pytwinnet.accelerate.vectorized

Functions

fspl_matrix_db(tx_xyz, rx_xyz, f_hz)	Vectorized Free-Space Path Loss in dB: (T,R) If f_hz is scalar and Numba is available -> JIT kernel.
noise_dbm_vector(bandwidth_hz[, ...])	Vectorized thermal noise power (dBm).
rsrp_matrix_dbm(tx_dbm, gt_dbi, gr_dbi, pl_db)	RSRP (received power) in dBm for all TX-RX pairs.
shannon_throughput_bps_vector(bandwidth_hz, ...)	Vectorized Shannon throughput per RX (bps).
sinr_db_from_rsrp_matrix(rsrp_dbm, ...)

pytwinnet.accelerate.vectorized.fspl_matrix_db(tx_xyz, rx_xyz, f_hz)

Vectorized Free-Space Path Loss in dB: (T,R) If f_hz is scalar and Numba is available -> JIT kernel.

Return type:

ndarray

Parameters:

• tx_xyz (ndarray)

• rx_xyz (ndarray)

• f_hz (ndarray | float)

pytwinnet.accelerate.vectorized.noise_dbm_vector(bandwidth_hz, temperature_k=290.0, noise_figure_db=0.0)

Vectorized thermal noise power (dBm). bandwidth_hz: scalar or (R,), noise_figure_db: scalar or (R,) -> (R,)

Return type:

ndarray

Parameters:

• bandwidth_hz (ndarray | float)

• temperature_k (float)

• noise_figure_db (ndarray | float)

pytwinnet.accelerate.vectorized.rsrp_matrix_dbm(tx_dbm, gt_dbi, gr_dbi, pl_db)

RSRP (received power) in dBm for all TX-RX pairs. tx_dbm, gt_dbi: (T,), gr_dbi: (R,), pl_db: (T,R) -> (T,R)

Return type:

ndarray

Parameters:

• tx_dbm (ndarray)

• gt_dbi (ndarray)

• gr_dbi (ndarray)

• pl_db (ndarray)

pytwinnet.accelerate.vectorized.shannon_throughput_bps_vector(bandwidth_hz, sinr_db, efficiency=1.0)

Vectorized Shannon throughput per RX (bps).

Return type:

ndarray

Parameters:

• bandwidth_hz (ndarray | float)

• sinr_db (ndarray)

• efficiency (float)

pytwinnet.accelerate.vectorized.sinr_db_from_rsrp_matrix(rsrp_dbm, serving_tx_idx, noise_dbm)

Return type:

ndarray

Parameters:

• rsrp_dbm (ndarray)

• serving_tx_idx (ndarray)

• noise_dbm (ndarray)