Section

class GridSection(num_repetitions=1, sample_offset=0, wave=None)

Bases: Generic[OWT], Serializable

Description of a part of a grid’s time domain.

Parameters:

• num_repetitions (int) – Number of times this section is repeated in time-domain.

• sample_offset (int) – Offset in samples to the start of the section.

• wave (TypeVar(OWT, bound= OrthogonalWaveform) | None) – Waveform this section is associated with. Defaults to None.

abstract num_samples(bandwidth, oversampling_factor)

Number of samples within this OFDM time-section.

Parameters:

• bandwidth (float) – Bandwidth of the OFDM waveform.

• oversampling_factor (int) – Oversampling factor of resulting time-domain signal.

Return type:

int

Returns: Number of samples within this section.

abstract pick_samples(signal, bandwidth, oversampling_factor)

Pick this section’s samples from the time-domain signal.

Parameters:

• signal (ndarray) – Time-domain signal to be picked from. Numpy vector of size num_samples.

• bandwidth (float) – Bandwidth of the OFDM waveform.

• oversampling_factor (int) – Oversampling factor of resulting time-domain signal.

Return type:

ndarray

Returns: Time-domain signal with the section’s samples picked.

pick_symbols(grid)

Pick this section’s data symbols from the resource grid.

Parameters:

grid (ndarray) – Resource grid. Two dimensional numpy array of size num_words`x`num_subcarriers.

Return type:

ndarray

Returns: Data symbols. Numpy vector of size num_symbols.

abstract place_samples(signal, bandwidth, oversampling_factor)

Place this section’s samples into the time-domain signal.

Parameters:

• signal (ndarray) – Time-domain signal to be placed. Numpy vector of size num_samples.

• bandwidth (float) – Bandwidth of the OFDM waveform.

• oversampling_factor (int) – Oversampling factor of resulting time-domain signal.

Return type:

ndarray

Returns: Time-domain signal with the section’s samples placed.

place_symbols(data_symbols, reference_symbols)

Place this section’s symbols into the resource grid.

Parameters:

• data_symbols (ndarray) – Data symbols to be placed. Numpy vector of size num_symbols.

• reference_symbols (ndarray) – Reference symbols to be placed. Numpy vector of size num_references.

Return type:

ndarray

Returns: Two dimensional numpy array of size num_words`x`num_subcarriers.

serialize(process)

Serialize this object’s state.

Objects cannot be serialized directly, instead a Factory must be instructed to carry out the serialization process.

Parameters:

process (SerializationProcess) – The current stage of the serialization process. This object is generated by the Factory and provides an interface to serialization methods supporting multiple backends.

Return type:

None

property num_references: int

Number of data symbols this section can modulate.

property num_repetitions: int

Number of section repetitions in the time-domain of an OFDM grid.

property num_subcarriers: int

Number of subcarriers this section requires.

property num_symbols: int

Number of data symbols this section can modulate.

property num_words: int

Number of OFDM symbols, i.e. words of subcarrier symbols this section can modulate.

property resource_mask: ndarray

property sample_offset: int

Offset in samples to the start of the section.

This can be used to explot cyclic prefixes and suffixes in order to be more robust against timing offsets.

property wave: OWT | None

Waveform this section is associated with.