flatten_precoding_mat#

sionna.phy.mimo.flatten_precoding_mat(precoding_mat: torch.Tensor, by_column: bool = True) → torch.Tensor[source]#

Flattens a […, num_ant_v, num_ant_h] precoding matrix associated with a rectangular array by producing a […, num_ant_v x num_ant_h] precoding vector.

Parameters:

precoding_mat (torch.Tensor) – Precoding matrix with shape […, num_antennas_vertical, num_antennas_horizontal]. The element \((i,j)\) contains the precoding coefficient of the antenna element located at row \(i\) and column \(j\) of a rectangular antenna array.
by_column (bool) – If True, flattening occurs on a per-column basis, i.e., the first column is appended to the second, and so on. Else, flattening is performed on a per-row basis.

Outputs:

precoding_vec – […, num_antennas_vertical x num_antennas_horizontal], torch.complex. Flattened precoding matrix.

Examples

mat = torch.randn(4, 8, dtype=torch.complex64)
vec = flatten_precoding_mat(mat)
# vec.shape = torch.Size([32])