COMMUNICATION METHOD AND COMMUNICATION SYSTEM FOR REDUCING OVERHEAD OF REFERENCE SIGNAL

    公开(公告)号:US20230379120A1

    公开(公告)日:2023-11-23

    申请号:US18024717

    申请日:2020-09-03

    CPC classification number: H04L5/0051 H04L5/006

    Abstract: According to the present disclosure, disclosed is a communication method for reducing an overhead of a reference signal. The communication method according to the present disclosure comprises the steps in which: a reception unit receives a reference signal from a transmission unit; the reception unit obtains channel state information on the basis of the reference signal; the reception unit obtains loss information on the basis of the channel state information; the reception unit selects a mask to be applied to the reference signal on the basis of the quality of the loss information; and the reception unit transmits the selected mask to the transmission unit. The terminal of the present disclosure can be linked to an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 6G services, and the like.

    METHOD FOR PREPROCESSING DOWNLINK IN WIRELESS COMMUNICATION SYSTEM AND APPARATUS THEREFOR

    公开(公告)号:US20230318691A1

    公开(公告)日:2023-10-05

    申请号:US18022436

    申请日:2020-08-19

    CPC classification number: H04B7/0868 H04B7/0413 G06N3/08

    Abstract: Disclosed is a method for controlling, by a terminal, an operation of a deep neural network in a wireless communication system. The method according to an embodiment of the present disclosure receives a downlink from abase station in a wireless communication system; and preprocesses the downlink on the basis of the result of an operation of a deep neural network of a terminal, wherein at least one reference signal is applied to the downlink while a statistical feature related to noise of the downlink are maintained. The terminal of the present disclosure may be linked to an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 6G services, and the like.

    METHOD FOR CONTROLLING CALCULATIONS OF DEEP NEURAL NETWORK IN WIRELESS COMMUNICATION SYSTEM, AND APPARATUS THEREFOR

    公开(公告)号:US20230318662A1

    公开(公告)日:2023-10-05

    申请号:US18042107

    申请日:2020-08-20

    CPC classification number: H04B7/0404 G06N3/045 H04B7/0452

    Abstract: Disclosed is a method by which a terminal controls the calculations of a deep neural network in a wireless communication system. A method according to one embodiment of the present disclosure receives a downlink from a base station of a wireless communication system by using a multi input multi output (MIMO) operation, pre-processes the downlink on the basis of a result of calculations of a deep neural network in a terminal, acquires the number of a plurality of transmission antennas connected to the terminal, acquires the number of a plurality of reception antennas connected to the terminal, and forms a plurality of overlapping neural networks overlapping in the deep neural network, on the basis of a preset number of reference antennas, the number of transmission antennas, and the number of reception antennas. The terminal of the present disclosure can be linked to an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 6G services, and the like.

    METHOD FOR PERFORMING FEDERATED LEARNING IN WIRELESS COMMUNICATION SYSTEM, AND APPARATUS THEREFOR

    公开(公告)号:US20250023609A1

    公开(公告)日:2025-01-16

    申请号:US18711460

    申请日:2022-11-07

    Abstract: The present specification provides a method by which a terminal performs federated learning with a plurality of terminals in a wireless communication system. More specifically, the method performed by one terminal comprises the steps of: receiving, from a server, a channel state information reference signal (CSI-RS); transmitting, to the server, channel state information (CSI) calculated on the basis of the CSI-RS; receiving, from the server, (i) information about a global parameter for the federated learning and (ii) compression state information for determining a weight compression method of the one terminal on the basis of channel state information of each of channels between the server and the plurality of terminals; determining a weight compression scheme based on (i) a difference value between the global parameter and a global parameter received before receiving the global parameter and (ii) the compression state information; and transmitting, to the server, an updated local parameter on the basis of the determined weight compression scheme.

    METHOD FOR PERFORMING FEDERATED LEARNING IN WIRELESS COMMUNICATION SYSTEM, AND APPARATUS THEREFOR

    公开(公告)号:US20250016619A1

    公开(公告)日:2025-01-09

    申请号:US18712453

    申请日:2022-11-07

    Abstract: The present disclosure provides a method for one user equipment (UE) to perform federated learning with a plurality of UEs in a wireless communication system. More specifically, the method performed by the one UE comprises receiving, from a server, a channel state information reference signal (CSI-RS); transmitting, to the server, channel state information (CSI) calculated based on the CSI-RS; receiving, from the server, compression state information for determining a weight compression method of the one UE based on (i) information on a global parameter for the federated learning and (ii) channel state information of each of channels between the server and the plurality of UEs; determining the weight compression method based on (i) a difference between the global parameter and a global parameter received before a reception of the global parameter and (ii) the compression state information; and transmitting, to the server, a local parameter updated based on the determined weight compression method.

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