End-to-end learning of csi feedback functions

A method to be performed by a wireless transmit/receive unit (WTRU), the method comprising:

• receiving configuration information, wherein the configuration information is associated with an artificial intelligence or machine learning (AI/ML) model that is configured to generate data for a channel state information (CSI) feedback report;
• generating a set of ground truth training bits based on one or more seed values;
• receiving downlink data from a network entity;
• determining a set of training data based on the downlink data;
• determining a loss function of the AI/ML model using the determined set of training data and the generated set of the ground truth training data;
• computing a first set of one or more gradients of the loss function;
• sending the first set of one or more gradients to the network entity;
• receiving a second set of one or more gradients from the network entity;
• updating the AI/ML model based on the first and the second sets of one or more gradients.

A base station comprising a processor and memory, wherein the processor and memory are configured to:

• send configuration information to a WTRU, wherein the configuration information is associated with a first artificial intelligence or machine learning (AI/ML) model that is configured to generate data for a channel state information (CSI) feedback report;
• generate a set of training data based on one or more seed values;
• send downlink data to the WTRU, wherein the downlink data indicates the set of training data bits;
• receive a first set of one or more gradients from the WTRU;
• determine a second set of one or more gradients;
• send the second set of one or more gradients to the WTRU;
• update a second AI/ML model based on the first and the second sets of one or more gradients.