METHOD AND APPARATUS FOR RETRANSMITTING PACKETS IN DUAL CONNECTIVITY NETWORK

    公开(公告)号:US20220337346A1

    公开(公告)日:2022-10-20

    申请号:US17417648

    申请日:2020-12-17

    Abstract: Provided is a data transmission method including obtaining, from a core network (CN), at least one packet to be transmitted to a user equipment via a first cell group or a second cell group, determining a packet to be transmitted via the second cell group, among the at least one packet, transmitting the determined packet to the user equipment via the second cell group, obtaining packet delivery state information of the first cell group and packet delivery state information of the second cell group, determining whether to retransmit the transmitted packet based on the packet delivery state information of the first cell group and the packet delivery state information of the second cell group, and retransmitting the packet determined to be retransmitted to the user equipment via the first cell group.

    ELECTRONIC APPARATUS AND CONTROLLING METHOD THEREOF

    公开(公告)号:US20240220818A1

    公开(公告)日:2024-07-04

    申请号:US18526818

    申请日:2023-12-01

    Inventor: Taejeoung KIM

    CPC classification number: G06N3/098

    Abstract: An electronic apparatus, including: a communication interface; a memory configured to store at least one instruction; and at least one processor configured to: receive information regarding a global neural network model and information regarding evaluation data from a server using the communication interface; obtain a data set for training the global neural network model; train the global neural network model based on the data set; evaluate the trained global neural network model by inputting the evaluation data to the trained global neural network model; and determine whether to transmit information regarding the trained global neural network model to the server based on a result of the evaluating.

    DISTRIBUTED LEARNING SERVER AND DISTRIBUTED LEARNING METHOD

    公开(公告)号:US20230059674A1

    公开(公告)日:2023-02-23

    申请号:US17735352

    申请日:2022-05-03

    Abstract: Provided is a method, performed by a server, of performing distributed learning. The server builds a computer cluster by selecting worker nodes that are to perform distributed learning, from among a plurality of nodes, wherein nodes in the computer cluster include the server that is a master node and the worker nodes. The server identifies, with respect to each of the nodes in the computer cluster, an operation time taken for each of the nodes in the computer cluster to perform training, and adjusts a number of data included in each of data subsets, based on the operation time of each of the nodes in the computer cluster, the data subsets being used in training of the nodes in the computer cluster.

    METHOD OF IMPLEMENTING SELF-ORGANIZING NETWORK FOR PLURALITY OF ACCESS NETWORK DEVICES AND ELECTRONIC DEVICE FOR PERFORMING THE SAME

    公开(公告)号:US20220104113A1

    公开(公告)日:2022-03-31

    申请号:US17235291

    申请日:2021-04-20

    Abstract: An electronic device configured to adjust a state of an access network including at least one cell may include: at least one processor, and a memory connected to the at least one processor, wherein the at least one processor is configured to control the electronic device to: obtain state history information of the access network at a first time point, determine, based on the obtained state history information, a first time period required to adjust a state of the access network, determine, based on the first time point and the first time period, a second time point, the second time point being a reference time point at which the state of the access network is to be adjusted, estimate a state of the access network at the second time point based on the obtained state history information, determine values of state control parameters for adjusting the state of the access network, based on the estimated state of the access network at the second time point, and transmit the determined values of the state control parameters to the access network, wherein the values of the state control parameters transmitted to the access network are applied, at the second time point, to the state control parameters of the access network, to adjust the state of the access network.

    ELECTRONIC DEVICE AND OPERATING METHOD FOR PERFORMING OPERATION BASED ON VIRTUAL SIMULATOR MODULE

    公开(公告)号:US20210357722A1

    公开(公告)日:2021-11-18

    申请号:US17320885

    申请日:2021-05-14

    Abstract: Provided is a method, performed by an electronic device, of an operation based on a virtual simulator module, wherein the electronic device obtains a simulation parameter set for each of a plurality of operations for performing simulations with respect to the plurality of operations, obtains first performance information for each operation using a simulator module, wherein the first performance information indicates performance of an operation simulated based on the simulation parameter set, obtains second performance information for each operation based on the first performance information using a modeling module, wherein the second performance information indicates performance of the operation simulated in the simulator module, and performs an operation of the plurality of operations based on the first performance information and the second performance information.

    SERVER AND METHOD FOR CONTROLLING SERVER

    公开(公告)号:US20210168195A1

    公开(公告)日:2021-06-03

    申请号:US16951398

    申请日:2020-11-18

    Abstract: A method for controlling a server is provided. The method for controlling a server includes obtaining a first neural network model including a plurality of layers, identifying a second neural network model associated with the first neural network model using metadata included in the first neural network model, based on the second neural network model being identified, identifying at least one changed layer between the first neural network model and the second neural network model, and transmitting information on the at least one identified layer to an external device storing the second neural network model.

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