Gradient dataset aware configuration for over-the-air (ota) model aggregation in federated learning

An apparatus for wireless communications performed by a user equipment (UE), comprising:

• a processor,
• memory coupled with the processor;
• and
• instructions stored in the memory and operable, when executed by the processor, to cause the apparatus:
• to generate local gradients for a federated learning task;
• to calculate a gradient Sum-Power level based on the local gradients;
• to receive a mapping between gradient Sum-Power levels and scaling factors for channel inversion coefficients to process a data block into an unencoded uplink signal;
• to determine a channel inversion coefficient based on a scaling factor obtained from the mapping and the calculated gradient Sum-Power level;
• to apply analog modulation and the channel inversion coefficient to the data block to form the unencoded uplink signal;
• and
• to transmit, to a network, the unencoded uplink signal on shared uplink resources for an over-the-air computation of global gradients for the federated learning task.