Bayesian optimization for beam tracking

A user equipment, comprising:

• at least one processor;
• and
• at least one memory
• storing instructions that, when executed with the at least one processor, cause the user equipment at least to:
• connect to a network node;
• infer, using an inference model during a time slot, a probability distribution of reference signal received power for at least one beam within a set of available beams, the probability distribution describing a likelihood of a reference signal received power value for the at least one beam among a plurality of reference signal received power values;
• wherein the probability distribution is inferred given at least one of past reference signal received power measurements;
• and
• transmit data to the network node using one of the beams within the set of available beams, based at least partially on the probability distribution of reference signal received power inferred for the at least one beam within the set of available beams.

A method, comprising:

• connecting to a network node;
• inferring, using an inference model during a time slot, a probability distribution of reference signal received power for at least one beam within a set of available beams, the probability distribution describing a likelihood of a reference signal received power value for the at least one beam among a plurality of reference signal received power values;
• wherein the probability distribution is inferred given at least one of past reference signal received power measurements;
• and
• transmitting data to the network node using one of the beams within the set of available beams, based at least partially on the probability distribution of reference signal received power inferred for the at least one beam within the set of available beams.