CPC H04B 17/373 (2015.01) [G06N 3/08 (2013.01); H04B 17/318 (2015.01); H04W 24/08 (2013.01)] | 30 Claims |
1. A method of wireless communication performed by a user equipment (UE), comprising:
receiving a signal comprising a synchronization signal block (SSB);
determining, based at least in part on a machine learning component, a predicted communication metric and a confidence indication, wherein the machine learning component comprising a machine learning model, and wherein determining the predicted communication metric and the confidence indication comprises:
receiving, by the machine learning model, an input that comprises an input metric and an error measurement corresponding to the input metric;
obtaining, by the machine learning model and based at least in part on a machine learning function associated with a set of reference signals and the error measurement, a set of measurements associated with a subset of the set of reference signals, wherein the subset includes fewer reference signals than the set of reference signals, wherein obtaining the set of measurements comprises skipping at least one configured measurement based at least in part on receiving a downlink communication during a measurement occasion corresponding to the at least one configured measurement;
generating, by the machine learning model and based at least in part on the machine learning function, an interpolated measurement corresponding to a first input port, of the machine learning function, for which the measurement was not obtained;
generating, by the machine learning model and based at least in part on the machine learning function, a measurement pattern indication, corresponding to the set of measurements, including:
an indication of at least one of the first input port for which the measurement was not obtained, or a second input port of the machine learning function for which the measurement was obtained, and
an indication of an interpolation error corresponding to the interpolated measurement;
providing, by the machine learning model and based at least in part on the machine learning function and the input, the predicted communication metric and the confidence indication; and
performing a wireless communication task based at least in part on the predicted communication metric and the confidence indication.
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