LAYER-SPECIFIC FEEDBACK PERIODICITY
    3.
    发明公开

    公开(公告)号:US20230361821A1

    公开(公告)日:2023-11-09

    申请号:US18246025

    申请日:2020-11-25

    CPC classification number: H04B7/0486 H04B7/0645

    Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a base station, a channel state information (CSI) configuration indicating a first feedback reporting periodicity for a dominant, or strong, spatial layer and a second feedback reporting periodicity for a non-dominant, or weak, spatial layer. The UE may transmit a first CSI report for at least the dominant spatial layer according to the first feedback reporting periodicity. The UE may transmit a second CSI report for the non-dominant spatial layer according to the second feedback reporting periodicity. In some cases, for aperiodic reporting, the UE may be triggered by downlink control information to report CSI for the dominant spatial layer. In some cases, the CSI configuration may indicate different codebooks for the dominant and non-dominant spatial layers.

    NEURAL NETWORK STRUCTURE FOR FEEDBACK OF ORTHOGONAL PRECODING INFORMATION

    公开(公告)号:US20250088226A1

    公开(公告)日:2025-03-13

    申请号:US18294997

    申请日:2021-10-29

    Abstract: A method of wireless communication by a base station includes receiving a channel state information (CSI) payload at a neural network CSI decoder. The method also includes decoding the CSI payload to generate a quantity (N) of precoding vectors for N transmission layers. The method further includes orthogonalizing the N precoding vectors to generate N orthogonal precoding vectors. The method still further includes transmitting, to a user equipment (UE), downlink data that is precoded in accordance with the N orthogonal precoding vectors.

    CHANNEL STATE FEEDBACK WITH FRACTIONAL RANK INDICATOR

    公开(公告)号:US20240413867A1

    公开(公告)日:2024-12-12

    申请号:US18695678

    申请日:2021-11-18

    Abstract: Certain aspects of the present disclosure provide techniques for reporting channel state information (CSI). According to certain aspects, a method for wireless communications by a user equipment (UE) generally includes generating channel state information (CSI) comprising a (at least one) fractional rank indication (RI) value for a set of candidate ranks, a first indication of a first layer or first singular vector, and a second indication of a second layer or second singular vector and transmitting the CSI to a network entity.

    NEURAL NETWORK ASSISTED COMMUNICATION TECHNIQUES

    公开(公告)号:US20240171428A1

    公开(公告)日:2024-05-23

    申请号:US18551382

    申请日:2022-05-26

    CPC classification number: H04L25/0254

    Abstract: Methods, systems, and devices for wireless communication are described. Neural networks may assist user equipments (UEs) and base stations in performing various operations related to wireless communications. For example, neural networks may be used to generate non-orthogonal cover codes for transmitting reference signals such as channel state information-reference signals (CSI-RSs). A base station may transmit, to a UE, a CSI-RS associated with a non-orthogonal cover code of a set of non-orthogonal cover codes. Using the CSI-RS, the UE may perform a channel estimation procedure that corresponds to the non-orthogonal cover code. Based on the channel estimation procedure, the UE may transmit a feedback message to the base station that indicates a channel quality parameter. Additionally, or alternatively, a UE may receive a CSI-RS, determine a precoding matrix using the CSI-RS and neural network, and transmit an indication of the pre-coding matrix to a base station.

    SIZE-BASED NEURAL NETWORK SELECTION FOR AUTOENCODER-BASED COMMUNICATION

    公开(公告)号:US20230353277A1

    公开(公告)日:2023-11-02

    申请号:US18006853

    申请日:2020-09-11

    CPC classification number: H04L1/0041 H04L1/0045 H04W72/12

    Abstract: Methods, systems, and devices for wireless communications are described. In some wireless communications systems, devices may implement multiple autoencoders for communications. A wireless device may select an autoencoder to use for communications based on a size parameter for a message. For example, a user equipment (UE) may receive a grant from a base station indicating a size parameter for communicating a message. The UE and base station may determine, from a set of neural network (NN)-based encoders configured at the UE, an NN-based encoder corresponding to the size parameter. The UE may communicate the message with the base station according to the grant and based on the determined NN-encoder. In some examples, the UE and base station may determine a number of resource segments from a set of resources allocated for communication and may determine respective NN-based encoders for the different resource segments.

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