Query-based channel state information feedback decoding for cross-node machine learning

An apparatus for wireless communication at a network node, comprising:

• one or more memories;
• and
• one or more processors, coupled to the one or more memories, which, individually or in any combination, are operable to cause the apparatus to:
• transmit, to a user equipment (UE), decoder configuration information associated with a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a query-based cross-node machine learning system;
• transmit, to the UE, query configuration information associated with a query-based decoder;
• and
• receive, from the UE and based at least in part on instantiation of the transmitter neural network by the UE, the at least one latent vector.

A method of wireless communication performed by a user equipment (UE), comprising:

• receiving, from a network node, decoder configuration information associated with a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a query-based cross-node machine learning system;
• receiving, from the network node, query configuration information associated with a query-based decoder;
• and
• transmitting, to the network node and based at least in part on instantiation of the transmitter neural network by the UE, the at least one latent vector.

A method of wireless communication performed by a network node, comprising:

• transmitting, to a user equipment (UE), decoder configuration information associated with a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a query-based cross-node machine learning system;
• transmitting, to the UE, query configuration information associated with a query-based decoder;
• and
• receiving, from the UE and based at least in part on instantiation of the transmitter neural network by the UE, the at least one latent vector.