count_block_errors

sionna.phy.utils.count_block_errors(b: torch.Tensor, b_hat: torch.Tensor) → torch.Tensor

Counts the number of block errors between two binary tensors.

A block error happens if at least one element of b and b_hat differ in one block. The BLER is evaluated over the last dimension of the input, i. e., all elements of the last dimension are considered to define a block.

This is also sometimes referred to as word error rate or frame error rate.

Parameters:

• b (torch.Tensor) – A tensor of arbitrary shape filled with ones and zeros.

• b_hat (torch.Tensor) – A tensor like b.

Outputs:

num_errors – torch.int64. Number of block errors.

Examples

import torch
from sionna.phy.utils import count_block_errors

b = torch.tensor([[0, 1], [1, 0]])
b_hat = torch.tensor([[0, 1], [1, 1]])
print(count_block_errors(b, b_hat).item())
# 1