Recommendation ITU-R P.530¶

This Recommendation provides prediction methods for the propagation effects that should be taken into account in the design of digital fixed line-of-sight links, both in clear-air and rainfall conditions. It also provides link design guidance in clear step-by-step procedures including the use of mitigation techniques to minimize propagation impairments. The final outage predicted is the base for other Recommendations addressing error performance and availability.

Title	PDF	Latest approved in
Recommendation ITU-R P.530	[PDF]	2021-09
Propagation data and prediction methods required for the design of terrestrial line-of-sight systems
Current recommendation version (In force)		Date
Recommendation ITU-R P.530-18	[PDF]	09/2021
Recommendations implemented in ITU-Rpy		Date
Recommendation ITU-R P.530-17	[PDF]	12/2017
Recommendation ITU-R P.530-16	[PDF]	07/2015
Recommendations not implemented in ITU-Rpy		Date
Recommendation ITU-R P.530-18	[PDF]	09/2021
Recommendation ITU-R P.530-15	[PDF]	09/2013
Recommendation ITU-R P.530-14	[PDF]	02/2012
Recommendation ITU-R P.530-13	[PDF]	10/2009
Recommendation ITU-R P.530-12	[PDF]	02/2007
Recommendation ITU-R P.530-11	[PDF]	03/2005
Recommendation ITU-R P.530-10	[PDF]	11/2001
Recommendation ITU-R P.530-9	[PDF]	02/2001
Recommendation ITU-R P.530-8	[PDF]	10/1999
Recommendation ITU-R P.530-7	[PDF]	08/1997
Recommendation ITU-R P.530-6	[PDF]	10/1995
Recommendation ITU-R P.530-5	[PDF]	08/1994

Introduction¶

The propagation loss on a terrestrial line-of-sight path relative to the free-space loss (see Recommendation ITU-R P.525) is the sum of different contributions as follows:

attenuation due to atmospheric gases;

diffraction fading due to obstruction or partial obstruction of the path;

fading due to multipath, beam spreading and scintillation;

attenuation due to variation of the angle-of-arrival/launch;

attenuation due to precipitation;

attenuation due to sand and dust storms.

Each of these contributions has its own characteristics as a function of frequency, path length and geographic location. These are described in the paragraphs that follow.

Module description¶

itur.models.itu530.change_version(new_version)[source]¶

Change the version of the ITU-R P.530 recommendation currently being used.

This function changes the model used for the ITU-R P.530 recommendation to a different version.

Parameters:

new_version (int) –

Number of the version to use. Valid values are:

16: Activates recommendation ITU-R P.530-16 (07/15) (Current version)

itur.models.itu530.get_version()[source]¶

Obtain the version of the ITU-R P.530 recommendation currently being used.

Returns:	version – The version of the ITU-R P.530 recommendation being used.
Return type:	int

itur.models.itu530.fresnel_ellipse_radius(d1, d2, f)[source]¶

Compute the radius of the first Fresnel ellipsoid.

Parameters:	d1 (number, sequence, or numpy.ndarray) – Distances from the first terminal to the path obstruction. [km] d2 (number, sequence, or numpy.ndarray) – Distances from the second terminal to the path obstruction. [km] f (number) – Frequency of the link [GHz]
Returns:	F1 – Radius of the first Fresnel ellipsoid [m]
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.diffraction_loss(d1, d2, h, f)[source]¶

Estimate the diffraction loss over average terrain.

Diffraction loss over average terrain. This value is valid for losses greater than 15 dB.

Parameters:	d1 (number, sequence, or numpy.ndarray) – Distances from the first terminal to the path obstruction. [km] d2 (number, sequence, or numpy.ndarray) – Distances from the second terminal to the path obstruction. [km] h (number, sequence, or numpy.ndarray) – Height difference between most significant path blockage and the path trajectory. h is negative if the top of the obstruction of interest is above the virtual line-of-sight. [m] f (number) – Frequency of the link [GHz]
Returns:	A_d – Diffraction loss over average terrain [dB]
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.multipath_loss_for_A(lat, lon, h_e, h_r, d, f, A)[source]¶

Estimate the single-frequency (or narrow-band) fading distribution.

Method for predicting the single-frequency (or narrow-band) fading distribution at large fade depths in the average worst month in any part of the world. Given a fade depth value ‘A’, determines the amount of time it will be exceeded during a year

This method does not make use of the path profile and can be used for initial planning, licensing, or design purposes.

This method is only valid for small percentages of time.

Multi-path fading and enhancement only need to be calculated for path lengths longer than 5 km, and can be set to zero for shorter paths.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points h_e (number) – Emitter antenna height (above the sea level) [m] h_r (number) – Receiver antenna height (above the sea level) [m] d (number, sequence, or numpy.ndarray) – Distances between antennas [km] f (number) – Frequency of the link [GHz] A (number) – Fade depth [dB]
Returns:	p_w – percentage of time that fade depth A is exceeded in the average worst month [%]
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.multipath_loss(lat, lon, h_e, h_r, d, f, A)[source]¶

Estimate the percentage of time that any fade depth is exceeded.

Method for predicting the percentage of time that any fade depth is exceeded. This method combines the deep fading distribution given in the multipath_loss_for_A’ and an empirical interpolation procedure for shallow fading down to 0 dB.

This method does not make use of the path profile and can be used for initial planning, licensing, or design purposes.

Multi-path fading and enhancement only need to be calculated for path lengths longer than 5 km, and can be set to zero for shorter paths.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points h_e (number) – Emitter antenna height (above the sea level) [m] h_r (number) – Receiver antenna height (above the sea level) [m] d (number, sequence, or numpy.ndarray) – Distances between antennas [km] f (number) – Frequency of the link [GHz] A (number) – Fade depth [dB]
Returns:	p_w – percentage of time that fade depth A is exceeded in the average worst month [%]
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.rain_attenuation(lat, lon, d, f, el, p, tau=45, R001=None)[source]¶

Estimate long-term statistics of rain attenuation.

Attenuation can also occur as a result of absorption and scattering by such hydro-meteors as rain, snow, hail and fog. Although rain attenuation can be ignored at frequencies below about 5 GHz, it must be included in design calculations at higher frequencies, where its importance increases rapidly.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points d (number, sequence, or numpy.ndarray) – Path length [km] f (number) – Frequency of the link [GHz] el (sequence, or number) – Elevation angle (degrees) p (number) – Percentage of the time the rain attenuation value is exceeded. R001 (number, optional) – Point rainfall rate for the location for 0.01% of an average year (mm/h). If not provided, an estimate is obtained from Recommendation Recommendation ITU-R P.837. Some useful values: 0.25 mm/h : Drizzle 2.5 mm/h : Light rain 12.5 mm/h : Medium rain 25.0 mm/h : Heavy rain 50.0 mm/h : Downpour 100 mm/h : Tropical 150 mm/h : Monsoon tau (number, optional) – Polarization tilt angle relative to the horizontal (degrees) (tau = 45 deg for circular polarization). Default value is 45
Returns:	A_r – Attenuation exceeded during p percent of the time [dB]
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.inverse_rain_attenuation(lat, lon, d, f, el, Ap, tau=45, R001=None)[source]¶

Estimate the percentage of time a given attenuation is exceeded.

Estimate the percentage of time a given attenuation is exceeded due to rain events.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points d (number, sequence, or numpy.ndarray) – Path length [km] f (number) – Frequency of the link [GHz] el (sequence, or number) – Elevation angle (degrees) Ap (number) – Fade depth R001 (number, optional) – Point rainfall rate for the location for 0.01% of an average year (mm/h). If not provided, an estimate is obtained from Recommendation Recommendation ITU-R P.837. Some useful values: 0.25 mm/h : Drizzle 2.5 mm/h : Light rain 12.5 mm/h : Medium rain 25.0 mm/h : Heavy rain 50.0 mm/h : Downpour 100 mm/h : Tropical 150 mm/h : Monsoon tau (number, optional) – Polarization tilt angle relative to the horizontal (degrees) (tau = 45 deg for circular polarization). Default value is 45
Returns:	p – Percentage of time that the attenuation A is exceeded.
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.rain_event_count(lat, lon, d, f, el, A, tau=45, R001=None)[source]¶

Estimate the number of fade events exceeding attenuation ‘A’.

Estimate the number of fade events exceeding attenuation ‘A’ for 10 seconds or longer.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points d (number, sequence, or numpy.ndarray) – Path length [km] f (number) – Frequency of the link [GHz] el (sequence, or number) – Elevation angle (degrees) A (number) – Fade depth R001 (number, optional) – Point rainfall rate for the location for 0.01% of an average year (mm/h). If not provided, an estimate is obtained from Recommendation Recommendation ITU-R P.837. Some useful values: 0.25 mm/h : Drizzle 2.5 mm/h : Light rain 12.5 mm/h : Medium rain 25.0 mm/h : Heavy rain 50.0 mm/h : Downpour 100 mm/h : Tropical 150 mm/h : Monsoon tau (number, optional) – Polarization tilt angle relative to the horizontal (degrees) (tau = 45 deg for circular polarization). Default value is 45
Returns:	p – Percentage of time that the attenuation A is exceeded.
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.XPD_outage_clear_air(lat, lon, h_e, h_r, d, f, XPD_g, C0_I, XPIF=0)[source]¶

Estimate the probability of outage due to cross-polar discrimination.

Estimate the probability of outage due to cross-polar discrimination reduction due to clear-air effects, assuming that a target C0_I is required.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points h_e (number) – Emitter antenna height (above the sea level) [m] h_r (number) – Receiver antenna height (above the sea level) [m] d (number, sequence, or numpy.ndarray) – Distances between antennas [km] f (number) – Frequency of the link [GHz] XPD_g (number) – Manufacturer’s guaranteed minimum XPD at boresight for both the transmitting and receiving antennas [dB] C0_I (number) – Carrier-to-interference ratio for a reference BER [dB] XPIF (number, optional) – Laboratory-measured cross-polarization improvement factor that gives the difference in cross-polar isolation (XPI) at sufficiently large carrier-to-noise ratio (typically 35 dB) and at a specific BER for systems with and without cross polar interference canceler (XPIC). A typical value of XPIF is about 20 dB. Default value 0 dB (no XPIC) [dB]
Returns:	p_XP – Probability of outage due to clear-air cross-polarization
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en

itur.models.itu530.XPD_outage_precipitation(lat, lon, d, f, el, C0_I, tau=45, U0=15, XPIF=0)[source]¶

Estimate the probability of outage due to cross-polar discrimination.

Estimate the probability of outage due to cross-polar discrimination reduction due to precipitation effects, assuming that a target C0_I is required.

Parameters:	lat (number, sequence, or numpy.ndarray) – Latitudes of the receiver points lon (number, sequence, or numpy.ndarray) – Longitudes of the receiver points d (number, sequence, or numpy.ndarray) – Distances between antennas [km] f (number) – Frequency of the link [GHz] el (sequence, or number) – Elevation angle (degrees) C0_I (number) – Carrier-to-interference ratio for a reference BER [dB] tau (number, optional) – Polarization tilt angle relative to the horizontal (degrees) (tau = 45 deg for circular polarization). Default value is 45 U0 (number, optional) – Coefficient for the cumulative distribution of the co-polar attenuation (CPA) for rain. Default 15 dB. XPIF (number, optional) – Laboratory-measured cross-polarization improvement factor that gives the difference in cross-polar isolation (XPI) at sufficiently large carrier-to-noise ratio (typically 35 dB) and at a specific BER for systems with and without cross polar interference canceler (XPIC). A typical value of XPIF is about 20 dB. Default value 0 dB (no XPIC) [dB]
Returns:	p_XP – Probability of outage due to precipitation cross-polarization
Return type:	Quantity

References

[1] Propagation data and prediction methods required for the design of terrestrial line-of-sight systems: https://www.itu.int/rec/R-REC-P.530/en