Neural network or layer configuration indicator for a channel state information scheme

A method for wireless communications at a network entity comprising:

• receiving, from a user equipment (UE) an indication of a set of trained layers of a neural network based at least in part on channel estimates over a set of resources;
• identifying a set of weights for the set of trained layers of the neural network based at least in part on the indication of the set of trained layers;
• transmitting, to the UE, an indication of an association between a first set of one or more signals and a second set of one or more signals based at least in part on the set of trained layers of the neural network;
• and
• transmitting the second set of one or more signals to the UE,
• wherein the indication of the association comprises a source identifier and a target identifier.

An apparatus for wireless communications at a user equipment (UE), comprising memory coupled to a processor, wherein the processor is configured to:

• train a first set of layers of a neural network based at least in part on channel estimates using a set of resources;
• generate a set of weights for the first set of layers of the neural network based at least in part on the training;
• receive, from a first network entity, an indication of an association between a first set of one or more signals and a second set of one or more signals;
• receive the second set of one or more signals from a second network entity;
• and
• process the second set of one or more signals using the set of weights for the first set of layers based at least in part on the association between the first set of one or more signals and the second set of one or more signals,
• wherein the indication of the association comprises a source identifier and a target identifier.

An apparatus for wireless communications at a network entity comprising memory coupled to a processor, wherein the processor is configured to:

• receive, from a user equipment (UE) an indication of a set of trained layers of a neural network based at least in part on channel estimates over a set of resources;
• identify a set of weights for the set of trained layers of the neural network based at least in part on the indication of the set of trained layers;
• transmit, to the UE, an indication of an association between a first set of one or more signals and a second set of one or more signals based at least in part on the set of trained layers of the neural network;
• and
• transmit the second set of one or more signals to the UE,
• wherein the indication of the association comprises a source identifier and a target identifier.