MACHINE LEARNING-BASED RADIO FREQUENCY CIRCUIT CALIBRATION

    公开(公告)号:US20230417870A1

    公开(公告)日:2023-12-28

    申请号:US17808745

    申请日:2022-06-24

    CPC classification number: G01S7/4008 G01S13/42

    Abstract: Certain aspects of the present disclosure provide techniques for identifying a minimal, or at least reduced, set of representative calibration paths in radio frequency (RF) circuits and calibrating other calibration paths based on calibration codes used for the representative calibration paths. An example method generally includes receiving a calibration data set including measurements associated with each calibration path of a plurality of calibration paths in an RF circuit. Based on a clustering model and the calibration data set, a plurality of calibration clusters is generated. From each respective calibration cluster of the plurality of calibration clusters, a respective representative calibration path for is selected for the respective calibration cluster. Generally, calibration codes generated for the representative calibration path are applicable to other calibration paths in the calibration cluster. A lookup table is generated associating a respective calibration path with other calibration paths in each respective calibration cluster.

Patent Agency Ranking