MODEL TRAINING METHOD, CHANNEL ADJUSTMENT METHOD, ELECTRONIC DEVICE, AND COMPUTER READABLE STORAGE MEDIUM

    公开(公告)号:US20240171359A1

    公开(公告)日:2024-05-23

    申请号:US18282817

    申请日:2022-03-14

    CPC classification number: H04L5/006 G06N20/00 H04L1/0004 H04L1/001 H04L1/0061

    Abstract: The present application provides a model training method, a channel adjustment method, an electronic device, and a computer readable storage medium, the model training method includes: collecting historical samples, with the historical samples including first scheduling information and first information corresponding to a historical data transmission, the first information representing a result of cyclic redundancy check, and the first scheduling information including first intermediate variable information in an adaptive modulation and coding process; and performing model training according to the historical samples to obtain a first prediction model, and during the model training, the first scheduling information is used as an input of the first prediction model, the first information is converted into second information corresponding to the historical data transmission to be used as an output of the first prediction model, and the second information represents a probability value of the result of the cyclic redundancy check.

    FLOW SUPPRESSION PREDICTION METHOD, ELECTRONIC DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20240283728A1

    公开(公告)日:2024-08-22

    申请号:US18567597

    申请日:2022-05-23

    CPC classification number: H04L43/50 H04L41/145 H04L41/147

    Abstract: A method for predicting traffic suppression, an electronic device and a storage medium are disclosed. The method may include: determining a traffic value of suppression point according to a preset network traffic model which represents a mapping relationship between a numerical value of a network parameter of a transmission network and a traffic value, wherein the traffic value of suppression point is a traffic threshold of the transmission network under a current running policy; determining a suppression reference value of a target network parameter corresponding to the traffic value of suppression point; and acquiring a parameter prediction value corresponding to the target network parameter, and determining a traffic suppression prediction result according to the parameter prediction value and the suppression reference value.

    Method and Apparatus for Adjusting Inner Loop Value, Storage Medium and Electronic Device

    公开(公告)号:US20230422220A1

    公开(公告)日:2023-12-28

    申请号:US18036925

    申请日:2021-12-09

    CPC classification number: H04W72/0446 H04W72/12 H04L1/1628

    Abstract: Provided are a method and an apparatus for adjusting an inner loop value, The method includes: repeatedly executing the following steps, wherein a history inner loop adjustment factor of each time-domain scheduling unit in a radio frame is initialized to be an initial inner loop adjustment factor of each time-domain scheduling unit: determining a block error rate corresponding to each time-domain scheduling unit according to ACK/NACK information corresponding to each time-domain scheduling unit, wherein the radio frame comprises N time-domain scheduling units, N being a positive integer; determining a current inner loop adjustment factor of each time-domain scheduling unit according to the block error rate corresponding to each time-domain scheduling unit and the history inner loop adjustment factor of each time-domain scheduling unit; and adjusting an inner loop value corresponding to each time-domain scheduling unit according to the current inner loop adjustment factor of each time-domain scheduling unit.

    Channel Identification Method and Apparatus, Transmission Method, Transmission Device, Base Station, and Medium

    公开(公告)号:US20230034994A1

    公开(公告)日:2023-02-02

    申请号:US17788023

    申请日:2020-12-15

    Abstract: Provided is a channel identification method. The method includes: acquiring channel data of a terminal; constructing a first feature vector based on the channel data, where the first feature vector represents a numerical value set of cross-correlation values, which change along with time intervals, between channel data at different moments and the channel data themselves and between the channel data at different moments and subsequent channel data at different time intervals; and inputting the first feature vector into a predetermined prediction model to predict a speed of the terminal, or to predict a speed type of a cluster to which the terminal belongs. Further provided are an adaptive transmission method and apparatus based on the channel identification method, a transmission device, a base station, and a computer storage medium.

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