LAYER 1 CROSS-LINK INTERFERENCE COLLISION MANAGEMENT

    公开(公告)号:US20250016819A1

    公开(公告)日:2025-01-09

    申请号:US18710592

    申请日:2022-01-20

    Abstract: Methods, systems, and devices for wireless communications are described. Generally, the described techniques provide for prioritization schemes for prioritizing colliding cross-link interference (CLI) measurements scheduled via Layer-1 signaling and a downlink transmissions scheduled according to periodic configurations. In some examples, a user equipment (UE) may prioritize downlink transmissions over CLI measurements. A UE may not monitor for or may not decode downlink control information scheduling CLI measurements in resources that the UE has a scheduled downlink reception according to a periodic scheduling configuration. In some examples, the UE may prioritize a colliding CLI measurement and downlink transmission based on an indicated priority of each, a type a CLI measurement, a type of downlink transmission, and/or a location of the UE within the cell. The UE may either monitor for the downlink transmission or perform the CLI measurement based on the priority scheme.

    PHYSICAL UPLINK SHARED CHANNEL TRANSMIT POWER CONFIGURATION

    公开(公告)号:US20240414658A1

    公开(公告)日:2024-12-12

    申请号:US18810598

    申请日:2024-08-21

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a wireless communication device may receive an indication of a first transmit power configuration and a second transmit power configuration for a physical uplink shared channel (PUSCH) communication. The wireless communication device may transmit, using a first transmit power that is based at least in part on the first transmit power configuration, a first portion of the PUSCH communication in a full-duplex portion of a time-frequency resource. The wireless communication device may transmit, using a second transmit power that is based at least in part on the second transmit power configuration, a second portion of the PUSCH communication in a non-full-duplex portion of the time-frequency resource. Numerous other aspects are provided.

    MACHINE LEARNING FEATURE GROUP FOR USER EQUIPMENT CAPABILITY

    公开(公告)号:US20240365108A1

    公开(公告)日:2024-10-31

    申请号:US18571982

    申请日:2021-09-03

    CPC classification number: H04W8/22 G06N3/0464 G06N3/06

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may select a machine learning (ML) feature group from among a first ML feature group and a second ML feature group based at least in part on a UE capability of the UE for ML features. The ML features or an ML feature parameter of the first ML feature group may be different than ML features or an ML feature parameter of the second ML feature group. The UE may perform an action associated with wireless communication based at least in part on a model with one or more ML features from the selected ML feature group. Numerous other aspects are described.

    REMOTE INTERFERENCE DETECTION BASED ON MACHINE LEARNING

    公开(公告)号:US20240357399A1

    公开(公告)日:2024-10-24

    申请号:US18682312

    申请日:2021-10-08

    CPC classification number: H04W24/10 H04L41/16

    Abstract: Methods, systems, and devices for wireless communications are described. The method may include a wireless device (e.g., a user equipment (UE) or a base station) receiving, from a network node, a machine learning model for use by the wireless device to detect remote interference from a base station. The wireless device may be associated with a first cell and the base station may be associated with a second cell different from the first cell. The wireless device may input one or more parameters into the machine learning model and detect whether the remote interference from the base station is present based on an output of the machine learning model.

    DCI-BASED INDICATION TO TRIGGER THE COMBINED ML MODEL

    公开(公告)号:US20240314798A1

    公开(公告)日:2024-09-19

    申请号:US18571053

    申请日:2021-08-10

    CPC classification number: H04W72/231 H04W24/02 H04W76/20

    Abstract: A base station may set one or more bits of DCI that at least one of indicate or trigger a configuration of an ML model at a UE. The configuration may be based on an association between at least one first ML block for a first procedure and at least one second ML block for a second procedure. The at least one second ML block may be dedicated to a task included in a plurality of tasks associated with the at least one first ML block. The base station may transmit the DCI including the one or more bits to the UE, which may cause the UE to configure the ML model including the association between the at least one first ML block for the first procedure and the at least one second ML block for the second procedure.

    MACHINE LEARNING GROUP SWITCHING
    108.
    发明公开

    公开(公告)号:US20240267710A1

    公开(公告)日:2024-08-08

    申请号:US18564986

    申请日:2021-08-04

    CPC classification number: H04W4/08 H04L41/16

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first user equipment (UE) may receive an indication on whether to switch from a first machine learning (ML) group to a second ML group or to continue with the first ML group. The UE may switch to the second ML group if the indication is to switch or continuing with the first ML group if the indication is to continue. The UE may perform a first action associated with wireless communication based at least in part on a first model developed with the first ML group if the indication is to continue. The UE may perform a second action associated with wireless communication based at least in part on a second model developed with the second ML group if the indication is to switch. Numerous other aspects are described.

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