Advances in Astronomy
Volume 2019 (2019), Article ID 9538061, 12 pages
https://doi.org/10.1155/2019/9538061

Research Article

Rain Attenuation Study at Ku-Band over Earth-Space Path in South Korea

Sujan Shrestha and Dong-You Choi

Department of Information and Communications Engineering, Chosun University, Republic of Korea

Correspondence should be addressed to Dong-You Choi; dychoi@chosun.ac.kr

Received 17 October 2018; Accepted 29 January 2019; Published 3 March 2019

Guest Editor: Feng Wang

Copyright © 2019 Sujan Shrestha and Dong-You Choi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Rain attenuation measurement techniques are studied with appropriate prediction of rain attenuation at Ku-band for Koreasat 6. This is accomplished by the establishment of experimental setup in Mokdong at 12.25 GHz link. The databases are analyzed for three years, 2013 till 2015. During observation period, rainfall rate of 50 mm/hr is obtained which is measured by OTT Parsivel showing the signal attenuated by 10.7 dB for 0.01% of the occurrence. Comparison with the measured data demonstrates that the proposed technique provides sufficiently accurate estimation for Ku-band signal attenuation in site specifically whose effectiveness is performed through the statistical analysis against the established rain attenuation models. The proposed technique is judged through the error matrices where relative error margins of 52.82, 4.11, and 23.64% are obtained for 0.1%, 0.01%, and 0.001% of the occurrence.

1. Introduction

Absorption and scattering by rain at frequencies above 10 GHz can result in the reduction of transmitted signal amplitude, which in turn reduce the reliability, availability, and performance of the communication link [1]. Ample spectrum is achieved through the satellite communication, but atmospheric propagation affects the service period at higher frequency such as Ku (14/12 GHz) bands [2]. This band of frequencies is suitable for direct to home (DTH) multimedia services, but significant attenuation is resulted due to rain during the transmission period [3]. The systems have been designed to operate at an acceptable performance level by providing adequate power margins on the uplink and the downlink segments [4]. Due to the lack of direct measurement of rain attenuation, modelling and prediction approaches are used for the estimation of attenuation [5]. Empirical method is suitable as compared to the physical methodology [6]. The variation of attenuation is dependent on specific attenuation, frequency, and polarization [7]. ITU-R P. 618-13 [8] shows reasonable good estimation for operating frequency till 55 GHz [4]. The analysis for 1-minute instance for rain rate is analyzed in local environment [9–12]. Additionally, the studies are carried out for Yong-in Station [13, 14]. Furthermore, rain induced attenuation is studied for beacon signals at Ka-band frequency in [15].

The technique for predicting the rain attenuation of Ku-band satellite signal during rain events has been presented for Mokdong Station. In addition, the established method of study of signal attenuation due to rain is analyzed [16–23]. The rain attenuation has been predicted from the synthetic storm technique and examination of storm speed effect, which is based on one year satellite beacon signal, rain intensity and storm speed measurement in Malaysia [24]. The site diversity techniques are studied in South East Asia [25]. The statistical variation has been assessed from the propagation experiment that was carried out in Madrid, Spain [26]. A channel model has been developed to predict time series of rain attenuation and the obtained rain rate and attenuation statistics at tropical and temperate regions are compared [27]. Similarly, the diurnal and monthly variation have been studied for Ka-band communication link [28]. The renowned methods for the estimation of signal attenuation due to rain have been analyzed [6, 8, 29–34]. However, the need for better prediction model is necessary to be studied as per the measurement performed in local environmental condition which signifies the need for the proposed work. The rain rate value for 0.01% of occurrence is a crucial parameter in the analysis of slant path attenuation [35]. The short descriptions of various techniques are stated in Section 2. Section 3 highlights the equipment building and the measurement system. The outcomes are detailed in Section 4. Section 5 gives conclusion.

2. Studied Models

Three methods are crucial for the better estimation of signal attenuation due to rain which can be categorized as the evaluation of specific attenuation [38], appropriate height of rain drops [39], and calculation for over all-time percentages. The relationship between specific attenuation, (dB/km) and rain rate R (mm/h) is given as

Two parameters for 12.25 GHz under circular polarization of the present location are obtained as k=0.024205 and α=1.151616. The ITU-R P. 839-4 [39] gives the required rain height estimation.

2.1. ITU-R P. 618-13

The ITU-R rain attenuation model [8] is the most widely accepted model by the international propagation community. The input parameters needed for the model are point rainfall rate of the location in 0.01% of an average year (mm/hr), height above sea level of the earth station (km), elevation angle (), the latitude of the earth station (), and frequency (GHz). The effective path length () can be obtained using (2a), where is the vertical adjustment factor and is calculated from the horizontal projection. The signal attenuations due to rain are analyzed from specific attenuation as

Similarly, (2c) can be used to find the attenuation for other instances of time percentage [8].

If % or ,.

If % and and , = −0.005().

Otherwise, and : = −0.005.

The model has been applied against the measurement result for earth-space communication at 12.25 GHz under circular polarization.

2.2. Unified Method

Full rainfall rate distributions are used to analyze the signal attenuation due to rain. The numerical coefficients are obtained by multiple nonlinear regressions, obtained from available ITU-R databanks [40]. Further description can be found in [29].

2.3. Dissanayake, Allnutt, and Haidara (DAH) Model

It is based on the log-normal distribution of rain rate and rain attenuation. Even though this method is similar to the ITU-R P. 618-12 [8] in which rain heights vary, in DAH model it is fixed to 5 km [6].

2.4. Simple Attenuation Model (SAM)

It was developed to utilize algebraic equations for specific attenuation coefficients, isotherm height, and path profile on earth-space communication links operating in the range from 10 to 35 GHz. This method consists of the relationship between specific attenuation and rain rate, statistics of the point rainfall intensity and spatial distribution of rainfall [30].

2.5. Crane Global (CG) Model

The model depends on the 0°C isotherm height, , and excessive precipitation events [31].

2.6. Ramachandran and Kumar (RK) Model

It studies the statistics that is based on elevation angle less than 60° [32].

2.7. Gracia Lopez (GL) Model

It features the suitable method for rain attenuation prediction to be used in satellite radio link which is tested over 77 satellite links placed in Europe, the US, Japan, and Australia. The coefficients details necessary for the calculation of rain attenuation are mentioned in [33].

2.8. Karasawa Model

This model was accepted by the European Space Agency as a suitable model which was designed to enhance the prediction performance at lower probability exceedance levels [34].

2.9. Proposed Approach

The proposed technique is based on the behavior of signal as it is attenuated towards the direction of communication path between satellite and ground station at 0.01% of occurrence. The two quantities are related as

The coefficient values are obtained from ITU-R P. 838-3 [38]. The quantitative relation between the attenuation due to rain and effective path length, , value at 0.01% of the occurrence is given as

This approach is studied for the experimental values of three years, from 2013 to 2015. Additionally, rain rate and beacon signal level data [14] in Young-in Station are analyzed together with Mokdong-13 na gil station database. The empirical notations are determined from the curve fitting technique as given in (3). The regression analysis relates, , to rain rate value as

Finally, substituting (4b) to (3), we get

Due to the insufficiency of experimental rain attenuation and rain rate database from other locations of South Korea, the proposed method utilizes the extrapolation equation as stated in (2c). We have proposed the empirical relation between rain attenuation and rain rate at 0.01% of time. Furthermore, for other time percentages we have used extrapolation equation as stated by ITU-R P. 618-13 [8]. Additionally, the proposed approach differs with other models as per the empirical relationship obtained between rain attenuation and rain rate at 0.01% of time.

3. Experimental Setup

Rain attenuation of Ku-band beacon signal over an earth-space link has been measured by a receiving signal at frequency 12.25 GHz transmitted with circular polarization from satellite Koreasat 6, situated at 116°E at an elevation angle of 45° since 2013 [36]. The sampling interval of the data acquisition used in the present study is 10 second which is averaged over 1-minute distribution. The beacon signal strength was measured using a spectrum analyzer at 10 second interval while monitoring of the data was done on a personal computer. In addition, an optical disdrometer is used to measure the rain rates which operate simultaneously with the monitoring system of satellite beacon signal whose specification is given in Table 1. The beacon receiver measures the amplitude fluctuations in the received signal with enough accuracy and dynamic range. The radome prevents the antenna from wetting condition. The link has availability of 99.95% whose details are given in Table 1.

Table 1: Link description for 12.25 GHz [36].

Type
Descriptions
Specification

System Location
Location
37.5447°N, 126.8833°E

Elevation angle
45°

Degree of tilt
197.5°

Low-lying (km)
0.055

Receiver Antenna
Prototype
Off-set parabolic

Operating range
10.95 ~ 31

Polarization
Circular

Gain
55 dB ± 2 dB

Dynamic Range (dB)
18.3

Optical Disdrometer
Type
OTT Parsivel

Measuring area
54 cm²

Particle size
0.2 to 25 mm

Velocity drop
0.2 to 20 m/s

Rain Intensity
Up to 1200 mm/hr

Temperature range
-40°C to +70°C

The received beacon signal levels are sampled for every 10 seconds and averaged over 1 minute. The rain rates are measured by OTT Parsivel with 99.95% of the validity. OTT Parsivel is the laser based optical disdrometer. The parallel rays between emitter and receiver help to measure the required precipitation characteristics with the change in signal output voltage. This determines the magnitude of drops particle size whereas the interval of original signal helps in determination of the velocity. This determines the required rain rate. The sensor built on the OTT Parsivel conveys messages to computer with the support of RS 485. Heating system obstructs the ice build-up process for every second. Further detail procedures are listed in [41, 42]. The system diagram of setup is shown in Figure 1.

Figure 1: System diagram of experimental setup [36].

Figure 1 shows the off-set antenna is faced towards Koreasat 6 satellites. The noise figure of 1.5 dB and bandwidth of 1000 MHz are maintained where the output is passed through the system that splits signal in 4 dB range which goes through spectrum analyzer. Finally, its output is stored in database. The excess attenuation over the clear weather values results in the calculation of required rain attenuation values which are measured simultaneously with the rain rates. The GPS antenna records the relative position through GPS signal receiver. Figure 2 shows the recorded signals.

Figure 2: Variation of 12.25 GHz signal attenuation [36].

Thus, the required attenuation is calculated as

where RSL stands for receiver signal level. The procedure as depicted in [14] is used to determine the required rain rate and attenuation for 1-minute instance. The required rain rate and attenuation are calculated by arranging the data in the descending order. For instance, at 0.01% of the occurrence, 1-minute rain rate and attenuation values are taken in 158 ((3×365×24×60×0.01)/100) = 157.68 ≈ 158). In each year of measurement the values of 53 ((1×365×24×60×0.01)/100) = 52.56 ≈ 53) were taken. The annual values of 1-minute rain rate from 2013 till 2015 are shown in [15, 43]. Figure 3 shows the rain attenuation for 12.25 GHz frequency which is obtained on the yearly basis and when combined together from 2013 till 2015. The rain rate is greater in 2013 and 2014 which resulted in higher rain attenuation values of 10.8 dB and 12.3 dB, respectively, for 0.01% of the time. The combined data is considered for further analysis, which indicates the lower attenuation values at higher time percentages and higher values at lower time percentage. As seen, the attenuation values of 7.9, 10.7, and 19 dB are observed for 0.1%, 0.01%, and 0.001% of the occurrence, respectively. The higher attenuation for 1% of an average year might be due to the summation performed for 10 seconds measured data to be equivalent to 1-minute interval. Additionally, it might be due to the higher rain rate experienced for the time interval of 1% of an average year.

Figure 3: Distribution of Rain attenuation at Mokdong [36].

Furthermore, the plot of rainfall rate distribution for various integration times near location of Icheon is presented in [15] which shows the rain rate obtained from the experimental 1-minute rainfall amount database provided by Korea Meteorological Administration (KMA) from 2004 to 2013 [44]. The effect of rain attenuation on the terrestrial communication links has been studied over the 18, 38, and 75 GHz links [45–47]. This signifies the need for measurement result of RRA with longer experimental periods, which is still under progress.

4. Result and Discussions

Distributions of rain attenuation at 12.25 GHz are shown in Figure 4. It shows that ITU-R P. 618-13 gives close value at 0.01% of the time but deviates in lower and higher time period. However, difference in prediction is lower as compared to higher time period. As observed, calculated 1-minute rain attenuation values are 7.9, 10.7, and 19 dB and ITU-R P. 618-12 estimates 3.73, 11.14, and 23.49 dB for 0.1%, 0.01%, and 0.001% of the occurrence, respectively. This might be due to the low spatial resolution of the matrices. ITU-R P. 618-13 gives the reasonable estimation at 0.01% of the time, but for, other time percentages, this method results in poor estimation. This highlights the need for suitable 1-minute rain attenuation model for Ku-band satellite communication link. Furthermore, the relation between rain attenuation and rain rate is shown in Figure 5 for three years of measurement along with the combined values. This figure indicates that there is positive correlation between the rain rate and rain attenuation. The manuscript illustrates the suitable approach along with the categorization of the applicable prediction methods over the earth-space path for Ku-band satellite communication.

Figure 4: Variation of signals against ITU-R P. 618-13 for various integration times [37].

Figure 5: Rain attenuation versus rain rate [37].

The proposed method along with the rain attenuation models is studied against the measured result as shown in Figures 6(a) and 6(b) for 12.25 GHz satellite communication links for Mokdong and Yong-in Station, respectively.

(a) Prediction at 12.25 GHz for Mokdong Station [37].

(b) Prediction at 12.25 GHz for Yong-in Station [37].

Figure 6

In 12.25 GHz from Figure 6(a), ITU-R P. 618-13 and the proposed approach are predicted preferably, but the chances of overestimation and underestimation are greater for lower and higher time percentages, respectively. The calculated rain attenuation values are 7.9, 10.7, and 19 dB at 0.1%, 0.01%, and 0.001% of occurrence, whereas ITU-R P. 618-13 and the proposed approach predict 3.73, 11.14, 23.49 dB and 3.56, 10.7, 22.67 dB, respectively. CG and SAM methods give similar result which overestimate and underestimate the measured values at lower and higher time percentages, respectively.

Interestingly, CG generates close approximation against the measured rain attenuation when P < 0.01%. It predicts 2.39, 11.05, and 25.84 dB, respectively, at 0.1%, 0.01%, and 0.001% of the time whereas SAM predicts 2.37, 12.52, and 26.2 dB, respectively. DAH, Unified, and GL show underestimation of rain attenuation for all-time percentage, but the closer prediction is obtained by the application of DAH method in low time of occurrence. As seen, DAH, Unified, and GL show 2.66, 8.19, and 17.84 dB; 2.63, 8.42, and 14.55 dB; and 2.09, 8.41, and 13.64 dB, respectively at 0.1%, 0.01%, and 0.001% of the time. Karasawa shows preferable estimation at 0.01% of the time, but greater overestimation and underestimation are observed for lower and higher time percentages, respectively, as compared to other methods. Additionally, RK gives the better estimation for higher time percentage, but overestimation is noted on lower time percentage. Karasawa and RK estimate 3.07, 9.72, and 37.45 dB and 5, 15.79, and 21.48 dB, respectively, at 0.1%, 0.01%, and 0.001% of occurrence. Additionally, effectiveness of methods is analyzed from error analysis.

Prominent methods along with proposed technique are tested in Yong-in Station. Unfortunately, unavailability of sufficient database for all-time percentages has limited the significance of the study. However, data at 0.1 and 0.01% of the time for 2007 as noted from [14] are considered for the suitability of methods. As depicted in Figure 6(b), ITU-R P. 618-13, RK, and proposed approach give the reasonable estimate with P ≤ 0.01%. For instance, measured rain attenuated signal variations are 4, 11, and 15 dB at 0.1, 0.01, and 0.005% of the occurrence while ITU-R P.618-13, proposed approach, and RK estimate 3.25, 9.84, and 12.83 dB; 4.15, 12.29, and 15.91 dB; and 5.51, 17.22, and 19.25 dB, respectively. Due to the dependability on the experimental data of rain rate that is available for only 0.1 and 0.01% of the occurrence, there is the limitation on analyses of Unified, SAM, CG, and GL methods. The finding suggests that these models are unable to give better estimation but at 0.1% of occurrence, SAM, CG, and GL result in closer estimation for measured rain attenuation data. For example, the attenuation values of 4.57, 9.48 dB; 5.36, 14.92 dB; 4.74, 12.51 dB; and 4.23, 9.39 dB are obtained from Unified, SAM, CG, and GL methods for 0.1 and 0.01% of occurrence. Thus, those models preference can be better categorized from the recent RRA data from Mokdong Station. DAH method shows underestimation whereas Karasawa gives the fair close prediction of measured rain attenuation. For instance, DAH and Karasawa result in 2.72, 8.37, and 10.96 dB and 4.87, 12.77, and 16.08 dB, respectively, for 0.1, 0.01, and 0.005% of the occurrence.

Rain attenuation prediction model for Earth-satellite link is determined for exceeding time percentages 0.001% to 1%. Hence, the percentage errors, (P), between measured Earth-satellite attenuation data () in dB and the model’s predictions () in dB are calculated as follows:

Variance (STD) and quadratic mean (RMS) are calculated as [9]. Ratio of predicted to measured attenuation is calculated and the natural logarithm of these error ratios is used as a test variable [48]. Average (), variance (), and quadratic mean () of test variable are calculated to provide statistics for prediction procedure whose comparison is given in Tables 2, 3, and 4 for 12.25 GHz link for Mokdong and Yong-in Station, along with the evaluation procedures adopted for comparison of prediction methods as recommended by ITU-R P.311-15 [48].

Table 2: Calculated error percentage [0.001% to 1%] for 12.25 GHz.

Procedures
Matrices
Occurrence
ITU-R P.311-15

1
0.5
0.3
0.2
0.1
0.05
0.03
0.02
0.01
0.005
0.003
0.002
0.001

ITU-R P. 618-13
ε(P)
-0.84
-0.78
-0.72
-0.66
-0.53
-0.38
-0.26
-0.15
0.04
0.19
0.29
0.32
0.24

STD
0.59
0.53
0.47
0.41
0.28
0.13
0.01
0.10
0.29
0.43
0.54
0.57
0.48
-0.45
0.64
0.78

RMS
4.70
4.98
4.94
4.79
4.17
3.23
2.40
1.49
0.44
2.27
3.89
4.77
4.49

Unified
ε(P)
-0.94
-0.88
-0.84
-0.79
-0.67
-0.51
-0.42
-0.34
-0.21
-0.15
-0.11
-0.14
-0.23

STD
0.46
0.40
0.36
0.31
0.19
0.03
0.06
0.14
0.27
0.33
0.37
0.34
0.25
-0.02
0.63
0.63

RMS
5.27
5.66
5.78
5.76
5.27
4.39
3.86
3.35
2.28
1.86
1.47
2.11
4.45

DAH
ε(P)
-0.89
-0.85
-0.80
-0.76
-0.66
-0.55
-0.46
-0.38
-0.23
-0.12
-0.03
0.00
-0.06

STD
0.44
0.40
0.35
0.31
0.22
0.10
0.02
0.06
0.21
0.33
0.41
0.44
0.39
-0.76
0.66
1.01

RMS
4.98
5.41
5.52
5.53
5.24
4.73
4.30
3.75
2.51
1.46
0.45
0.06
1.16

SAM
ε(P)
-0.99
-0.95
-0.91
-0.86
-0.70
-0.45
-0.27
-0.12
0.17
0.36
0.49
0.47
0.38

STD
0.73
0.69
0.65
0.60
0.44
0.19
0.01
0.14
0.43
0.62
0.75
0.73
0.64
-0.87
1.35
1.61

RMS
5.53
6.09
6.28
6.27
5.54
3.88
2.49
1.14
1.82
4.37
6.57
6.91
7.20

Crane Global
ε(P)
-0.99
-0.95
-0.90
-0.85
-0.70
-0.48
-0.32
-0.20
0.03
0.18
0.28
0.26
0.36

STD
0.66
0.62
0.57
0.52
0.37
0.15
0.01
0.13
0.36
0.51
0.61
0.59
0.69
-0.9
1.26
1.55

RMS
5.52
6.05
6.22
6.19
5.51
4.11
3.01
1.94
0.35
2.16
3.72
3.80
6.84

Ramachandran and Kumar
ε(P)
-0.79
-0.71
-0.63
-0.55
-0.37
-0.12
0.13
0.42
0.48
0.45
0.43
0.36
0.13

STD
0.73
0.65
0.57
0.49
0.31
0.06
0.19
0.47
0.54
0.51
0.49
0.42
0.19
-0.21
0.62
0.65

RMS
4.43
4.56
4.34
4.01
2.90
1.00
1.25
4.07
5.09
5.48
5.69
5.28
2.48

Gracia Lopez
ε(P)
-0.99
-0.95
-0.91
-0.87
-0.74
-0.55
-0.44
-0.35
-0.21
-0.16
-0.13
-0.17
-0.28

STD
0.47
0.43
0.39
0.35
0.22
0.03
0.08
0.17
0.31
0.36
0.39
0.35
0.24
-1.16
1.16
1.64

RMS
5.53
6.10
6.31
6.34
5.81
4.74
4.05
3.44
2.30
1.98
1.78
2.56
5.36

Karasawa
ε(P)
-0.89
-0.83
-0.77
-0.72
-0.61
-0.49
-0.39
-0.29
-0.09
0.07
0.41
0.80
0.97

STD
0.67
0.61
0.55
0.50
0.39
0.27
0.17
0.08
0.13
0.29
0.63
1.02
1.19
-0.53
0.81
0.97

RMS
4.97
5.30
5.32
5.25
4.83
4.18
3.61
2.87
0.98
0.83
5.47
11.76
18.45

Proposed
ε(P)
-0.85
-0.79
-0.73
-0.67
-0.55
-0.40
-0.29
-0.19
0.00
0.14
0.24
0.28
0.19

STD
0.57
0.51
0.45
0.39
0.27
0.12
0.01
0.09
0.28
0.42
0.52
0.55
0.47
-0.49
0.64
0.81

RMS
4.74
5.05
5.03
4.91
4.34
3.45
2.69
1.83
0.00
1.72
3.25
4.06
3.67

Table 3: Calculated error percentage [0.005% to 0.5%] for 12.25 GHz.

Procedures
Matrices
Occurrence
ITU-R P.311-15

0.5
0.2
0.1
0.05
0.02
0.01
0.005

ITU-R P. 618-13
ε(P)
-0.59
-0.38
-0.35
-0.22
0.04
-0.11
-0.14

STD
0.46
0.24
0.22
0.08
0.18
0.03
0.01
-0.15
0.19
0.24

RMS
1.77
1.32
1.75
1.30
0.31
1.16
2.17

DAH
ε(P)
-0.66
-0.48
-0.46
-0.34
-0.12
-0.24
-0.27

STD
0.46
0.28
0.26
0.14
0.08
0.04
0.07
-0.23
0.22
0.32

RMS
3.94
2.85
5.21
4.19
0.66
6.94
16.30

Ramachandran and Kumar
ε(P)
-0.32
0.04
0.10
0.39
1.16
0.57
0.28

STD
0.49
0.13
0.07
0.22
0.99
0.39
0.11
0.12
0.23
0.26

RMS
0.96
0.13
0.51
2.34
8.14
6.22
4.25

Karasawa
ε(P)
-0.63
-0.42
-0.03
-0.26
-0.01
0.16
0.07

STD
0.55
0.33
0.06
0.18
0.08
0.25
0.16
-0.1
0.24
0.26

RMS
1.90
1.45
0.13
1.58
0.07
1.77
1.08

Proposed
ε(P)
-0.47
-0.20
-0.17
0.00
0.31
0.12
0.06

STD
0.44
0.17
0.14
0.02
0.34
0.14
0.09
-0.03
0.17
0.17

RMS
1.41
0.70
0.85
0.03
2.20
1.29
0.91

Table 4: Calculated error percentage over 0.1% and 0.01% of the time.

Methods
Parameters
Time Percentage
ITU-R P.311-15

0.1
0.01

Unified
ε(P)
-0.09
-0.14
-0.11
0.04
0.12

STD
0.03
0.03

RMS
0.43
1.52

SAM
ε(P)
0.07
0.36
0.18
0.12
0.22

STD
0.14
0.14

RMS
0.36
3.92

Crane Global
ε(P)
-0.05
0.14
0.04
0.09
0.10

STD
0.10
0.10

RMS
0.26
1.51

Gracia Lopez
ε(P)
-0.15
-0.15
-0.15
0.01
0.15

STD
0.00
0.00

RMS
0.15
0.15

As depicted from Table 2, in the case of 12.25 GHz in Mokdong Station, ITU-R P.618-13, Unified, DAH, SAM, CG, GL, Karasawa, and the proposed technique result in greater inappropriateness in 0.05% ≤ P ≤ 1% as supported by higher variance and quadratic mean. Conversely, RK shows low error for same time percentage. Hence, in greater occurrence probability when 0.05% ≤ P ≤ 1%, RK method is suitable. When 0.001% ≤ P < 0.01%, ITU-R P. 618-13, SAM, CG, RK, Karasawa, and the proposed approach result in greater unsuitability. Interestingly, overestimation is observed to be lesser for ITU-R P. 618-13 and proposed procedure as shown by decreased variance and quadratic mean.

In contrast, DAH, Unified, and GL models give underestimation against the calculated rain attenuation, but less underestimation is shown by DAH method which signifies its suitability in low time occurrence. In addition, at 0.01%, ITU-R P. 618-13 and the proposed approach seem to provide fairly more accurate results than the other models of interest. To illustrate, ITU-R P. 618-13 results in error percentage of 53%, 4%, and 24% while it is 67%, 21%, 23%; 66%, 23%, 6%; 70%, 17%, 38%; 70%, 3%, 36%; 37%, 48%, 13%; 74%, 21%, 28%; 61%, 9%, 97%; 55%, 0%, 19% for Unified, DAH, SAM, CG, RK, GL, Karasawa, and the proposed approach at 0.1%, 0.01%, and 0.001% of occurrence, respectively. ITU-R P.618-13 and the proposed technique result in fewer values of , , and . In order to support the scientific argument for these finding, we have tested the validity of prominent rain attenuation models and proposed techniques in Yong-in Station. Unfortunately, due to the limited availability of the data sources, accurate nature of these models cannot be justified clearly. However, in this region too, similar nature is observed from the application of ITU-R P. 618-13 and the proposed technique. The tests have been carried out from the data sources as mentioned in [14] for 2007.

Table 3 shows the similar trends of statistical results. ITU-R P. 618-13 and the proposed technique result in reasonable estimation for lower period 0.005% ≤ P ≤ 0.05%, as supported by decreased and . Conversely, DAH and Karasawa give higher error chances for the same percentage of time where higher values of and are observed. Hence, ITU-R P. 618-13 and the proposed technique have better effectiveness in low occurrence period, particularly at 0.01% of occurrence. In addition, in upper occurrence period for 0.1% ≤ P ≤ 0.5%, RK gives better estimation which is assisted by decreased error percentage, and as compared to ITU-R P. 618-13, DAH, Karasawa and proposed procedure. As example, ITU-R P. 618-13 shows error chances of 22%, 11%, and 14% whereas 0%, 0.12%, and 6% for proposed procedure in 0.05%, 0.01%, and 0.005% of occurrence, respectively. Similarly, DAH, RK, and Karasawa show 34%, 24%, and 27%; 39%, 57%, and 0.28%; and 26%, 16%, and 7% for same percentage exceedance. Conversely, in 0.1 % ≤ P ≤ 0.5 %, ITU-R P. 618-13, DAH, RK, Karasawa, and the proposed procedure give 59%, 35%; 66%, 46%; 32%, 10%; 63%, 3% and 47%, 17% for 0.5% and 0.1% of occurrence, respectively. DAH, RK, and Karasawa generate excessive . In contrast, ITU-R P. 618-13 and proposed method result in less , as accomplished by less and Additionally, for fixed two percentages of time particularly, 0.1% and 0.01% of occurrence, the calculated error matrices are tabulated in Table 4 due to the limited data sources for rest of the models performance as they are dependent on rain rate values.

Table 4 shows the CG gives less errors percentage values as supported by lower values of and . As tested through ITU-R P. 311-15 [38] approach, this model gives lower , , and . In opposite, Unified, SAM, and GL result in higher error chances. For instance, CG, Unified, SAM, and GL show 5%, 14%; 9%, 14%; 7%, 36%; 15%, 15% for 0.1% and 0.01% of occurrence, respectively. CG shows lower value as compared to other models, but still there is the requirement of test for the suitability of model throughout the all-time percentage ranging from 1% to 0.001% of occurrence. Thus, this paper gives more priority to estimate better prediction approach for the analyses done from Mokdong Station database due to the most recent and well-arranged system.

5. Conclusions

Various models are compared to predict rain attenuation at Ku-band over an earth-space path. The propagation impairments for 12.25 GHz satellite communication links in Mokdong Station, along with database provided from Young-in station are studied. The rain rates at 0.01% of the time are 50.35 and 59 mm/hr for two experimental locations, namely, Mokdong and Yong-in Stations. The results show that at higher time percentage when 0.01% ≤ P ≤ 1%, ITU-R P.618-13, Ramachandran and Kumar, proposed approach shows the better estimation of rain attenuation. Conversely, when 0.001% ≤ P ≤ 0.1%, ITU-R P. 618-13, DAH, and the proposed approach show good estimation against the measured results. The predictive capability of the model is judged through the relative error analyses, standard deviation, root mean square values, and ITU-R P. 311-15. Thus, the paper presents comparison of measured data with the existing rain attenuation prediction models and categorizes the best fitting models. Overall, ITU-R P. 618-13 shows better applicability for prediction of rain attenuation until the sufficient database from other locations become available. ITU-R P. 618-13 model shows better estimation and could be used until and unless sufficient dataset of rain attenuation measurement at Ku-band is made available from other location of South Korea. However, as per the rain attenuation and rain rate measurement obtained from two specific locations, the proposed method shows better estimation. This emphasizes the advantages of the proposed approach as compared to existing models.

The empirical result generated would be the helpful tool for system designers to determine the link margin at the specific site. However, additional tests and experimental data are necessary for better understanding of the present line of study for Ku-band satellite communication link. The contribution describes some preliminary steps aiming at devising appropriate methodology for prediction of rain attenuation affecting earth-space communication link.

Data Availability

It could be provided upon request from the reader on the approval from National Radio Research Agency (RRA).

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

We want to extend our thankfulness towards National Radio Research Agency (RRA) for providing and supporting us with the valuable database of satellite system. Authors also like to thank School of Engineering, Macquarie University, NSW, Australia, for providing the environment to further carry out the research work.

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