torchsig.transforms.impairments_wideband

Wideband Transforms and Impairments for Impairment Levels 0-2

Impairments are transforms applied to Signal objects, after the Signal Builder generates an isolated signal. Transforms are applied to DatasetSignal objects, after isolated signals are placed on an IQ cut of noise.

Example

>>> impairments = WidebandImpairments(level = 2, dataset_metadata=dm)
>>> iq_samples = <random noise>
>>> metadatas = []
>>> for i in range(3): # 3 signals in wideband sample
>>>     sb = SignalBuilder(...)
>>>     new_signal = sb.build()
>>>     impaired_new_signal = impairments(new_signal)
>>>     iq_samples[start:stop] += new_signal.data
>>>     metadatas.append(impaired_new_signal.metadata)

>>> new_dataset_signal = DatasetSignal(data=iq_samples, metadata=metadatas)

>>> transforms = WidebandTransforms(level = 2, dataset_metadata=dm)
>>> transformed_dataset_signal = transforms(new_dataset_signal)

Classes

WidebandImpairments

Applies impairements to Wideband dataset