公开(公告)号：US11909675B2

公开(公告)日：2024-02-20

申请号：US17173253

申请日：2021-02-11

Applicant: Huawei Technologies Co., Ltd.

Inventor： Lv Ding ,  Jun Wu ,  Jiyuan Shi ,  Fuxing Chen

IPC: H04L5/00 ,  H04W72/0446 ,  H04W72/541

CPC classification number: H04L5/0032 ,  H04W72/0446 ,  H04W72/541

Abstract: An interference source identification method includes obtaining a first parameter, where the first parameter includes a co-channel interference rate of a first access point in a preset time period, a receive channel utilization rate and a transmit channel utilization rate of a second access point in the preset time period, and a receive frame rate of data received from a first station by the second access point in the preset time period, and determining that the data causes co-channel interference to the first access point when the first parameter meets a preset condition.

公开(公告)号：US20210167907A1

公开(公告)日：2021-06-03

申请号：US17173253

申请日：2021-02-11

Applicant: Huawei Technologies Co., Ltd.

Inventor： Lv Ding ,  Jun Wu ,  Jiyuan Shi ,  Fuxing Chen

IPC: H04L5/00 ,  H04W72/08 ,  H04W72/04

Abstract: An interference source identification method includes obtaining a first parameter, where the first parameter includes a co-channel interference rate of a first access point in a preset time period, a receive channel utilization rate and a transmit channel utilization rate of a second access point in the preset time period, and a receive frame rate of data received from a first station by the second access point in the preset time period, and determining that the data causes co-channel interference to the first access point when the first parameter meets a preset condition.

公开(公告)号：US20230031387A1

公开(公告)日：2023-02-02

申请号：US17957889

申请日：2022-09-30

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xiaoyun Si ,  Xinyu Hu ,  Li Xue ,  Liang Zhang ,  Fuxing Chen

IPC: G06N3/063 ,  G06N3/08 ,  G11C11/54

Abstract: A method, an apparatus, and a device for obtaining an artificial intelligence model, and a storage medium are provided. A client receives a first artificial intelligence AI model sent by a service end (303). The first AI model includes a plurality of neurons. The client determines, from the plurality of neurons, a target neuron participating in a current round of training, where the current round of training is a non-first round of training, and a quantity of target neurons is less than a total quantity of the plurality of neurons (304). The client trains the target neuron based on local data (305). The client returns parameter data corresponding to the target neuron to the service end (306). The parameter data corresponding to the target neuron is used by the service end to obtain a converged target AI model.

公开(公告)号：US20220210026A1

公开(公告)日：2022-06-30

申请号：US17695271

申请日：2022-03-15

Applicant: Huawei Technologies Co., Ltd.

Inventor： Siyu Yan ,  Yinben Xia ,  Xiaolong Zheng ,  Weishan Deng ,  Zhigang Ji ,  Di Qu ,  Fuxing Chen

IPC: H04L41/14 ,  H04L41/0816 ,  H04L41/147 ,  H04L43/062

Abstract: A network parameter configuration method, where in the method, network running data corresponding to a first period is input into a prediction model, so that the prediction model predicts, based on the input network running data, a value of a parameter of a network device in a second period, and the parameter of the network device in the second period is configured to the value predicted by the prediction model.