Topology

class sionna.phy.channel.tr38901.Topology(velocities: torch.Tensor, moving_end: str, los_aoa: torch.Tensor, los_aod: torch.Tensor, los_zoa: torch.Tensor, los_zod: torch.Tensor, los: torch.Tensor, distance_3d: torch.Tensor, tx_orientations: torch.Tensor, rx_orientations: torch.Tensor)

Bases: object

Class for conveniently storing the network topology information required for sampling channel impulse responses

Parameters:

• velocities (torch.Tensor) – UT velocities, shape [batch size, number of UTs, 3], torch.float

• moving_end (str) – Indicated which end of the channel (TX or RX) is moving. One of "tx" or "rx".

• los_aoa (torch.Tensor) – Azimuth angle of arrival of LoS path [radian], shape [batch size, number of base stations, number of UTs], torch.float

• los_aod (torch.Tensor) – Azimuth angle of departure of LoS path [radian], shape [batch size, number of base stations, number of UTs], torch.float

• los_zoa (torch.Tensor) – Zenith angle of arrival for LoS path [radian], shape [batch size, number of base stations, number of UTs], torch.float

• los_zod (torch.Tensor) – Zenith angle of departure for LoS path [radian], shape [batch size, number of base stations, number of UTs], torch.float

• los (torch.Tensor) – Indicate for each BS-UT link if it is in LoS, shape [batch size, number of base stations, number of UTs], torch.bool

• distance_3d (torch.Tensor) – Distance between the UTs in X-Y-Z space (not only X-Y plane), shape [batch size, number of base stations, number of UTs], torch.float

• tx_orientations (torch.Tensor) – Orientations of the transmitters, which are either base stations or UTs depending on the link direction [radian], shape [batch size, number of TXs, 3], torch.float

• rx_orientations (torch.Tensor) – Orientations of the receivers, which are either base stations or UTs depending on the link direction [radian], shape [batch size, number of RXs, 3], torch.float