Development of rain-attenuation and rain-rate maps ...

DeveIopment of Rain-Attenuation and Rain-Rate Maps for Satellite System Design in the Ku and Ka Bands in Colombia L. D. Emiliani'z2,J. Agudelo', E. Gutierrez', J. Restrepo', and C. Fradique-Mendez3 'Informatics and Telecommunications Research Group - GlDATl Universidad Pontificia Bolivariana Circ. l a No. 70-01, Medellin, Colombia Tel: 57-4-41 59086; E-mail: [email protected]; [email protected]; [email protected]; [email protected] 'Currently: Orbitel S.A. Medellin, Colombia E-mail: [email protected] 3Circulo d e Estrategia S.A.

Calle 73 #IO-IO. Ofc.402. Medellin, Colombia Tel: 57-4-21 74641 ; E-mail: [email protected]

Abstract

The predictions of rain rate and rain attenuation are the most important steps when analyzing a satellite link operating in the Ku and Ka bands. It can be a time-consuming process, especially when the analyses are made on a large number of sites. as might be the case with the broadband satellite systems of today. In this paper, tools for the prediction of rain rate and rain attenuation are given in the form of contour maps for a tropical region (Colombia). The maps presented use the rain rate predicted by different methodologies, and the attenuation caused by these rain rates, using ITU recommendations. The information from these maps can then be entered into attenuation-prediction or system-planning tools. Additionally, a review of the results of the most important rain-rate and rain-attenuation campaigns is presented. Keywords: Communication system planning; microwave radio propagation meteorological factors; microwave propagation; millimeter wave radio propagation meteorological factors; millimeter wave propagation; propagation; rain; satellite communication

1. Introduction

modeling a behavior that is statistical in nature, considering several variables, such as rain height (the maximum height where rain is found in the liquid state under average conditions), rain rate (the amount of rain per unit time), and Earth-station latitude and longitude.

T

he presence of rain in the transmission path is the main cause for microwave system degradation, particularly when operating at frequencies above 10 GHz. Raindrops absorb and scatter radio waves, resulting in signal attenuation and in reduction of the overall system availability and performance. Several methodologies exist for the prediction of rain attenuation on microwave paths. These methodologies can he grouped in two classes: empirical methodologies, based on measurement databases from stations in different climatic zones within a given region; and physical models, anempting to reproduce the physical behavior involved in the attenuation process. As pointed out in [I], oftentimes, when a physical approach is used, not all inputs required for the analysis of the process are available. Therefore, the most used group of methodologies is the empirical group. Models belonging to this category contain a set of equations 54

ISSN 1045.924312004120 02W4 IEEE

Inputs to measurement databases are provided by administrations, meteorological and environmental agencies, universities,and independent researchers. These consist of rain-rate measurements restricted to one to five minutes integration time' - and rainattenuation measurements. Rain-rate measurements are generally performed using tipping-bucket rain gauges, and rain-attenuation measurements can be made using radiometers,beacon receivers, or ~

'Rain rates obtained through longer periods of inteption might fail to capture a high-intensity short-duration rain event, and are not recommended for communication-system design.

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Eb,”o [bit enerW--to-noise-densityratio] data from an active sation [2].

The most important issue that exists today affecting the empirical models is certainly that not enough information exists in propagation-measurement databases to allow for the complete modeling of the attenuation phenomenon throughout all the different climatic regions, worldwide. Therefore, researchers use proxy procedures to till voids in sites for which data are unavailable. Examples of these are the ITU model and the Crane Global Climatic model for rain-rate prediction. The lack of rain-measurement data from tropical regions for verification or for modeling purposes causes predictions obtained from existing models to deviate from real measurements. Only a few tropical countries in the world have submitted rain and attenuation measurements to ITU study groups for inclusion in the world database. Examples are the administration of Brazil, a regular contributor to ITU study group 3-M, and research conducted in Singapore and Indonesia. However, these submissions are not sufficient to reduce the uncertainty that exists when a system designer uses a prediction method to estimate rain margins in other tropical countries. As can be seen from research efforts in the European Space Agency (ARTES 1 1B.002 Tender) [3], the need for more data from tropical zones continues to be one of the most important issues in propagation modeling today. A very important effort towards gathering more information, developed jointly by the United States and Japan, is the Tropical Rain Measurement Mission (see http://mnm.gsfc.nasa.gov). The data available fmm this mission, however, can not be directly employed in system design, due to its long integration time. Another source of long-integration-time rain measurements is the Global Precipitation Climatology Project (CPCP: http://cics.umd.edul-yin/CPCPOof the World Climate Research Programme (WCRP). From a services point of view, nowadays the need for satellite broadband services - IF’ services, Intemet access, tele-medicine, tele-education - is high, and so is the pressure for low monthly service rates. To achieve a low service rate, several objectives must be met: first, low terminal cost;.second, low space segment costs (U$/MHz); and third, a low value of power-equivalent bandwidth. This is where the determination of proper link margins comes into play. The power-equivalent bandwidth (PEB) is a concept by which a space-segment provider determines the share of high-power amplifier power consumption of a specific link, and associates it with a normalized reference carrier for which a hypothetical bandwidth can he calculated. Should the reference bandwidth he larger that the actual usage, an overcharge is normally observed. Therefore, a direct relationship exists between the fading margins of the system and the equivalent bandwidth needed. If a “wong” combination of rain prediction and rainattenuation models is used, a potential over-cost appears, due to the excess power determined from the link-analysis process (a high power-equivalent bandwidth value), leading to larger antenna sizes and also to a higher-than-necessary monthly service charge. Besides pure power compensation, rain margins can also be dealt with via more redundant coding in the terminals. This approach lowers the Eb/No required to achieve the objective bit-error rate (BER), helping to reduce the power specification for a given rain scenario at the expense of higher bandwidth consumption. A downside of this is that increasing the complexity of the VSAT [very small aperture terminal] indoor unit (IDU) also increases the terminal’s price. The Earth segment is therefore also affected by the election of the rain-rate and attenuation prediction methods (both in the RF front-end and the indoor equipment for baseband 56

processing), because the price of the terminal and additional equipment needed can adversely affect the project. In all cases, a potential for over-cost appears, both in initial expenses (investment) and in periodic expenses (space-segment charges). Conversely, an inaccurate prediction model can also lead to underestimating the effect of rain on the links, severely impacting end users as a result of lower-than-expected availability. The severity of the impact on a service depends on the criticality of the applications being utilized by underlying end usen. Residential users accessing the Intemet may be more permissive lhan users of mission-critical applications, such as tele-medicine or tele-education, which normally cannot be rescheduled without impacting the community. As can be seen, the issue of a proper rain margin is very sensitive and, as such, it has been addressed by several researchers all over the world. The focus of this paper is to give system designers additional tools, in the form of contour maps of rain intensity and rain attenuation, for the design of satellite systems in tropical countries and particularly in Colombia, perhaps the most active satellite market in Latin America, excluding Brazil. These tools can be used for satellite-payload design (ERP estimation, satellite-coverage analysis), and Earth-terminal and Earth-segment design. The applicability of these tools is not limited to local systems in Colombia, but to regional and hemispherical broadband access systems. Rain-rate and rain-attenuation maps for the counhy of Colombia were developed using methodologies proposed by ITU (P 837-4), P. N. Rice and N. Holmberg [4], and J. Chebil [SI for the estimation of point rainfall rate, and ITU’s P-618-8 rainattenuation prediction method [6].Both sets of maps (ITU rain and attenuation and Rice-Holmberg and Chebil rain and ITU attenuation) will be given for comparison. The task of developing contour maps of rain rate and attenuation has been conducted before for the USA [SI, Europe [S-lo], Malaysia [SI, andNigeria [SI, and on a global scale by [6, 11, 121.

2. A Review of Previous Work in the Field of Rain-Attenuation and Rain-Rate Model Development and Comparison As mentioned before, several methodologies exist for the prediction of rain rate and rain attenuation. Together with the development of these models, several measurement campaigns have been conducted, with the objective of determining the best performing model for a given geographical zone.

This section reviews some of the most important models developed and the most important campaigns conducted, and their results.

2.1 Rain-Rate Prediction Models The point rain rate is the rain rate measured at a point using a single rain gauge, as opposed to being measured over the full

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length of the link. A procedure for the calculation of a cumulative rain-attenuation distribution from a point rain-rate distribution is therefore required if predictions are to he made.

that it is able to determine the cumulative distribution based on long-integration-timedata. This fact led us to the use of the model for our analysis of the rain-rate distributions in Colombia.

Several models exist that provide an estimation of the pointrainfall-rate cumulative distribution. Perhaps the most widely known (and adopted by the industry) are Crane’s Global Climatic Model, developed in 1980 and revised in 1996 [12], and the ITU P-837 recommendation [7], originally developed under the CCIR in 1974, and now in its fourth revision under ITL-R. Both models -Crane’s Global and the ITU P.387 - were developed using databases of measurements from various zones in the world, the limit being the number of station-years of measurements available and their integration time. Not all climatic measurement stations fulfilled the one-minute integration time requirement, and this, of course, limited the availability of data for consideration in the development of these climatic models.

As explained in the previous paragraphs and shown in Equations (1) to (3), the Rice-Holmberg model requires several data for the calculation of the cumulative distribution function of rain. The data required to calculate the model’s parameters - and specifically, the thunderstorm ratio - are not always readily available from local weather agencies. The use of J. Chebil’s model [5] appears suitable as an alternative to the sites where thunderstorm occurrence data were unavailable. This model is exemplified by the following expression:

The models attempt to characterize the world within given zones or isopleths of rain rate (isohyets). These curves become more precise as more data are available when the model is developed. For instance, consider the tropical section of South America. Crane’s Global model encompasses in one zone, zone H, the climatic behavior of this large area, characterizing it with the same value of rain rate occurring in 0.01% of a typical year (209.7 “ m r ) [12]. Although useful for system calculations, there is always doubt regarding the accuracy of this value. The ITU model goes further, characterizing the zone with three isohyets: 80 “ihr,100 “/hr, and 120 m h r [6]. Notice the difference between the estimations obtained with both models: 100%. Another approach ‘for obtaining rain-rate values for use in fading calculations is Rice-Holmberg’s model, R-H [4]. This model was developed in 1973 by N. Holmberg and P. Rice, after an analysis performed on measurements fiom stations inside and outside the US, including cumulative distributions of rain, maximum monthly rainfall accumulation,and a map of the highest rates expected in a two-year period. The result of the study, an empirical approach, is a methodology to obtain a point rain-rate Cumulative distribution based on a set of parameters obtained from the analysis of local rain-accumulation data. Parameter number one, U, is the number of thunderstorm days expected in an average year. Parameter number two is M , , the highest monthly precipitation observed in a set, and M is the average annual accumulation. Values of U and M,,, must he averaged over a 30-year period. These are combined in a set of equations, resulting in the probability that a rain rate, R [mmJhr], with an integration time of one minute, is exceeded

P(r>R)=-{0.03,L-o.03R M

where a = 12.2903, p = 0.2973, and M is the average annual precipitation. J. Chebil’s model was verified against data from several tropical localities, including Malaysia, Indonesia, Brazil, Singapore, and Vietnam [ 5 ] , resulting in the best estimate of measured data. Several comparison campaigns have been conducted in an effort to improve existing models and to compare and determine the best-performing model. Comparisons performed at the Communications Research Center of Canada (CRC) and presented at the 2002 URSI General Assembly [I31 indicated that, for locations on Canada’s pacific coast, the average error between measurements and predictions was as large as 73%, using ITU-R P-837 for the rain rate exceeded 0.01% of an average year. The minimum error was found to be 5% for locations in central Canada. Similar comparisons developed in Norway in 2001 [14] indicated that for rain rates of 20 “ / h r (corresponding to 0.04% of the time) and higher, the ITU-R model predicted rain rates 50% higher than those measured. For tropical zones, a comparison performed with two years of data from terrestrial links in Brazil [I51 concluded that the rain maps issued by ITU underestimated the rain rate cumulative distribution function. Older comparisons (1993) in Singapore [I61 indicated that the ITU model over-predicted the measured mean by 24% at 0.01% of the time [it has to be said that ITU’s model has changed over time; nowadays, the result is about 8%]. The ACTS campaign results on rain-rate measurements and model comparisons [17] indicated that for the ACTS propagation terminal (APT) in New Mexico, the ITU model (P837-3) was the best fit to the measured data. A comparison using fewer years of measurements [18] indicated that the three models evaluated Crane, ITU, and R-H - did not perform well in predicting the attenuation distributions collected by the ACTS propagation experiment. The results of the five stations analyzed in the paper differed in terms of the best-performing model. ~

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2.2 Attenuation-Prediction Models Together with rain-rate measnrement campaigus, it is also necessaly to obtain measurements of the attenuation experienced by signals, in order to compare these data with the results of the existing prediction models. It has been acknowledged [ I l l that the Rice-Holmberg method overestimates rain rates in the high-availability range (0.01%), and underestimates in the range between 0.1% to 1%. Even though the model is old, the fact that its results are based on local data makes it an alternative to consider, as was pointed out in [2]. An advantage of the Rice-Holmberg methodology is the fact 58

If number of participating countries and scientists is considered, the most important campaigns are the ACTS campaign (finished in 2000), the OPEX initiative using the Olympus satellite, and the European COST actions 255 (finished in 1999, final results published in 2002) and 280 (active). The 1TU is also involved in

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Table 1. The results of the model evaluation performed by the ITU 1191. Model

I

DHA ITU-R 618-5 ExCell

II

I1nn.n

Rank Full Frequency Range I 15-35 GHz 1 I 2 2 3 3 8

!I

A

5

Brazil CCIR Leitao-Watson Misme-Waldteufel Two-Components

The results of the ACTS and OPEX campaigns and of the COST initiatives include an analysis of the deviation of the predictions with respect to the measurements, a "rank" of the bestperforming models (usually constructed by means of the error variable used to measure the deviation between predictions and measurements), followed by a recommendation regarding which models to use, given the climatic behavior of the regions under evaluation. Table 1 compiles the results of the comparison developed by the ITU within the framework of Study Group 3.

I

6 7 4 10 9

5

6 7 8 9

In 1997, G. Feldhake and L. Ailes-Sengers [20] found that the errors in the models were around 30% to 40%. For this comparison, they used 21 station years of ACTS propagation data. The previously mentioned analysis for the New Mexico ACTS propagation terminal indicated that the Excell attenuation model performed consistently better than the other models compared (ITU 618-5, DHA, Crane Global) but, in general, all models performed equally well in high-attenuation conditions. This comparison included a correction to the data set due to the wet-antenna effect'. Table2 summarizes the comparison developed for an ACTS propagation terminal in Tampa, Florida, employing five years of ACTS data.

Table 2. Results of the comparison developed using five-year data from an APT in Tampa, Florida 1211.

I

Rank Model

ACTS

I

to-space and point-to-point propagation, dealing with the issues of rain attenuation,among others.

ACTS

ACTS also installed propagation terminals in South America, and more precisely in Quito, Ecuador, and Bogota, Colombia. These two terminals were located in the Andean region, at a height above 2600111 above sea level (masl). These two stations are important, not only because they represent contributions from a tropical zone, hut also because of the height at which they were installed3. The results of the campaign conducted in these stations showed that no model performed satisfactorily. However, for a very small range, between 0.1% and 0.2%, Crane's two-component-model predictions were in good agreement with measurements, as shown in [22]. Table 3 summarizes the results of the Olympus satellite-propagationexperimenters group (OPEX).

Table 3. A summary of the results obtained in the OLYMPUS program [23).

Included in Table 4 are the results of the comparison developed in Colombia [24], using data from a verysmall-:iperture terminal (VSAT) located in Medellin (6.2"N, 76.4"W, 1650 masl).

Table 4. The results of the comparisons developed in Colombia 1241. The comparison was based on the error variable as defined in 1251. The table values are attenuation data for 12.6 GHz, for each of the three 0.01% rain models.

3. Rain-Rate and Attenuation Contour Maps: ITU Models Before presenting the rain-rate and rain-attenuation maps, it

Attenuation Model Garcia-Hemando Leitao-Watson ITU-R 618-6 Crane 2C Pontes-DaSilva Crane Global Flavin

_ _

Rain Model

I

C. Global I ITU-R 0.584

I

-0.167

is important that the reader know more about Colombian geoma-

I Rice-Holmher I -0.097

phy. Figure 1 is a topographic map of Colombia, showing the most important climatic zones of the country. The northem area includes a large desert area (Guajira), with an annual average rain accumulation of less than 500 mm. The Caribbean coast (north) and the

-0.093 0.256 0.660

4.135 0.605 0.202 n 679

the matter by promoting participation of all member countries with data for the databases and model evaluations and development, usually within the frame of each of the Study Groups' (SGs') meetings. Study Group 3 is in charge of radiowave propagation, and Study Group 3M is devoted specifically to the area of Earth-

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'The wet-antenna effect refers to the fact that water accumulated in the reflector of an antenna causes attenuation in addition to that of the rain itself. Therefore, measurements should be corrected to isolate falling rain from accumulated water. 'Most of the contributions from tropical regions come from stations at or near sea level. This fact adds to the uncertainty in the applicability of the prediction models to stations located simultaneouslyin tropical rain zones and in elevated places.

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pacific coast (west) are areas with annual accumulations of 10002000 nun and 4000 nun, respectively. The central mountainous area corresponds to the Andean Cordillera, with an average accumulation of 800-2000 mm. The eastem part of the country is an area of plains, with an average accumulation of 1000-3000 mm, and the south-east of the country belongs to the Amazonian rain forest, with an average accumulation of 4000 nun. The map also shows the location of small desert areas, which represent “discontinuities” in the isohyets of the climatic models. Recommendations ITU-R P837-4, P838-1, P839-3, and P618-8, combined, depicted a methodology for the prediction of a fading margin for a given probability of exceedance. We will now proceed to a brief description of the ITU model, and the approach used by the authors to obtain the necessary data to draw up the contour maps.

3.1 Rain-Rate Contour Map Using ITU P-8374 This method involves the use of a database of parameters (P,6,M , , and M , ), available from ITU’s 3M Group Web site [26], each of which is matched to a (latitude, longitude) pair. MATLAB scripts, associated with the implementation of the model, are available on ITU’s 3M Group Web site. Using these scripts, the calculation of the cumulative distribution function for rain rate is simple. The user needs only to input the probability of exceedance value, and the latitude and longitude of the Earth station under analysis. The results of the process are shown in Figure 2, a rainintensity map developed using a probability of exceedance objective of 0.01%. The contour map in Figure 2 agreed with the isopleths displayed in the recommendation, and gives more detail to system designers. The map was developed according to ITU’s recommendations for interpolation between rain-rate values contained in the matrices part of the recommendation.

3.2 Attenuation Contour Maps Using ITU P.618-8

To develop the map of rain attenuation, and because of the lack of a topographic database of Colombia in electronic format, a database of over 8000 locations of meteorological measurement stations was used. This information was obtained from IDEAM, Colombia’s meteorological and environmental agency. The database consisted of the latitude, longitude, and height of the station, values used as the inputs for the ITU P.618-8 attenuation model. Additional information used to draw the maps was: * Frequency of operation: The center of the band for the Ku- and

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because it corresponds to the position of one of the satellites used to provide telecommunications services in rural and remote areas of the country (the COMPARTEL Program, with more than 10,000 very small aperture terminals countrywide: http://www.compartel.gov.co).

-

Rain rate: As obtained from the ITU P.838-4 method, considering station coordinates and height.

Considering a typical very small aperture (VSAT) service monthly unavailability objective (OS%), and using the ITU worst month average year conversion model, an average-ysar propagation objective of 0.1% was obtained. Figure 3 shows the contour maps for attenuation in Colombia for a 0.1% availability objective for the Ku-band downlink frequency. Figure 4 is the attenuation contour map for the Ka-band downlink center frequency. Figures 3 and 4, and the subsequent rain-attenuation maps included in this paper, were developed for downlink frequenciesbecause the use of an uplink power-control (UPC) device to compensate for fades in the uplink is common today in these types of networks, and therefore the need is for information on the downlink. The attenuation contour maps of Figures 3 and 4 were consistent with the expected results of an attenuation model: a lower value of attenuation with increasing station height. An additional factor contributing to the use of the ITU rainattenuation prediction model in the development of these maps was pointed out in [24], where it was shown that predictions obtained from the ITU model were close to the average prediction of a set of results obtained from the application of eight different methodologies.

4. Development of Rain-Rate and Rain-Attenuation Contour Maps Using Local Climatological Data With the objective of providing additional information on rain rates for tropical zones and, in OUT particular case, for Colombia - we proceeded to gather all the necessary information in order to apply the models proposed by [4] and [SI, using local climatological data. After a review of the number of active measurement stations in the country, the number of years of data per station (at least 30 years of data per station are required for the Rice-Holmberg model), and the locations of the stations (in order to have data for several regions of OUT geography), we obtained the information displayed in Table 5 , indicating the availability of thunJ,rstonii-occuTTcnce information and awragc munthly rain a.cu~nulaiion for 42 >lies in Colombia The informstion in Tnblc 5 was useful in considering the parameters needed for the application of the Rice-Holmherg and J. Chebil methodologies. Based on the data gathered, the parameters U (average number of thunderstorms), M (average annual accumulation), and M , (average monthly accumulation) could be obtained. This information is shown in Table 6 . ~

The attenuation-prediction modeling consists of the application of three methodologies: first, the calculation of the specific attenuation [27]; second, the calculation of rain height [28]; and third, the attenuation-calculation methodology. The attenuation calculation is presented in the Appendix. For the other two parts of the model, the reader is asked to go to the ITU recommendations.

Ka-band downlinks (12.675 GHz and 19.45 GHz, respectively).

* Satellite orbital position: 304.5” East. This value was used

~~~~~~

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After application of the methodologies described in Equations (1) to (4) (the Rice-Holmberg and Chebil models), using the set of local climatological parameters in Table 6 , the results of Table 7 were obtained. Using the rain-rate values in Table 7 as

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Table 5. A description of the data that were available and used (AMA average monthly accumulation; Th: average number of thunderstorms per year, 1974-1978).

Table 6. The parameters required for the application of the J. Chebil and Rice-Holmberg models. The absence of data (-) is due to the lack of information required to obtain such a parameter.

Buenaventura 1011.6 4789.4 3691.5 1407.0

Cdcuta Florencia Ipiales La CNZ Leticia L l a r d e Palmas Manizales Medellin MiM

input, the rain-rate contour map of Figure 5 was developed. The contour lines of Figure 5 were developed using the inversedistance method. The triangles in the map represent the locations of the stations from which the data was obtained. The results appeared to be very close to those obtained using the ITU model. A higher rain rate was shown in some regions, such as the Amazonian region (in the south-west), which is expected because this area is characterized by rain forests. However, due to the lack of measurement stations in the area, there was a high level of uncertainty in the interpolation of the local data. The northern area of the country showed lower values of rain rate and the contour lines covered a larger area. Lower rain rates were due to the annual and 64

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Quibdi, Riohacha Rionegro San andres San Jose del Guaviare I Santa Elena I Santa Marta I Tumaco Valledu ar [clej; Villavicencio Ya ara Yo a1

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8032.6 546.0 1844.5 1899.8 2504.7 2729.7 506.1 1116.1 2291.8 968.4 4352.5 1644.3 2309.5

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24 54 58

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400.1

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2030

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monthly accumulation values of stations in this region. It can be^ concluded that the differences obtained in the rain-rate contours were not large, and therefore both maps can be used for system planning. The rain-rate values of each contour line were then applied to the ITU P.618-8 model, and the maps of Figures 6 and 7 were obtained. The attenuation contour maps were developed for two frequency hands, Ku and Ka, considering today’s active satellite broadband networks and the efforts currently on course to develop broadband Internet access systems in Ka band. Future systems are planned to be deployed at Ka-band rather than Ku-hand frequen-

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cies, due to the bandwidth requirements of the applications they are expected to support. Ka hand is also being considered for these types of systems because of the interference that Ku-band broadband systems employing small dishes would experience from terminals operating on adjacent satellites, and because Ka-band regulations require lower levels of adjacent-satellite interference, enabled by higher frequencies. Also, Ka-band frequencies allow for a higher return-link data rate. A discussion of the results follows. Comparing the results obtained using the ITU methodologies and the combined Rice-Holmberg-Chehil rain rates and ITU rain attenuation, we observed a difference in both tbe Ku- and Ka-band predicted attenuation values. For Ku hand, the difference in the southem part of Colombia (the Amazonian region) was 1 dB, due to the higher rain rates obtained by processing local data. Predictions in the northern area of the country were higher using ITU’s models than those obtained using the local data set. The 6 dB and 4 dB contours were larger in the attenuation map with local rain data than were those on the ITU map. The Ka-band results were consistent with this, being larger in the east and west and inferior in the north. The results of the ITU prediction in the eastern area of Colombia were 4 dB lower compared to the results of the prediction using local data. This is a region characterized by rain forests and plains. For Ka frequencies, the center of the country showed no major differences, and the western part, towards the pacific coast, showed a region of 20 dB more localized than that of the ITU map, and also a small region of 22 dB. The magnitude of the difference in Ku-band predictions was of the order of 1 dB, on average. The difference between predictions in Ka band was ahout 2 dB, hut could be as large as 4 dB in some areas of the southern part of the country. Systems designers need to he aware of these differences, because they represent an uncertainty in the design of each link. This uncertainty might result in either an over-cost, due to higher-than-required power amplifiers (in some areas, effectively doubling the power of the high-power amplifier), larger antennas, or additional space segment (redundant coding); or in lower service availability, affecting the quality of service for the end users, specially in sensitive services such as tele-education and tele-medicine.

the applicability (or lack thereof) of the ITU recommendations to tropical zones, more measurement stations have to he deployed, and those stations should comply with the recommendations regarding sample time.

5. Conclusions A review of the results of some of the most important rainrate and rain-attenuation measurement campaigns has been presented. The main conclusion that can he drawn from these campaigns is that the average deviation between models and measure-

Table 7. A comparison of the &,ol% valuesobtained with the Riee-Holmberg (RH),Chebil, and ITU P837-4models. All quantities are in mmlhr.

I

Station

1

e : :

1

Chehil Rate

I

ITU Rate

1

I

Although the maps show contours for locations outside the borders of the country, since the data used to generate the maps were restricted to locations inside the country, the values shown on the contour lines should not he used for locations outside Colombia. Figure 8 displays the differences between ITU predictions and predictions obtained using the Rice-Holmherg and Chehil’s models. Based on these differences between rain-rate predictions, the attenuation-prediction results can be understood. Figure 9 illustrates the differences between Ku-hand rain-attenuation predictions, due to the difference in rain rates obtained using ITU P.837-4 and the results of the Rice-Holmherg and Chebil methodologies mentioned in the previous comparative analysis. Figure 10 illustrates the differences between Ka-band rain-attenuation predictions. At this point, the results from the comparisons presented can not he interpreted as a definitive conclusion regarding the applicability of the ITU model to tropical zones. As mentioned before, both models used for the development of the maps using local information represent an altemative to the use of other models of a global nature, because of their explicit use of local climatological factors, such as thunderstorm occurrences (U) and maximum monthly accumulations (M,). In order to draw conclusions about /E€€ AntennasandPrapagation Magazine, Vol. 46, No. 6, December 2004


65

ments is around 30%, and that none of the models performs equally well in all climatic zones of the world. Therefore, a global model always runs the risk of overestimating or underestimating the phenomenon. It has to he noted that the statistical nature of the rain phenomenon and the inherited statistical behavior of the attenuation phenomenon are such that the variability between yearly cumulative functions (measured via comparison of equi-probable values in empirical cumulative distribution functions for each year) and between seasons (measured via comparison of equi-probable values from empirical cumulative distribution h c t i o n s for different seasons, i.e., summer-to-fall or spring-to-summer,as in temperate zones, or rainy and dry seasons, as in tropical zones) is comparable to the deviation between predictions and measuremenis, therefore putting all models at the same order of precision. This uncertainty is reduced by the analysis of long-term data sets (>lo years) and by comparisons including the expected variability based on what is observed. The year-to-year variability for rain is around 30%, as reported in the final report of COST Action 255. Rain-rate and rain-attenuation contour maps were developed for Colombia for rain-rate statistics for 0.01% of the time and attenuation for 0.1% of the time, a typical very small aperture terminal (VSAT) network service-availability objective. The information provided in the maps is very useful for preliminw system design, both for rural telecommunications systems in Colombia (most of which use satellite networks as a technological platform) and for regional or hemispherical VSAT broadband-access initiatives, such as those currently operational and promoted by satellite operators such as Intelsat, SES Americom, Eutelsat, Telesat, 'Andesat, Hughes (Spaceway), and Inmarsat (B-GAN). The results of the analysis performed to obtain the oneminute rain-rate contour maps using ITU-R predictions show that the results are comparable in magnitude with the values obtained by the other methodologies used in this paper, even though differences exist for some locations. The differences in rain rates predicted by the models employed in this paper result in differences in rain-attenuation margins. This fact points out the over-cost mentioned in the introduction of the paper: it is necessary to compensate for the dl3 difference in predictions via RF modifications (larger antennas, larger amplifiers), or to reduce service availability These modifications in the terminals are reflected in the service price. The question of the precision of the predictions obtained with each of the models used remains to be answered. However, comparisons cannot he made at this time, due to the lack of measuring stations fulfilling the integration-time restriction in Colombia.

9:

latitude of the Earth station [degrees]

f

frequency [GHz]

Re:

effective radius of the Earth (8,500 km)

Procedure: Step 1. Calculate the rain height, hk [27]. Step 2. For a given 0 , compute the slant-path length, Ls , below the rain height from

Step 3. Calculate the horizontal projection, LG, of the slantpath length from

(8)

LG=Lscose.

Step 4. Obtain the rainfall rate, exceeded for 0.01% of an average year (with an integration time of one minute). If this long-term statistic cannot he obtained from local data sources, an estimate can be obtained from the maps of rainfall rate given in 171. Step 5. Obtain the specific attenuation, yR , using the frequencydependent coefficients given in [26] and the rainfall rate, &,ol, determined from Step 4, by using

Step 6. Calculate the horizontal reduction factor, rn,ol,for 0.01% of the time:

Step 7. Calculate the vertical adjustment factor, the time:

6. Appendix: Calculation of Rain Attenuation According to ITU P618-8

Y ~ . for ~ 0.01% ~ ,

of

(11)

Input parameters:

&.,, h, :

:

point rainfall rate for the location for 0.01% of an average year [mmh]

if IpI < 36",

x = 36-14

else

height above mean sea level of the Earth station [kml

e: 66

elevation angle [degrees] IEEfi AntennasandPropagation Magazine, Vol. 46, No. 6 , December 2004


7. I'fU-R, "Ch3ractcrisiir~of Prccipiration for Propaption hlodcling." Recommendation P.837-4, IT['-K Rscommcndarions, P Series, Geneva. International Tcleconimunications L'ni~iii,2001

Step 8. The effective path length is LE

= LRvO.Ol

(13)

'

Step 9. The predicted attenuation exceeded for 0.01% of an average year is obtained from 4.01

=YRLE.

(14)

Step 10. The estimated attenuation to be exceeded for other percentages of an average year, in the range 0.001% to 5%, is determined from the attenuation to be exceeded for 0.01% for an average year:

8. E. J . Dutton, ".Misrua,atc 'Terrestrial Link Rain .41renunriun Prsrlicrion Paramerer Analysis," L S Dspanmcnt o i Communications, Natiunal Telecommunicalions and Information AdininisIration (STIA) Tech. Rep. 84.148, Apnl, IY8-L 9 . A. P. Gallois. 1'. I' 113nigan. and A \I Heck, "A Comparison of Slanr Path Arrenuntion hlodels Applied tu rhe Selection of Satellite Beacon Receiver Sires," I'roceding~ oJ' ihr 6rh hrcrnurionnl C'onti,reiirr fin Anirnnas unJ I'ropugution, I3XY, pp. 27 1-275.

i f p > l % orlp1>364,P=0

Iu. 51. Ciiines, F. Cline$, and K. Dimiller, "l>e\,elopmenr of a Climatic Map of Atmuation by Rainfdll for Turkey," Prnr.ec4itfg> ./ rhr 7ih .+lediierrun.'nn € l e ~ ~ ~ r u r e c l('onferrncz. ~ ~ ~ u l ~ ~ 1994. i ~ pp.

if p < l % and I p / < 3 6 " and 0 2 2 5 " , p=-O.OOS(lp-361)

383-386.

(15)

else

p = -O.OOS(l91-

36)

I I . L. T Salonen and J. P. V. l'OiJrC\ I3aptisia. "A Ncw Glubal Rainfall Rate .Vodsl," Priihy Rain G;iii~eYework In Singapore," Elrcr,onrearch index.shrml

Ik. R. K Cr3nc and P c'. Ruhinjun, "ACTS Prrrpngation Expcrimsnt: Kain-rate I>i~triburionOb,cn:itions a i d I'redictioir \lode1 Satellite Applications: http:// telecom.esa.intitelecomiuwwicatego~/index.cfm?fcatego~~d=42.Compari~oiis."Prowding\ ~ d r h c/ELL, 85. June 1997. pp. Y.16958. 4. P. Rice and N. Holmberg, "Cumulative Time Statistics of Sur19. I..J. Ippuliio. Pr~~pujiurion E f l k i . ~I h d b o o k lor .Snrrllril~.!irface-Point Rainfall Rates," IEEE Transactions on Communicai ~ Dk,wgn, m I..i/Ih Edirio,i, (second revision), ITT Indusrries. 2000 tions, COM-21, October 1973, pp. 1131-1136. 3. ESA Telecommunications

~

5 . J. Chebil and T. A. Rahman, "Development of 1 min Rain Rate Contour Maps for Microwave Applications in Malaysia PeninsuIa,''E/ecfronicsLetters, 35, pp. 1712.1774.

6. ITU-R, "Propagation Data and Prediction Methods Required for the Design of Earth-Space Telecommunications Systems," Recommendation P.618-8, ITU-R Recommendations, P Series, Geneva, International Telecommunications Union, 1999.

21). ci. Feldhake and I.. Ailci-Sen$eri. "Coniparisoii o i Multiple Rain Ittenuatim 3lodels with 'rhrcc Years of K3 Band I'rop3gar i m I)ata Con:urrently Tdksn ill Cighr Diiiercnr Loc3lims," 3tallissue02 crpsriments.htnlI abl: at hrrp: satji~um.il.tcoin.~~hiou.edi~

21. R Acu1t3 and S Juhnron,

"K3 Bmd Symni and I'nipagdtion System I'srbmiance," avnilablc at hiip: acrs.grs.najs.gov libsearch index ,hinil.

I:fieas

on

/€E€ Antennasandpropagation Magazine, Vol. 46, No. 6, December 2004


67

22. Sandra K. Jhonson, “Propagation Models Comparison with Measurements Taken in a Tropical Rain Zone Using the ACTS System,” available at http://acts.grc.nasa.gov/libsearchi indexshtml.

23. J. P. V Poiares-Baptista (ed.), “OPEX - Reference Book on Attenuation Measurement and Prediction,” available at

Universidad Pontificia Bolivariana, Medellin, Colombia, in 1999 and 2003, respectively. He works for INTERNEXA S A . , where he is in charge of business analysis and strategic planning. He is also a researcher with the Informatics and Telecommunications Research Group - GIDATI - at Universidad PonLificia Bolivariana, in the areas of satellite communications and radiowave propagation.

http:llwww.estec.esa.nllxewwwlcost255lopex.htn1. 24. J. Restrepo, L. D. Emiliani, and C. Fradique-Mendez, “Rain Attenuation Prediction in Tropical Zones: Theoretical Analysis, Measurement Campaigns and Model Comparisons,” 20th ICSSC, Montreal, Canada, 2002. 25. ITU-R, “Acquisition, Presentation and Analysis of Data in

Studies of Tropospheric Propagation,” Recommendation P.311-10, ITU-R Recommendations, P Series, ITU, Geneva, International Telecommunications Union, 2001.

Jhon Alexander Agudelo received the BSc degree in Electronic Engineering from Universidad Pontificia Bolivariana, Medellin, Colombia, in 2004. He is a researcher with GIDATI the Informatics and Telecommunications Research Group at the Universidad Pontificia Bolivariana. MI. Agudelo is also Secretaw of the students’ IEEE branch at the Univenidad Pontificia Bolivariana, Medellin, Colombia.

HCctor Esteban GutiCrrez received the BSc in Electronic 26. ITU-R Study Group 3 Web site: http://www.itu.intlITU-R/ Engineering from Universidad Pontificia Bolivariana, Medellin, study-groups/rsg3/index.asp. Colombia in 2004. He is a researcher with GIDATI, the Informatics and Telecommunications Research Group at the Universidad Pontificia Bolivariana. Mr. Gutierrez is also Chair of the students’ 27. ITU-R, “Specific Attenuation Model for Rain for Use in Prediction Methods,” Recommendation P.838-1, ITU-R RecommenIEEE branch at the Universidad Pontificia Bolivariana, Medellin, dations, P Series, ITU, Geneva, Intemational Telecommunications Colombia. Union, 1999. 28. ITU-R, “Rain Height Model for Prediction Methods,” Recommendation P.839-3, ITU-R Recommendations, P Series, Geneva, International Telecommunications Union, 2001. 29. R. K. Crane and D. V Rogers, “Review of the Advanced Communications Technology Satellite (ACTS) Propagation Campaign in North America,’’ IEEE Antennas and Propagation Magazine, 40, December 1998, pp. 23-27. 30. R. Gedney and F. Gargione, ACTS -Technology Description and Results, report NASA/CR-2000-209806, Februay, 2000; available at hrrp://acts.grc.nasa.gov/libsearch/index.sh~l.

Introducing the Feature Article Authors Luis David Emiliani received the BSc degree in Electronic Engineering and the MEng degree in Telecommunications from

L.D. Emiliani

68

J.A. Agudelo

Joaquin G. Restrepo received his BSc degree in Electronic Engineering and his MSc degree in Technology Management from the Universidad Pontificia Bolivariana. He received his MSc and PhD .degrees in satellite telecommunications from E.N.S.T. site de Tolouse: He hac been advisor on social communications systems and satellite systems for the Ministry of Communications of Colombia, with active participation in COPUOS. Dr. Restrepo has autbored several articles and conference presentations in non-geosynchronous systems in America and Europe, and co-authored two European patents on non-geosynchronous systems. CCsar A. Fradique-MCndez received his BSc in Physics, his BSc in Electrical Engineering, and his MBA from Los Andes University in Bogota, Colombia, in 1997, 1998, and 2002, respectively. He is NTS Team Leader for Wireline and Optical systems in the Andean Region for Nortel Networks. He is also co-founder, partner, and strategy-technology consultant for Bogota-based Circulo de Estrategia.

H.E. Gutierrez

J.G. Restrepo

IEEE Antennasandpropagation Magazine, Vol.


C.A. Fradique-Mendez

46, No. 6, December 2004