PATH LOSS DUE TO RAIN FADING AND PRECIPITATION IN 26 GHZ LMDS SYSTEMS: CONSIDERATION OF IMPLEMENTATION IN TURKEY Sercan Uslu and İbrahim Tekin Faculty of Engineering and Natural Sciences, Sabancı University Orhanlı – Tuzla, 34956 İstanbul, Turkey E-mail:
[email protected],
[email protected] Abstract - This paper explains the rainfall attenuation prediction model recommended in ITU-R PN.838 and investigates the variability of 26 GHz LMDS radio channel obscured by rain attenuation in seven representative cities for the climate of turkey. Model is applied both with recommended input values presented in ITU-R PN.837-1 and values obtained by processing long term monthly precipitation data for Adana, Ankara, Antalya, Erzurum, Istanbul, Izmir, and Samsun. Results for both applications are presented and the necessity of using locationspecific monthly climate statistics for the LMDS system design is addressed.
I. Introduction Availability of radio link and the system range defines the reliability of Local Multipoint Distribution Services (LMDS) as in any radio system. Since system range and availability are highly constrained by climate characteristics of region of operation, path loss caused by precipitation in that region is one of the key issues that must be considered for the LMDS system design process. Precipitation based path loss of the signal is an issue which is easy to understand but difficult to predict. Under good weather conditions precipitation based path loss is not evident whereas during heavy rainfalls, signals are absorbed by the water within the rain and this absorption causes signal attenuation. Atmospheric disturbances such as thunderstorms also distort the signal and cause unacceptable number of errors [1]. Although the difficulty is obvious for prediction, it is possible to make some estimation. By means of the standardized method of calculation for the precipitation based path loss in International Telecommunications Union – Radio Communications sector (ITU-R) documents, we can calculate the effect of precipitation in the region of operation for the former years via historical precipitation data and make predictions for the possible future effects. Taking this as a starting point, this paper investigates the variability of LMDS radio channel obscured by precipitation in seven cities of Turkey; Adana, Ankara, Antalya, Erzurum, Istanbul, Izmir, and Samsun, which are representative for typical precipitation regions of the country. The underlying reason of investigating variability in seven cities, which fall into two rain climatic zones specified by ITU-R recommendations, is the necessity of using location-specific data due to the high value of estimated attenuation standard deviation (19%) within a rain climatic zone [2].
II. Overview of Turkey’s Climate and Regional Rainfall Characteristics In general, when the geographic location is taken into consideration, Turkey is under the effect of Mediterranean climate. But significant differences in climatic conditions and therefore in precipitation characteristics are observable between diverse regions of the country as a result of irregular topography. As given in Figure 1, in the driest regions (the Central Anatolia), annual rainfall is less than 300 millimeters whereas in the wettest regions
68
(the Black Sea coastal region) annual rainfall can reach up to 2,200 millimeters, and the region receives rainfall throughout the year [3]. In the Eastern region of Anatolia, terrestrial climate is seen as a result of its topography and annual precipitation in this region averages about 500-800 millimeters with actual amounts determined by elevation. Anatolian Plateau, experiencing a steppe climate, rainfall is low and usually in the form of snow whereas annual precipitation in the Aegean and Mediterranean coastal areas varies from 580 to 1,300 millimeters, almost all the time in the form of rain [3]. Figure 2 represents monthly temperature and precipitation values for Turkey over long term.
III. Propagation Environment Path losses relative to free-space in line-of-sight (LOS) radio systems are classified under eight groups which are listed in Table I. Among these, the most significant factor on signal attenuation in the bands from about 1 GHz to 40 GHz is precipitation – rain in specific. Precipitation is a wide term that includes cloud, fog, hail, rain, and snow. Although signal degradation due to hail can also be important, as its occurrence is relatively uncommon when compared to rain in the selected regions, its affects are ignored in this research. Other forms of precipitation – snow, hail, and fog are also not considered since they are not affective in frequencies between 1 GHz to 40 GHz due to their drier nature when compared to rain [1]. The only form that could be considered as wet is snow but since precipitation data used classifies this form under rain, it has already been covered. In general, for radio communication systems operating above 10 GHz signal attenuation due to rainfall is the main component of the path loss. Specifically, it is rain drops that cause attenuation effects in signal like absorption and scattering. So the rain attenuation is dependent on shape and size distribution of the rain drops as well as on temperature, angle and velocity of rainfall, and rain rate [4].
IV. Estimation of Rain Fading and Precipitation Effects Modeling ITU-R recommendations PN.838 and PN.837 are about specific rain attenuation and characterization of precipitation for propagation modeling. In ITU-R PN.838, for frequencies under 40 GHz and path lengths shorter than 60 km [1], attenuation originating from rainfall is defined by γR and modeled as follows:
γ R = k ⋅ Rα
in dB / km
(1)
where R is the rainfall rate in mm/hour with different values for each climate zone [5]. k and α are frequency dependent coefficients for linear or horizontal polarization [4]. These frequency-dependent coefficients are calculated by
2003ѝ13thѝInt.ѝCrimeanѝConferenceѝ“Microwaveѝ&ѝTelecommunicationѝTechnology”ѝ(CriMiCo’2003).ѝ8-12ѝSeptember,ѝSevastopol,ѝCrimea,ѝUkraineѝ ©ѝ2003:ѝCriMiCo’2003ѝOrganizingѝCommittee;ѝWeberѝCo.ѝISBN:ѝ966-7968-26-X.ѝIEEEѝCatalogѝNumber:ѝ03EX697
k=
α=
k v + k h + (k h − k v ) ⋅ cos 2 Θ ⋅ cos 2τ 2
k hα h + k v α v + (k hα h − k v α v ) ⋅ cos 2 Θ ⋅ cos 2τ 2k
(2)
(3)
In equations (2) and (3), Θ is the path elevation angle and τ is the polarization tilt angle relative to the horizontal polarization[1]. kh, kv, αh, and αv are frequencydependent regression coefficients for estimating specific attenuation in Equation (1). Values of these coefficients for different frequencies can be found in [5]. Table II gives the values of inputs, k and α, that are used in this paper. k and α values for 26 GHz are calculated by interpolation and since rainfall attenuation calculations are performed for different cities representing diversified regions in Turkey, long term monthly rainfall rates are used instead of the values provided in [6] for rain climatic zone K which covers almost all the land of Turkey. Daily average rainfall rates throughout the year are given in Table III. These values are calculated by using climatological information of the cities based on long term monthly averages [7] containing mean total rainfall and mean number of rain days. To better examine the volatility of precipitation throughout the year, Figure 3 illustrates the distribution of mm amounts of rainfall for the selected cities. As illustration indicates, the least volatile distribution is observed in Ankara and the most in Antalya. In order to interpret the precipitation data more accurately, percentage of time that rain is observed is also calculated. Rainy days average precipitation values and the percentage of rainy days throughout a year are given in Figure 4. According to these values, average precipitation in Istanbul is about 1.854 mm/h for the rainy days, which constitute approximately 34.03% of a year. Final inputs for the rainfall attenuation prediction model are Θ and τ angles. Meaningful values for Θ are expected to range between 0° and 20°, whereas for τ values are 0°, 45° or 90° indicating horizontal, 45° slanted and vertical polarizations respectively. A simple method for calculation of Θ is taking the inverse tangent of quotient obtained by dividing the average height difference between the transmitter and receiver to the distance among them. Figure 5 shows an example where the numerator – height difference – is 30 m and the denominator – distance– is 3 km. In this case Θ value is about 0.573°.
V. Effective Path Length Calculation As rain is not uniformly distributed with distance [4], exact path length can not be considered as equal to the simple actual distance, d, between transmitting and receiving points. ITU-R P.530 recommendation proposes a model for the calculation of the effective path length. According to this model, actual path length, d, is to be corrected by a factor, r, which is indirectly dependent on the rainfall rate. Below given are the formulae for the effective path length calculation. (4) d eff = d ⋅ r
r=
1 ⎡ ⎛ d ⎞⎤ ⎢1 + ⎜⎜ ⎟⎟⎥ ⎣⎢ ⎝ d 0 ⎠⎦⎥
(5)
⎧⎪35 ⋅ e −0.015⋅Ri do = ⎨ ⎪⎩7.81
, Ri < 100 mm / h , Ri > 100 mm / h
(6)
where Ri is the rainfall rate that exceeded i percent of time, i.e. R0.01 for 0.01% of the time. In calculation of d0 for cities in Turkey which are either in K or L rain climatic zones represented in [6], there are two exceptional cases which are both seen in Aegean coastal areas that fall into L zone. In these areas, for less than 0.003% of each average year [1] rainfall rate exceeds the boundary of 100 mm/h. In other words, for R0.003 and R0.001 values, meaning that for about 15.78 and 5.26 minutes of rainfall throughout a year with 105 and 150 mm/h amounts respectively, d0 value is to be taken as 7.81.
VI. Results Effective path length values for an average actual path length of 3 km in K and L rain climatic zones varying with different percentage-of-time values are also presented in Table IV. Results given in Table V are obtained by applying the model presented in [5] the values of rainfall intensity exceed for certain percentages of time for K and L rain climatic zones presented in [6]. In this application, actual path length is taken as 3 km and height difference between the transmitter and the receiver is assumed to be 30 m. Results of L rain climatic zone are valid only for Izmir due to its location. For the other cities, results of K rain climatic zone are to be considered. If we consider our example case for Istanbul with 3 km distance and 30 m height difference between the transmitter and the receiver, on rainy days during January. Rain attenuation takes an average value about 1.119 dB when the polarization is horizontal (τ = 0°). This is also the largest value that could be observed throughout a year for Istanbul with the given settings. On the other hand, the smallest attenuation observed due to rain is expected to be in August with 0.282 dB. Another important point to mention is that the effective path length is 2.75 km though the actual path length is 3 km. Average annual attenuation values calculated for the selected cities are given in Table VI, VII, and VIII. Finally, Figure 6 illustrates the rainfall attenuation values for the selected cities in horizontal polarization case. It is the graphical presentation of values given in Table VI.
VII. Conclusions At high frequencies like 26 GHz band, rain fading becomes a more challenging issue for LMDS systems. Therefore attenuation due to rain is an important factor that has to be considered when implementing LMDS systems. As high as 3 dB rain attenuation, which could severely effect the reliable communication, has been calculated for some regions. Results presented in this paper address the requirement of location-specific monthly climate statistics consideration for the LMDS system design. Since the threshold values for rainfall are not exceeded all at once monthly availability of the system will have a different level from the annual availability. In other words, as rainfall does not regularly spread over the year, monthly precipitation characteristics of geographic location where the system will be implemented are to be studied well enough to reduce the probability of propagation failure due to rainfall. In addition to considering narrower intervals of time, using location-specific rainfall rates is also necessary due to the high standard deviation of estimated attenuation within a rain climatic zone.
2003ѝ13thѝInt.ѝCrimeanѝConferenceѝ“Microwaveѝ&ѝTelecommunicationѝTechnology”ѝ(CriMiCo’2003).ѝ8-12ѝSeptember,ѝSevastopol,ѝCrimea,ѝUkraineѝ ©ѝ2003:ѝCriMiCo’2003ѝOrganizingѝCommittee;ѝWeberѝCo.ѝISBN:ѝ966-7968-26-X.ѝIEEEѝCatalogѝNumber:ѝ03EX697
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[4]
VIII. References [1] [2]
[3]
Clark, M. P., 2000, Wireless Access Networks: Fixed Wireless Access and WLL Networks – Design and Operation, John Wiley & Sons, UK. Panichakul, Y., Park, G., Pongthaipat, N., and Sirivatanagul, D., 2000, “LMDS: The Technical Consideration of Implementation In Bangkok, Thailand”, Capstone proceeding paper, Interdisciplinary Telecommunications Program, University of Colorado. Sensoy, S., 2003, “Climate of Turkey”, Turkish State Meteorological Service Official Web Site, http://www.meteor.gov.tr/2003eng/general/climate/climateo fturkey.htm
Burr, A. G., Daly, N. E., Grace, D., Pearce, D. A. J., and Tozer, T. C., 2000, “Capacity Effects on Terrestrial Broadband Wireless Access Networks Operating in the LMDS Frequency Band during Rainfall Conditions”, IEEE VTCSpring 2000, May 2000 ITU – Recommendations Assembly, “Specific Rain Attenuation”, Recommendation ITU-R PN.838-1,1992-1994 ITU – Recommendations Assembly, “Characterization of Precipitation for Propagation Modeling”, Recommendation ITU-R PN.837-1,1992-1994 World Meteorological Organization - World Weather Information Service Website, 2003, http://www.worldweather.org/014/m014.htm
[5] [6] [7]
Temperature (°C)
Precipitation (mm)
25 20 15 10 5 0
1
2
3
4
Temperature
5
6
7
Months
8
9
10 11 12
10 9 8 7 6 5 4 3 2 1 0
Precipitation
Fig. 2. Long Term Monthly Temperature and Precipitation in Turkey [3]
Fig. 1. Annual Average Precipitation of Turkey [3] 10.0 9.0 Percipitation (mm)
8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 1
2
3
4
Istanbul Adana Erzurum
5
6
7
8
Months
Ankara Antalya
9
10 11 12 Izmir Samsun
Fig. 4. Annual precipitation statistics for the selected cities
Fig. 3. Distribution of Rainy Days Average Precipitations over Months 4.0
Distance ~ 3 k Height Difference ~ 30 m
Rainfall Attenuation [dB]
3.5 Θ ≈ 0.573°
3.0 2.5 2.0 1.5 1.0 0.5 0.0 1
Fig. 5. Example for Θ Calculation
2
3
4
ISTANBUL ADANA ERZURUM
5
6
7
Months ANKARA ANTALYA
8
9
10
11
12
IZMIR SAMSUN
Fig. 6. Illustration of Rainfall Attenuation for the Worst Case ( Horizontal Polarization, τ = 0°)
70
2003ѝ13thѝInt.ѝCrimeanѝConferenceѝ“Microwaveѝ&ѝTelecommunicationѝTechnology”ѝ(CriMiCo’2003).ѝ8-12ѝSeptember,ѝSevastopol,ѝCrimea,ѝUkraineѝ ©ѝ2003:ѝCriMiCo’2003ѝOrganizingѝCommittee;ѝWeberѝCo.ѝISBN:ѝ966-7968-26-X.ѝIEEEѝCatalogѝNumber:ѝ03EX697
TABLE I Causes of Path Loses [1] Absorption due to precipitation
Rain, snow, fog, clouds or other weather effects
Absorption due to atmospheric gases and/or the dielectric state of the atmosphere
The degree that the atmosphere is ionized or non-ionized
Attenuation due to ground coverage
Buildings, vegetation, sand or dust storms, etc.
Fading due to multipath Losses due to path obstruction or partial obstruction, and signal diffraction
TABLE III Rainy Days Average Precipitations (mm/h) Throughout a Year in Seven Different Cities CITIES MONTHS
Harmful interference of the different reflections of the original signal Affects waves that are propagated near the earth’s surface
Istanbul Ankara I z m i r A d a n a Antalya Samsun Erzurum
Jan
2.816
1.252
4.232
3.558
7.497
2.248
0.745
Feb
2.546
1.254
3.529
3.218
5.739
2.150
0.982
Mar
2.039
1.184
2.474
2.116
3.123
2.087
1.155
Apr
1.497
1.393
1.470
1.757
1.540
1.930
1.740
May
1.052
1.648
1.026
1.503
0.968
1.506
2.339
Jun
0.843
1.127
0.263
0.720
0.320
1.487
1.663
Jul
0.765
0.471
0.068
0.203
0.071
1.071
0.910
Signal polarization effects
Horizontal and vertical polarization
Aug
0.761
0.352
0.071
0.155
0.081
1.061
0.577
Sep
1.477
0.560
0.357
0.507
0.410
1.863
0.847
Signal reflection or scattering of the signal
Affects transmission through the ionosphere
Oct
2.281
0.832
1.223
1.410
2.184
2.548
1.477
Nov
2.732
1.013
2.971
2.358
4.255
2.723
1.132
Dec
3.442
1.474
4.865
3.900
8.494
2.548
0.742
Magnetic and electrical effects of the earth’s surface and geography
TABLE IV Effective Path Length Values for 3 km Actual Path
% of Time
TABLE II Input Values for the Rain Attenuation Prediction Model k
1.000% 0.300% 0.100% 0.030% 0.010% 0.003% 0.001%
α
kh
kv
αh
αv
0.1366
0.1238
1.053
1.024
Effective Path Length deff, [km] K Zone
L Zone
2.758 2.749 2.721 2.676 2.584 2.410 2.167
2.757 2.739 2.709 2.630 2.478 2.167 2.167
TABLE VI Average Rainfall Attenuation Values [dB] for Horizontal Polarization (τ = 0°) TABLE V Rainfall Attenuation Values for Different Availability Targets
% of Time (i %)
Rainfall intensity exceeded (mm/h)
CITIES
Attenuation due to rain, Ai , [dB] Horizontal Vertical PolariPolarization 45° Slanted zation
τ = 0°
τ = 45° K L
K
L
K
L
Zone
Zone
Zone
Zone
Zone
1.000%
1.5
2
0.577
0.781
0.300%
4.2
7
1.702
2.904
Istanbul
Ankara
Jan
1.119
0.476 1.719 1.432 3.138
0.883
0.276
Feb
1.007
0.477 1.419 1.288 2.368
0.842
0.369
Mar
0.796
0.449 0.976 0.828 1.248
0.816
0.438
Apr
0.575
0.533 0.564 0.681 0.593
0.752
0.674
May
0.397
0.637 0.386 0.578 0.363
0.579
0.920
Jun
0.314
0.426 0.092 0.266 0.113
0.571
0.643
MONTHS
τ = 90°
Zone
K Zone
L Zone
0.537
0.713
0.497
0.649
1.483
2.451
1.289
2.064
Izmir
Adana
Antalya Samsun Erzurum
Jul
0.284
0.170 0.022 0.070 0.023
0.404
0.340
0.282
0.125 0.023 0.053 0.027
0.400
0.211
0.100%
12
15
5.088
6.408
4.152
5.157
3.380
4.140
Aug
0.030%
23
33
9.928
14.270
7.779
10.933
6.081
8.356
Sep
0.567
0.204 0.127 0.184 0.147
0.724
0.316
0.010%
42
60
18.073
25.228
13.639
18.619
10.268
13.708
Oct
0.896
0.310 0.465 0.540 0.856
1.007
0.567
0.003%
70
105
28.861
39.784
21.096
28.353
15.383
20.158
Nov
1.084
0.381 1.184 0.928 1.728
1.080
0.429
0.001%
100
150
37.791
57.918
27.015
40.368
19.265
28.068
Dec
1.382
0.566 1.990 1.577 3.579
1.007
0.275
Std. Dev.
0.37
0.16
0.23
0.21
0.69
0.52
1.25
2003ѝ13thѝInt.ѝCrimeanѝConferenceѝ“Microwaveѝ&ѝTelecommunicationѝTechnology”ѝ(CriMiCo’2003).ѝ8-12ѝSeptember,ѝSevastopol,ѝCrimea,ѝUkraineѝ ©ѝ2003:ѝCriMiCo’2003ѝOrganizingѝCommittee;ѝWeberѝCo.ѝISBN:ѝ966-7968-26-X.ѝIEEEѝCatalogѝNumber:ѝ03EX697
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TABLE VII Average Rainfall Attenuation Values [dB] for 45° Slanted Polarization (Τ = 45°) CITIES MONTHS
Istanbul
Ankara
Izmir
Adana
TABLE VIII Average Rainfall Attenuation Values [dB] for Vertical Polarization (Τ = 90°)
Antalya Samsun Erzurum
CITIES MONTHS
Istanbul
Ankara
Izmir
Adana
Antalya Samsun Erzurum
Jan
1.052
0.453 1.606 1.341 2.909
0.832
0.264
Jan
0.984
0.429 1.494 1.251 2.682
0.782
0.252
Feb
0.947
0.453 1.329 1.208 2.204
0.794
0.352
Feb
0.888
0.430 1.240 1.128 2.040
0.747
0.335
Mar
0.752
0.427 0.919 0.781 1.171
0.770
0.416
Mar
0.707
0.405 0.862 0.735 1.094
0.724
0.395
Apr
0.545
0.506 0.535 0.644 0.562
0.710
0.638
Apr
0.515
0.479 0.506 0.607 0.530
0.668
0.601
May
0.378
0.603 0.368 0.548 0.347
0.549
0.867
May
0.359
0.569 0.350 0.518 0.330
0.519
0.814
Jun
0.300
0.406 0.090 0.255 0.110
0.541
0.608
Jun
0.286
0.385 0.087 0.244 0.106
0.512
0.574
Jul
0.271
0.164 0.022 0.068 0.023
0.385
0.325
Jul
0.259
0.158 0.022 0.067 0.023
0.366
0.309
Aug
0.270
0.121 0.023 0.052 0.026
0.381
0.203
Aug
0.258
0.117 0.023 0.050 0.026
0.362
0.194
Sep
0.538
0.196 0.123 0.177 0.142
0.685
0.302
Sep
0.508
0.188 0.119 0.170 0.137
0.645
0.287
Oct
0.845
0.296 0.442 0.512 0.807
0.948
0.538
Oct
0.793
0.282 0.419 0.485 0.759
0.889
0.508
Nov
1.019
0.363 1.112 0.874 1.615
1.015
0.408
Nov
0.954
0.345 1.040 0.821 1.502
0.951
0.387
Dec
1.295
0.537 1.856 1.475 3.312
0.948
0.263
Dec
1.209
0.507 1.723 1.374 3.048
0.889
0.251
Std. Dev.
0.35
0.15
0.21
0.20
Std. Dev.
0.32
0.14
0.20
0.18
72
0.65
0.49
1.16
0.60
0.46
1.07
2003ѝ13thѝInt.ѝCrimeanѝConferenceѝ“Microwaveѝ&ѝTelecommunicationѝTechnology”ѝ(CriMiCo’2003).ѝ8-12ѝSeptember,ѝSevastopol,ѝCrimea,ѝUkraineѝ ©ѝ2003:ѝCriMiCo’2003ѝOrganizingѝCommittee;ѝWeberѝCo.ѝISBN:ѝ966-7968-26-X.ѝIEEEѝCatalogѝNumber:ѝ03EX697
