TB5GScrambler#

class sionna.phy.fec.scrambling.TB5GScrambler(n_rnti: int | Sequence[int] = 1, n_id: int | Sequence[int] = 1, binary: bool = True, channel_type: str = 'PUSCH', codeword_index: int = 0, *, precision: str | None = None, device: str | None = None, **kwargs)[source]#

Bases: sionna.phy.block.Block

5G NR Scrambler for PUSCH and PDSCH channel.

Implements the pseudo-random bit scrambling as defined in [3GPPTS38211] Sec. 6.3.1.1 for the “PUSCH” channel and in Sec. 7.3.1.1 for the “PDSCH” channel.

Only for the “PDSCH” channel, the scrambler can be configured for two codeword transmission mode. Hereby, codeword_index corresponds to the index of the codeword to be scrambled.

If n_rnti is a list of ints, the scrambler assumes that the second last axis contains len(n_rnti) elements. This allows independent scrambling for multiple independent streams.

Parameters:

  • n_rnti (int | Sequence[int]) – RNTI identifier provided by higher layer. Defaults to 1 and must be in range [0, 65535]. If a list is provided, every list element defines a scrambling sequence for multiple independent streams.

  • n_id (int | Sequence[int]) – Scrambling ID related to cell id and provided by higher layer. Defaults to 1 and must be in range [0, 1023]. If a list is provided, every list element defines a scrambling sequence for multiple independent streams.

  • binary (bool) – Indicates whether bit-sequence should be flipped (i.e., binary operations are performed) or the signs should be flipped (i.e., soft-value/LLR domain-based).

  • channel_type (str) – Can be either 'PUSCH' or 'PDSCH'.

  • codeword_index (int) – Scrambler can be configured for two codeword transmission. codeword_index can be either 0 or 1.

  • precision (str | None) – Precision used for internal calculations and outputs. If None, precision is used.

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

Inputs:

  • x – torch.Tensor. Tensor of arbitrary shape. If n_rnti and n_id are a list, it is assumed that x has shape [..., num_streams, n] where num_streams = len(n_rnti).

  • binary – None | bool. Overrules the init parameter binary if explicitly given. Indicates whether bit-sequence should be flipped (i.e., binary operations are performed) or the signs should be flipped (i.e., soft-value/LLR domain-based).

Outputs:

x_out – torch.Tensor. Tensor of same shape as x.

Notes

The parameters radio network temporary identifier (RNTI) n_rnti and the datascrambling ID n_id are usually provided by the higher layer protocols.

For inverse scrambling, the same scrambler can be reused (as the values are flipped again, i.e., result in the original state).

Examples

import torch
from sionna.phy.fec.scrambling import TB5GScrambler

scrambler = TB5GScrambler(n_rnti=1, n_id=1)
bits = torch.randint(0, 2, (10, 100), dtype=torch.float32)
scrambled = scrambler(bits)
unscrambled = scrambler(scrambled)  # Re-use for descrambling
assert torch.allclose(bits, unscrambled)

Attributes

property keep_state: bool#

Required for descrambler, is always True for the TB5GScrambler.