QAM2PAM#

class sionna.phy.mapping.QAM2PAM(num_bits_per_symbol: int, precision: Literal['single', 'double'] | None = None, device: str | None = None, **kwargs: Any)[source]#

Bases: sionna.phy.object.Object

Transforms QAM symbol indices to PAM symbol indices.

For indices in a QAM constellation, computes the corresponding indices for the two PAM constellations corresponding to the real and imaginary components of the QAM constellation.

Parameters:

  • num_bits_per_symbol (int) – Number of bits per QAM constellation symbol, e.g., 4 for QAM16.

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

  • device (str | None) – Device for tensor operations. If None, device is used.

  • kwargs (Any)

Inputs:

ind_qam – torch.Tensor, torch.int32. Indices in the QAM constellation.

Outputs:

  • ind_pam1 – torch.Tensor, torch.int32. Indices for the first component of the corresponding PAM modulation.

  • ind_pam2 – torch.Tensor, torch.int32. Indices for the second component of the corresponding PAM modulation.

Examples

import torch
from sionna.phy.mapping import QAM2PAM

converter = QAM2PAM(4)  # 16-QAM
ind_qam = torch.tensor([0, 5, 10, 15])
ind_pam1, ind_pam2 = converter(ind_qam)
print(ind_pam1, ind_pam2)
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