Adaptive carrier selection for random access channel procedures using machine learning

A method for wireless communications at a user equipment (UE), comprising:

• receiving configuration information indicating for the UE to evaluate a plurality of parameters at each random access channel (RACH) attempt;
• monitoring one or more carriers of a plurality of different carriers, based at least in part on the configuration information, to obtain a channel dataset comprising values for the plurality of parameters associated with a first RACH attempt;
• selecting a first carrier from the plurality of different carriers in accordance with a prediction associated with the first carrier based at least in part on the channel dataset, wherein the prediction indicates a likelihood of successfully performing a RACH procedure using the first carrier;
• and
• communicating one or more messages of a RACH procedure using the first carrier.

A non-transitory computer-readable medium storing code for wireless communications, the code comprising instructions executable by one or more processors to:

• receive configuration information indicating to evaluate a plurality of parameters at each random access channel (RACH) attempt;
• monitor one or more carriers of a plurality of different carriers, based at least in part on the configuration information, to obtain a channel dataset comprising values for the plurality of parameters associated with a first RACH attempt;
• select a first carrier from the plurality of different carriers in accordance with a prediction associated with the first carrier based at least in part on the channel dataset, wherein the prediction indicates a likelihood of successfully performing a RACH procedure using the first carrier;
• and
• communicate one or more messages of a RACH procedure using the first carrier.