MEASUREMENT REPORTING PRIORITY FOR LOS-NLOS SIGNALS

    公开(公告)号:US20240236743A1

    公开(公告)日:2024-07-11

    申请号:US18559033

    申请日:2022-06-10

    CPC classification number: H04W24/10 H04B17/328 H04L5/0051 H04W16/28

    Abstract: A first wireless device receives, from a second wireless device, one or more of an indication of a maximum number of measurement reports or an indication of a threshold probability associated with at least one of an LOS probability or an NLOS probability for a plurality of signal or beam paths. The first wireless device calculates at least one of an LOS probability or an NLOS probability of at least one signal or beam path of the plurality of signal or beam paths. The first wireless device transmits, to the second wireless device, one or more indications of signal or beam information associated with the at least one signal or beam path based on one or more of the maximum number of measurement reports or the threshold probability, the one or more indications of signal or beam information including at least one of the LOS probability or the NLOS probability.

    INDEPENDENT TX AND RX TIMING-BASED PROCESSING FOR POSITIONING AND SENSING

    公开(公告)号:US20240147399A1

    公开(公告)日:2024-05-02

    申请号:US18050012

    申请日:2022-10-26

    CPC classification number: H04W56/009 H04J3/0682 H04W56/006

    Abstract: Aspects presented herein may enable a network entity to calculate a relative clock drift between a Tx antenna panel and an Rx antenna panel that use different RF hardware/circuits (e.g., clocks). In one aspect, a network entity obtains a plurality of RTT measurements between a Tx antenna panel, a device with a known position, and an Rx antenna panel over a period of time, where the Tx antenna panel is associated with a first clock and the Rx antenna panel is associated with a second clock. The network entity obtains a first timing delay associated with the device based on the plurality of RTT measurements. The network entity calculates a clock offset between the Tx antenna panel and the Rx antenna panel based on the obtained first timing delay associated with the device.

    POSITIONING ASSISTANCE DATA DELIVERY FOR REDUCED SIGNALING OVERHEAD

    公开(公告)号:US20240098688A1

    公开(公告)日:2024-03-21

    申请号:US18263259

    申请日:2022-03-08

    CPC classification number: H04W64/006 G01S5/0236 H04L5/0048

    Abstract: Techniques for positioning assistance data (AD) delivery for reduced signaling overhead may comprise determining a combined positioning AD for a requesting user equipment (UE) based at least in part on the area ID in which the requesting UE is located. The combined positioning AD may include positioning AD for the first area and one or more additional areas. For each of the area, the positioning AD may comprise information regarding Positioning Reference Signal (PRS) resources, Base Station Almanac (BSA) information, or both, to be used for positioning the requesting UE within the respective area. The first area and the one or more additional areas may comprise cells of the wireless communication network or sidelink (SL) group zones.

    SIGNALING OF MEASUREMENT PRIORITIZATION CRITERIA IN USER EQUIPMENT BASED RADIO FREQUENCY FINGERPRINTING POSITIONING

    公开(公告)号:US20240064689A1

    公开(公告)日:2024-02-22

    申请号:US17820138

    申请日:2022-08-16

    CPC classification number: H04W64/003 G01S5/02521

    Abstract: Disclosed are techniques for UE-based wireless positioning. In an aspect, a user equipment (UE) may acquire, from a first set of transmission/reception entities (TREs), a first set of measurements of signals. The UE may select, from the first set of TREs, a second set of TREs, based on criteria for selecting and/or prioritizing TREs for radio frequency fingerprint (RFFP)-based positioning. The UE may acquire, from the second set of TREs, a second set of measurements, the second set of measurements comprising RFFP measurements. The UE may estimate a position of the UE based on the second set of measurements. In an aspect, the UE may input the second set of measurements into a trained machine learning (ML) model that outputs an estimated position of the UE. In an aspect, the UE receives the selection/prioritization criteria and/or the trained ML model from a network node.

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