MACHINE-LEARNING-BASED INTER-FREQUENCY SIGNAL LEVEL ESTIMATION

    公开(公告)号:US20240275637A1

    公开(公告)日:2024-08-15

    申请号:US18168637

    申请日:2023-02-14

    CPC classification number: H04L25/0204 H04W72/0453

    Abstract: Certain aspects of the present disclosure provide techniques and apparatus for inter-frequency signal property prediction using machine learning techniques. An example method generally includes determining one or more properties of a received signal from a wireless device on a first frequency band. An estimate of the one or more properties of signals on a second frequency band is generated, while a transceiver is tuned to the first frequency band, using a machine learning model trained to generate the estimate based on the determined one or more properties of the received signal on the first frequency band. The transceiver is tuned to the second frequency band for subsequent communications with the wireless device based on the estimate of the one or more properties of the signals on the second frequency band.

    COVERAGE ENHANCEMENT FOR DUAL CONNECTIVITY

    公开(公告)号:US20210258826A1

    公开(公告)日:2021-08-19

    申请号:US17179309

    申请日:2021-02-18

    Abstract: In certain aspects, a method for wireless communication at a user equipment (UE) includes attempting to receive, from a first base station, data via a first communication link, generating a radio link control (RLC) status report indicating a status of the data at the UE, and transmitting, to a second base station, the RLC status report via a second communication link. The UE may be simultaneously connected to the first base station and the second base station using dual connectivity. In one example, the first base station may be configured as a secondary cell group (SCG) and the second base station may be configured as a master cell group (MCG). In one example, the first communication link may be a New Radio (NR) link and the second communication link may be a Long-Term Evolution (LTE) link.

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