The rain Attenuation Characteristics at 12.7 GHz on Earth-Space Path in Bangkok T.Boonchuk1, S.Noppanakeepong1, P.Supnithi1, N.Hemmakorn1, and Y.Moriya2 1
Faculty of Engineering and Research Center for Communication and Information Technology (ReCCIT) King Mongkut’s Institute of Technology Ladkrabang (KMITL) 3-2 Chalongkrung Road, Ladkrabang, Bangkok 10520, THAILAND. Tel: +66-2737-3000 Ext. 3326 2
Tokai University, 1117 Kitakaname, Hiratsuka, Kanakawa, JAPAN E-mail:
[email protected],
[email protected],
[email protected] ABSTRACT This paper presents a statistical analysis of the rainfall rate and the rain attenuation data on satellite to ground propagation path. By measuring 12.7-GHz beacon signal attenuation from satellite and the rainfall rate continuously from February 2000 to August 2002 and January 2003, respectively. The smaller integration time interval yields the higher the rainfall rate. Correlation between 10-second and 1-minute integration time of the rainfall rate is presented. Yearly cumulative distribution functions were then compared with predicted models Two predicted models, ITU-R [5] and Crane Global [4] models, for the rain attenuation and ITU-R [6] model for the rainfall rate. The Crane Global model for the rain zone H provides close predicted values to measured ones. For the rain zone G, the Crane Global model provides close values to ITU-R model; both are smaller than measured ones. The ITU-R method is proven to underestimate the rain attenuation in the equatorial region like Bangkok. Keywords: Ku-band, Earth-Space propagation, Yearly cumulative distribution function 1. INTRODUCTION The rain attenuation characteristics on earth-space paths are important to the system reliability at Ku-band, especially for small aperture antennas such as Very Small Aperture Terminal (VSAT) and TeleVision Receive Only (TVRO). In [1]-[2], we have conducted continuous measurements of the beacon signal attenuation at 12.7GHz from JC-Sat satellite using the 1.8-m antenna. This paper describes a statistical analysis of the rainfall rate and the rain attenuation. The analysis focuses on (1) the comparison between predicted and measured values of the rain attenuation, and the rainfall rate and (2) the comparison of 10-sec., 1-min. and 1-hour integration time of the rainfall rates. In this paper, the measurement of the rainfall rate and the rain attenuation last 3 years and 2 years and 7 months, respectively. The experiment parameters and periods of available data are listed in Table 1. The experimental site is located near the
boundary line of G and H rain zone of the Crane Global rain zone model as shown in figure 9. Table 1: Parameters of propagation experiment Satellite JCSAT 1B, 150oE Downlink Frequency 12.7475 GHz (beacon, vertical) Elevation angle 32o Location KMITL (100o 46’E, 13o43’N) Height above mean 50 m sea level The rain gauge type Tipping Bucket, Drop count Sample data interval 1-min, 10-sec. for both satellite signal and rainfall rate Available data 1-min. sample for both data 2001/02-2002/08 10-sec. sample for the rainfall data 2001/09-2003/01 2. EXPERIMENTAL METHODS Figure 1 illustrates the configuration of the propagation experiment system at KMITL. The satellite signal is received by the 1.8-m antenna to the down converter and the beacon receiver. Pulse number or the rainfall amount of drop-count rain gauge is counted. D o w n Converter
Beacon Receiver
Data Logger
1.8m Antenna
Pulse Counter
PC
The rain
Fig. 1: Configuration of experiment system The data of the received signal and the rainfall amount are sampled at every 1 min. and 10 sec., respectively. The data is continuously recorded by the personal computer. The dynamic range of attenuation of the measurement is approximately 20 dB below the clear
sky level. The resolution of the drop-count rain gauge is 1/60 mm/drop, a minimum detectable sensitivity, and equivalent to the step size of the rainfall rate of 6 mm/hr for 10-sec. integration time using half-sized receiving aperture. The resolution of the tipping-bucket type the rain gauge is 0.5 mm/tip, a minimum detectable sensitivity, and equivalent to the step size of the rainfall rate of 30 mm/hr for integration time of 1 minute. 350
instantaneous correlation between integration time of 10sec. and 1-min. the rainfall rate from September 2001 to January 2003. The integration time of 1-min. the rainfall rate is obtained by summing 6 values of 10-second integration time. From the figure, it can be seen that in the case of the rainfall rate above 200 mm/hr, the relationship between both the rainfall rates is largely scattered. Note that, in ITU-R model, an intensity of the rainfall is expressed by the rainfall rate (mm/hr) which measured at integration time of 1 minute.
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3.MEASUREMENTS RESULTS AND DISCUSSIONS 3.1 Example of intense rainfall event and effect of integration time In [3], the extremely intense rainfall rate reaches 400 mm/hr. Intense rainfall rate measurement was conducted from September 2001. During the observed period, the intense rainfall event reaching 300 mm/hr was observed only once. The record of an intense rainfall rate using integration time of 10-sec and correspondence the rain attenuation is presented in Fig. 2. From the figure, it can be seen that the duration of intense rain is shorter than the duration of the rain attenuation. Figure 3 illustrates the
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(b) Satellite signal attenuation Fig. 2: Recording example of an intense rain fall event reaching 300 mm/hr and satellite signal attenuation on Sep 23, 2001
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Fig. 4: Comparison between integration time of 10-sec., 1-min. and 1-hour rainfall rate The effects of integration time of 10-sec., 1-min. and 1-hour are illustrated in figure 4. We obtain and one-hour integration time by summing 360 data of the integration time 10-second. From the figure, the integration time of 1 hour gives the lowest value of the rainfall rate with almost even distribution. For 10-sec. and 1-min. integration times, the difference of the rainfall rates are quite small up to rain rate of about 150 mm/hr, but the difference is more noticeable for the rainfall rate above 200 mm/hr,: with deviated up to 90 mm/hr.
3.2 Yearly cumulative distributions of rain attenuation and rainfall rate Yearly cumulative distribution of three-year rainfall rate and two-year rain attenuation are presented in figure 5 and figure 6, respectively. The year-to-year variations of both cumulative time distributions are minimal. In figure 5, the cumulative distribution of 10-sec. integration time is included. The cumulative distribution of 10-sec. and 1min. integration times is not much different and both follow predicted ones from ITU-R. Monthly cumulative distribution from February to August 2002 is presented in Fig. 7. During this period, the rain attenuation occurs at maximum in June and at minimum in April. 250
rainfall rate for all the rain events for one year from September 2001 to August 2002. The relationship is largely scattered and can be easily separated into two parts. The first part, A, is the data near the vertical axis, the rain attenuation axis, when low rainfall rate results in high attenuation. It is caused by the intense rainfall somewhere along the propagation path which cannot be detected by the point rain gauge. The other part, B, is the area where the rain attenuation and the rainfall rate are proportional. Some times the high the rainfall rate does not point to high the rain attenuation. If the experimental site considered at KMITL can be used to represent this region, it is evident the rainfall events in Thailand are categorized as a convective type rainfall.
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Fig. 6: Yearly cumulative time distribution of the rain attenuation at 12.7 GHz
Fig. 8: Correlation between the rainfall rate and the rain attenuation
3.3 Correlation between the rainfall rate and the rain attenuation
3.4 Comparison between measured and predicted value of the rain attenuation at 12.7 GHz
The relationship between the rainfall rate and the rain attenuation of 10-sec. integration time is presented in figure 8. This figure plots the rain attenuation against the
The standard prediction models such as the Crane Global and ITU-R [4]-[6] calculate the rain attenuation in dB, A (dB), from
Even though ITU-R model predicts yearly cumulative the rainfall rate accurately as shown in figure 5 (using point rainfall rate), the correlation between the point rainfall rate and the rain attenuation shown in figure 8 indicates 2 regions of correlation. We believe this is the reason of underestimation. 4. CONCLUSIONS KMITL
Fig. 9: Crane Global the rain zone boundaries
A(dB) = aR b L( R)
(1)
Where R is rainfall rate [mm/hr], a and b are frequency- and polarization- dependent constant, and L (R) is the effective path length. These parameters are shown in figure 10. The ITU-R and Crane prediction model use different derivation of L(R). ITU-R calculates this term by using rainfall rate at only 0.01% of yearly cumulative time distribution while Crane Global model includes all desired percentages of yearly cumulative distribution of the rainfall rate. The comparison between predicted and measured values is illustrated in figure 6. As seen in the figure, Crane Global model with the zone H yields the close predicted values to measured ones, but smaller values for the G zone. The H the rain zone is more appropriated the rain zone than G zone to predict the rain attenuation by the Crane Global model. Because the ITU-R model gives smaller values for all measured ones, it underestimates the equatorial region like Bangkok. Geneva.
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Fig. 10: Schematic and parameters for the rain attenuation prediction
For measurement at 12.7 GHz in the elevation angle of 32 degree, the rain attenuation characteristics are analyzed. For the rainfall rate over 200 mm/hr, the integration time is an important parameter to obtain accurate intense rainfall rate. Yearly cumulative time between integration time of 10-sec. and 1-min. is not much different. ITU-R model [6] agrees well with measured cumulative time of the rainfall rate while the yearly cumulative time of measured the rain attenuation is larger than the predicted ones from ITU-R model [5] for all percentages. ITU-R model underestimates the rain attenuation in the equatorial zone like Bangkok, while Crane Global model [4] with the rain zone H gives close predicted values to measured ones. 5. ACKNOWLEDGEMENT The authors would like to express special thanks to The Research Center for Communication and Information Technology (ReCCIT), Japan international Cooperation Agency (JICA) and New-post-PARTERS Promotion council. 6. REFERENCES [1] T.Boonchuk, N.Hemmakorn, K.Igarashi, T.Ojima, Y. Moriya, and K.Takagi, “Ku-band satellite signal propagation experiments of Post-PARTNERS project”, Proc. of ISAP-2000, Fukuoka, Japan, 2000. [2] T.Boonchuk, N.Hemmakorn, K.Igarashi, H.Minakoshi, M.Kawamura, Y.Moriya, and T.Minode, “Result of Kuband satellite signal propagation experiments under Post-PARTNERS project”, AP-RASC2001, Tokyo, Japan, 2001. [3] M. Yamada, R. Saotome, N. Katayama, K. Tokushige “Earth-Space propagation characteristics at 12 GHz due to especially intense the rains in Japan” Proc. of APSBC 2000, Dec 21-23, 2000, Bangkok, Thailand. [4] R. K. Crane, Electromagnetic Wave Propagation Through The rain, John Wiley & Sons, Inc., New York, 1996, Ch. 3 & 4. [5] ITU-R, “Propagation data and prediction method required for the design of Earth-space telecommunication systems”, Recommendation ITU-R P.618-7, 2001, P Series Fascicle, Radio wave Propagation, International Telecommunication Union, Geneva. [6] ITU-R, “Characteristics of precipitation for propagation modeling”, Recommendation ITU-R P.837-3, 2001, P Series Fascicle, Radio wave Propagation, International Telecommunication Union,
