COMMUNICATION METHOD AND APPARATUS
    1.
    发明公开

    公开(公告)号:US20240306119A1

    公开(公告)日:2024-09-12

    申请号:US18665749

    申请日:2024-05-16

    CPC classification number: H04W64/00

    Abstract: A communication method and an apparatus. A terminal device (or an access network device) obtains a channel feature through inference by using a channel feature extraction model, where the channel feature corresponds to a channel between the terminal device and the access network device. The terminal device (or the access network device) sends the channel feature to a location management function LMF. The LMF obtains, based on the channel feature, positioning information of the terminal device through inference by using a positioning information obtaining model. The LMF may determine location information of the terminal device based on the positioning information. An artificial intelligence model may be used to implement positioning or assist in implementing positioning of the terminal device.

    COMMUNICATION METHOD, APPARATUS, AND SYSTEM
    2.
    发明公开

    公开(公告)号:US20230259742A1

    公开(公告)日:2023-08-17

    申请号:US18303157

    申请日:2023-04-19

    CPC classification number: G06N3/045

    Abstract: A method includes: A first device sends indication information to a second device, where the indication information indicates information about a first neural network model, the first neural network model includes a dedicated layer network and a common layer network, the dedicated layer network is dedicated to the first neural network model, and the common layer network is a common network of the first neural network model and a second neural network model; and the second device determines the information about the first neural network model based on the indication information.

    MODEL APPLICATION METHOD AND APPARATUS

    公开(公告)号:US20250088258A1

    公开(公告)日:2025-03-13

    申请号:US18963204

    申请日:2024-11-27

    Abstract: A model application method and an apparatus are provided. The method includes: determining first information based on a received reference signal, where the first information includes data of m ports for the reference signal; and mapping the data of the m ports to an input of a first model based on a correspondence between the m ports and n ports in an input dimension of the first model, to obtain an output of the first model, where both m and n are integers greater than or equal to 1, and m and n are not equal. By using the method and the apparatus in this application, self-adaptation to a port of the reference signal can be implemented, and model storage and training overheads can be reduced.

    UPLINK PRECODING METHOD AND APPARATUS
    4.
    发明公开

    公开(公告)号:US20240356595A1

    公开(公告)日:2024-10-24

    申请号:US18758984

    申请日:2024-06-28

    CPC classification number: H04B7/0481 H04W72/046 H04W72/21

    Abstract: An uplink precoding method and an apparatus are provided. The method includes: A terminal device receives first information from an access network device; the terminal device determines a first precoding matrix based on the first information and a first model, where the first precoding matrix is determined based on an output of the first model, and an input of the first model is determined based on the first information; the terminal device precodes an uplink signal based on the first precoding matrix; and the terminal device sends a precoded uplink signal to the access network device. In the method, the terminal device determines the first precoding matrix based on the first information and the first model. The precoding matrix is no longer selected from an offline codebook, but is a floating-point matrix generated by the terminal device based on the first information.

    DATA PROCESSING METHOD AND COMMUNICATION APPARATUS

    公开(公告)号:US20240313873A1

    公开(公告)日:2024-09-19

    申请号:US18672286

    申请日:2024-05-23

    CPC classification number: H04B17/3913 H04B17/3912

    Abstract: This application provides a data processing method and a communication apparatus. The method includes: receiving or sending a plurality of reference signals; obtaining a first channel data set, where the first channel data set is a set of a plurality of pieces of channel data obtained based on the plurality of reference signals; obtaining a data quality screening policy, where the data quality screening policy is used to obtain, through screening, model training data that meets a data quality requirement; and screening the channel data in the first channel data set according to the data quality screening policy, to obtain a training data set. In this way, quality of the training data for model training is improved, so that a trained intelligent model meets a performance requirement.

    COMMUNICATION METHOD AND APPARATUS

    公开(公告)号:US20240422032A1

    公开(公告)日:2024-12-19

    申请号:US18815330

    申请日:2024-08-26

    Abstract: This disclosure provides a communication method and apparatus, to improve positioning performance. The method includes: obtaining M pieces of first channel estimation information, where an mth piece of first channel estimation information in the M pieces of first channel estimation information is estimation information of a channel between an mth cell node in M cell nodes and a terminal device, M is a positive integer greater than 1, and m is a positive integer from 1 to M; and determining M pieces of second channel estimation information based on at least one of the M pieces of first channel estimation information, where an mth piece of second channel estimation information in the M pieces of second channel estimation information corresponds to the channel between the mth cell node and the terminal device.

    DATA PROCESSING METHOD FOR MODEL, AND APPARATUS

    公开(公告)号:US20240357560A1

    公开(公告)日:2024-10-24

    申请号:US18759095

    申请日:2024-06-28

    CPC classification number: H04W72/04 H04W72/12

    Abstract: A data processing method for a model and an apparatus are provided. The method includes: A first node determines the data processing method for the model; and the first node implements, according to the data processing method for the model, at least one of the following: performing model training or performing model inference. Based on the method and the apparatus, inference tasks for different radio resource configurations can be completed by using one model, so that overheads for model training and storage are reduced.

    COMMUNICATION METHOD AND APPARATUS
    9.
    发明公开

    公开(公告)号:US20240314613A1

    公开(公告)日:2024-09-19

    申请号:US18672072

    申请日:2024-05-23

    CPC classification number: H04W24/10 H04W8/22 H04W24/02

    Abstract: This application provides a communication method and apparatus. The method includes: determining a first downlink signal and a second downlink signal, where the first downlink signal is a downlink signal determined based on an output of a first prediction model, an input of the first prediction model is determined based on Y pieces of downlink measurement information in X pieces of downlink measurement information, and the second downlink signal is determined based on the X pieces of downlink measurement information; and indicating the second downlink signal and the Y pieces of downlink measurement information to an access network device if the first downlink signal and the second downlink signal meet a first condition. According to the method, the first prediction model can be updated based on the foregoing information, and performance of the prediction model can be continuously improved.

    COMMUNICATION METHOD AND APPARATUS
    10.
    发明公开

    公开(公告)号:US20240211770A1

    公开(公告)日:2024-06-27

    申请号:US18598592

    申请日:2024-03-07

    CPC classification number: G06N3/098

    Abstract: A communication method and apparatus. A terminal receives first information from a network device. The terminal determines N pieces of training data based on the first information, and N is an integer. The terminal performs model training based on the N pieces of training data, to obtain a first AI model. The network device configures the first information used to determine the N pieces of training data for the terminal. The terminal performs model training based on the N pieces of training data autonomously. Separately configuring an AI model for the terminal is not necessary and air interface overheads are reduced.

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