifier of the "inference data of the AI model or AI function" is different from the association identifier of the training data, the terminal sends the supported AI/ML model or AI/ML function, or a valid AI/ML model or AI/ML function, or a rollback request to the LMF.
  • This scheme does not require the terminal to send its supported association identifiers, but the LMF needs to include/indicate the association identifiers in the relevant configurations of the terminal's AI/ML model or AI/ML function during both the data collection and inference phases.
  • the execution of behavior 1 may require certain conditions to be met, such as the first condition in the embodiments of this disclosure.
  • the first condition may specifically include the following:
  • the terminal determines that the association identifier of "LMF sent” or "AI model or AI function inference data" does not meet the association identifier of the training data, that is, the first identifier and the second identifier are different, the terminal sends the difference between the first identifier and the second identifier as a message to LMF;
  • the association identifier of the "LMF sent" or “the inference data of the AI model or AI function does not meet the association identifier of the training data” can be extended to M times within a period of time that do not meet the association identifier of the training data or N consecutive times that do not meet the association identifier of the training data.
  • the terminal will send the difference between the first identifier and the second identifier as a message to the LMF.
  • the LMF can be configured with the time period and the values of M and N.
  • the information sent by the terminal to the LMF includes: the association identifier currently sent by the LMF does not satisfy the association identifier of the training data of "inference data of AI model or AI function"; and/or the association identifier of the training data of "inference data of AI model or AI function”; and/or several association identifiers of the network-side “conditions or additional conditions" expected by the UE (different association identifiers may correspond to different AI models or AI functions).
  • association identifier may be related to TRP, TRP set, cell, or region.
  • the association identifier of "AI model or AI function inference data" may not meet the association identifier of training data in the following situations:
  • association identifiers of multiple TRPs in the inference data of the AI model are different from those of multiple TRPs in the training data, it is counted as 1 instance of non-compliance.
  • the AI model is considered satisfied only if the association identifiers of multiple TRPs in the inference data and the association identifiers of multiple TRPs in the training data are the same; otherwise, it is not satisfied.
  • the number of association identifiers of multiple TRPs included in the inference data of the AI model is different from the number of association identifiers of multiple TRPs included in the training data, and the proportion of such number exceeds the first ratio threshold, it is counted as 1 instance of non-compliance.
  • the first proportional threshold or the first quantity threshold can be agreed upon by the protocol or configured by LMF;
  • association identifier of the TRP set included in the inference data of the AI model is different from the association identifier of the TRP set included in the training data, it is counted as 1 instance of non-compliance.
  • association identifiers of multiple cells corresponding to the inference data of the AI model are different from the association identifiers of multiple cells corresponding to the training data, it is counted as 1 instance of non-compliance.
  • the AI model is considered satisfied only if the association identifiers of multiple cells corresponding to the inference data are the same as the association identifiers of multiple cells corresponding to the training data; otherwise, it is not satisfied.
  • the number of association identifiers of multiple cells corresponding to the inference data of the AI model are different from the association identifiers of multiple cells corresponding to the training data, and the number of such identifiers exceeds the second quantity threshold or the proportion of such identifiers exceeds the second proportion threshold, it is counted as one instance of non-compliance.
  • the second quantity threshold and the second proportion threshold can be agreed upon by the protocol or configured by LMF.
  • association identifiers of the regions containing multiple TRPs in the inference data of the AI model are different from the association identifiers of the regions containing multiple TRPs in the training data, it is counted as 1 instance of non-compliance.
  • the terminal when the terminal sends the second information to the LMF, it is a dynamic reporting process, which can be performed according to the LMF's instructions or by the terminal itself.
  • the LMF sends a location request to the terminal.
  • the location request may carry indication information that instructs the UE to report the associated identifier of the AI model or AI function.
  • the terminal can then report the relevant information in Action 1 and/or Action 2 based on the indication information.
  • the terminal may trigger a location request, carrying the relevant information from Action 1 and/or Action 2. For example, if the terminal downloads a new AI model, the associated identifier of which may change, and the UE actively informs the LMF of the changed association identifier.
  • Step 1 The LMF determines the first information, which includes: the effective area (first area) of the reference signal configuration, and the reference signal may be a DL-PRS;
  • Step 2 The LMF sends the first message to the UE.
  • the valid area (validity area) (first area) of the reference signal configuration can be the area where auxiliary data (e.g., NR-DL-TDOA-ProvideAssistanceData) is available. Based on this valid area, the UE can determine the valid area for auxiliary data such as DL-PRS. That is, the valid area of auxiliary data related to the reference signal configuration is mainly controlled by LMF.
  • auxiliary data e.g., NR-DL-TDOA-ProvideAssistanceData
  • the LMF sends the valid area (first area) of the reference signal configuration to the UE.
  • the UE determines that the valid area of the "LMF-sent" or “inference data of the AI model or AI function" does not meet the valid area of the training data, the UE sends this information to the LMF.
  • the information sent by the UE to the LMF includes: the effective area of the reference signal configuration currently sent by the LMF does not satisfy the effective area of the reference signal configuration of the training data of the "AI model or AI function inference data" (third indication information); and/or, the effective area of the reference signal configuration of the training data of the "AI model or AI function inference data” (third area); and/or, several effective areas of the reference signal configuration of the network-side "conditions or additional conditions" expected by the UE (third area).
  • Dynamic reporting The UE reports the effective area (third area) of the reference signal configuration according to the LMF's instructions, or the UE actively reports the effective area (third area) of the reference signal configuration.
  • the valid area (third area) of the reference signal configuration may also include the valid area (third area) of the AI model or AI function.
  • the valid area (third area) of the AI model or AI function can be sent by the UE to the LMF.
  • the valid area is all combinations of TRPs corresponding to the AI model or AI function. That is, the valid area (third area) of the AI model or AI function may be a set of N valid TRPs, which is the valid area of the AI model, mainly related to the UE's measurement.
  • the LMF sends the effective area (first area) of the reference signal configuration to the UE.
  • the UE can determine the measurement quantities related to the AI model and determine the effective area (third area) corresponding to the AI model or AI function.
  • the UE then sends the effective area corresponding to the AI model or AI function to the LMF.
  • the TRP or set of TRPs included in the effective area (third area) corresponding to the AI model or AI function should belong to or be located within the effective area (first area) of the reference signal configuration.
  • the LMF When the AI model is on the LMF side, the LMF sends the effective area (first area) corresponding to the AI model or AI function to the UE.
  • the LMF can also configure the effective area (first area) of the reference signal configuration to the UE.
  • the UE will not provide the measurement quantity to the LMF.
  • the UE provides the LMF with measurement quantities and auxiliary information (the second region corresponding to the measurement quantity) to determine the effective region corresponding to the AI model or AI function, such as TRP-ID or dl-PRS-ID, according to the LMF configuration.
  • auxiliary information the second region corresponding to the measurement quantity
  • this disclosure also provides an information transmission device.
  • This information transmission device can realize the functions of the terminal in the foregoing embodiments.
  • the information transmission device may include: a receiving unit 701, a processing unit 702, and may also include a sending unit 703.
  • the receiving unit 701 is a receiving unit used to receive first information sent by the network device, the first information including a first identifier and/or a first area;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • the first identifier and the first element satisfy at least one of the following conditions:
  • the first identifier is a condition-related identifier of the TRP
  • the first identifier is a condition-related identifier for the TRP set
  • the first identifier is a condition-related identifier for the cell
  • the first identifier is a condition-related identifier for the region.
  • the first information may further include set information of the TRP set;
  • the set information of the TRP set includes the TRP set identifier, and/or the identifier of at least one TRP in the TRP set.
  • the sending unit 703 is configured to send second information to the network device, the second information including identification-related information and/or region-related information.
  • the identification-related information includes at least one of the following:
  • the second identifier is an identifier related to the conditions of the first element
  • the first indication information indicates that the first identifier is different from the second identifier
  • a rollback request is used to request the network device to roll back to a first positioning function, wherein the first positioning function is a positioning function other than a positioning function based on an AI/ML model or an AI/ML function.
  • the terminal supports AI/ML models or AI/ML functions
  • the second identifier is any one of the following:
  • the terminal expects an identifier related to the conditions of the first element.
  • the second identifier and the first element satisfy at least one of the following conditions:
  • the second identifier is a condition-related identifier for the TRP
  • the second identifier is a condition-related identifier for the TRP set
  • the second identifier is a condition-related identifier for the cell
  • the second information includes the identification-related information
  • the processing unit 702 is further configured to perform the following operations:
  • the second information is sent to the network device via the sending unit 703;
  • the first condition includes at least one of the following:
  • the first identifier is different from the second identifier
  • the second instruction Upon receiving the second instruction, the second instruction indicates that the identification-related information be reported.
  • the first identifier is different from the second identifier if any one of the following conditions is met:
  • the first identifier and the second identifier are different M times consecutively, where M is a positive integer;
  • the first identifier and the second identifier are different N times within a first time period, where N is a positive integer.
  • the first element includes P TRPs, and the first identifier and the second identifier are different from each of the following:
  • the first and second identifiers corresponding to the P TRPs are all different;
  • At least one of the P TRPs has a different first identifier and a different second identifier
  • the first identifier and the second identifier corresponding to Q TRPs in the P TRPs are different, and Q is greater than or equal to a first quantity threshold, or the ratio of Q to P is greater than or equal to a first ratio threshold;
  • P is a positive integer
  • Q is a positive integer
  • the first identifier includes P′ cells, and the first identifier and the second identifier are different from each of the following:
  • the first and second identifiers corresponding to the P′ cells are all different;
  • At least one of the P′ cells has a different first identifier and a different second identifier
  • the first identifier and the second identifier of Q′ cells in the P′ cells are different, and Q′ is greater than or equal to the second quantity threshold, or the ratio of Q′ to P′ is greater than or equal to the second ratio threshold;
  • P′ is a positive integer
  • Q′ is a positive integer
  • the first region includes at least one of the following:
  • the effective area for measuring the reference signal is the effective area for measuring the reference signal
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device includes at least one of the following: TRP, TRP set, cell, or region.
  • the sending unit 703 is further configured to perform the following operations:
  • the second region is at least one of the TRP, TRP set, cell, or region corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.
  • processing unit 702 is further configured to perform the following operations:
  • the first measurement quantity and/or the second region are sent to the network device through the sending unit 703.
  • the region-related information includes a third region, which is any one of the following: the effective region corresponding to the AI/ML model or AI/ML function of the terminal, or the effective region expected by the terminal.
  • the third region includes at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • the third region is located in the first region, where the first region is an effective region configured for the reference signal and/or an effective region for the reference signal measurement.
  • the apparatus provided in this embodiment can implement all the method steps implemented by the method embodiment executed by the network device and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.
  • this disclosure also provides an information transmission device.
  • This information transmission device can realize the functions of the network device in the foregoing embodiments.
  • the information transmission device may include a receiving unit 801 and a sending unit 802.
  • the sending unit 802 is configured to: send first information to the terminal, wherein the first information includes a first identifier and/or a first region;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • the first identifier and the first element satisfy at least one of the following conditions:
  • the first identifier is a condition-related identifier of the TRP
  • the first identifier is a condition-related identifier for the TRP set
  • the first identifier is a condition-related identifier for the cell
  • the first identifier is a condition-related identifier for the region.
  • the first information may further include set information of the TRP set;
  • the set information of the TRP set includes the TRP set identifier, and/or the identifier of at least one TRP in the TRP set.
  • the receiving unit 801 may specifically be used for:
  • the terminal sends a second message, which includes identification-related information and/or region-related information.
  • the identification-related information includes at least one of the following:
  • the second identifier is an identifier related to the conditions of the first element
  • the first indication information indicates that the first identifier is different from the second identifier
  • a rollback request is used to request the network device to roll back to a first positioning function, wherein the first positioning function is a positioning function other than a positioning function based on an artificial intelligence/machine learning ML model or an AI/ML function.
  • the terminal supports AI/ML models or AI/ML functions
  • the second identifier is any one of the following:
  • the terminal expects an identifier related to the conditions of the first element.
  • the second identifier and the first element satisfy at least one of the following conditions:
  • the second identifier is a condition-related identifier for the TRP
  • the second identifier is a condition-related identifier for the TRP set
  • the second identifier is a condition-related identifier for the cell
  • the second identifier is a condition-related identifier for the region.
  • the first region includes at least one of the following:
  • the effective area for measuring the reference signal is the effective area for measuring the reference signal
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device includes at least one of the following: TRP, TRP set, cell, or region.
  • the receiving unit 801 is further configured to perform the following operations:
  • the second region is at least one of the TRP, TRP set, cell, or region corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.
  • the region-related information includes a third region, which is any one of the following: the effective region corresponding to the AI/ML model or AI/ML function of the terminal, or the effective region expected by the terminal.
  • the third region includes at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • the third region is located in the first region, where the first region is an effective region configured for the reference signal and/or an effective region for the measurement of the reference signal.
  • the apparatus provided in this embodiment can implement all the method steps implemented by the method embodiment executed by the network device and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.
  • Figure 9 is a schematic diagram of an information transmission device provided in an embodiment of this disclosure. As shown in Figure 9, the device includes a memory 901, a transceiver 902, and a processor 903. This information transmission device is, for example, a terminal.
  • Memory 901 is used to store computer programs
  • Transceiver 902 is configured to receive first information sent by a network device under the control of processor 903, the first information including a first identifier and/or a first area;
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • the processor 903 is used to read computer programs stored in the memory 901 and perform related operations.
  • the conditions of the first identifier and the first element satisfy at least one of the following:
  • the first identifier is a condition-related identifier for the TRP
  • the first identifier is a condition-related identifier for the TRP set
  • the first identifier is a condition-related identifier for the cell
  • the first identifier is a condition-related identifier for the region.
  • the first information may further include set information of the TRP set;
  • the set information of the TRP set includes the TRP set identifier, and/or the identifier of at least one TRP in the TRP set.
  • the transceiver 902 is further configured to:
  • the identification-related information includes at least one of the following:
  • the second identifier is an identifier related to the conditions of the first element
  • the first indication information indicates that the first identifier is different from the second identifier
  • a rollback request is used to request the network device to roll back to a first positioning function, wherein the first positioning function is a positioning function other than a positioning function based on an AI/ML model or an AI/ML function.
  • the terminal supports AI/ML models or AI/ML functions
  • the second identifier is any one of the following:
  • the terminal expects an identifier related to the conditions of the first element.
  • the second identifier and the first element satisfy at least one of the following conditions:
  • the second identifier is a condition-related identifier for the TRP
  • the second identifier is a condition-related identifier for the TRP set
  • the second identifier is a condition-related identifier for the cell
  • the second identifier is a condition-related identifier for the region.
  • the second information includes the identification-related information
  • the processor 903 is specifically used for:
  • the second information is sent to the network device via transceiver 902;
  • the first condition includes at least one of the following:
  • the first identifier is different from the second identifier
  • the second instruction Upon receiving the second instruction, the second instruction indicates that the identification-related information be reported.
  • the first identifier is different from the second identifier if any one of the following conditions is met:
  • the first identifier and the second identifier are different M times consecutively, where M is a positive integer;
  • the first identifier and the second identifier are different N times within a first time period, where N is a positive integer.
  • the first element includes P TRPs, and the first identifier and the second identifier are different from each of the following:
  • the first and second identifiers corresponding to the P TRPs are all different;
  • At least one of the P TRPs has a different first identifier and a different second identifier
  • the first identifier and the second identifier corresponding to Q TRPs in the P TRPs are different, and Q is greater than or equal to a first quantity threshold, or the ratio of Q to P is greater than or equal to a first ratio threshold;
  • P is a positive integer
  • Q is a positive integer
  • the first identifier includes P′ cells, and the first identifier and the second identifier are different from each of the following:
  • the first and second identifiers corresponding to the P′ cells are all different;
  • At least one of the P′ cells has a different first identifier and a different second identifier
  • the first identifier and the second identifier of Q′ cells in the P′ cells are different, and Q′ is greater than or equal to the second quantity threshold, or the ratio of Q′ to P′ is greater than or equal to the second ratio threshold;
  • P′ is a positive integer
  • Q′ is a positive integer
  • the first region includes at least one of the following:
  • the effective area for measuring the reference signal is the effective area for measuring the reference signal
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device includes at least one of the following: TRP, TRP set, cell, or region.
  • the transceiver 902 is further used for
  • the second region is at least one of the TRP, TRP set, cell, or region corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.
  • the processor 903 is specifically used for:
  • the first measurement quantity and/or the second region are sent to the network device via transceiver 902.
  • the region-related information includes a third region, which is any one of the following: the effective region corresponding to the AI/ML model or AI/ML function of the terminal, or the effective region expected by the terminal.
  • the third region includes at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • the third region is located in the first region, where the first region is an effective region configured for the reference signal and/or an effective region for the reference signal measurement.
  • the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 903 and memory represented by memory.
  • the bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described herein.
  • the bus interface provides an interface.
  • the transceiver may be multiple elements, including a transmitter and a receiver, providing units for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc.
  • Processor 903 is responsible for managing the bus architecture and general processing, and the memory may store data used by processor 903 during operation.
  • the processor 903 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD).
  • the processor 903 can also adopt a multi-core architecture.
  • Figure 10 is a schematic diagram of an information transmission device provided in an embodiment of this disclosure. As shown in Figure 10, the device includes: a memory 1001, a transceiver 1002, and a processor 1003. This information transmission device is, for example, a network device.
  • Memory 1001 is used to store computer programs
  • Transceiver 1002 is used to send first information to a terminal under the control of processor 1003, the first information including a first identifier and/or a first area.
  • the first identifier is an identifier related to the conditions of the first element, and the first element includes at least one of the following: Transmission Receiver Point (TRP), TRP set, cell, and region, wherein the region includes at least one cell.
  • TRP Transmission Receiver Point
  • the processor 1003 is used to read computer programs stored in the memory 1001 and perform related operations.
  • the conditions of the first identifier and the first element satisfy at least one of the following:
  • the first identifier is a condition-related identifier of the TRP
  • the first identifier is a condition-related identifier for the TRP set
  • the first identifier is a condition-related identifier for the cell
  • the first identifier is a condition-related identifier for the region.
  • the first information may further include set information of the TRP set;
  • the set information of the TRP set includes the TRP set identifier, and/or the identifier of at least one TRP in the TRP set.
  • the transceiver 1002 is further configured to:
  • the terminal sends a second message, which includes identification-related information and/or region-related information.
  • the identification-related information includes at least one of the following:
  • the second identifier is an identifier related to the conditions of the first element
  • the first indication information indicates that the first identifier is different from the second identifier
  • a rollback request is used to request the network device to roll back to a first positioning function, wherein the first positioning function is a positioning function other than a positioning function based on an artificial intelligence/machine learning ML model or an AI/ML function.
  • the terminal supports AI/ML models or AI/ML functions
  • the second identifier is any one of the following:
  • the terminal expects an identifier related to the conditions of the first element.
  • the second identifier and the first element satisfy at least one of the following conditions:
  • the second identifier is a condition-related identifier for the TRP
  • the second identifier is a condition-related identifier for the TRP set
  • the second identifier is a condition-related identifier for the cell
  • the second identifier is a condition-related identifier for the region.
  • the first region includes at least one of the following:
  • the effective area for measuring the reference signal is the effective area for measuring the reference signal
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device.
  • the effective area corresponding to the AI/ML model or AI/ML function of the network device includes at least one of the following: TRP, TRP set, cell, or region.
  • the transceiver 1002 is further configured to:
  • the second region is at least one of the TRP, TRP set, cell, or region corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.
  • the region-related information includes a third region, which is any one of the following: the effective region corresponding to the AI/ML model or AI/ML function of the terminal, or the effective region expected by the terminal.
  • the third region includes at least one of the following: a TRP, a set of TRPs, a cell, or a region.
  • the third region is located in the first region, where the first region is an effective region configured for the reference signal and/or an effective region for the reference signal measurement.
  • the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 1003 and memory represented by memory.
  • the bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described herein.
  • the bus interface provides an interface.
  • the transceiver may be multiple components, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium, including wireless channels, wired channels, optical fibers, etc.
  • the user interface may also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.
  • the processor 1003 is responsible for managing the bus architecture and general processing, and the memory can store the data used by the processor 1003 when performing operations.
  • the processor 1003 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a CPLD (Complex Programmable Logic Device).
  • the processor 1003 may also adopt a multi-core architecture.
  • the processor 1003 executes any of the methods provided in the embodiments of this disclosure according to the obtained executable instructions by calling a program stored in memory.
  • the processor 1003 and the memory 1001 may also be physically separated.
  • the division of units in the embodiments of this disclosure is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used.
  • the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
  • the integrated units described above can be implemented in hardware or as software functional units.
  • the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium.
  • the technical solution of this disclosure in essence, or the part that contributes to the related technology, or all or part of the technical solution, can be embodied in the form of a software product.
  • This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this disclosure.
  • This disclosure also provides a non-transitory readable storage medium storing a computer program that causes a processor to execute all the method steps of the network device in the above method embodiments.
  • This disclosure also provides a non-transitory readable storage medium storing a computer program that causes a processor to execute all the method steps of the terminal device in the above method embodiments.
  • Non-transitory readable storage media can be any available medium or data storage device that a computer can access, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).
  • magnetic storage such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.
  • optical storage such as CDs, DVDs, BDs, HVDs, etc.
  • semiconductor storage such as ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)
  • This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the above method embodiments.
  • this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.
  • processor-executable instructions may also be stored in a processor-readable memory that can instruct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and/or one or more block diagrams.

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Abstract

La présente divulgation se rapporte au domaine technique des communications, et concerne des procédés et un appareil de transmission d'informations, et un support de stockage. Un procédé comprend les étapes suivantes : un dispositif de réseau peut envoyer des premières informations à un terminal, les premières informations pouvant comprendre un premier identifiant et/ou une première zone, le premier identifiant constituant un identifiant associé à une condition d'un premier élément, et le premier élément constituant un TRP, et/ou un ensemble TRP, et/ou une cellule, et/ou une zone. Le terminal obtient l'identifiant associé à la condition du TRP, et/ou de l'ensemble TRP, et/ou de la cellule et/ou de la zone, de sorte que l'identifiant sur un côté réseau associé à la condition soit synchronisé avec le terminal, et ainsi le terminal peut rester cohérent avec la condition sur le côté réseau au moyen des premières informations, ce qui permet d'assurer la performance de modèles AI/ML ou de fonctions AI/ML.
PCT/CN2025/111034 2024-08-09 2025-07-28 Procédé et appareil de transmission d'informations, et support de stockage Pending WO2026032071A1 (fr)

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CN118175513A (zh) * 2022-12-09 2024-06-11 维沃移动通信有限公司 模型输入信息的确定方法、装置、设备、系统及存储介质

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CN117676628A (zh) * 2022-08-30 2024-03-08 大唐移动通信设备有限公司 信息传输方法、装置及存储介质
CN117835262A (zh) * 2022-09-26 2024-04-05 维沃移动通信有限公司 Ai模型的处理方法、装置及通信设备
WO2024093739A1 (fr) * 2022-11-04 2024-05-10 华为技术有限公司 Procédé et appareil de communication
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