KBestDetector#
- class sionna.phy.ofdm.KBestDetector(output: str, num_streams: int, k: int, resource_grid: sionna.phy.ofdm.resource_grid.ResourceGrid, stream_management: sionna.phy.mimo.stream_management.StreamManagement, constellation_type: str | None = None, num_bits_per_symbol: int | None = None, constellation: sionna.phy.mapping.Constellation | None = None, hard_out: bool = False, use_real_rep: bool = False, list2llr: Callable | None = None, precision: Literal['single', 'double'] | None = None, device: str | None = None, **kwargs)[source]#
Bases:
sionna.phy.ofdm.detection.OFDMDetectorK-Best detector for OFDM MIMO transmissions.
This block wraps the MIMO K-Best detector for use with the OFDM waveform. Both detection of symbols or bits with either soft- or hard-decisions are supported. The OFDM and stream configuration are provided by a
ResourceGridandStreamManagementinstance, respectively. The actual detector is an instance ofKBestDetector.- Parameters:
output (str) – Type of output, either “bit” or “symbol”
num_streams (int) – Number of transmitted streams
k (int) – Number of paths to keep. Cannot be larger than the number of constellation points to the power of the number of streams.
resource_grid (sionna.phy.ofdm.resource_grid.ResourceGrid) – ResourceGrid to be used
stream_management (sionna.phy.mimo.stream_management.StreamManagement) – StreamManagement to be used
constellation_type (str | None) – Type of constellation, None (default), “qam”, “pam”, or “custom”. For “custom”, an instance of
Constellationmust be provided.num_bits_per_symbol (int | None) – Number of bits per constellation symbol, e.g., 4 for QAM16. Only required for
constellation_typein [“qam”, “pam”].constellation (sionna.phy.mapping.Constellation | None) – Instance of
Constellationor None. If None,constellation_typeandnum_bits_per_symbolmust be provided.hard_out (bool) – If True, the detector computes hard-decided bit values or constellation point indices instead of soft-values.
use_real_rep (bool) – If True, the detector uses the real-valued equivalent representation of the channel. Note that this only works with a QAM constellation.
list2llr (Callable | None) – The function to be used to compute LLRs from a list of candidate solutions. If None, the default solution
List2LLRSimpleis used.precision (Literal['single', 'double'] | None) – Precision used for internal calculations and outputs. If set to None,
precisionis used.device (str | None) – Device for tensor operations. If None,
deviceis used.
- Inputs:
y – [batch_size, num_rx, num_rx_ant, num_ofdm_symbols, fft_size], torch.complex. Received OFDM resource grid after cyclic prefix removal and FFT.
h_hat – [batch_size, num_rx, num_rx_ant, num_tx, num_streams_per_tx, num_ofdm_symbols, num_effective_subcarriers], torch.complex. Channel estimates for all streams from all transmitters.
err_var – [Broadcastable to shape of
h_hat], torch.float. Variance of the channel estimation error.no – [batch_size, num_rx, num_rx_ant] (or only the first n dims), torch.float. Variance of the AWGN.
- Outputs:
z –
One of:
[batch_size, num_tx, num_streams, num_data_symbols*num_bits_per_symbol], torch.float. LLRs or hard-decisions for every bit of every stream, if
outputequals “bit”.[batch_size, num_tx, num_streams, num_data_symbols, num_points], torch.float or [batch_size, num_tx, num_streams, num_data_symbols], torch.int32. Logits or hard-decisions for constellation symbols for every stream, if
outputequals “symbol”. Hard-decisions correspond to the symbol indices.