UNSUPERVISED LOCATION ESTIMATION AND MAPPING BASED ON MULTIPATH MEASUREMENTS

    公开(公告)号:WO2023086912A1

    公开(公告)日:2023-05-19

    申请号:PCT/US2022/079680

    申请日:2022-11-11

    Abstract: Certain aspects of the present disclosure provide methods, apparatus, and systems for predicting a location of a device in a spatial environment using a machine learning model. An example method generally includes measuring a plurality of signals received from a network entity at a device. A channel state information (CSI) measurement is generated from the measured plurality of signals. Generally, the CSI measurement includes a multipath component. Positions of one or more anchors in a spatial environment are identified based on a machine learning model trained to identify the positions of the one or more anchors based on the CSI measurement. A location of the device is estimated based on the identified positions of the one or more anchors.

    PROBABILISTIC NUMERIC CONVOLUTIONAL NEURAL NETWORKS

    公开(公告)号:WO2022072863A1

    公开(公告)日:2022-04-07

    申请号:PCT/US2021/053219

    申请日:2021-10-01

    Abstract: Certain aspects of the present disclosure provide techniques for performing operations with probabilistic numeric convolutional neural network, including: defining a Gaussian Process based on a mean and a covariance of input data; applying a linear operator to the Gaussian Process to generate pre-activation data; applying a nonlinear operation to the pre-activation data to form activation data; and applying a pooling operation to the activation data to generate an inference.

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