AI-based CSI prediction with weight sharing

A device comprising:

• a transceiver configured to receive a pilot signal or a measurement report from a user equipment (UE) or a base station (BS);
• and
• a processor operably connected to the transceiver, the processor configured to:
• update a CSI buffer with channel state information (CSI) obtained from the pilot signal or the measurement report, the CSI buffer configured to store previous uplink or downlink channel estimates;
• provide at least a portion of the CSI buffer to a CSI predictor comprising an artificial intelligence (AI) model that utilizes one or more weight sharing mechanisms, the AI model comprising a sequence of layers;
• and
• predict temporal CSI using the CSI predictor,
• wherein to predict the temporal CSI using the CSI predictor, the processor is further configured to:
• for each layer of the AI model:
• perform circular padding along multiple dimensions representing angles of the CSI buffer to generate a padded signal;
• provide the padded signal to that layer;
• and
• perform at least one nonlinear activation function using that layer.

A non-transitory computer readable medium comprising program code that, when executed by a processor of a device, causes the device to:

• receive a pilot signal or a measurement report from a user equipment (UE) or a base station (BS);
• update a CSI buffer with channel state information (CSI) obtained from the pilot signal or the measurement report, the CSI buffer configured to store previous uplink or downlink channel estimates;
• provide at least a portion of the CSI buffer to a CSI predictor comprising an artificial intelligence (AI) model that utilizes one or more weight sharing mechanisms, the AI model comprising a sequence of layers;
• and
• predict temporal CSI using the CSI predictor,
• wherein to predict the temporal CSI using the CSI predictor, the program code, when executed by the processor of the device, further causes the device to:
• for each layer of the AI model:
• perform circular padding along multiple dimensions representing angles of the CSI buffer to generate a padded signal;
• provide the padded signal to that layer;
• and
• perform at least one nonlinear activation function using that layer.