3.2.2 Attenuation Computation and Measurenment
Attenuation prediction
Based on our literature review, rain attenuation may be calculated using the ITU-R or the manning model. It is important to note that these models have not been tested for frequencies higher than 40GHz, and might not work for the V/W band. However, data captured by this experiment could be used to modify or fine-tune these prediction models for lower frequencies. For water vapor and cloud liquid water, the most accurate model is believed to be the Liebe complex refractivity model. The ITU-R models will provide attenuation estimates for water vapor and clouds respectively. Both the Liebe and ITU-R models for gaseous absorption include the effects of oxygen with the water vapor attenuation.
Statistical correlation of different A(p) attenuation probability distributions may be modeled as total attenuation through summation of the individual attenuation values at a specific probability level. This relationship may be represented by Eq. 1, assuming that water vapor absorption is included in the gaseous attenuation production [1]:
3.2 Physical Models
Otherwise, when water vapor is considered separately, Eq. 2 better relates the atmospheric effects:
ITU-R P.618-9 determined that for systems operating at frequencies above about 18 GHz, and especially those operating with low elevation angles and/or margins, the effect of multiple sources of simultaneously occurring atmospheric attenuation must be considered.
Total attenuation (dB) represents the combined effect of rain, gas, clouds and scintillation and requires one or more of the following input parameters:
where p is the probability of the attenuation being exceeded in the range 50% to 0.001%.
A general method for calculating total attenuation for a given probability, ATOTAL (p), is given by Eq. 3 [2]:
Eq. 4 and Eq. 5 take into account of "the fact that a large part of the cloud attenuation and gaseous attenuation is already included in the rain attenuation prediction for time percentages below 1%" [2].
Attenuation computation for V/W band
A Direct Link Library (DLL) developed by the French Space Agency incorporates the main attenuation models. A sample Excel file provided by the French Space Agency was downloaded and adapted to the V/W band proposal. Some technical errors in the calculation of columnar content of liquid water and also the use of the Direct Link Library were corrected by Altech’s engineers. This tool is of importance during phase 1 to obtain theoretical predictions.
The library allows the calculation of the following values with Eq. 3:
- Atmospheric gases attenuation in dB (ITU-R P.676-8)
- Rain attenuation in dB (ITU-R P.618-9)
- Clouds attenuation in dB (ITU-R P. 840-4)
- Scintillation in dB (ITU-R P.618-9)
- Rain intensity in dB (ITU digital maps)
- Wet term of refraction co-index (ITU digital maps)
- Rain height (ITU digital maps)
- Total Columnar content (ITU digital maps)
- Water vapor content (ITU digital maps)
- Temperature (ITU digital maps)
Table 1 provides the total attenuation computation for 70 GHz to an earth station in South Florida from a geostationary satellite with a 100 west longitude. The library also provides tools for calculating the attenuation for both uplink and downlink, as well as the link budget.
TABLE 1. Atmospheric Propagation Losses for a sample Altech Earth Station in South Florida using Available Propagation Models (70GHz). Computed using the French Space Agency DDL
Based on the V/W-Band modulation described in [2] and sample values provided by the French Space Agency, Table 2 provides a sample link budget computed for the same Earth Station with the DDL. The values of Table 2 are nominal and do not consider interference, but this exemplifies a typical calculation that will be conducted during phase 1 in the design of the earth stations, beacons, and their location.
TABLE 2. Sample Link Budget Calculation for an Earth Station in South Florida using Available Propagation Models (70GHz). Computed using the French Space Agency DDL
Attenuation measurement
Combined attenuation can be measured at the earth stations, but it is difficult to differentiate the specific causes of attenuation when many atmospheric effects interact simultaneously. Our approach is to place earth station in geographic locations that:
- Address correlation issues among different attenuation effects
- Provide contrast and variety of sampled data
- Ideally already collect meteorological data
Based on these criteria, useful data collection depends on the diversity of geographic locations chosen for the ground stations, but also on the certainty that individual measurements can be attributed to a single atmospheric effect. The following approaches can be applied to fog, clouds, and scintillation, but an example is given for rain.
Multiple locations, local data correlation approach:
Rain attenuation example:
Attenuation measurements during a clear day (data set 1)
Attenuation measurements during rain (data set 2)
Meteorological conditions during a clear day (data set 3)
Meteorological conditions during rain (data set 4)
In this case, the most valuable data exists when the data sets 2 and 3 are the closest to each other. If those two sets are constant, including temperature, pressure and humidity, then it is expected that scintillation and gas absorption effects are similar for the two sample sets. However, in the same location during a short interval of time, humidity, pressure, and temperature are likely to change in the event of a rain. Thus, during short periods of time:
- Scintillation is likely to change during rain because humidity and temperature change
- Gas absorption is likely to change because humidity increases
- Cloud attenuation is likely to change because of different cloud formations
According to our literature review, rain attenuation tends to be an order of magnitude larger than other attenuation effects. Therefore, even though it is no possible to differentiate among the specific causes of attenuation, rain attenuation will account for most of the attenuation during rain leading to four outcomes:
- Approximate rain attenuation measurement
- Unknown fluctuation of scintillation and gas absorption attenuation
- Worse case attenuation scenarios measurements
- Evaluation of current attenuation prediction models
Multiple locations, global data correlation approach:
The idea of this approach is to use different georprahic locations for which rain happens at similar humidity, pressure, and temperature. However, a detailed study of historical meteorological data is proposed to determine the feasibility of this approach. In this approach, the following outcomes are expected:
- More accurate approximate rain attenuation
- Known approximate fluctuation of scintillation and gas absorption attenuation combined
- Worse case attenuation scenarios
- Evaluation of current attenuation prediction models
Multiple locations, local correlation approach, different seasons:
The idea of this approach is to use the same geographic locations for which rain happens at similar humidity, pressure, and temperature during different seasons. However, a detailed study of historical meteorological data is proposed to determine the feasibility of this approach.
Weather data collection
Collect distributions of weather data for absolute humidity, cloud liquid water, and rain rate.
Absolute humidity:
"There are many climatic databases available that provide daily or even hourly long-term records of local temperature and humidity values. Often, such data can be found on World Wide Web sites. The data can be compiled to create long term distributions of local values. Another possible source is ITU-R Recommendation P.836-1. The recommendation provides global maps of surface and integrated water vapor content for various percentages of time. The disadvantage of the ITUR maps is that not all locations are based on local measurements. Also, the time percentages for which maps are provided are spaced rather widely. Estimating water vapor for other percentages of time requires an interpolation" [1].
Cloud liquid distributions:
"One possibility is to use radiosonde. Several empirical detection algorithms are available to estimate the amount of cloud liquid water present along a vertical path from a single radiosonde sounding. Radiosonde data is available in many parts of the world and is relatively inexpensive. A second possible source of cloud liquid water data comes from ITU-R Recommendation P.840-2. Like the ITU-R recommendation for water vapor, P.840 provides global maps of cloud liquid water for various percentages of time" [1].
Rain rate:
"Rain rate data is the most difficult to obtain. The two primary sources are the Crane global rain maps and the maps provided in ITU-R Recommendation P.837-1. Both maps divide the world into climatic regions. Each region has its own unique rain rate distributions assigned to it. Accuracy will be increased if we take detailed rain rate measurements at our Earth Stations. The European Space Agency has recently published a third set of rain maps. These maps are based on global remote sensing data. They divide the world into 1.5° latitude by 1.5° longitude grid squares. Each grid square has its own unique rain rate distribution" [1].
References
[1] Ippolito, L, “Propagation Effects Handbook for Satellite Systems Design,” Stanford Telecom ACS, prepared for Jet Propulsion Laboratory, Pasadena, CA, 1998.
[2] ITU-R, "Propagation data and prediction methods required for the design of Earth-space telecommunication systems", Recommendations and Reports of the ITU-R, Report P.618-10-2, International Telecommunications Union, Geneva, Switzerland, 2009.
[3] Sacchi, C.; Musso, M.; Gera, G.; Regazzoni, C.; De Natale, F.G.B.; Jebril, A.; Ruggieri, M.; , "An efficient carrier recovery scheme for high-bit-rate W-band satellite communication systems," Aerospace Conference, 2005 IEEE , vol., no., pp.1379-1390, 5-12 March 2005