set_3gpp_scenario_parameters#

sionna.phy.channel.set_3gpp_scenario_parameters(scenario: str, min_bs_ut_dist: float | None = None, isd: float | None = None, bs_height: float | None = None, min_ut_height: float | None = None, max_ut_height: float | None = None, indoor_probability: float | None = None, min_ut_velocity: float | None = None, max_ut_velocity: float | None = None, precision: str | None = None, device: str | None = None) → Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor][source]#

Set valid parameters for a specified 3GPP system level scenario (RMa, UMi, or UMa)

If a parameter is given, then it is returned. If it is set to None, then a parameter valid according to the chosen scenario is returned (see [TR38901V1920]). The default minimum BS-UT distances for the UMi and UMa scenarios, including their calibration variants, are 10 m and 35 m, respectively, as specified in Table 7.8-1 of [TR38901V160100].

Parameters:

  • scenario (str) – System level model scenario. One of "uma", "umi", "rma", "uma-calibration", or "umi-calibration".

  • min_bs_ut_dist (float | None) – Minimum BS-UT distance [m]

  • isd (float | None) – Inter-site distance [m]

  • bs_height (float | None) – BS elevation [m]

  • min_ut_height (float | None) – Minimum UT elevation [m]

  • max_ut_height (float | None) – Maximum UT elevation [m]

  • indoor_probability (float | None) – Probability of a UT to be indoor. For RMa, the remaining UTs are interpreted as in-car by RMa unless an explicit in_car mask is passed to set_topology().

  • min_ut_velocity (float | None) – Minimum UT velocity [m/s]

  • max_ut_velocity (float | None) – Maximum UT velocity [m/s]

  • precision (str | None) – Precision used for internal calculations and outputs. If set to None, precision is used.

  • device (str | None) – Device for computation. If None, device is used.

Outputs:

  • min_bs_ut_dist – torch.float. Minimum BS-UT distance [m].

  • isd – torch.float. Inter-site distance [m].

  • bs_height – torch.float. BS elevation [m].

  • min_ut_height – torch.float. Minimum UT elevation [m].

  • max_ut_height – torch.float. Maximum UT elevation [m].

  • indoor_probability – torch.float. Probability of a UT to be indoor.

  • min_ut_velocity – torch.float. Minimum UT velocity [m/s].

  • max_ut_velocity – torch.float. Maximum UT velocity [m/s].

Examples

The returned tensors can be passed to topology-generation helpers that require scenario-dependent defaults.

import torch
from sionna.phy.channel import (
    generate_uts_topology,
    set_3gpp_scenario_parameters,
)

params = set_3gpp_scenario_parameters("umi")
(min_bs_ut_dist, isd, bs_height, min_ut_height, max_ut_height,
 indoor_probability, min_ut_velocity, max_ut_velocity) = params

ut_loc, ut_orientations, ut_velocities, in_state = generate_uts_topology(
    batch_size=1,
    num_ut=4,
    drop_area="sector",
    cell_loc_xy=torch.zeros(1, 1, 2),
    min_bs_ut_dist=min_bs_ut_dist,
    isd=isd,
    min_ut_height=min_ut_height,
    max_ut_height=max_ut_height,
    indoor_probability=indoor_probability,
    min_ut_velocity=min_ut_velocity,
    max_ut_velocity=max_ut_velocity,
)