- •Foreword
- •Policy on Intellectual Property Right (ipr)
- •A general purpose wide-range terrestrial propagation model in the frequency range 30 mHz to 50 gHz
- •Annex Wide-range propagation model Description of the calculation method
- •1 Introduction
- •1.1 Applicability
- •1.2 Reciprocity, and the designation of terminals
- •1.3 Iteration
- •1.4 Organization of the Recommendation
- •1.5 Style of description
- •2 Inputs
- •2.1 Terrain profile
- •2.2 Other inputs
- •Other inputs
- •2.3 Constants
- •Constants
- •2.4 Integral digital products
- •Digital products
- •3 Preliminary calculations
- •Principal parameters
- •3.1 Limited percentage times
- •3.2 Path length, intermediate points, and fraction over sea
- •3.3 Antenna altitudes and path inclination
- •3.4 Climatic parameters
- •3.4.1 Refractivity in the lowest 1 km
- •3.4.2 Refractivity in the lowest 65 m
- •3.4.3 Precipitation parameters
- •3.5 Effective Earth-radius geometry
- •3.6 Wavelength
- •3.7 Path classification and terminal horizon parameters
- •Case 1. Path is LoS
- •Case 2. Path is nLoS
- •Continue for both cases
- •3.8 Effective heights and path roughness parameter
- •3.9 Tropospheric-scatter path segments
- •3.10 Gaseous absorption on surface paths
- •3.11 Free-space basic transmission loss
- •3.12 Knife-edge diffraction loss
- •4 Obtaining predictions for the principal sub-models
- •5 Combining sub-model results
- •5.1 Combining sub-models 1 and 2
- •5.3 Combining sub-models within a Monte-Carlo simulator
- •Appendix a Diffraction loss a.1 Introduction
- •A.2 Spherical-Earth diffraction loss
- •A.3 First-term spherical-Earth diffraction loss
- •Start of calculation to be performed twice
- •A.4 Bullington diffraction loss for actual profile
- •Case 1. Path is LoS for effective Earth curvature not exceeded for p% time
- •Case 2. Path is nLoS for effective Earth curvature not exceeded for p% time
- •A.5 Bullington diffraction loss for a notional smooth profile
- •Case 1. Path is LoS for effective Earth radius exceeded for p% time
- •Case 2. Path is nLoS for effective Earth radius exceeded for p% time
- •Appendix b Clear-air enhancements and fading b.1 Introduction
- •B.2 Characterize multi-path activity
- •For LoS path:
- •For nLoS path:
- •B.3 Calculation of the notional zero-fade annual percentage time
- •B.4 Percentage time a given clear-air fade level is exceeded on a surface path
- •B.5 Percentage time a given clear-air fade level is exceeded on a troposcatter path
- •Appendix c Precipitation fading c.1 Introduction
- •C.2 Preliminary calculations
- •Probability distribution of rain height
- •C.3 Percentage time a given precipitation fade level is exceeded
- •C.4 Melting-layer model
- •Factor (abscissa) plotted against relative height h (ordinate)
- •C.5 Path-averaged multiplier
- •Example of path geometry in relation to melting layer slices
- •Appendix d Anomalous/layer-reflection model
- •D.1 Characterize the radio-climatic zones dominating the path
- •Radio-climatic zones
- •Large bodies of inland water
- •Large inland lake or wet-land areas
- •D.2 Point incidence of ducting
- •D.3 Site-shielding losses with respect to the anomalous propagation mechanism
- •D.4 Over-sea surface duct coupling corrections
- •D.5 Total coupling loss to the anomalous propagation mechanism
- •D.6 Angular-distance dependent loss
- •D.7 Distance and time-dependent loss
- •D.8 Basic transmission loss associated with ducting
- •Appendix e Troposcatter e.1 Introduction
- •E.2 Climatic classification
- •Climatic zones
- •Meteorological and atmospheric structure parameters
- •E.3 Calculation of troposcatter basic transmission loss
- •Appendix f Attenuation due to gaseous absorption f.1 Introduction
- •F.2 Gaseous absorption for surface path
- •F.3 Gaseous absorption for a troposcatter path
- •F.4 Gaseous absorption for terminal/common-volume troposcatter path
- •F.5 Water-vapour density in rain
- •F.6 Specific sea-level attenuations
- •Appendix g Sporadic-e propagation
- •G.1 Derivation of foEs
- •Conditions for setting p1 and p2
- •G.4 Basic transmission loss
- •Appendix h Great-circle path calculations h.1 Introduction
- •H.2 Path length and bearing
- •H.3 Calculation of intermediate path point
- •Appendix I Iterative procedure to invert a cumulative distribution function
- •I.1 Introduction
- •I.2 Iteration method
- •Stage 1: setting the search range
- •Stage 2: binary search
- •Appendix j Structure of the wide-range propagation model j.1 Introduction
- •J.2 Combining the sub-models
Annex Wide-range propagation model Description of the calculation method
1 Introduction
This Recommendation describes a radio-wave propagation method for terrestrial paths. It has a wide range of applicability in frequency, distance, and percentage time. In particular, it predicts both fading and enhancements of signal level. It is thus particularly suitable for Monte-Carlo simulations.
Appendix J describes the structure of the model, and in particular how results representing different propagation mechanisms are combined.
1.1 Applicability
The range of applicability is as follows:
Frequency: 30 MHz to 50 GHz.
Distance: The model is believed to be most accurate from about 3 km to 1 000 km. At shorter distances, the effect of clutter (buildings, trees, etc.) will tend to dominate unless the antenna heights are high enough to given an unobstructed path. There is no specific lower limit, although the path length must be greater than zero. A prediction of basic transmission loss less than 20 dB should be considered unreliable. Similarly, there is no specific maximum distance.
Percentage time: The method predicts the basic transmission loss not exceeded for a given percentage of an average year. Any percentage time can be used as an input to the model in the range 0% to 100%. This is limited in a progressive manner within the method such that the time used in the model varies from 0.00001% to 99.99999%. This internal limitation has no significant effect from 0.001% to 99.999% time.
1.2 Reciprocity, and the designation of terminals
The terms “transmitting antenna” and “receiving antenna”, or more briefly just “transmitter” and “receiver”, are used to distinguish the two terminals. This is convenient for the purposes of description.
The method, however, is symmetrical. Which terminal is designated the “transmitter” makes no difference to the result. By convention the “transmitter” is at the start of the terrain profile.
1.3 Iteration
Some parts of the method require iterative calculations. Explicit iteration procedures are described which have been found to be efficient and stable. However, these are not necessarily optimal. Other iterative methods can be used if they are shown to give very similar results.
1.4 Organization of the Recommendation
The inputs, and the symbols used to denote them, are described in § 2.
Preliminary calculations, including obtaining various radio-climatic parameters, are described in § 3. Climatic parameters, and values derived from the inputs, are listed in approximately alphabetical order of their symbols in Table 3.1. Many of these parameters are used in more than one place in the overall method, and all symbols in Table 3.1 are unique within this Recommendation.
Section 4 describes the four main sub-models into which the method is divided. The following subsections describe the calculation of these sub-models, most of which apply to a group of propagation mechanisms. These descriptions refer extensively to appendices which define various blocks of calculation. The sub-models in WRPM are independent of each other and each calculates results over the range 0% to 100%.
Section 5 describes how the final prediction is obtained by combining results from the four main sub‑models. The combination method takes account of the statistical correlation properties between the sub-models. Two alternative methods are given. One is appropriate when a direct calculation of the overall basic transmission loss is required for a given value of time percentage. This method involves an approximate treatment of uncorrelated statistics. The second method is appropriate when the wide-range propagation model (WRPM) is used within a Monte-Carlo simulator. In this case, the uncorrelated statistics can be modelled more accurately by combining the sub-models within the Monte-Carlo method.