building_entry_loss

pycraf.pathprof.building_entry_loss(freq, theta, prob, building_type)

Calculate building entry loss (BEL).

The BEL model is according to Rec. ITU-R P.2109-1.

Parameters:

freqQuantity

Frequency of radiation [GHz]

thetaQuantity

Path elevation angle (w.r.t. horizon) [deg] The minimal loss happens at zero horizontal incidence (0 deg)

probQuantity

Probability that loss is not exceeded [%]

building_typeBuildingType enum

Building type allowed values: BuildingType.TRADITIONAL or BuildingType.THERM_EFF

Returns:

L_belQuantity

Building entry loss [dB]

Notes

• The result of this function is to be understood as a cumulative value. For example, if prob = 2%, it means that for 2% of all possible outcomes, the loss will not exceed the returned L_bel value, for the remaining 98% of locations it will therefore be lower than L_bel. The smaller prob, the smaller the returned L_bel, i.e., low BELs are more unlikely.

Examples

With the following, one can create the Figures in Rec. ITU-R P.2109-1.

import matplotlib.pyplot as plt
from pycraf import conversions as cnv
from pycraf import pathprof
from astropy import units as u

freq = np.logspace(-1, 2, 100) * u.GHz
theta = 0 * u.deg
prob = 0.5 * cnv.dimless

plt.figure(figsize=(8, 6))

for btype in [
        pathprof.BuildingType.TRADITIONAL,
        pathprof.BuildingType.THERM_EFF
        ]:

    L_bel = pathprof.building_entry_loss(freq, theta, prob, btype)

    plt.semilogx(freq, L_bel, '-', label=str(btype))

plt.xlabel('Frequency [GHz]')
plt.ylabel('BEL [dB]')
plt.xlim((0.1, 100))
plt.ylim((10, 60))
plt.legend(*plt.gca().get_legend_handles_labels())
plt.title('Median BEL at horizontal incidence')
plt.grid()

import matplotlib.pyplot as plt
from pycraf import conversions as cnv
from pycraf import pathprof
from astropy import units as u

freqs = [0.1, 1, 10, 100] * u.GHz
colors = ['k', 'r', 'g', 'b']
theta = 0 * u.deg
prob = np.linspace(1e-6, 1 - 1e-6, 200) * cnv.dimless

plt.figure(figsize=(8, 6))

for freq, color in zip(freqs, colors):

    for btype, ls in zip([
            pathprof.BuildingType.TRADITIONAL,
            pathprof.BuildingType.THERM_EFF
            ], ['--', ':']):

        L_bel = pathprof.building_entry_loss(freq, theta, prob, btype)

        plt.plot(L_bel, prob, ls, color=color)

    # labels
    plt.plot([], [], '-', color=color, label=str(freq))

plt.xlabel('BEL [dB]')
plt.ylabel('Probability')
plt.xlim((-20, 140))
plt.ylim((0, 1))
plt.legend(*plt.gca().get_legend_handles_labels())
plt.title('BEL (dashed: Traditional, dotted: Thermally inefficient')
plt.grid()