kaira.channels.LaplacianChannel

Inheritance diagram for LaplacianChannel

class kaira.channels.LaplacianChannel(scale: float | None = None, avg_noise_power: float | None = None, snr_db: float | None = None, *args: Any, **kwargs: Any)

Bases: BaseChannel

Channel with additive Laplacian (double-exponential) noise.

Models a channel with noise following the Laplacian distribution, which has heavier tails than Gaussian noise. This channel supports both real and complex-valued inputs. Laplacian noise is often used to model impulsive noise environments [Middleton, 1977].

Mathematical Model:

y = x + n where n follows a Laplacian distribution

Parameters:

• scale (float, optional) – Scale parameter of the Laplacian distribution.

• avg_noise_power (float, optional) – The average noise power.

• snr_db (float, optional) – SNR in dB (alternative to scale or avg_noise_power).

Example

>>> # Create a Laplacian channel with scale=0.5
>>> channel = LaplacianChannel(scale=0.5)
>>> x = torch.ones(10, 1)
>>> y = channel(x)  # Output with Laplacian noise

Methods

__init__	Initialize the Laplacian channel.
forward	Apply Laplacian noise to the input signal.
get_config	Get a dictionary of the channel's configuration.

Attributes

scale
avg_noise_power
snr_db

__init__(scale: float | None = None, avg_noise_power: float | None = None, snr_db: float | None = None, *args: Any, **kwargs: Any)

Initialize the Laplacian channel.

Parameters:

• scale (float, optional) – Scale parameter of the Laplacian distribution.

• avg_noise_power (float, optional) – The average noise power.

• snr_db (float, optional) – SNR in dB (alternative to scale or avg_noise_power).

• *args – Variable length argument list passed to the base class.

• **kwargs – Arbitrary keyword arguments passed to the base class.

avg_noise_power: float | None

scale: float | None

snr_db: float | None

forward(x: Tensor, *args: Any, **kwargs: Any) → Tensor

Apply Laplacian noise to the input signal.

Parameters:

• x (torch.Tensor) – The input tensor.

• *args – Additional positional arguments (unused).

• **kwargs – Additional keyword arguments (unused).

Returns:

The output tensor with Laplacian noise added.

Return type:

torch.Tensor

get_config() → Dict[str, Any]

Get a dictionary of the channel’s configuration.

This method returns a dictionary containing the channel’s parameters, which can be used to recreate the channel instance.

Returns:

Dictionary of parameter names and values

Return type:

Dict[str, Any]