WO2023206028A1 - Procédé et appareil de réception d'informations d'assistance, procédé et appareil d'envoi d'informations d'assistance, appareil de communication et support de stockage - Google Patents

Procédé et appareil de réception d'informations d'assistance, procédé et appareil d'envoi d'informations d'assistance, appareil de communication et support de stockage Download PDF

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Publication number
WO2023206028A1
WO2023206028A1 PCT/CN2022/089095 CN2022089095W WO2023206028A1 WO 2023206028 A1 WO2023206028 A1 WO 2023206028A1 CN 2022089095 W CN2022089095 W CN 2022089095W WO 2023206028 A1 WO2023206028 A1 WO 2023206028A1
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Prior art keywords
auxiliary information
model
terminal
base station
network device
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PCT/CN2022/089095
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English (en)
Chinese (zh)
Inventor
李小龙
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北京小米移动软件有限公司
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Application filed by 北京小米移动软件有限公司 filed Critical 北京小米移动软件有限公司
Priority to PCT/CN2022/089095 priority Critical patent/WO2023206028A1/fr
Priority to CN202280001210.5A priority patent/CN117296402A/zh
Publication of WO2023206028A1 publication Critical patent/WO2023206028A1/fr

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    • 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

Definitions

  • the present disclosure relates to the field of communication technology, and specifically, to an auxiliary information receiving method, an auxiliary information sending method, an auxiliary information receiving device, an auxiliary information sending device, a communication device and a computer-readable storage medium.
  • 5G NR New Radio, New Radio introduces a variety of positioning technologies to realize the positioning of terminals. But in order to further improve positioning accuracy, 5G NR began to consider positioning based on artificial intelligence (Artificial Intelligence, AI).
  • AI Artificial Intelligence
  • embodiments of the present disclosure propose an auxiliary information receiving method, an auxiliary information sending method, an auxiliary information receiving device, an auxiliary information sending device, a communication device and a computer-readable storage medium to solve technical problems in related technologies.
  • a method for receiving auxiliary information is proposed, which is suitable for a first device.
  • the method includes: receiving auxiliary information sent by a second device, wherein the auxiliary information is used to assist the third device.
  • a device determines an AI model, and the AI model is used for terminal positioning.
  • a method for sending auxiliary information is proposed, which is suitable for a second device.
  • the method includes: sending auxiliary information to a first device, wherein the auxiliary information is used to assist the first device.
  • the device determines an AI model, which is used for terminal positioning.
  • an auxiliary information receiving device which is suitable for a first device.
  • the device includes: a receiving module configured to receive auxiliary information sent by a second device, wherein the auxiliary information Used to assist the first device in determining an AI model, where the AI model is used for terminal positioning.
  • an auxiliary information sending device which is suitable for a second device.
  • the device includes: a sending module configured to send auxiliary information to the first device, wherein the auxiliary information is To assist the first device in determining an AI model, the AI model is used for terminal positioning.
  • a communication device including: a processor; a memory for storing a computer program; wherein when the computer program is executed by the processor, the above-mentioned auxiliary information receiving method is implemented.
  • a communication device including: a processor; and a memory for storing a computer program; wherein when the computer program is executed by the processor, the above-mentioned auxiliary information sending method is implemented.
  • a computer-readable storage medium for storing a computer program.
  • the steps in the above auxiliary information receiving method are implemented.
  • a computer-readable storage medium for storing a computer program.
  • the steps in the above auxiliary information sending method are implemented.
  • the network device can send auxiliary information to the terminal, so that the terminal can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • the terminal can send auxiliary information to the network device, so that the network device can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • Figure 1 is a schematic flow chart of a model determination method according to an embodiment of the present disclosure.
  • FIG. 2 is a schematic flow chart of another model determination method according to an embodiment of the present disclosure.
  • Figure 3 is a schematic flow chart of yet another model determination method according to an embodiment of the present disclosure.
  • Figure 4 is a schematic flow chart of a method for sending auxiliary information according to an embodiment of the present disclosure.
  • Figure 5 is a schematic block diagram of an auxiliary information receiving device according to an embodiment of the present disclosure.
  • Figure 6 is a schematic block diagram of an auxiliary information sending device according to an embodiment of the present disclosure.
  • FIG. 7 is a schematic block diagram of a device for assisting information transmission according to an embodiment of the present disclosure.
  • FIG. 8 is a schematic block diagram of a device for assisting information reception according to an embodiment of the present disclosure.
  • first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, the information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other.
  • first information may also be called second information, and similarly, the second information may also be called first information.
  • word “if” as used herein may be interpreted as "when” or "when” or "in response to determining.”
  • the terms used in this article are “greater than” or “less than”, “higher than” or “lower than” when characterizing size relationships. But for those skilled in the art, it can be understood that: the term “greater than” also covers the meaning of “greater than or equal to”, and “less than” also covers the meaning of “less than or equal to”; the term “higher than” covers the meaning of “higher than or equal to”. “The meaning of “less than” also covers the meaning of "less than or equal to”.
  • Figure 1 is a schematic flow chart of a method for receiving auxiliary information according to an embodiment of the present disclosure.
  • the auxiliary information receiving method shown in this embodiment may be applicable to the first device.
  • the auxiliary information receiving method may include the following steps:
  • step S101 auxiliary information sent by the second device is received, where the auxiliary information is used to assist the first device in determining an AI model, and the AI model is used for terminal positioning (determining terminal location).
  • the first device includes a terminal
  • the second device includes a network device.
  • the first device includes a network device
  • the second device includes a terminal.
  • the terminals include but are not limited to mobile phones, tablets, wearable devices, sensors, Internet of Things devices and other communication devices.
  • the terminal can communicate with network equipment, which includes but is not limited to network equipment in 4G, 5G, 6G and other communication systems, such as base stations, core networks, etc.
  • the following embodiments first illustrate the technical solution of the present disclosure in the case where the first device includes a terminal and the second device includes a network device. It should be understood that some embodiments are applicable in both scenarios where the first device includes a terminal and the second device includes a network device, and the first device includes a network device and the second device includes a terminal. For example, the following specific assistance Regarding the limitation of information, in order to avoid redundancy, this disclosure does not repeat the description. Those skilled in the art can select the application scenarios of the embodiments as needed.
  • the AI model can be obtained by training a sample set through a machine learning (deep learning) algorithm.
  • the sample set is different, and the resulting AI model can also be different.
  • the positioning device (such as a terminal or network device) needs to accurately determine the AI model to be used.
  • the terminal when the terminal performs terminal positioning based on the AI model, in order to determine the AI model to be used, there are still certain deficiencies based solely on the information it possesses.
  • the terminal mainly grasps user-side information and only selects an AI model among multiple AI models based on user-side information.
  • the selected AI model may be less applicable to network-side information. Therefore, the network device can send auxiliary information to the terminal, so that the terminal can accurately determine the AI model required for positioning based on the auxiliary information.
  • auxiliary information #1 corresponds to AI model #1
  • auxiliary information #2 corresponds to AI model #2.
  • the AI corresponding to auxiliary information #1 can be determined among multiple AI models (for example, pre-stored). Model #1, and then perform accurate positioning based on the determined AI model.
  • the network device can send auxiliary information to the terminal, so that the terminal can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • the method further includes: sending an acquisition request to the network device for requesting the auxiliary information.
  • the terminal can send an acquisition request to the network device. After receiving the acquisition request, the network device can send the auxiliary information to the terminal. Of course, when the network device does not receive the acquisition request, it can also send the auxiliary information to the terminal as needed.
  • the auxiliary information includes at least one of the following:
  • the terminal can use the AI model recommended by the network device for terminal positioning; and when the first device includes a network device and the second device includes When a terminal is used, the network device can choose to use the AI model recommended by the terminal for terminal positioning, or it can select other AI models for terminal positioning as needed.
  • the usage conditions of the AI model include at least one of the following:
  • the terminal can determine the current conditions, determine which AI model's usage conditions the current conditions meet, and then select the AI model that meets the usage conditions for terminal positioning.
  • the current application scenario can be determined, and then the AI model corresponding to the current application scenario can be determined based on the first association relationship, and then the terminal positioning can be performed using the determined AI model.
  • specific information (such as positioning reference signals, base station information, etc.) can be measured to obtain measurement information, and then the AI model corresponding to the measured measurement information is determined according to the second association relationship, and terminal positioning is performed through the determined AI model.
  • the auxiliary information when the network device includes a base station, the auxiliary information further includes:
  • the type of base station such as macro base station Macro BS and micro base station Micro BS;
  • the transmit power of the base station is the transmit power of the base station.
  • the base station By sending some of its own parameters to the terminal as auxiliary information, the base station helps the terminal determine the AI model to be used more accurately.
  • the measurement information includes at least one of the following:
  • the transmit power of the base station
  • the transmit power of the base station can be obtained by measurement, and then the AI model corresponding to the measured transmit power of the base station can be determined based on the second association relationship, and the terminal positioning can be performed using the determined AI model.
  • the number of base stations can be obtained through measurement, and then the AI model corresponding to the measured number of base stations can be determined according to the second association relationship, and the terminal positioning can be performed through the determined AI model.
  • the positioning reference signal sent by the base station can be measured to obtain the measurement result of the positioning reference signal, and then the AI model corresponding to the measurement result of the positioning reference signal can be obtained according to the second correlation relationship, and the terminal positioning can be performed through the determined AI model.
  • the measurement results of the positioning reference signal include but are not limited to Positioning Reference Signal Reference Signal Receiving Power (PRS-RSRP), reference signal time difference (Reference signal time difference, RSTD), receiving time and sending time.
  • PRS-RSRP Positioning Reference Signal Reference Signal Receiving Power
  • RSTD reference signal time difference
  • the time difference Rx-Tx timing difference
  • the application scenario includes at least one of the following:
  • InF-SL Indoor Factory Sparse clutter, Low BS
  • InF-DL Indoor Factory Dense clutter low-power base station InF-DL (Indoor Factory Dense clutter, Low BS);
  • InF-SH Indoor Factory Sparse clutter, High BS
  • InF-DH Indoor Factory Dense clutter, High BS
  • FIG. 2 is a schematic flow chart of another model determination method according to an embodiment of the present disclosure. As shown in Figure 2, when the auxiliary information includes the first association relationship, the method further includes:
  • step S201 determine the current application scenario
  • step S202 the AI model corresponding to the current application scenario is determined according to the first association relationship.
  • the first association relationship may be sent to the terminal by the network device, and the terminal may determine the current application scenario, and then determine the AI model corresponding to the current application scenario based on the first association relationship, Then the terminal is positioned through the determined AI model.
  • the first association relationship may be pre-stored by the terminal, and the network device may carry the application scenario in which the terminal is located in auxiliary information and send it to the terminal (of course, it may also be independently determined by the terminal), so that the terminal can The first association determines the AI model corresponding to the current application scenario, and then uses the determined AI model to perform terminal positioning.
  • Figure 3 is a schematic flow chart of yet another model determination method according to an embodiment of the present disclosure. As shown in Figure 3, in the case where the auxiliary information includes the second association relationship, the method further includes:
  • step S301 obtain the measurement information
  • step S302 the AI model corresponding to the obtained measurement information is determined according to the second association relationship.
  • the terminal can measure specific information (such as positioning reference signals, base station information, etc.) to obtain measurement information, and then determine the AI model corresponding to the measured measurement information based on the second association relationship, and use the determined AI model performs terminal positioning.
  • specific information such as positioning reference signals, base station information, etc.
  • the auxiliary information is carried in a Radio Resource Control (RRC) message;
  • RRC Radio Resource Control
  • the assistance information is carried in a Long Term Evolution Positioning Protocol LPP (LTE Positioning Protocol) message, for example, LPP provide assistance information (LPP provides assistance information).
  • LPP Long Term Evolution Positioning Protocol
  • the following embodiments illustrate the technical solution of the present disclosure in the case where the first device includes a network device and the second device includes a terminal.
  • the core network mainly grasps the information on the network side, and only selects an AI model among multiple AI models based on the information on the network side.
  • the selected AI model may be less applicable to the information on the terminal side. Therefore, the terminal can send auxiliary information to the network device, so that the network device can accurately determine the AI model required for positioning based on the auxiliary information.
  • auxiliary information #1 corresponds to AI model #1
  • auxiliary information #2 corresponds to AI model #2.
  • the AI corresponding to auxiliary information #1 can be determined among multiple AI models (for example, pre-stored). Model #1, and then perform accurate positioning based on the determined AI model.
  • the terminal can send auxiliary information to the network device, so that the network device can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • the network device may choose to determine the AI model based on the auxiliary information, or may choose not to determine the AI model based on the auxiliary information, but determine the AI model based on the needs of the network device.
  • the method further includes: sending an acquisition request to the terminal for requesting the auxiliary information.
  • the network device can send an acquisition request to the terminal. After receiving the acquisition request, the terminal can send the auxiliary information to the network device.
  • the terminal may also send the auxiliary information (for example, periodically, or when the terminal needs to perform terminal positioning) to the network device.
  • the assistance information is carried in a radio resource control RRC message;
  • the auxiliary information is carried in a Long Term Evolution Positioning Protocol (LPP) message, such as LPP provide location information (LPP provides location information).
  • LPP Long Term Evolution Positioning Protocol
  • the method when the network device includes a core network, the method further includes: receiving auxiliary information sent by a base station, where the auxiliary information sent by the base station is used to assist in determining the AI model.
  • the assistance information sent by the base station includes at least one of the following:
  • the type of base station such as macro base station Macro BS and micro base station Micro BS;
  • the transmit power of the base station is the transmit power of the base station.
  • the base station By sending some of its own parameters to the core network as auxiliary information, the base station helps the core network more accurately determine the AI model to be used. Among them, the base station can carry the auxiliary information in the NRPPa (NR Positioning Protocol A, NR Positioning Protocol A) message and send it to the core network, for example, in the NRPPa positioning information request.
  • NRPPa NR Positioning Protocol A, NR Positioning Protocol A
  • Figure 4 is a schematic flow chart of a method for sending auxiliary information according to an embodiment of the present disclosure.
  • the auxiliary information sending method shown in this embodiment can be applied to the second device.
  • the auxiliary information sending method may include the following steps:
  • step S401 auxiliary information is sent to the first device, where the auxiliary information is used to assist the first device in determining an AI model, and the AI model is used for terminal positioning.
  • the first device includes a terminal
  • the second device includes a network device.
  • the first device includes a network device
  • the second device includes a terminal.
  • the terminals include but are not limited to mobile phones, tablets, wearable devices, sensors, Internet of Things devices and other communication devices.
  • the terminal can communicate with network equipment, which includes but is not limited to network equipment in 4G, 5G, 6G and other communication systems, such as base stations, core networks, etc.
  • the following embodiments first illustrate the technical solution of the present disclosure in the case where the first device includes a terminal and the second device includes a network device. It should be understood that some embodiments are applicable in both scenarios where the first device includes a terminal and the second device includes a network device, and the first device includes a network device and the second device includes a terminal. For example, the following specific assistance Regarding the limitation of information, in order to avoid redundancy, this disclosure does not repeat the description. Those skilled in the art can select the application scenarios of the embodiments as needed.
  • the AI model can be obtained by training a sample set through a machine learning (deep learning) algorithm.
  • the sample set is different, and the resulting AI model can also be different.
  • the positioning device (such as a terminal or network device) needs to accurately determine the AI model to be used.
  • the terminal when the terminal performs terminal positioning based on the AI model, in order to determine the AI model to be used, there are still certain deficiencies based solely on the information it possesses.
  • the terminal mainly grasps user-side information and only selects an AI model among multiple AI models based on user-side information.
  • the selected AI model may be less applicable to network-side information. Therefore, the network device can send auxiliary information to the terminal, so that the terminal can accurately determine the AI model required for positioning based on the auxiliary information.
  • auxiliary information #1 corresponds to AI model #1
  • auxiliary information #2 corresponds to AI model #2.
  • the AI corresponding to auxiliary information #1 can be determined among multiple AI models (for example, pre-stored). Model #1, and then perform accurate positioning based on the determined AI model.
  • the network device can send auxiliary information to the terminal, so that the terminal can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • the method further includes: receiving an acquisition request sent by the terminal for requesting the auxiliary information.
  • the terminal can send an acquisition request to the network device. After receiving the acquisition request, the network device can send the auxiliary information to the terminal. Of course, when the network device does not receive the acquisition request, it can also send the auxiliary information to the terminal as needed.
  • the auxiliary information includes at least one of the following:
  • the usage conditions of the AI model include at least one of the following:
  • the terminal can determine the current conditions, determine which AI model's usage conditions the current conditions meet, and then select the AI model that meets the usage conditions for terminal positioning.
  • the current application scenario can be determined, and then the AI model corresponding to the current application scenario can be determined based on the first association relationship, and then the terminal positioning can be performed using the determined AI model.
  • specific information (such as positioning reference signals, base station information, etc.) can be measured to obtain measurement information, and then the AI model corresponding to the measured measurement information is determined according to the second association relationship, and terminal positioning is performed through the determined AI model.
  • the auxiliary information when the network device includes a base station, the auxiliary information further includes:
  • the type of base station such as macro base station Macro BS and micro base station Micro BS;
  • the transmit power of the base station is the transmit power of the base station.
  • the base station By sending some of its own parameters to the terminal as auxiliary information, the base station helps the terminal determine the AI model to be used more accurately.
  • the measurement information includes at least one of the following:
  • the transmit power of the base station
  • the transmit power of the base station can be obtained by measurement, and then the AI model corresponding to the measured transmit power of the base station can be determined based on the second association relationship, and the terminal positioning can be performed using the determined AI model.
  • the number of base stations can be obtained by measurement, and then the AI model corresponding to the measured number of base stations can be determined based on the second association relationship, and the terminal positioning can be performed using the determined AI model.
  • the positioning reference signal sent by the base station can be measured to obtain the measurement result of the positioning reference signal, and then the AI model corresponding to the measurement result of the positioning reference signal can be obtained according to the second correlation relationship, and the terminal positioning can be performed through the determined AI model.
  • the measurement results of the positioning reference signal include but are not limited to the positioning reference signal received power PRS-RSRP, the reference signal time difference RSTD, and the time difference Rx-Tx timing difference between the receiving time and the sending time.
  • the application scenario includes at least one of the following:
  • InF-DH a high-power base station with dense clutter in indoor factories
  • the assistance information is carried in a radio resource control RRC message;
  • the assistance information is carried in a Long Term Evolution Positioning Protocol (LPP) message, such as LPP provide assistance information (LPP provides assistance information).
  • LPP Long Term Evolution Positioning Protocol
  • the following embodiments illustrate the technical solution of the present disclosure in the case where the first device includes a network device and the second device includes a terminal.
  • the core network mainly grasps the information on the network side, and only selects an AI model among multiple AI models based on the information on the network side.
  • the selected AI model may be less applicable to the information on the terminal side. Therefore, the terminal can send auxiliary information to the network device, so that the network device can accurately determine the AI model required for positioning based on the auxiliary information.
  • auxiliary information #1 corresponds to AI model #1
  • auxiliary information #2 corresponds to AI model #2.
  • the AI corresponding to auxiliary information #1 can be determined among multiple AI models (for example, pre-stored). Model #1, and then perform accurate positioning based on the determined AI model.
  • the terminal can send auxiliary information to the network device, so that the network device can accurately determine the AI model required for positioning in the current application scenario based on the auxiliary information, and then perform accurate positioning based on the determined AI model.
  • the network device may choose to determine the AI model based on the auxiliary information, or may choose not to determine the AI model based on the auxiliary information, but determine the AI model based on the needs of the network device.
  • the method further includes: receiving an acquisition request sent by the network device for requesting the auxiliary information.
  • the network device can send an acquisition request to the terminal. After receiving the acquisition request, the terminal can send the auxiliary information to the network device.
  • the terminal may also send the auxiliary information (for example, periodically, or when the terminal needs to perform terminal positioning) to the network device.
  • the assistance information is carried in a radio resource control RRC message;
  • the auxiliary information is carried in a Long Term Evolution Positioning Protocol (LPP) message, such as LPP provide location information (LPP provides location information).
  • LPP Long Term Evolution Positioning Protocol
  • the present disclosure also provides embodiments of an auxiliary information receiving device and an auxiliary information sending device.
  • Figure 5 is a schematic block diagram of an auxiliary information receiving device according to an embodiment of the present disclosure.
  • the auxiliary information receiving device shown in this embodiment can be applied to the first device.
  • the auxiliary information receiving device may include:
  • the receiving module is configured to receive auxiliary information sent by the second device, where the auxiliary information is used to assist the first device in determining an AI model, and the AI model is used for terminal positioning.
  • the first device includes a terminal
  • the second device includes a network device.
  • the first device includes a network device
  • the second device includes a terminal.
  • the terminals include but are not limited to mobile phones, tablets, wearable devices, sensors, Internet of Things devices and other communication devices.
  • the terminal can communicate with network equipment, which includes but is not limited to network equipment in 4G, 5G, 6G and other communication systems, such as base stations, core networks, etc.
  • the auxiliary information includes at least one of the following: usage conditions of the AI model; the application scenario where the terminal is currently located; and the AI model recommended for use.
  • the usage conditions of the AI model include at least one of the following: a first association relationship between the AI model and the application scenario; a second association relationship between the AI model and measurement information.
  • the measurement information includes at least one of the following: the transmission power of the base station; the number of base stations; and the measurement result of the positioning reference signal.
  • the first device includes a terminal
  • the second device includes a network device.
  • the device further includes: a processing module configured to determine the current application scenario; according to the The above association relationship determines the AI model corresponding to the current application scenario.
  • the device further includes: a processing module configured to obtain the measurement information; according to the first The second correlation relationship determines the AI model corresponding to the obtained measurement information.
  • the auxiliary information when the network device includes a base station, the auxiliary information is carried in a radio resource control RRC message; and/or when the network device includes a core network, the auxiliary information is carried In the Long Term Evolution Positioning Protocol LPP message.
  • the auxiliary information when the network device includes a base station, the auxiliary information further includes: the type of the base station; and the transmission power of the base station.
  • the apparatus further includes: a sending module configured to send an acquisition request to the network device for requesting the auxiliary information.
  • the first device includes a network device
  • the second device includes a terminal
  • the auxiliary information when the network device includes a base station, the auxiliary information is carried in a radio resource control RRC message; and/or when the network device includes a core network, the auxiliary information is carried In the Long Term Evolution Positioning Protocol LPP message.
  • the receiving module is further configured to receive auxiliary information sent by a base station, wherein the auxiliary information sent by the base station is used to assist in determining the AI model. .
  • the auxiliary information sent by the base station includes at least one of the following: the type of the base station; the transmission power of the base station.
  • the apparatus further includes: a sending module configured to send an acquisition request to the terminal for requesting the auxiliary information.
  • FIG. 6 is a schematic block diagram of an auxiliary information sending device according to an embodiment of the present disclosure.
  • the auxiliary information sending apparatus shown in this embodiment can be applied to the second device.
  • the auxiliary information sending device may include:
  • the sending module 601 is configured to send auxiliary information to the first device, where the auxiliary information is used to assist the first device in determining an AI model, and the AI model is used for terminal positioning.
  • the first device includes a terminal
  • the second device includes a network device.
  • the first device includes a network device
  • the second device includes a terminal.
  • the terminals include but are not limited to mobile phones, tablets, wearable devices, sensors, Internet of Things devices and other communication devices.
  • the terminal can communicate with network equipment, which includes but is not limited to network equipment in 4G, 5G, 6G and other communication systems, such as base stations, core networks, etc.
  • the auxiliary information includes at least one of the following: usage conditions of the AI model; the application scenario where the terminal is currently located; and the AI model recommended for use.
  • the usage conditions of the AI model include at least one of the following: a first association relationship between the AI model and the application scenario; a second association relationship between the AI model and measurement information.
  • the measurement information includes at least one of the following: the transmission power of the base station; the number of base stations; and the measurement result of the positioning reference signal.
  • the first device includes a terminal
  • the second device includes a network device.
  • the auxiliary information when the network device includes a base station, the auxiliary information is carried in a radio resource control RRC message; and/or when the network device includes a core network, the auxiliary information is carried In the Long Term Evolution Positioning Protocol LPP message.
  • the auxiliary information when the network device includes a base station, the auxiliary information further includes at least one of the following: the type of the base station; and the transmit power of the base station.
  • the apparatus further includes: a receiving module configured to receive an acquisition request sent by the terminal for requesting the auxiliary information.
  • the first device includes a network device
  • the second device includes a terminal
  • the auxiliary information when the network device includes a base station, the auxiliary information is carried in a radio resource control RRC message; and/or when the network device includes a core network, the auxiliary information is carried In the Long Term Evolution Positioning Protocol LPP message.
  • the apparatus further includes: a receiving module configured to receive an acquisition request sent by the network device for requesting the auxiliary information.
  • the device embodiment since it basically corresponds to the method embodiment, please refer to the partial description of the method embodiment for relevant details.
  • the device embodiments described above are only illustrative.
  • the modules described as separate components may or may not be physically separated.
  • the components shown as modules may or may not be physical modules, that is, they may be located in One place, or it can be distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Persons of ordinary skill in the art can understand and implement the method without any creative effort.
  • An embodiment of the present disclosure also provides a communication device, including: a processor; a memory for storing a computer program; wherein, when the computer program is executed by the processor, the auxiliary information reception described in any of the above embodiments is implemented method.
  • An embodiment of the present disclosure also provides a communication device, including: a processor; a memory for storing a computer program; wherein, when the computer program is executed by the processor, the auxiliary information transmission described in any of the above embodiments is implemented method.
  • Embodiments of the present disclosure also provide a computer-readable storage medium for storing a computer program.
  • the computer program is executed by a processor, the steps in the auxiliary information receiving method described in any of the above embodiments are implemented.
  • Embodiments of the present disclosure also provide a computer-readable storage medium for storing a computer program.
  • the computer program is executed by a processor, the steps in the auxiliary information sending method described in any of the above embodiments are implemented.
  • FIG. 7 is a schematic block diagram of a device 700 for assisting information transmission according to an embodiment of the present disclosure.
  • the apparatus 700 may be provided as a base station.
  • apparatus 700 includes a processing component 722, which may further include one or more processors, a wireless transmit/receive component 724, an antenna component 726, and a signal processing portion specific to the wireless interface.
  • processors in the processing component 722 may be configured to implement the auxiliary information sending method described in any of the above embodiments.
  • FIG. 8 is a schematic block diagram of a device 800 for assisting information reception according to an embodiment of the present disclosure.
  • the device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like.
  • the apparatus 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power supply component 806 , a multimedia component 808 , an audio component 810 , an input/output (I/O) interface 812 , a sensor component 814 , and Communication component 816.
  • a processing component 802 a memory 804 , a power supply component 806 , a multimedia component 808 , an audio component 810 , an input/output (I/O) interface 812 , a sensor component 814 , and Communication component 816.
  • Processing component 802 generally controls the overall operations of device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations.
  • the processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned auxiliary information receiving method.
  • processing component 802 may include one or more modules that facilitate interaction between processing component 802 and other components.
  • processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.
  • Memory 804 is configured to store various types of data to support operations at device 800 . Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, etc.
  • Memory 804 may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EEPROM), Programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read-only memory
  • EEPROM erasable programmable read-only memory
  • EPROM Programmable read-only memory
  • PROM programmable read-only memory
  • ROM read-only memory
  • magnetic memory flash memory, magnetic or optical disk.
  • Power supply component 806 provides power to the various components of device 800.
  • Power supply components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 800 .
  • Multimedia component 808 includes a screen that provides an output interface between the device 800 and the user.
  • the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user.
  • the touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide action.
  • multimedia component 808 includes a front-facing camera and/or a rear-facing camera.
  • the front camera and/or the rear camera may receive external multimedia data.
  • Each front-facing camera and rear-facing camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.
  • Audio component 810 is configured to output and/or input audio signals.
  • audio component 810 includes a microphone (MIC) configured to receive external audio signals when device 800 is in operating modes, such as call mode, recording mode, and speech recognition mode. The received audio signal may be further stored in memory 804 or sent via communication component 816 .
  • audio component 810 also includes a speaker for outputting audio signals.
  • the I/O interface 812 provides an interface between the processing component 802 and a peripheral interface module, which may be a keyboard, a click wheel, a button, etc. These buttons may include, but are not limited to: Home button, Volume buttons, Start button, and Lock button.
  • Sensor component 814 includes one or more sensors that provide various aspects of status assessment for device 800 .
  • the sensor component 814 can detect the open/closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor component 814 can also detect a change in position of the device 800 or a component of the device 800. , the presence or absence of user contact with the device 800 , device 800 orientation or acceleration/deceleration and temperature changes of the device 800 .
  • Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact.
  • Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications.
  • the sensor component 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
  • Communication component 816 is configured to facilitate wired or wireless communication between apparatus 800 and other devices.
  • the device 800 can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G LTE, 5G NR, or a combination thereof.
  • the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel.
  • the communications component 816 also includes a near field communications (NFC) module to facilitate short-range communications.
  • NFC near field communications
  • the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • apparatus 800 may be configured by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable Gate array (FPGA), controller, microcontroller, microprocessor or other electronic components are implemented for executing the above auxiliary information receiving method.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGA field programmable Gate array
  • controller microcontroller, microprocessor or other electronic components are implemented for executing the above auxiliary information receiving method.
  • a non-transitory computer-readable storage medium including instructions such as a memory 804 including instructions, which can be executed by the processor 820 of the device 800 to complete the above auxiliary information receiving method is also provided.
  • the non-transitory computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

Abstract

La présente divulgation concerne un procédé et un appareil de réception d'informations d'assistance, un procédé et un appareil d'envoi d'informations d'assistance, un appareil de communication et un support de stockage. Le procédé de réception d'informations d'assistance consiste à : recevoir des informations d'assistance envoyées par un second dispositif, les informations d'assistance étant utilisées pour aider un premier dispositif à déterminer un modèle d'IA et le modèle d'IA étant utilisé pour positionner un terminal. Selon la présente divulgation, un dispositif de réseau peut envoyer des informations d'assistance à un terminal, de sorte que le terminal puisse déterminer avec précision, sur la base des informations d'assistance, un modèle d'IA qui doit être utilisé pour un positionnement dans le scénario d'application actuel et puisse ensuite effectuer un positionnement précis en fonction du modèle d'IA déterminé.
PCT/CN2022/089095 2022-04-25 2022-04-25 Procédé et appareil de réception d'informations d'assistance, procédé et appareil d'envoi d'informations d'assistance, appareil de communication et support de stockage WO2023206028A1 (fr)

Priority Applications (2)

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PCT/CN2022/089095 WO2023206028A1 (fr) 2022-04-25 2022-04-25 Procédé et appareil de réception d'informations d'assistance, procédé et appareil d'envoi d'informations d'assistance, appareil de communication et support de stockage
CN202280001210.5A CN117296402A (zh) 2022-04-25 2022-04-25 辅助信息接收、发送方法和装置、通信装置及存储介质

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PCT/CN2022/089095 WO2023206028A1 (fr) 2022-04-25 2022-04-25 Procédé et appareil de réception d'informations d'assistance, procédé et appareil d'envoi d'informations d'assistance, appareil de communication et support de stockage

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