UNIFIED MEASUREMENT CONFIGURATIONS FOR CROSS-LINK INTERFERENCE, SELF-INTERFERENCE, AND WIRELESS SENSING

    公开(公告)号:US20250024289A1

    公开(公告)日:2025-01-16

    申请号:US18903462

    申请日:2024-10-01

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a measurement configuration that is associated with a common measurement object or a common resource pool for at least two of cross-link interference (CLI) measurements, self-interference (SI) measurements, or wireless sensing measurements. The UE may perform, based at least in part on the measurement configuration, one or more measurements that include at least one of a CLI measurement, an SI measurement, or a wireless sensing measurement. The UE may transmit, based at least in part on the measurement configuration, a measurement report indicating at least one measurement of the one or more measurements. Numerous other aspects are described.

    NON-COHERENT COMBINING FOR FULL GRADIENTS TRANSMISSION IN FEDERATED LEARNING

    公开(公告)号:US20240421950A1

    公开(公告)日:2024-12-19

    申请号:US18186911

    申请日:2023-03-20

    Abstract: A first UE may identify, in at least one round of a federated learning procedure, at least one gradient update based on local data and a local copy of a machine learning model associated with the federated learning procedure. The first UE may transmit, based on a non-coherent OTA aggregation scheme and for a network node, an indication of the at least one gradient update via a set of resources associated with the non-coherent OTA aggregation scheme. The indication of the at least one gradient update may include at least one sequence. A transmit power associated with the at least one sequence may be based at least in part on a magnitude of the at least one gradient update. Based on the non-coherent OTA aggregation scheme, the network node may obtain the combined gradients associated with all participating UEs by averaging the received power over the set of resources.

    DYNAMIC CODEBOOK SUBSET RESTRICTION CONFIGURATIONS

    公开(公告)号:US20240421869A1

    公开(公告)日:2024-12-19

    申请号:US18706185

    申请日:2022-01-17

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, a dynamic codebook subset restriction (CBSR) configuration that indicates time-variant CBSR information associated with a channel state information reference signal (CSI-RS) or synchronization signal block (SSB) resource selection codebook, or with a joint CSI-RS resource and CSI-RS port selection codebook. The UE may transmit, to the base station, channel state information (CSI) feedback that indicates the CSI-RS or SSB resource selection codebook or the joint CSI-RS resource and CSI-RS port selection codebook based at least in part on the dynamic CBSR configuration indicating the time-variant CBSR information. Numerous other aspects are described.

    QUANTIZED ORTHOGONAL MODULATION
    118.
    发明公开

    公开(公告)号:US20240276534A1

    公开(公告)日:2024-08-15

    申请号:US18160222

    申请日:2023-01-26

    CPC classification number: H04W72/542 G06N20/00

    Abstract: Aspects of the disclosure are directed to quantized orthogonal modulation for non-coherent over-the-air (OTA) federated learning (FL). In some examples, a wireless device may compare a gradient to a threshold value to determine whether the gradient satisfies a threshold condition. The wireless device may also output, for transmission to a network node, signaling via one of a first resource or a second resource, wherein the signaling is outputted via the first resource if the gradient satisfies the threshold condition, and wherein the signaling is outputted via the second resource if the gradient does not satisfy the threshold condition.

    ADJUSTING BIASED DATA DISTRIBUTIONS FOR FEDERATED LEARNING

    公开(公告)号:US20240224064A1

    公开(公告)日:2024-07-04

    申请号:US18091293

    申请日:2022-12-29

    CPC classification number: H04W16/22 G06N20/00

    Abstract: A method for wireless communication at a first user equipment (UE) includes transmitting, to a network node, a first message indicating one or more distributions of a group of local data instances associated with a machine learning model at the first UE, each local data instance of the group of local data instances associated with a class of a group of classes. The method also includes receiving, associated with transmitting the first message, from the network node, a second message indicating an update to the group of local data instances, for satisfying one or more data distribution conditions. The method further includes training, associated with the update to the group of local data instances, the machine learning model.

    SENSING-ASSISTED USER EQUIPMENT TO OBJECT ASSOCIATION

    公开(公告)号:US20240214979A1

    公开(公告)日:2024-06-27

    申请号:US18069919

    申请日:2022-12-21

    CPC classification number: H04W64/006

    Abstract: A network node may transmit a set of data collection schedules to a first set of network nodes and a first set of user equipment (UEs) to obtain a first set of attributes associated with a user equipment (UE) and a second set of attributes associated with an object associated with an area of interest. The first set of UEs may include the UE. The network node may receive the first set of attributes and the second set of attributes from the first set of network nodes and the first set of UEs based on the set of data collection schedules. The network node may transmit an association of the UE with the object based on the first set of attributes and the second set of attributes.

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