GenerateFlatFadingChannel#

class sionna.phy.channel.GenerateFlatFadingChannel(num_tx_ant: int, num_rx_ant: int, spatial_corr: sionna.phy.channel.spatial_correlation.SpatialCorrelation | None = None, precision: Literal['single', 'double'] | None = None, device: str | None = None, **kwargs)[source]#

Bases: sionna.phy.block.Block

Generates tensors of flat-fading channel realizations

This class generates batches of random flat-fading channel matrices. A spatial correlation can be applied.

Parameters:

  • num_tx_ant (int) – Number of transmit antennas

  • num_rx_ant (int) – Number of receive antennas

  • spatial_corr (sionna.phy.channel.spatial_correlation.SpatialCorrelation | None) – Spatial correlation to be applied. Defaults to None.

  • precision (Literal['single', 'double'] | None) – Precision used for internal calculations and outputs. If set to None, precision is used.

  • device (str | None) – Device for computation (e.g., ‘cpu’, ‘cuda:0’). If None, device is used.

Inputs:

batch_size – int. Number of channel matrices to generate.

Outputs:

h – [batch_size, num_rx_ant, num_tx_ant], torch.complex. Batch of random flat fading channel matrices.

Examples

import torch
from sionna.phy.channel import GenerateFlatFadingChannel

gen_chn = GenerateFlatFadingChannel(num_tx_ant=4, num_rx_ant=16)
h = gen_chn(batch_size=32)
print(h.shape)
# torch.Size([32, 16, 4])

Attributes

property spatial_corr: sionna.phy.channel.spatial_correlation.SpatialCorrelation | None#

Get/set spatial correlation to be applied